Year 1 Annual Report – Volume 2 - PBworks

Year 1 Annual Report – Volume 2

ii

COE CST YEAR 1 ANNUAL REPORT This report is produced by the FAA Office of Commercial Space Transportation in fulfillment of FAA Centers of Excellence program requirements.

This report is broken into three volumes:

Volume 1 gives a description of the FAA COE CST, its research, structure, member universities and research tasks.

Volume 2 is a comprehensive set of presentation charts of each research task as presented at the first Annual Technical Meeting in November 2011.

Volume 3 is a comprehensive set of notes from all FAA COE CST teleconferences and face-to-face meetings.

Any questions or comments about the content of this report should be directed to Mr. Ken Davidian, FAA COE CST Program Manager or Dr. Patricia Watts, FAA COE Program Director.

1

Federal AviationAdministration 1

COE CST First Annual Technical Meeting (ATM1)November 9 & 10, 2011

COE CST First Annual Technical Meeting:

1. Physiologic Database Definition & Design

James Vanderploeg, MD

November 10, 2011

Federal AviationAdministration


COE CST First Annual Technical Meeting November 9 & 10, 2011

Overview• Team Members

• Purpose of Task

• Schedule & Milestones

• Next Steps

• Contact Information



Team Members • UTMB

• PI: Jim Vanderploeg, MD (UTMB Aerospace Med.)

• Student: Jennifer Law, MD (UTMB Aerospace Med.)

• Student: Charles Mathers, MD (UTMB Aerosp. Med.)

• Co-I: Richard Jennings, MD (UTMB Aerospace Med)

• NASA Johnson Space Center• Mary Van Baalen

• Dr. John Charles

• Dr. Jeffrey Davis

• Wyle Integrated Science & Engineering• Eric Kerstman, MD

• Christine Smith

• FAA CAMI• Dr. Melchor Antunano



Height

Visual Acuity

Arm Reach

Gender

Native Language

Strength

Endurance

Mechanical Aptitude

Reaction Time (Scan Pattern)

Cultural Differences

Susceptibility to SAS

Operational Background

Underlying Medical

Conditions

Weight

Situational Awareness

Depth of Knowledge

(Preparedness)

Auditory Acuity

Verbal Clarity & Fluency

G-TolerancePain

(Discomfort) Tolerance

Understanding Human Complexity

2



Purpose of Task• Purpose:

• Create a database of medical & physiological data from commercial crew and spaceflight participants

• Objectives:

• Identify the appropriate data elements

• Recommend a scalable design for the database

• Establish security, approved access, appropriate uses of data

• Goals

• Initial step is to begin defining the requirements and elements though a workshop of stakeholders



Existing Data Sets

• Longitudinal Study of Astronaut Health (LSAH)

• Historical data in Integrated Medical Model (IMM)

• Individual NASA research experiments data

• Flight Surgeon post-flight astronaut debrief data

• Data from experiments performed on Life Science research Shuttle missions



Problems with Existing Data Sets• Small numbers of astronauts so de-identification

is difficult

• Getting data out of the LSAH is difficult

• No integration among the data sets

• No standardization among the data sets

FAA – NASA

COMMERCIAL SPACE FLIGHT BIOMEDICAL DATA

ACQUISITION AND MANAGEMENT PROPOSAL

Jeffrey R. Davis, MD (NASA)

COMSTAC

RLV Working Group

October 10, 2007

3

Jeffrey R. Davis, MD 9


• NASA goals are to:

– Encourage and support the emerging commercial space flight industry

– Provide opportunities to expand the body of evidence characterizing human responses to space consistent with the proposed Enhanced Longitudinal Study for Astronaut Health (LSAH)

• LSAH data gathering captures and studies all relevant medical data necessary to identify and ameliorate the health risks associated with human space flight to enable future human space exploration initiatives

• Including commercial space flight participants will give NASA a better understanding of the physiological effects of space flight and further define what is required to safely fly humans in space



• NASA and the FAA are proposing to establish an MOA in which:– NASA will provide a data management, archive, and reporting system

for commercial space flight participant biomedical monitoring data as a supplement to its enhanced LSAH database

– NASA will establish an administrative structure to receive, manage, organize, and report the data

– NASA will provide non-attributable (individual and/or company) commercial space flight passenger biomedical monitoring data to the FAA and participating operators upon request (at NASA cost)

– NASA will provide operator-specific commercial space flight passenger biomedical monitoring data to each operator based on established agreements with that operator

– FAA will provide non-attributable (individual and/or company) space flight crew certification and biomedical monitoring data to NASA upon request



• NASA and the FAA are proposing to establish an MOA in which (continued):– FAA will oversee the collection and management of commercial

space flight crew certification and biomedical monitoring data

– NASA and the FAA will jointly analyze and utilize commercial space flight certification and biomedical monitoring data to better define medical risk factors involved with space flight crews and space flight participants before, during, and after space flight.

– NASA and the FAA will jointly identify collaborative projects and approve project plans for collection and management of commercial space flight participant data

– NASA and the FAA will jointly oversee the collection and management of commercial space flight participant data on a periodic basis



• Benefit of data collection and analysis to commercial space flight operators

– Gain greater insight into the medical risks, thereby reducing risk

• Operators• Insurers

– Enhance risk mitigation for space flight participants

4



Stakeholders

Data Repository

OperatorsVirgin GalacticXCORSierra Nevada CorpSpace XOthers

TrainersNASTARQinetiQOthers

Flight SurgeonsCompany Medical DirectorsAviation Medical ExaminersConsultants

ResearchersSuborbitalOrbital

GovernmentFAANASAESAOthers

IndividualsFuture customersFamily & FriendsAdventures



Next Steps• Identify stakeholders (in progress)

• Initial draft of data elements (in progress)

• Identify hosting options and resources

• Initial draft of security, confidentiality, and access requirements

• Conduct workshop in Spring 2012

• Draft report – mid 2012

• Final report and recommendations – Dec. 2012



Schedule & Milestones



Contact Information

• Jim Vanderploeg, MD, MPH

2.102 Ewing Hall, UTMB

301 University Blvd.

Galveston, Texas 77555-1110

Phone: 1-409-747-5357

Fax: 1-409-747-6129

Email: [email protected]

1




2. Human System Risk Management Approach


November 10, 2011





• Purpose of Task

• Research Methodology

• Schedule & Milestones

• Results

• Next Steps




Team Members • UTMB

• Jim Vanderploeg, MD – PI

• Richard Jennings, MD – Co-I

• Jennifer Law, MD – Resident in Aerospace Med

• Charles Mathers, MD – Resident in Aerosp Med

• Wyle Integrated Science & Engineering

• Eric Kerstman, MD

• NASA Johnson Space Center

• Multiple participants



Purpose of Task• Purpose

• Investigate the feasibility of applying the JSC Human System Risk Management approach for long-duration spaceflight to commercial suborbital and short duration orbital spaceflight

• Objectives

• Select subset of risks appropriate for commercial spaceflight

• Quantify the health and performance risk

• Define mitigation strategies

2



Research Methodology• Sources of Information:

• NASA Human Research Roadmap (HRR)

• Historical Human Spaceflight Data

• Integrated Medical Model

• Thirty-one operationally focused risks defined in HRR Program Requirements Document

• Integrated Research Plan and Evidence Book (IRD) details activities to fill the knowledge and mitigation gaps



Research Methodology - 2• Assign level of concern for each risk applicable to

commercial flight

• Develop risk mitigation strategies for each definite and possible concern

Concern Level Crew PassengersDefinite 3 4

Possible 21 21

Least 7 6



Example• Risk: Abnormal cardiac rhythm

• Rationale: • Passengers in poorer health with history of heart problems

• Reduced cardiac function

• Increased risk of cardiac arrest

• Mitigation: • Pre-screening to identify

• Pre-treatment to eliminate or control arrhythmia

• Pre-flight testing/training under simulated environment (centrifuge and/or Zero-G flight)




3



Results

• Thirty-one risks have been identified and categorized

• Twenty-four risks for crew members and 25 for passengers are being evaluated for mitigation strategies

• Draft report is under review



Next Steps• Complete the final report for submission to the

FAA Office of Commercial Space Transportation

• Consider publication in peer-reviewed medical journal

• Follow-on project to create software system to identify and categorize risks and define mitigation strategies



Contact Information





Phone: 1-409-747-5357

Fax: 1-409-747-6129


1





Flight Crew Medical Standards and Passenger Acceptance

Guidelines

Richard T. Jennings, MD

November 10, 2011 Federal AviationAdministration 2





• Purpose of Task


• Results or Schedule & Milestones




Team Members • Melchor Antunano, MD, MS, FAA CAMI

• Smith Johnston, MD, MS, NASA-JSC

• Vernon McDonald, PhD, Wyle

• Jan Stepanek, MD, MPH, Mayo Clinic Scottsdale

• Mark Campbell, MD, Paris Surgical Associates

• Col Steve Nagel, NASA-JSC, University of Missouri

• Leigh Lewis, MD, MPH UTMB/FAA CAMI*

• Chuck Mathers, MD, MPH UTMB*

• Jim Vanderploeg, MD, MPH UTMB (Co-PI)

2



Objectives

• Develop recommendations for the medical standards for suborbital and orbital space vehicle crew members

• Develop recommendations for passenger acceptance criteria for suborbital and orbital flight

• Develop a passenger ‘Informed Consent’ document for space launch operators and flight surgeons to convey risks related to personal medical status





Research Methodology• Expert review of existing documents addressing space flight

crew member medical certification, passenger medical evaluation

guidelines, and testing and training recommendations for crew

members and passengers(GOMSAT).

• Prepare a draft document incorporating standards/guidelines and

recommendations identified in Phase One and distribute for

review/input to individuals, agencies, organizations, and companies

involved in commercial space flight.

1. Collect and review the existing documents addressing space flight crew member medical certification, passenger medical evaluation guidelines, and recomm2. Prepare a document incorporating the various standards and recommendations identified in phase one and send for review and comment to people and org3. Convene a working group of experts in aerospace medicine and physiology, operational support personnel, training experts, safety professionals, and comm4. Conduct a study of the information that is required for passengers to complete an “Informed Consent” declaration. In addition to the content of an “Informe



“At least you can still be a spaceflight passenger.”

3



Research Methodology• Convene a working group of company representatives and

experts in aerospace medicine and physiology, operations, training, safety, and commercial space flight to consider comments from Phase One and prepare recommendations for the medical certification of crew members, medical clearance guidelines of passengers, and recommended training procedures

• Conduct a preliminary study of the information that is required for passengers to receive appropriate risk-based “Informed Consent.” Analyze and test the language competency most appropriate for use in individuals with limited English language

capability



Results or Schedule/Milestones• Phase I document

completed and distributed for review

• Updated document to be distributed by end of 2011

• Phase 2 meeting of players in Feb-March 2012

• Final Document to FAA by June 30, 2012

• Informed Consent Dec 31



Contact Information• Richard Jennings

University of Texas Medical Branch

301 University Blvd

Galveston, TX 77555-1110

409-747-6131

[email protected]

1



Federal AviationAdministrationCOE CST First Annual

Technical Meeting

Task 184Human Rating of

Commercial Spacecraft

David KlausUniversity of Colorado




• Purpose of Task



• Next Steps




Team Members - to date (in progress)

• David Klaus, PI, University of Colorado

• Christine Fanchiang, PhD student, CU Aerospace (funded by COE)

• Robert Ocampo, PhD student, CU Aerospace (funded by SNC)

• Rene Rey, FAA

• Mark Weyland, NASA JSC

• Kenneth Stroud, Sierra Nevada Corp.

• Merri Sanchez, Sierra Nevada Corp.

• Scott Norris, Lockheed Martin

• Todd Sullivan, Lockheed Martin

• Paul Eckert, Boeing (Sheryl Kelley)

• Tim Bulk, Special Aerospace Services

• Jeffrey Forrest, Metropolitan State College of Denver

• John Dicks, L3 Stratis, NASA IV&V



Purpose of Task• Purpose

• To define the criteria for human rating (or certification?) of an integrated commercial spacecraft and launch vehicle system

• Objectives - year 1 of 3 planned (6/1/11 to 5/31/12)

• Review and summarize human rating literature and practice

• Compile database of guidelines for commercial spaceflight

• Identify and seek collaboration with individuals to participate in a Working Group to identify and address implementation needs

• Goals• Develop baseline Human Rating (Certification?) Guidelines and

Considerations for Commercial Space Transportation addressing requirements, validation & verification, and flight certification processes

• Extend study from initial needs and capabilities of crew and space flight participants toward era of passenger carrying space vehicles

2



Research Methodology• Fundamental tenets underlying Human Rating are to:

• accommodate physiological needs of the crew

• protect the crew and passengers from harm, including ground crew and public

• utilize the crew’s capabilities to safely and effectively achieve the goals of the mission

• Essentially, to Protect and Utilize the Crew• Drives Life Support Requirements, Risk Mitigation

Strategies, and Vehicle Functionality Design Goals



Research Methodology• No spacecraft to date has been Human Rated *

• Relevancy to launch vehicle or aircraft design / certification practices?

• Legal / liability issues? International law implications…

• Assess and define appropriate criteria and protocols needed to achieve the essential Human Rating ‘accommodate, protect and utilize’ objectives, and to characterize and quantify ensuing associated hazards and risks

• Risk mitigation success ultimately captured by predicted Loss of Crew (LOC), Loss of Vehicle (LOV) and/or Loss of Mission (LOM) probabilities (per passenger, flight, mission?)

• Risk acceptance is a programmatic decision

*per literature, to the best of our knowledge



Research MethodologySome Perspective… • 6.8 commercial air carrier fatalities per 100,000,000

passengers (FAA FY09 Citizens’ Report)

• 1 in ~15 million passengers• Shuttle LOC/LOV ultimately was 2 out of 135

• 1 in ~68 missions (or ~4 in 270)• Shuttle fatalities 14 out of ~800 ‘passengers’

• 1 in ~60 / passengers over ~30 yrs• Overall LOC probability distribution for an ISS mission shall

have a mean value no greater than… (NASA CCT-REQ-1130, 4.0)

• 1 in 270



Research Methodology

Σ S/C = f (physics) + f (physiology)Non-negotiable Design Parameters

required to effectively accomplish mission objectives

+ f (safety) + f (operability)Design Trade Space ‘Figures of Merit’

incorporated to reduce risk and improve crew utilization

3



NASA CCT-REQ-1130 ISS Crew Transportation and Services Requirements Document

NASA SSP-50808 ISS to COTS Interface Requirements Document

NASA NPR 8705.2B Human-Rating Requirements for Space Systems

AFSPCMAN-91-710 Range Safety User Requirements

131

31ESMD-CCTSCR-12.10 CCTS Certification Requirements for NASA LEO Missions

258

Requirements

724

4692

5721

Research MethodologyGoverning Documents



Research MethodologySelect Literature (of ~160+)

• NASA (1965), “Apollo Launch-Vehicle Man-Rating: Some Considerations and an Alternative Contingency Plan”, RM-4489-NASA, May 1965.

• Hacker, BC and Grimwood, JM (1977), “On the Shoulders of Titans: A History of Project Gemini”, NASA SP-4203.

• NASA (1988), “Guidelines for Man Rating Space Systems,” JSC-23211, September 1998.

• NASA (1995), “A Perspective on the Human-Rating Process of U.S. Spacecraft: Both Past and Present”, NASA-SP-6104, 1995.

• Bond, AC (1998), “A Review of the Man-Rating in Past and Current Manned Space Flight Programs”

• Aerospace America (2010), “Human Rating: A Roundtable Discussion”, American Institute of Aeronautics and Astronautics, Vol. 48, No. 7

• Franzini, BJ and Fragola, JR (2011), "Human rating of launch vehicles: Historical and potential future risk," Reliability and Maintainability Symposium, Lake Buena Vista, FL, Jan 24-27, 2011.



Results or Schedule/Milestones ~yr 1

• Task 1 – Literature review, ~160 papers compiled and categorized to date, government / industry practice surveys in work

• Task 2 – Attended COE Roadmap Workshop Wash. DC (August 2011) and assimilated outcome into research objectives

• Task 3 – Collaboration with stakeholders initiated, other commercial partners are being contacted

• Goals identified during the Washington DC Roadmap Workshop to be further reviewed with industry and government partners

• Task 4 – COE research objectives for Human Rating task being aligned with academic plans for the PhD student, Christine, working on this project



Next Steps – outcome from Aug 2011 Roadmap Workshop

4









Next Steps – new AIAA ICES Conference Session, July 2012

Human Rating for Space SystemsThis session engages industry, government, and academia in the definition and analysis of safety and mission assurance parameters as they relate to the design and operations of spacecraft intended for human occupancy. One key objective is to assess the relevancy and commonality of requirements and policies for NASA and FAA commercial human spaceflight missions.

Organizers:David Klaus, University of Colorado, klaus@ colorado.eduRene Rey, FAA



Contact Information

Professor David KlausAerospace Engineering Sciences Dept.University of Colorado / 429 UCBBoulder, CO 80309-0429

[email protected]

5/15/2012

1

1

Unified 4D Trajectory Approach for Integrated

Management of Commercial Air and Space

Traffic

FAA CoE for CST Technical MeetingMillennium Harvest House, Boulder, CO

November 9, 2011

Juan J. Alonso and Thomas ColvinDepartment of Aeronautics & Astronautics

Stanford University

1 2

Overview

• Team members

• Purpose of Task


• Results

• Next Steps


3

Team Members

• PI: Juan J. Alonso, Department of Aeronautics & Astronautics, Stanford University

• Thomas J. Colvin, Graduate Student, Department of Aeronautics and Astronautics, Stanford University

• Collaborations/discussions with:

• Banavar Sridhar, NASA Ames

• Karl Billimoria, NASA Ames

4

Purpose of Task

• Projected growth in demand will make it increasingly hard to accommodate launches on a SUA basis

• Looking for a more rational approach that:

• can adapt to fluctuating frequency of launches

• can accommodate uncertainties in trajectories

• ensures proper separation at all times

• can be integrated with FAA’s NextGen system

5/15/2012

2

5

Research Objectives

1.Develop plausible architectures for an Integrated Airspace Management System (IAMS)

2.Research and develop the foundation of such a tool based on time-space probabilistic trajectories

3.Create a prototype implementation for a proof-of-concept system

• During first few months, we are focusing on item 2

6

Methodology & Results• Problem:

Need Special Use Airspace (SUA) for rocket launch

Current method for creating SUA may be overly conservative

Fairness issues: are we favoring one industry over another?

No quantitative framework for creating SUAs

• Proposed Solution:

Create a probabilistic framework for creating SUAs to a specified level of safety

7

Conceptual Framework

Uncertain Trajectory

Time

Alti

tude

8

Initial Research Goals• Focus on:

✓ Investigate ways in which a compact 4-D envelope can be created and specified

✓Demonstrate the 4-D envelope concept in 3-D (x,y,t)

✓Begin creating a software architecture that generates 4-D envelopes for specific launch profiles

✓Use Monte Carlo simulation to approximate the rocket location PDF, sampled at many points, to a given level of safety

• Provide hooks for, but do not spend significant time on (refined later):

- Accurate characterization of weather profiles, failure modes and probabilities, debris model

5/15/2012

3

9

• 2-D round rotating Earth

Propagate r, V, φ, γ

• SSTO launch vehicle

• Optimal trajectory has thrust vectoring (T, ξ)

• Aerodynamic effects are roughly modeled

Nominal Trajectory

Source: Capristan, F. “Aerodynamic Effects in Launch Vehicle Optimal Trajectories”

10

Weather Uncertainty5% Uncertainty in Temperature

20% Uncertainty in Wind Velocity

11

Creates Drag Uncertainty

12

Uncertain Lift-off Time

• Rockets do not always launch on time

One-sided, multi-modal pdf

5/15/2012

4

13

Failure Uncertainty

Assume 1% of all launches fail

Failure occurs near pad or at max q

14

• Software framework that accepts arbitrary:

• Thrust profiles (TVC, etc)

• Weather profiles for wind and temperature, with uncertainty parameters for each

• Failure parameters and distributions

• Debris model

• Outputs:

• Collection of uncertain trajectories with debris-generating failure events from a MC simulation

What We’ve Got So Far

15

• Trajectories as points in space and time

• Risk level of 10^-10, approximated with MC

• How do we turn this set of trajectories into something useful?

• Methods Available

• Level Sets

• Delauney Triangulation

• Convex Hulls

• Non-convex Footprints

4D Probabilistic Trajectories and Envelopes

16

Swinging Arm• Generates multiple

disconnected “footprints”

• Non-convex, non-regular polygon

• Creates groupings that visually appear more accurate

• Generalizes up to 3D

• Arm short enough, multiple footprints

• Cons:

• Non-regular polygons

Source: Galton, A. “What is the region occupied by a set of points?”

5/15/2012

5

17

Footprint Example

18

QuickTime™ and a decompressor

are needed to see this picture.

Footprint Example

19

Making the next footprint• Arm length short

enough, get multiple footprints

• Remove interior and boundary points

• Crossings:

• Odd is in

• Even is out

20

An Early Footprint



5/15/2012

6

21

Footprint Through NAS (L=40km)



22




23




24

• Tube: 51,400 km2 sec

• Conservative. No safety factors.

• Convex: 15,300 km2 sec

• 30% of the original volume

• Footprint 2km arm: 6,500 km2 sec

• Only 13% of the original volume!

Volume Savings



5/15/2012

7

25

• Conclusions:

• Code accepts arbitrary thrust, weather, and failure profiles for Monte Carlo simulation of uncertain trajectories

• Creates multiple polygonal envelopes around the trajectories (and debris) that represent a no-fly zone

• Demonstrates the possibility of significant volume (area*sec) savings over conventional tube approach

• Future Work:

Full 4-D (Swinging Slab)

Accurate weather and debris models with uncertainty

Active control in rocket during ascent and staging

Integration with NASA’s FACET tool for scenarios with various launch sites frequencies + typical day in the NAS

Conclusions & Future Work

26

• De Berg, M., et al. “Computational Geometry - Algorithms and Applications”, Springer 1998

• Capristan, F. “Aerodynamic Effects in Launch Vehicle Optimal Trajectories”, Stanford 2010

• Osher, S.J., Fedkiw, R.P. “Level Set Methods and Dynamic Implicit Surfaces”, Springer 2002

• Galton, A., Duckham, M. “What is the region occupied by a set of points?” GIScience 2006, LNCS 4197, pp. 81-98, 2006

• Goldman, R. "Intersection of Two Lines in Three-Space." In Graphics Gems I (Ed. A. S. Glassner). San Diego: Academic Press, p. 304, 1990.

• Colonno, M. R., S. Reddy, and J. J. Alonso. "Multi-Fidelity Trajectory Optimization with Response Surface-Based Aerodynamic Prediction." (2008)

• Stengel, Robert. "Launch Vehicle Design: Trajectories and Aerodynamics." Launch Vehicle Design Class Notes. N.p., n.d. Web. 26 May 2010. <http://www.princeton.edu/~stengel/MAE342Lecture3.pdf>.

References

27

Backup Slides

28

Level Sets• Useful for visualizing dynamic

interfaces

• N-Dimensional surface is slice of an (N+1)D function

• Easily handles pinching and merging interfaces

• Set operations are easySource: http://en.wikipedia.org/wiki/Level_set_method

5/15/2012

8

29

• Hard to create the distance function

• Finding the area enclosed is not straightforward

• Allows holes within the boundary

• Slow



Level Set Example

30

Delauney Triangulation

Source: Galton, A. “What is the region occupied by a set of points?”

• Overview

• Connect all dots with series of triangles

• Remove boundary edges

• Generates single connected regular polygon

• Cons:

• Want to eliminate most points! Worth it?

• Creates a single shape

31

Convex Hulls

• Easy to generate

• Wastes a lot of space

• Only get one shape

• Can get these with footprint methods

32

• Order all points from top to bottom, right to left.

• Set all points as ‘available’ and pick an arm length

• Store top-right available point in footprint and set it as current point:

• Swing the arm clockwise from current point until it hits another point

• Store this point as being in the footprint and set it as the new current point

• Repeat until current point == starting point

• Set all points that form or are interior to the footprint as ‘unavailable’

• Repeat until all points are unavailable

• xxxx

Swinging Arm Algorithm

1





Space Environment MMOD Modeling and Prediction

Sigrid Close



Overview• Team Members• Purpose of Task• Research Methodology• Results• Next Steps• Contact Information



Team Members • Sigrid Close, Stanford University• Alan Li, Stanford University (graduate student)



Purpose of Task• Spacecraft are routinely impacted by space debris and

natural impactors- Mechanical damage: “well-known”, larger (> 120 microns), rare- Electrical damage: “unknown”, smaller/fast, more numerous

• Debris vs. meteoroids threat to LEO spacecraft- Mechanical threat: comparable- Electrical threat: dominated by meteoroids

• Goal: Characterize impactor population through data analysis and modeling

2



Impactors

• Dust and Meteoroids− Speeds

• 11 to 72.8 km/s (interplanetary)• > 72.8 km/s (interstellar)

− Densities• rocky or ice-like

− Sizes• < 62 microns in diameter (dust)• 62 microns to 0.3 m in diameter (meteoroid)

• Space Debris− Speeds: < 12 km/s− Higher densities− Varying sizes



Methodology: Meteoroids• Models: Formation of plasma (PIC), Interaction of

electromagnetic waves with plasma (FDTD), Atmosphere• Data: Ground-based plasma, in-situ impact• Research and Deliverables

- Flux- Mass, density- Velocity, orbit

Time (sec)

Alti

tude

(km

)

SNR

(dB

)



Methodology: Debris• Models: Propagation of debris in space and time (Force

Model), Atmospheric models (MSIS, Jacchia-Bowman)• Data: Ground-based/in-situ impact for detection, Light-

gas gun for debris source• Research and Deliverables

- Flux- Source- Prediction



Radar Data High-power ground-based meteor observations

Multi-frequency, multi-polarization, high-sensitivity, high range resolution

RadarsALTAIR

MIT HaystackEISCAT

Arecibo Observatory

8

3



Meteoroid Plasma Modeling

Plas

ma

Freq

uenc

y (M

Hz)

Plasma Radius (a) (m)

|R|2

ALTAIR VHF



Meteoroid Results



Debris Modeling

11

• NASA: ORDEM, LEGEND• ESA: MASTERS• Modeling from sources, propagation, conjunction• Newer sources (perhaps hybrids), newest atmospheric

models (Jacchia-Bowman)• NASA collision model (inadequate in many areas)

- No material dependence- No size and shape factor dependence- Velocity distribution inadequate



Debris Results• Based upon three primary sources

- US Space Command Catalog, Haystack Radar, and in-situ- Auxiliary data provided by HAX radar, Goldstone radar, returned

solar array from Hubble Space Telescope

• Extrapolation based upon EVOLVE for ranges of debris where data is scarce

-200

2040

6080

100

0

500

1000

1500

20000

0.2

0.4

0.6

0.8

1x 10-7

Latitude [degrees]

Spatial Density vs Latitude and Altitude for Debris > 10 cm

Altitude [km]

Spat

ial D

ensi

ty [n

o/km

2 ]

-200

2040

6080

100

0

500

1000

1500

20000

10

20

30

40

Latitude [degrees]

Spatial Density vs Latitude and Altitude for Debris > 0.001 cm

Altitude [km]

Spa

tial D

ensi

ty [n

o/km

2 ]

12

4



Next Steps• Meteoroids

- Compressed sensing techniques for improved detection/analysis- Force modeling for improved orbit determination- Electromagnetic scattering models for plasma diagnostics

• Debris- Characterization of all sources/breakups- Comparison between MASTERS/ORDEM- Propagation and atmospheric models



Publications• Close et al., “Determining Meteoroid Bulk Densities Using

a Plasma Scattering Model with High-Power Large-Aperture Radar Data”, Icarus, in review, 2011

• Reference: National Academies Report: “Limiting Future Collision Risk to Spacecraft: An Assessment of NASA’s Meteoroid and Orbital Debris Programs”



Thank You!• Sigrid Close ([email protected])• Alan Li ([email protected])



Backup

5



ALTAIR Radar Data

VHF

UHF

Time (sec)85

105

Alti

tude

(km

)

0 5



Mechanical and Electrical Damage

Mechanical Damage

massdensity

plasma strengthvelocity

deceleration

Specs Radiated

power

18

Specs

Larger Impactors

FasterImpactors

ElectricalDamage

1





Mitigating threats through space environment modeling/prediction

PI: Tim Fuller-Rowell

Presented by

Tomoko Matsuo

November 9th, 2011 Federal AviationAdministration 2


Team Members

Timothy Fuller-Rowell, Tomoko Matsuo, Houjun Wang, Fei WuCooperative Institute for Research in Environmental Sciences (CIRES)University of Colorado, BoulderNOAA Space Weather Prediction Center

Rashid Akmaev, Mihail Codrescu, Rodney ViereckNOAA Space Weather Prediction Center, Boulder, CO

Jeffrey ForbesAerospace Engineer Sciences, University of Colorado, Boulder



Purpose of Task

Purpose: An integrated air and space traffic management system requires seamless and real-time access to density predictions for on-orbit collision avoidance and atmospheric re-entry, and near-surface weather prediction

Objectives: Develop a “weather” (terrestrial weather and space weather) prediction model extending from Earth’s surface to the edge of space

Goals: Predict the environmental conditions needed for safe orbital, sub-orbital, re-entry, descent, and landing



Drivers of the density variability

Actual Position

Predicted Position

Understandable:since 80% of the forcing above 200km comes from solar and geomagnetic activity

Satellite drag and orbit prediction has traditionally relied on understanding the response to solar and geomagnetic forcing

2



So why a Whole Atmosphere Model• Re-entry calculations have been notoriously bad at predicting

place and time of impact

• With rise in Commercial Space Transportation increasing use of sub-orbital vehicles and need for controlled re-entry, decent and landing

• Altitude region of interest is impacted by both “terrestrial or tropospheric weather” and “space weather”

• Therefore need to characterize the atmospheric conditions seamlessly from the ground to orbital altitudes



Whole Atmosphere Model (WAM)• T62L150 (~ 22, ~ 0-600 km) • Composition thermodynamics• Timing ~ 8 min/day on 32 nodes

Physics- Horizontal & vertical mixing- Radiative heating (EUV & UV) and

cooling (non-LTE)- Ion drag & Joule heating- Major species composition- Non-orographic gravity waves- Eddy mixing

Whole Atmosphere Model (WAM)Global Forecast System (GFS)

• T382L64 (~ 0.30.3, ~ 0-60 km)• 4 forecasts daily• Global ensemble (14 members)

forecasts up to 16 days

Physics- O3 chemistry (parameterized) &

transport- Radiative heating and cooling- Cloud physics & hydrology- Surface exchange processes- Orographic gravity waves- Eddy mixing and convection



Strong Variability at Sub-orbital / Re-entry Altitudes

Observed Variability:zonal winds at mid/low latitudes from rocket-released chemical trails (Larsen, 2002)



Data Assimilation

• Gridpoint Statistical Interpolation (GSI) is the NCEP operational analysis system for global and regional NWP

• Uses a 3-D variational (3DVAR) analysis technique

• Replace GFS with WAM

• Analysis system was modified to use incremental analysis updates (IAU) to avoid use of digital filter, which excessively damps tidal propagation to the thermosphere

• Simulate January 2009 and 2010 periods during large sudden stratospheric warmings

3



70KComparison withEuropean Centre for Medium Range Weather Forecasting (ECMWF)

Terrestrial Weather:Jan 2009 SSW



• Global thermosphere 80 - 500 km, solves momentum, energy, composition, etc., O, O2, N2 (Fuller-Rowell et al., 1996)

• Global ionosphere 80 - 10,000 km, solves plasma continuity, momentum, energy, electrodynamics etc., O+, H+, O2

+, NO+, N2

+, N+(Millward et al., 1996)

• Solar and geomagnetic forcing solar UV and EUV, Weimer electric field, TIROS/NOAA auroral precipitation

(Fedrezzi et al., 2011)

Space Weather Modeling: Coupled Thermosphere-Ionosphere-Plasmasphere (CTIPe) Model

Coupling with WAM



Summary• WAM is designed to forecast the environmental conditions from the

ground to 600km• WAM will cover the orbital, sub-orbital, re-entry, descent, and landing

requirements for atmospheric density• WAM will simulate the internal atmospheric sources of variability (gravity waves,

tides, planetary waves, midnight density maximum, wave 4 structure, sudden stratospheric warmings, etc.)

• Coupled to an ionosphere module, WAM will also be able to respond to space weather forcing (solar flares, geomagnetic storms, solar proton events) to address not only density requirements, but also communications and navigation needs

• WAM will follow, and forecast several days ahead, the whole atmosphere dynamical response to atmospheric processes using a modified version of the NCEP GSI operational data assimilation system

• WAM will also provide environment conditions for micrometeoroid and orbital debris detection / avoidance (Sigrid Close) and collision probability for space situational awareness (Dan Scheeres)



Next Steps• Extend WAM data assimilation into the lower thermosphere

(SABER, MLS temperatures, etc.)

• Test higher resolution WAM T382 (35 km resolution) to resolve wave field penetrating to the thermosphere and test semi-annual variation in density

• Full coupling of the ionosphere (e.g., Ionosphere-Plasmasphere-Electrodynamcis (IPE) model, CTIPe) to respond to solar and magnetospheric forcing

• Explore assimilation of ionospheric data for density prediction

• Whole atmosphere/ionosphere data assimilation at high resolution

• Transition at NOAA

4



Contact Information• Dr. Tim Fuller-Rowell, Physicist, Cooperative Institute for Research in Environmental Sciences,

University of Colorado/Space Weather Prediction Center, [email protected]

• Dr. Tomoko Matsuo, Physicist, Cooperative Institute for Research in Environmental Sciences, University of Colorado/Space Weather Prediction Center, [email protected]

• Dr. Houjun Wang, Physicist, Cooperative Institute for Research in Environmental Sciences, University of Colorado/Space Weather Prediction Center, [email protected]

• Dr. Fei Wu, Physicist, Cooperative Institute for Research in Environmental Sciences, University of Colorado/Space Weather Prediction Center, [email protected]

• Dr. Rashid Akmaev, Physicist, NOAA/Space Weather Prediction Center, [email protected]

• Dr. Mihail Codrescu, Physicist, NOAA/Space Weather Prediction Center, [email protected]

• Dr. Rodney Viereck, Physicist, NOAA/Space Weather Prediction Center, [email protected]

• Professor Jeffrey M. Forbes, Department Chair, Aerospace Engineering Sciences, University of Colorado, [email protected]


COE CST First Annual Technical Meeting (ATM1)November 9 & 10, 2011 1



Space Situational Awareness

D.J. Scheeres

November 9, 2011 Federal AviationAdministration


Overview•Team Members•Purpose of Task•Research Methodology•Results•Next Steps•Contact Information



SSA Team Members Direct Support from the FAA COE•Dan Scheeres, CU Professor, PI•George Born, CU Professor, Co-I•Bob Culp, CU Professor Emeritus, Co-I•Brandon Jones, CU Research Scientist•Kohei Fujimoto, CU PhD CandidateRelated Research from Fellowship Students•Aaron Rosengren, CU Graduate Student•Antonella Albuja, CU Graduate Student•Ddard Ko, CU Graduate StudentGovernment and Industry Partners•AFRL Kirtland and Maui•NASA Orbit Debris Program Office •Analytical Graphics, Incorporated•Orbital Sciences Corporation



SSA Team Members Direct Support from the FAA COE•Dan Scheeres, CU Professor, PI•George Born, CU Professor, Co-I•Bob Culp, CU Professor Emeritus, Co-I•Brandon Jones, CU Research Scientist•Kohei Fujimoto, CU PhD CandidateRelated Research from Fellowship Students•Aaron Rosengren, CU Graduate Student•Antonella Albuja, CU Graduate Student•Ddard Ko, CU Graduate StudentGovernment and Industry Partners•AFRL Kirtland and Maui•NASA Orbit Debris Program Office •Analytical Graphics, Incorporated•Orbital Sciences Corporation



Purpose of Task•Space Situational Awareness

SSA = Cognizance of Resident Space Objects (RSO) and activities in orbital regions of interest, both now and in the short and long-range future.

•Objectives: Improve SSA abilities in regions of interest to the FAA for space-based activities.

•Current regions of focus: LEO-down and GEO-up•Goals are to improve: uncertainty modeling and propagation, precision long-term orbit propagation, non-gravitational model prediction and estimation, orbit estimation techniques.

D.J. Scheeres, A. Richard Seebass Chair, University of Colorado at Boulder 5

Long-Term Probability Density Function Propagation

• Developing novel semi-analytical solutions for propagation– Enables rapid and accurate uncertainty propagation

– Leverages decades of research in analytical celestial mechanics research

– Is being extended to perturbations and non-conservative forces

– Serves as an enabling and foundational framework for other advances in estimation, dynamic modeling, and conjunction analysis

2-Body Propagation over 100 orbits

80 60 40 20 0 20 40 60−12

−10

−8

−6

−4

−2

0

2x 10

−3

2-Body + Drag over 10 orbits

D.J. Scheeres, A. Richard Seebass Chair, University of Colorado at Boulder 6

Non-Gravitational Modeling & Dynamics

• Solar Radiation Pressure non-grav models developed for asteroids can be directly applied to RSO dynamics and models– Time scale of interest for asteroids, ~ 1E4 -> 1E6 years

– Equivalent time scale of interest for RSO ~2 -> 200 years for LEO to GEO

– Current focus on High Area to Mass Ratio object dynamics in GEO, rotational dynamics of debris, estimation of non-grav models (drag and solar radiation)

Initial Condition

A/M = 15

A/M = 45

A/M = 75

esinω

e cosω

−1 −0.5 0 0.5

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

1

Eccentricity Vector of HAMR Objects

0 2 4 6 8 100

0.5

1

1.5

2

2.5

3

3.5x 10

8 Eccentricity

# of Orbits

Ecc

entr

icity

NumericalAnalyticalShort

Eccentricity of the Grace Satellite

of Colorado at Boulder

0

D.J. Scheeres, A. Richard Seebass Chair, University of Colorado at Boulder

Short-Arc RSO Correlation

• Given two observations of RSO separated in time, can we determine if these are the same object?

• If they are, can we achieve an initial orbit determination estimate?

• A new approach to initial orbit determination and correlation has been developed – “Best Paper of Conference” in 2010.– Hypothesis-free correlation testing – fundamental improvement of process

– Robust and rigorous approach to combining sparse track observations

– Method based on the topology of probability density functions in 6-D space

7



Lp-norm Orbit Determination• Orbit determination in LEO faces data association and quality challenges.

• Mis-tagged data or measurement outliers can force an orbit estimate to diverge or yield poor convergence that compromises the entire catalog maintenance activity.

• To remedy this we are developing nonlinear, adaptive estimation capabilities that are independent of and insensitive to measurement error distribution

• Current focus is on using minimum L1-norm orbit determination, which provides robust estimation capabilities that are insensitive to data mis-tagging and outliers.

• Tools are being developed to explore the applicability and use of this approach



Results since commencement of funding

• Journal Papers in press:• K. Fujimoto and D.J. Scheeres. “Correlation of Optical Observations of Earth-Orbiting Objects and Initial Orbit Determination,"

Journal of Guidance, Control and Dynamics, in press, 2011.

• K. Fujimoto, D.J. Scheeres and K.T. Alfriend. “Analytical Non-Linear Propagation of Uncertainty in the Two-Body Problem," Journal of Guidance, Control and Dynamics , in press, 2011.

• Conference Papers:• K. Fujimoto, D.J. Scheeres , and K.T. Alfriend. “Analytical Non-Linear Propagation of Uncertainty in the Two-Body Problem," paper

presented at the 2011 AAS/AIAA Spaceflight Mechanics Meeting, New Orleans, February 2011. Paper AAS 11-202.

• A. Rosengren and D.J. Scheeres. “Averaged Dynamics of HAMR Objects: Effects of Attitude and Earth Oblateness,” paper presented at the 2011 AAS/AIAA Astrodynamics Specialist Meeting, Girdwood, Alaska, August 2011. Paper AAS 11-594.

• D.J. Scheeres and A. Rosengren. “Closed Form Solutions for the Averaged Dynamics of HAMR Objects,” paper presented at the 62nd International Astronautical Congress, Cape Town, South Africa, October 2011.

• K. Fujimoto and D.J. Scheeres. “Non-Linear Propagation of Uncertainty With Non-Conservative Effects," paper submitted to the 2012 AAS/AIAA Spaceflight Mechanics Meeting, Charleston, SC, Jan/Feb 2012.

• S. Gehly, B. A. Jones, P. Axelrad, G. H. Born, "Minimum L1 Norm Orbit Determination Using a Sequential Processing Algorithm", paper submitted to the 2012 AAS/AIAA Spaceflight Mechanics Meeting, Charleston, SC, Jan/Feb 2012.

• Industry Interactions:• Exchanges of simulated data with AFRL Maui research personnel.

• Interactions with NASA Orbit Debris Program Office and the Center for Space Standards & Innovation (AGI)

• Dissemination of orbit determination tools to Aerospace Corp. researchers for analysis and testing.



Next Steps•Funding for Year 2 is now in-place.•Mechanisms for matching funds have been identified and taken advantage of.

•Research progressing on all fronts identified.•Dissemination of research into conference and journal literature is on-track.

Interested in collaborations with other COE-CST supported Research Tasks

10 Federal AviationAdministration


Contact Information

Dan [email protected]

720-544-1260

1





Defining the Future by Engaging Emerging

Leaders

Task 193:Role of COE CST in EFP

PI: George H. BornBradley Cheetham

11.10.2011 Federal AviationAdministration 2



• Task Purpose/Objectives

• Theory Based Analysis

• ESIL Workshops

• SpaceVision 2011

• Next Steps




Team Members • George H. Born – Director, Colorado Center for

Astrodynamics Research

• Bradley Cheetham – Graduate Research Assistant, Aerospace Engineering Sciences

• Juliana Feldhacker – Graduate Research Assistant, Aerospace Engineering Sciences



Purpose of Task• Objectives:

• Identify key industry characteristics to facilitate EFP efforts

• Support on-going FAA COE CST roadmapping efforts

• Hosted workshops for student and young professionals

• Support conferences to educate students and young professionals

• Incorporate young professional perspectives in ongoing efforts

2



FAA COE CST Objectives• Research

• Industry Structural Analysis – Commercial Crew to Orbit Industry Segment

• Training• Emerging Space Industry Leaders (ESIL-01)

Workshop

• Outreach• SpaceVision2011 Support



Theory Based AnalysisStrategic Evaluation of Commercial Crew to Orbit Transportation Industry Structure and Status

• Presented at 2011 International AstronauticalCongress

• IAC-11-D4.2.1

• Second iteration on analysis

• Based on Michael Porter Competitive Strategy Theory



Theory Based AnalysisScope: Commercial delivery of humans to Earth orbit

– Considering the transport vehicle only

– Launch vehicle is a supplier



ESIL Workshop• Bring together emerging industry leaders

• Objectives• Inform – perspective, background, context

• Perform – group analysis on identified market

• Network – internal and external to industry

• Output• Theory based analysis on self-selected market

3



ESIL WorkshopESIL-01

10.26-10.27



ESIL Workshop



ESIL Workshop



SpaceVision 2011• Objective

• Support dissemination of industry information to broad diverse student population

• Mechanism of Support• Partner with CU SEDS chapter

• Speaker advising and assistance

• Recording/Dissemination of programming

• Corporate partnerships

4



SpaceVision 2011



SpaceVision 2011



SpaceVision 2011



Next Steps• Industry Structural Analysis

• Third iteration as industry evolves – Fall 2012

• ESIL-02• Discussing options in Spring 2011

• ESIL-##• Future workshops hosted around the country in

collaboration with other industries

• SpaceVision 2012• Support efforts Fall 2012

5



Contact Information

George H. [email protected]

Bradley [email protected]



Questions

Federal Aviation Administration 1

COE CST First Annual Technical Meeting (ATM1) November 9 & 10, 2011

Federal Aviation Administration COE-CST Research

Roadmapping

Professor Scott Hubbard & Graduate Student Jonah Zimmerman

Department of Aeronautics and Astronautics

Stanford University

November 10th, 2011 Federal Aviation Administration 2


• Phase I - Preliminary Foundation - Identify Scope - Find leadership and acquire sponsorship - Demonstrate problem being solved

• Phase II - Development Phase - Designate “product” that is the focus - Identify the critical requirements and technology/research areas - Study research alternatives and create needs timeline - Write roadmap report

• Phase III - Building Consensus and Follow-up - Explain roadmap to larger community - Obtain independent critique and validation - Update as needed

Roadmapping Methodology

*Adapted from Fundamentals of Technology Roadmapping , Garcia and Bray, SNL, 1997

Current Status: Beginning Phase III



Workshops • Stanford University -April 6-7, 2011 -51 representatives of industry, academia,

government -Defined initial theme objectives and structure

• Washington DC -Lockheed Martin Global Vision Center -August 15-17, 2011 -73 representatives in attendance -Refined theme structure and research prioritization



Results

Finalized Research Theme Structures



Results – Research Priorities • Theme 1 - Space Traffic Management (STM) and Operations: - Mission Statement: The STM task will focus on facilitating commercial

utilization of orbital space resources, free from physical interference, by implementing technical and regulatory provisions. The National Airspace System (NAS) integration and spaceport operations task will focus on integrating commercial space vehicle and spaceport operations into the NAS by providing equitable sharing of NAS resources for both air and space traffic.

- High-Priority Research: In order to reduce the imposition made on the National Airspace System and facilitate the integration of air and space vehicle traffic, a minimum safe corridor for launches and re-entries must be identified.



Results – Research Priorities • Theme 2 - Space Transportation Operations,

Technologies, and Payloads: -Mission Statement: Perform research to significantly

improve reliability/safety/risk posture and availability for stakeholders in full mission cycle vehicle operations and ground operations while ensuring that proper business case closes (and no negative interactions with rest of participants).

-Recommendation: Further effort is ongoing to identify top research objectives from the technological landscape. This will require iterative effort between this theme and the other three themes.



Results – Research Priorities • Theme 3 - Human Spaceflight: -Mission Statement: It is the goal of the human spaceflight

research area to optimize the human and spacecraft systems for performance, safety, and access for commercial human spaceflight.

-High-Priority Research: Verifiable guidelines are needed for all spaceflight participants. To develop these, extensive data on the risks of various medications and conditions in the space environment are required.



Results – Research Priorities • Theme 4 - Space Transportation Industry Viability: -Mission Statements: - 1) The purpose of the Industry Viability research area

support effective policy decision-making and reflect the dual regulatory and promotional missions of the FAA Office of Commercial Space Transportation.

- 2) Research addressing regulation is designed to maximize regulatory cost-effectiveness; research concerning promotion aims to maximize industry growth.

-High-Priority Research: What “the market” is remains an open question to the CST industries. Identifying and verifying the suborbital and orbital microgravity commerce and research opportunities is of prime importance.



Results – Sample Research Tasks • Theme 1 - Space Traffic Management (STM) and Operations:

- De-confliction of air and space traffic • Required airspace for different vehicles and missions • Air-space transition corridors

• Theme 2 - Space Transportation Operations, Technologies, and Payloads: - Research and recommend safe, expeditious, and cost efficient processing of

reusable manned or unmanned vehicles that are payloads on ELV’s • Landing, inspection, modification if needed, transportation, and integration

• Theme 3 - Human Spaceflight: - Evaluate specific medical conditions in high-g environment utilizing centrifuge

facilities - Support the development of medical kits for various suborbital and orbital flight

scenarios • Theme 4 - Space Transportation Industry Viability:

- Retrospective analysis of: • Transition from government to private customers • Commercial failures

- Proactive analysis of research capabilities and research requirements



Future Work • Report status: -First draft completed -Major revisions based on Ken Davidian’s

comments underway • Next steps: -Disseminate results to the community -Improve based on resulting comments and

critiques -Update periodically -Implement roadmap into COE’s research planning

and decision making



Contact Information

• Scott Hubbard <[email protected]>

• jonah zimmerman <[email protected]>

5/15/2012

1





COE CST FIRST ANNUALTECHNICAL MEETING:

Develop an Accepted Framework to Capture the Body of Knowledge for Commercial Spaceport

Operations Best Practices Through 2012

PI: Patricia C. Hynes, Ph.D.

November 9, 2011

1






Overview

• Team Members• Purpose of Task• US Spaceports• Research Methodology• Results• Next Steps• Website• Contact Information

2





Team Members• Pat Hynes, PI, New Mexico State University

• Herb Bachner, Commercial Space Working Group, CSSI

• Jim Hayhoe, Spaceport America Consultants

• Judy McShannon, New Mexico State University

• Paul Arthur, Rear Admiral (Retired), Former Technical Director/Deputy Commander, White Sands Missile Range

• Craig Day, Director, Business Development, AIAA

• Terri Alexander, Project Manager, The Boeing Company

• Robert Reuter, Project Manager, The Boeing Company

• Sandy Saunders, Vice President Operations, Locked On, Inc.• Morgan McPheeters, NMSU Graduate, Spring 2011

3Federal AviationAdministration 4




Purpose of Task

Task 1: Develop a Framework ‐ CompletedPrepare the framework in collaboration with spaceport directors• February 2011 • Public meeting to discuss framework variables• Update framework variables to account for public input• Survey spaceport executive directors and selected range

operators

4

5/15/2012

2





U.S. SpaceportsCommercial/Government/Private Active and Proposed Launch Sites

Kodiak Launch Complex

Blue Origin Launch site

Vandenberg AFB

California Spaceport

Mojave AirportEdwards AFB

White Sands Missile Range

SpaceportAmerica

Oklahoma SpaceportWallops FlightFacility

Spaceport Florida

‐Kennedy Space Center‐Cape CanaveralAir Force Station

Mid‐AtlanticRegional Spaceport

Reagan Test SiteKwajalein Atoll, Marshall Islands

Sea Launch PlatformEquatorial Pacific Ocean

KeyU.S. Federal Launch Site (2)Non-Federal FAA-LicensedLaunch Site (7)Owned by University of Alaska GeophysicalInstituteSole Site Operator

Cecil FieldSpaceport

FAA/AST: August 2011

Other spaceports have been proposed by: Alabama, Washington,Hawaii, Wisconsin, Wyoming, Indiana and multiple locations in Texas.

Poker FlatResearchRange






• Develop a framework for spaceport operations and test the framework through the use of a survey of Spaceport Directors and military Range Commanders.

• Analyze the classification system for further categories until the results of general operations procedures and practices reflect a comprehensive body of knowledge of best practices for commercial spaceport operations.

6





Results

• Survey• N=8 (spaceport directors and members of the Range Commanders Council who operate federal ranges)

• 142 variables were surveyed

7Federal AviationAdministration 8




Include

Not In This Topic

Do Not Include

142 Survey Items (100%)

Broad Agreement Among Spaceport Operators

5%

86%

9%

Average Response Scores for COE Body of Knowledge

5/15/2012

3





Survey Results ‐sample

9

1.0 AIRFIELD AND LAUNCH OPERATIONS Include Do Not Include

Not in This Topic

1.1 OPERATIONAL INFRASTRUCTURE & ACTIVITIES1.1.1 Runways 87.5% 12.5% 0.0% 1.1.2 Terminal Facilities 75.0% 12.5% 12.5% 1.1.3 Aircraft Rescue & Fire Fighting Facilities 87.5% 0.0% 12.5% 1.1.4 Hazardous Materials Storage & Transfer Facilities 75.0% 0.0% 25.0% 1.1.5 Aircraft/Spacecraft Tie‐Down Areas 75.0% 25.0% 0.0% 1.1.6 Hangar Facilities 75.0% 25.0% 0.0% 1.1.7 Mission Control Facilities 75.0% 25.0% 0.0% 1.1.8 Launch Control Facilities 75.0% 25.0% 0.0% 1.1.8.1 Launch Pad Safety 50.0% 0.0% 50.0%1.1.8.2 Maintenance of Ground‐Based Launch & Flight Safety Sys. 62.5% 25.0% 12.5%1.1.9 Spaceflight Preparation Facilities 87.5% 12.5% 0.0%





Task 2: Research into existing and applicable practices, documents and other relevant material related to framework classification areas: The study will be conducted to capture documents related to existing practices and standards from all sources applicable to commercial spaceports. Task will start January 1 and will be completed by December 31. 2012.

10

Next Steps





Task 3: Gap Analysis:A gap analysis will be conducted to compare the variables in Framework of Task 1 with the existing practices, standards, policies and best practices documentation identified in Task 2. Identify where gaps exist.Task 3 will be completed by the end of 2013.

11

Next Steps (cont.)





COE CST Study TeamDocument Website

http://aiaa.kavi.com/apps/org/workgroup/coe_st/?referring_url=%2Fkws

12

5/15/2012

4





Contact Information• Pat Hynes, [email protected]• Herb Bachner, [email protected]• Jim Hayhoe, [email protected]• Judy McShannon, [email protected]• Paul Arthur, [email protected]• Craig Day, [email protected]• Terri Alexander, [email protected]• Robert Reuter, [email protected]• Sandy Saunders, [email protected]

13

1




Task 228:Magneto-Elastic Sensing

for Structural Health Monitoring

Andrei Zagrai and Warren Ostergren



Overview• Structural Health Monitoring (SHM)

of Space Vehicles• Motivation, needs and objectives• Research team• Tasks progress• Schedule & Milestones• Next Steps• Contact Information



Structural Health Monitoring3



SHM ofSpacecraft

4

2



Example: Monitoring of Bolted Joints

Key Issues: Structural complexity Many interfaces Classification of nonlinearsource



SHM Tasks for Space Vehicles• Rapid assembly and launch

• Validating the condition of stored (in a warehouse) structural elements

• Facilitating rapid assembly of spaceship components,• Insuring that no structural damage occurred during spaceship

assembly and handling• Minimizing or eliminating pre-flight tests, e.g. thermavac, vibration• Model update using SHM data• Monitoring during transport

• Monitoring system condition and dynamics during launch,• In-orbit / mission monitoring

• Component deployment and wakeup• Mission parameters and associated loads• Assessing in-service variation of structural properties suitable for

model updating and in-orbit system optimization.• Micro-meteorite / debris impact detection and characterization• Electrical signature, electronics, space weather – indirectly.



SHM Tasks for Reusable Spacecraft7

2.63 2.64 2.65 2.66 2.67 2.68 2.69

-0.05

0

0.05

0.1

0.15

0.2

Frequency, kHz

Impe

danc

e

SYB-NonSt-UFSYB-NonSt-F-10,000SYB-NonSt-F-20.000SYB-NonSt-F-30,000SYB-NonSt-F-40,000SYB-NonSt-F-50.000

30 35 40 45 50

-0.2

0

0.2

Time, microseconds

Sign

al A

mpl

itude

UndamagedDamaged

• Re-entry• Structural integrity and material

deterioration• Breakup (if any)• Components deploymentBLACK BOX FOR SPACECRAFT !

Re-launch• Fatigue data from previous

mission• Assisting in re-qualification pre-

launch tests.• Spacecraft degradation model

update. GO/NO-GO?



NMT Current Space Activities ME&EEPRACTICAL TESTS AND HARDWARE

• Validation of SHM on AFRL’s PnP Sat, 2009• SL5 suborbital 2011• Swiss PnP Sat Langmiur probe mech. design

(scheduled for launch later this 2011 year)• ELANA New Mexico Sat (NASA)• Nano-sat program/competition: Boston Univ. Sat• New Mexico Tech Sat (NASA EPSCoR)• SL7 suborbital 2013

3



9

16.55 16.6 16.65 16.7 16.75 16.84

4.5

5

5.5

6

6.5

7

7.5

8

8.5x 10

4

Frequency (kHz)

Res

ista

nce

(Ohm

)

S1 Bolted Joint

T=47.0 sT=86.3 sT=164.9 sT=204.2 sT=282.7 sT=322.0 sT=361.3 sT=400.5 sT=439.8 sT=479.0 sT=518.3 sT=557.5 sT=636.0 sT=675.3 sT=753.8 sT=793.0 sT=832.3 sT=871.5 sT=910.8 s

Very small frequency changes during first 3.5 minutes of flight

Substantial amplitude and frequency changes during

reentry

Stable readings after landing ≈ 13 minutes

LAUNCH SITEUPHAM,NEWMEXICO

BOOSTERBURNOUT

11.7SECONDSTOUCHDOWN

13MINUTES 12.6SECONDS

DEFINITION OFSPACE

62MILES(100KM) DROGUE DEPLOYMENT


ENTER SPACE1MINUTE 41SECONDS

APOGEE70.75MILES


RE‐ENTRY3MINUTES 29.1

SECONDS

PAYLOADSEPARATION45SECONDS

PARACHUTEDEPLOYMENT7MINUTES39.8

SECONDS

SHM During Suborbital Flight of Spaceloft Rocket

May 20, 2011



Needs• Reliable multi-purpose sensing technology with• Very robust durable sensors that would have long

lifespan in space environment and can:• Detect and characterize impact damage from

space debris• Assess structural integrity of a spacecraft• Provide information on structural interfaces• Explore spacecraft electrical signature• Enable reusable component requalification for flight• Possibly conduct non-contact inspection in space.



Team Members Task 228 NMT Team

• Jaclene Gutierrez (UG ME)• Daniel Meisner (GR ME)• David Conrad (GR ME)• Andrei Zagrai• Warren Ostergren

Collaborators• Igor Sevostianov (MAE NMSU)• Whitney Reynolds (AFRL Space Vehicles)



Purpose and Objectives• The objective of the proposed project is to develop innovative

magneto-elastic sensing technologies for structural diagnosis of space vehicles.

• In achieving this objective, the investigation team conducts both theoretical and experimental research on the physical mechanism of sensing, its practical realization in the engineering system, information inference from the magneto-elastic response and automatic data classification / decision support.

• A separate objective of this research is educating young aerospace professionals at the undergraduate and graduate levels as well as broadening participation of minority groups such as students with disabilities and Hispanics.

4



Schedule/MilestonesTasks

Year 1 Year 2

Months 2 4 6 8 10 12 14 16 18 20 22 24

1. Analytical and numerical magneto-elastic modeling.

2. Magneto-elastic characterization of interfaces and fatigue damage.

3. Damage manifestation in magneto-elastic sensing

4. Damage classification algorithms for magneto-elastic sensing

1-D models for magneto-elastic sensing

Experimental data on magneto-elastic sensing of interfaces in structures of simple geometry

Experimental data on manifestation of electromagnetic and elastic structural characteristics in MMI signature.

Selection of suitable feature extraction algorithms.

Analysis of data classification algorithms formagneto-elastic sensing. A preliminary example

of damage detection and classification.

Milestones

Experimental data on magneto-elastic sensing of fatigue damage in

available laboratory specimens.

Presentation and a full paper in Proceedings of ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, September 2011:Conrad, D. and Zagrai, A. (2011) “Active Detection of Structural Damage in Aluminum Alloy Using Magneto-Elastic Active Sensors (MEAS),” SMASIS2011-5219.



Magneto-elastic Active Sensors (MEAS)

14

Electric current passing through the coil induces eddy currents in the structure.The eddy currents interact with the applied static magnetic field, resulting inLorentz forces, responsible for generating elastic waves.

S

N B

I

FL

FL

z

xy

Structure

Fiberglass tape

Neodymium magnet

CoilAcrylic

tape

Capable ofNON-CONTACT

excitationINSIDE material -NO COUPLING

MEDIUM NEEDED

MEASTypical EMAT

www.qnetworld.com



MEAS Damage Detection Methodologies15

MEAS Electromagnetic Response MEAS Mechanical Response

Lorentz Force

Elastic W

ave

Continuous Wave – Magneto-mechanical impedance (MMI)

Pulse Wave – Pitch-catch ultrasonics



Task 1: MEAS SHM Theory16

0 1 2 3 410

20

30

40

Frequency, kHz

IZI,

Ohm

s

experimenttheory

2 4

2 4

( , ) ( , ) ( , )Lw x t w x tA EI F x t

t x

( , ) ( ) i tL a aF x t I B b x x e

2

2 20

( ( ) )( )

2n a a

strn n n n

i W x b BZ

A i

Zstr~

M

LsLMEAS

RMEAS

A

A`

Lorentz excitation force

Electro-magnetic interaction between MEAS and structure is represented as a transformer

2 2

MEAS S CMEAS MEAS

S S str

L L kZ R i Li L R Z

5



Mechanical Manifestation of Damage

3.59 3.595

39

40

41

Frequency, kHz

IZI,

Ohm

s

h = 1/16

3.19 3.195 3.2 3.205

35

36

37

Frequency, kHz

IZI,

Ohm

s

h = 1/18

Damage was imitated by considering reduction of specimen thickness fromh1 = 1/16 in to h2 = 1/18 in.

Due to reduction of specimen thickness:

1. Frequency shifted from 3.592 kHz to 3.193 kHz, i.e. Δf = 400 Hz.

2. Impedance amplitude increased slightly: 0.5 Ohms.

3. Impedance slope has changed.



Electrical Manifestation of Damage

3.59 3.592 3.594

39

40

41

IntactR10%L and R 10%

Frequency, kHz

IZI,

Ohm

s



3 3.5 4 4.5 5 5.5 61

1.5

2

2.5

3

3.5

Frequency, kHz

Impe

danc

e, O

hms

A0-0mmA1-5mmA2-10mm

A3-15mmA4-20mm

Task 2: Damage in Adhesive Interfaces

3.5 4 4.5 5 5.5 6

0

0.01

0.02

0.03

Frequency, kHz

Impe

danc

e, A

.U.

A0-0mmA1-5mm

A2-10mmA3-15mm

A4-20mm

A0-0mm

A1-5mm

A2-10mm

A3-15mm

A4-20mm



Task 2: Fatigue Testing

0 5 10 15 201

2

3

4

5

6

7

Frequency, kHz

Impe

danc

e, O

hms

0 kc10kc15kc

20kc30kc40kc-crack

ASTM standard: Parameters

6



Task 2: Fatigue Testing

0 5 10 15 200

0.05

0.1

0.15

0.2

0.25

Frequency, kHz

Impe

danc

e, A

.U.

0 kc10kc15kc

20kc30kc40kc-crack

2.2 2.4 2.6 2.8 3 3.2

0.05

0.1

0.15

Frequency, kHz

Impe

danc

e, A

.U.

0 kc10kc15kc

20kc30kc40kc-crack

13 13.2 13.4 13.6 13.8

0.05

0.055

0.06

0.065

Frequency, kHz

Impe

danc

e, A

.U.

0 kc10kc15kc

20kc30kc40kc-crack



Two Aluminum alloy plates (1mm thick), each with a machined slot

One plate was to subjected to 185kcycles of loading from 1.7-17.8kN at which point a fatigue crack was visible on both sides of the slot

The same sensor pair was used on both fatigued and non-fatigued specimens

Fatigue Crack

12

12

Transmitter Locations

Receiver Locations3

3

Machined Slot

Task 3: Damage Manifestation in MEAS Signal



Elastic wave amplitude and phase change due to the introduction of a fatigue crack is easily detectedElastic Wave

MEAS 1 MEAS 2Aluminum Plate

Fatigue Crack

62 64 66 68 70 72 74 76 78 80-4

-2

0

2

4

Time, s

Am

plitu

de, m

A

Fatigued Plate Non-Fatigued PlateTransmitted Elastic WaveSensor

LocationMean Amplitude

Reduction, %

1 3.02 4.53 15.5

Sensor Location

Mean Phase Shift, deg

1 32.62 32.53 32.2




24

60 65 70 75 80 850

10

20

30

40

50

60

Time, sP

hase

, rad

Fatigued Non-Fatigued Ideal

Unwrapped Instantaneous Phase

28.2˚ Phase Difference

60 65 70 75 80 85 90-2

-1.5

-1

-0.5

Time, s

Pha

se, r

ad

Fatigued Non-FatiguedInst. Phase Difference from Ideal

Analytical signal

Instantaneous amplitude and phase

1 Im( ( ))( ) tanRe( ( ))

x ttx t

( ) ( ( )) Re( ( )) Im( ( ))x t Hilbert s t x t i x t

A(t) = |x(t)|=|Hilbert(s(t))|

70 75 80

-50

0

50

Time, s

Phas

e, m

rad

Fatigued Non-FatiguedInst. Phase Diff. – L3

70 75 80

-50

0

50

Time, s

Phas

e, m

rad

Fatigued Non-FatiguedInst. Phase Diff. – L2


7



Next StepsTasks

Year 1 Year 2

Months 2 4 6 8 10 12 14 16 18 20 22 24

1. Analytical and numerical magneto-elastic modeling.

2. Magneto-elastic characterization of interfaces and fatigue damage.

3. Damage manifestation in magneto-elastic sensing

4. Damage classification algorithms for magneto-elastic sensing

1-D models for magneto-elastic sensing

Experimental data on magneto-elastic sensing of interfaces in structures of simple geometry

Experimental data on manifestation of electromagnetic and elastic structural characteristics in MMI signature.

Selection of suitable feature extraction algorithms.

Analysis of data classification algorithms formagneto-elastic sensing. A preliminary example

of damage detection and classification.

Milestones

Experimental data on magneto-elastic sensing of fatigue damage in

available laboratory specimens.

Model for damaged interface

Additional set of samples with interface damage +

experiments with fatigues samples

Separation of electrical and mechanical responses

Long term goal:Black box for spacecraft with integrated SHM data



Contact Information

• Andrei Zagrai• Department of Mechanical Engineering• New Mexico Institute of Mining and Technology• 801 Leroy Pl., Weir Hall, Room 124, Socorro, NM• Ph: 575-835-5636; • Fax: 575-835-5209;• E-mail: [email protected]

5/15/2012

1

Justin CollinsAdvisor: William Oates

Department of Mechanical EngineeringFlorida A&M / Florida State University

Tallahassee, FL 32310

Collaborators: Mark Sheplak, David Mills, Daniel Blood

Motivation Background◦ Structure Property Relations

Current Work◦ SEM Characterization◦ Fracture Analysis

Summary and future work

2

Commercial sensors capable of up to approximately 600 Uses SOI technology

Alternative material sapphire: potentially capable of up to 1600

Laser machining to cut specimens◦ Hard ◦ Chemically Inert

3

Kulite Pressure Transducer

Conceptual Design

• Sapphire crystallographic structure• Complicated by hexagonal cage &

internal rhombohedral structure

• Anisotropic elastic behavior• Rhombohedral—not hexagonal

• Melting temperature 2030

4

klijklij c

Ohno, Phys. Chem. Solids Vol. 47, No. 12. pp. I ION 108. 1986

Kyocera wafer cutsKronberg, acta metallurgica, vol.5, 1957

5/15/2012

2

Fracture characterization◦ Virgin vs. laser

machining Crack opening

quantified◦ Intrinsic crack tip

toughness measured

5

Crack opening displacement

6

o K1c ≅ 2.3 MPa*m1/2

o Gc ≅ 11.65 N/m

7

• K1c ≅ 2.65 MPa*m1/2

• Gc ≅ 16.22 N/m

Indentation at ∼0° Indentation at ∼45°

Preliminary Vicker’s indentation characterization No visible cracks Laser machining parameters◦ 10 kHz rep rate, 10 mm/s scanning speed, 3.8 J/cm2 fluence, 3um stepover

8

5/15/2012

3

Correlated crystal structure with anisotropic elastic properties

Quantified crack tip toughness in virgin sapphire specimens◦ Good correlation with data in literature

Laser machining effects on fracture◦ Unusual toughness enhancement

Hypothesis: Laser induced dislocations◦ TEM characterization and dislocation/fracture

modeling currently underway

9

NHMFL-ASC FAA FAMU-FSU College of Engineering University of Florida◦ Mark Sheplak, David Mills, Daniel Blood, Tony Smitz

(UNC Charlotte)

10

11 12

a

P

5/15/2012

4

Basal dislocations associated with a 100-g indentation on a (0001) basal plane section

Specimen polished with abrasive paper.

How does laser machining affect the properties of sapphire? Are dislocations induced during the process?

13

Hockey ,Journal of The American Ceramic SocietyVol. 54, 1971

1





High Temperature Pressure Sensors for Hypersonic Vehicles

David Mills



Overview• Team Members• Purpose of Task• Research Methodology• Results• Next Steps• Contact Information



Team Members • University of Florida

• Mark Sheplak - Professor, Dept. of Mechanical and Aerospace Engineering

• David Mills - Graduate Research Assistant• Daniel Blood - Graduate Research Assistant

• Florida State University• William Oates - Asst. Professor, Dept. of

Mechanical Engineering• Justin Collins - Graduate Research Assistant



Purpose of Task• Design, fabricate, and characterize a robust, high-bandwidth

micromachined pressure sensor for harsh environments− Applications

• High speed reentry vehicles• Hypersonic transports• Gas turbines• Scramjets

− Performance Metrics• Temperature: >1000°C• Bandwidth: >10 kHz

• Develop novel processing techniques for the fabrication of high temperature sensors− Laser micromachining processes for patterning of structures in

sapphire and alumina− Bonding process to for fabrication of multi-wafer sensors enabling

three-dimensional structures

2



Research Methodology• Fiber optic lever

– Intensity modulation– Single fiber in/fiber out

• Optical configuration– Multimode silica fibers

• More efficient coupling to sapphire fiber

– Incoherent LED light source

– Reference photodiode to monitor source drift

Image Plane

Sapphire Diaphragm

Sapphire Fiber



• “Long” Pulsewidths (>10 ps)– Industry standard– High reliability– Large heat affected zone (HAZ)– Micro-cracking and redeposit

Laser Micromachining



• Ultrashort Pulsewidths (<10 ps)– Direct solid-vapor transition– Reduced HAZ and micro-cracking– Lower fluence required– Deterministic material removal rate– Research tools

Laser Micromachining

• Oxford Lasers J-355PS Laser Micromachining Workstation– Coherent Talisker 355 nm DPSS laser– Pulse length <10 – 15 ps– Pulse frequency up to 200 kHz– Power adjustable from ~0.05 – 4.5 W– XYZ stages & galvonometer 2.5 mm



Thermocompression Bonding• High temperature bonding process

• 70-90% of melting point (up to 1450°C for sapphire & Pt)• 1-10 MPa substrate pressure• Up to 24 hour hold time – issues with survivability of

patterned features

• Spark Plasma Sintering (SPS) process• Large current density (~1000 A/cm2) causes rapid resistive

heating of substrates• Faster heating and cooling rates than hot press• Reduced temperature and holding time for similar

performance

3



Fabrication• 5.5 mm Tube Package

– 50 μm sapphire diaphragm– Deposit platinum reflective layer w/

titanium adhesion layer– Laser machine 4.5 mm recess in

alumina tube– Epoxy diaphragm inside recess

• 8 mm Flat package– 50 μm sapphire diaphragm– Deposit platinum reflective layer w/

titanium adhesion layer– 500 μm alumina back cavity– Laser machine 5 mm back cavity

and 150 μm through hole– Align and bond diaphragm to cavity

substrate



Process Development Results• Laser Machining

– Cutting speed: 100 mm/s– Frequency: 100 kHz– Pulse overlap: ~86%– Laser fluence

• Alumina: 2.45 J/cm2

• Sapphire: 4.48 J/cm2

• Bonding– Bond parameters

• Max temp: 800°C• Heating rate: 25°C/min• Hold time: 5 minutes

– Tensile strength: ~350 kPa– Substrate cracking issues



Fabrication Results• Low Temperature Prototype

–Silicon diaphragm–Silica fiber and low temp epoxy

• High Temperature Sensor–Pt-coated sapphire diaphragm–Sapphire fiber w/ zirconia

optical ferrule



Next Steps• Process development

– Laser machining parameters for thinning sapphire diaphragms

– Bonding• Improve temperature and

pressure control• Eliminate substrate cracking

• Package high temp sensor• PWT Calibration

– Frequency response– Linearity

• High Temperature Calibration– Temperature drift– Environmental chamber

4



Contact Information• David Mills – [email protected]• Mark Sheplak – [email protected]



Backup Slides• Prototype Sensor Static Calibration



Opto-mechanical Transduction

2d Federal AviationAdministration 16


Laser Micromachining Trends

0

2

4

6

8

10

12

14

16

18

20

0% 20% 40% 60% 80% 100%

Side

wall Ang

le (degrees)

Pulse Area Overlap (%)

Pulse Area Overlap vs. Sidewall Angle~7.5 J/cm^2, 1000 Passes

Left Opening

Right Opening

0

2

4

6

8

10

12

14

16

18

20

0.0 5.0 10.0 15.0 20.0 25.0 30.0

Side

wall Ang

le (d

egrees)

Fluence (J/cm^2)

Fluence vs. Sidewall Angle100 kHz, 100 mm/s, 1000 Passes

Left Opening

Right Opening

0

2

4

6

8

10

12

14

16

18

20

0 500 1000 1500 2000 2500

Side

wall Ang

le (d

egrees)

Number of Passes

Passes vs. Sidewall Angle7.38 J/cm^2, 100 kHz, 100 mm/s

Left Opening

Right Opening

5



Laser Micromachining Trends

0

2

4

6

8

10

12

14

16

18

20

0% 20% 40% 60% 80% 100%Side

wall Ang

le (degrees)

Pulse Area Overlap (%)

Pulse Area Overlap vs. Sidewall Angle~7.5 J/cm^2, 1000 Passes

Left Opening

Right Opening

0

2

4

6

8

10

12

14

16

18

20

0.0 5.0 10.0 15.0 20.0 25.0 30.0

Side

wall Ang

le (d

egrees)

Fluence (J/cm^2)

Fluence vs. Sidewall Angle100 kHz, 100 mm/s, 1000 Passes

Left Opening

Right Opening

0

2

4

6

8

10

12

14

16

18

20

0 500 1000 1500 2000 2500

Side

wall Ang

le (d

egrees)

Number of Passes

Passes vs. Sidewall Angle7.38 J/cm^2, 100 kHz, 100 mm/s

Left Opening

Right Opening



Oxsensis “Wavephire” Sensor• Micro-machined sapphire pressure sensor with sapphire fiber-optic

• Extrinsic Fabry Perot interferometer using at least two wavelengths• Diaphragm is micromachined using proprietary process

• Limitations prevents further miniaturization to sub-millimeter size

• Specifications• Temperature range

• -40 to 600°C (continuous)• -40 to 1000°C (research and development)

• 100 dB dynamic range• Uncertainty <±10%



Dynamic Pressure Sensors Diaphragm Sensors

Diaphragm deflects vertically due to incoming pressure Displacement sensed via transduction method

Transduction Schemes Capacitive, optical, piezoresistive, piezoelectric, etc.

Microphone structure

Electrical connections



• Factors Influencing Choice of Transducer Concept• Specifications: “what do you want to measure?”

• Physics related: dynamic range, bandwidth, spatial resolution, single sensor versus arrays, fundamental vs. control, etc.

• Environment: “where do you want to measure it?”• Wind tunnel, flight test, gas versus liquid, etc.

• Temperature, pressure, humidity, dirt, rain, EMI, shocks, cavitation, fouling, etc.

• Packaging Requirements: “where do you mount device?”• Application dependent: flush-mounting, single sensor

versus arrays (packing density), etc.

• Other Factors:• Budget, time-scale for test, risk tolerance, etc.

Choosing a Transduction Scheme

6



• Somewhat Unchartered Territory in MEMS• Silicon starts to plastically deform at 650 °C• Any circuit devices will be temperature limited (diodes, ICs,

etc.)• High-Temperature Limits Transducer Choices

• Piezoresistive: • Leakage current and resistor noise increase with temperature• Limited to around 200 °C or must be cooled

• Capacitive: • Low capacitance requires buffer amplifier close to sensor

• High-temperature, low noise, high-input impedance amplifiers do not exist

• Optical is best if you can get it off optical bench• Detection electronics are remotely located• High temperature sapphire fibers and substrates exist

Towards High-Temperature



Microphones / Pressure Sensors Capacitive: Sensitivity= 0.28 mV/Pa, DR= 22-160 dB, fres = 158 kHz

Arrays, benign environments

Microphone structure

Electrical connections

Piezoelectric: Sensitivity= 0.75 mV/Pa, DR= 48-169 dB, fres = 50 kHz Fuselage TBL studies Piezoelectric

AnnularRing

1.8 mm

TopElectrode

BottomElectrode

SiliconDiaphragm



Fiber Optic: Sensitivity= 0.5 mV/Pa, DR= 70-160 dB, fres > 100 kHz Hostile environments

Piezoresistive: Sensitivity= 1.8 V/Pa, DR= 52-160 dB, fres > 100 kHz Directional acoustic arrays

Silicon Nitride DiaphragmBulk Silicon

Cavity

Fiber Bundle

Aluminum

Acoustic Waves

Tx

Rx

Rx

RxRx

RxRx

DCVEX VOUT

oR R

oR R oR R

oR R

Microphones / Pressure Sensors



Material PropertiesUnits Silicon Silica Sapphire Diamond 6H SiC

Material P

rope

rties

Melting Temp °C 1412 1 1650 2040 2 3650 ‐ sublimes 2830 ‐ sublimes 1

Max Use Temp °C 650 ‐ strain point 1100 ‐ no load 7 1800 ‐ no load 2 650 ‐ Si substrate 1650 ‐ no load 5

Tensile Strength GPa 7.0 6 8.4 6 15.4 6 53.0 6 21.0 6

Poission's Ratio ‐0.28 ‐ [100] plane, 0.26 ‐ [110] plane 1 0.14 ‐ 0.17 9 0.25 ‐ 0.3 2 0.1 1 0.14 5

Young's Modulus GPa130 ‐ [100] plane, 170 ‐ [110] plane 1 73 6 530 6 1035 6 700 6

CTE, 20°C µm/m‐°C 2.6 1 0.55 9 5 ‐ to C‐axis 2 0.8 14.7 ‐ ∥ to C‐axis, 4.3 ‐ to C‐axis 1

Thermal Conductivity, 20°C W/m‐°C 130 1 1.4 9 41.9 2 600‐2000 1 490 1

Thermal Shock Parameter 8 1.52E+06 2.52E+05 1.83E+05 3.46E+07 2.94E+06

Optical Transmission, UV‐NIR %

~0 ‐ λ < 1.05µm, 50 ‐ λ > 1.05µm 4 86‐93 7 80‐90 3 60‐70 9 70‐80 1

Refractive Index ‐ 3.42 (IR) 1 1.45 @ 589 nm 7 1.8 ‐ 1.6, UV‐IR 2 2.4 (IR) 12.59 ‐ ∥ to C‐axis,

2.55 ‐ to C‐axis (IR)1

Tran

sducer

Issues

Optical Fiber Availability no yes yes no no

Substrate Availability excellent excellent excellent poor limited

Patternability / ProcessStandard MEMS

Processes Laser Micromachining LiftoffSiC specific DRIE

process, micromolding

Transduction Mechanisms

1





Autonomous Rendezvous & Docking

Penina Axelrad




• Purpose of Task



• Next Steps




AR&D Team• CU – Basis for requirements, standards and methods

• Florida State – Approach trajectories

• Stanford – Target pose and shape sensing

• U of Florida – Post capture operations

• Identifying and addressing key technology gaps



Team Members Current

• Penina Axelrad, CU

• Holly Borowski, PhD Student, CU, Aerospace Engineering Sciences (Summer 2011)

+ Planned

• Draper Lab, Ball Aerospace, LMCO

• Stanford (Todd Walter)

• IIT (Boris Pervan)

2



Purpose of Task

• Purpose – Develop a framework to enable licensing of multiple vendor vehicle systems that will make LEO orbital rendezvous and docking a routine and safe activity.

• Objectives – Define requirements and identify critical safety and technological issues for each phase of AR&D timeline; identify technology gaps and viable system alternatives

• Goals – Construct a draft basis for standards for AR&D of vehicles in LEO encompassing approach trajectories, sensing, estimation, guidance and control, human interaction, and reliability.



Research MethodologyFirst year is a small-scale ($17K) effort to construct a roadmap for the overall project

• Review relevant aspects of the state-of-the-art in LEO rendezvous and docking, UAV formation flying and mid-air refueling, aircraft landing

• Establish AR&D mission phases and classes of requirements and risks for each

• Identify critical systems, technologies, and concepts required

• Organize and plan research tasks that will lead to comprehensive basis for standards at the end of 5 years



Roadmap for Commercial LEO AR&D• Identify stages, requirements & risks for commercial

LEO AR&D

• Evaluate the maturity of key technologies

• Develop requirements flow down (technology pull)

• Look at promising technologies that can enhance performance, safety, robustness, reliability (technology push)

• Identify connections to other FAA activities including aircraft collision avoidance, UAV flight rules, mid-air refueling, and space situational awareness

• Draft plan for bringing the pieces together over a 5 year period to form the basis for standards development



AR&D Technologies•Sensors and algorithms

•Guidance and control algorithms and actuators

•Software – real-time onboard mission manager and flight software

•Docking/capture systems

AR&D Phases & TechnologiesAR&D Phases• Phasing (>5 km)

• Homing

• Closing (few km to 250m)

• Final approach (<250m)

• Docking (vehicle dimension)

3



Commercial, LEO AR&D considerations

• Manned or unmanned

• Automated or autonomous

• Target geometry known or unknown

• Target cooperative or non-cooperative

• Target attitude controlled or uncontrolled

• Number of vehicles - two or more

• Duration – long (multi-orbit) or short



Results or Schedule/Milestones• Initial literature search completed, summary of

existing AR&D approaches compiled.

• Key mission phases defined and relevant technology elements and some risks for each identified.

• Met with potential industrial collaborators from Ball Aerospace who provided information on sensor development and experiments.



Next Steps• Coordinate with COE partners

• Meet with other industrial potential partners

• Develop draft roadmap and proposal for 3 year project



Contact Information• Penny Axelrad

• [email protected]

• 303.492.6872

1





Autonomous Rendezvous and Docking for Space Degree Mitigation: Fast Trajectory Generation

Emmanuel CollinsFlorida State University




• Purpose of Task



• Next Steps




Team Members • Emmanuel Collins

• Griffin Francis, Mechanical Engineering, PhD Student

• Oscar Chuy, Assistant Scholar Scientist



Purpose of Task• Purpose: As indicated by a

recent NASA study, there is an immediate need to develop space debris mitigation technology.• The development of

“Space Tow Truck”capabilities is a promising approach toward direct debris removal.

• Requires automated guidance to approach target debris.

1981 2011

Space Debris

2



Purpose of Task• Objectives: Develop the

onboard ability to quickly (within a few seconds) generate dynamically feasible trajectories that enable a space tow truck to approach debris for docking.

This is the main propellant tank of the second stage of a Delta 2 launch vehicle which landed near Georgetown, TX,

on 22 January 1997. This approximately 250 kg tank is

primarily a stainless steel structure and survived reentry

relatively intact.Taken from the web site of the NASA Orbital Debris Program Office.



Purpose of Task• Goals:

1. Use of space tow truck dynamic model to account for actuator characteristics and vehicle momentum.

2. Effective planning of position, orientation, and velocity with respect to target debris.

3. Optimization of relevant trajectory metrics such as distance, time, or energy.

4. Avoidance of moving debris.5. Fast replanning using prior

trajectory plan.

On 21 January 2001, a Delta 2 third stage, known as a PAM-D (Payload Assist Module - Delta), reentered the atmosphere over the Middle East. The titanium motor casing of the PAM-D,

weighing about 70 kg, landed in Saudi Arabia about 240 km from

the capital of Riyadh. (NASA Orbital Debris Program Office)



Research Methodology• The primary tool used is Sampling

Based Model Predictive Optimization (SBMPO).

• SBMPO is a graph search method, which has the following characteristics:

• Graph is based on sampling model inputs;

• Uses A* optimization;

• Enables rapid replanning;

• Result is a trajectory, not simply a path.

Illustrative Graph, Including Collision Detection



Research Methodology• The key to fast computations

with SBMPO is wise choice of an optimistic A* “heuristic” (i.e., a rigorous lower bound on the cost from the current node to the goal).

• For example, for minimum time optimization for problems requiring specification of an end velocity and position, a heuristic can be based upon the solution to a “simple” minimum time control problem.

Miniimum Time ControlCurve for Äq = u

3



Research MethodologyBeginning in January, the research will take place in the new AME (Aeropropulsion, Mechatronics, Energy) Building.



Results• 3D Trajectory Generation

• Initially spacecraft is disoriented and trailing the target by 270 m.

• SBMPO sampled thrusters and rotation wheels aligned to the body axes (6 inputs).

• Distance was optimized.

• Zero relative velocity at goal enforced.

• Route shown to goal position and orientation computed in ~0.1 sec.

• Have generated 3+ km trajectories in 0.1-0.5 sec.

• Other approaches compute similar trajectories in 25+ sec.

VIDEO



Results Relative Position History (450 sec)

Relative Velocity History (450 sec)

x

vx

zy

vzvy

00

0



Results

1

0

0

0

0

0 0

Euler Angle History (450 sec)

Quaternion History (450 sec)

Roll YawPitch

Q1 Q4Q3Q2

4



Results• Planar Trajectory

Generation with Obstacles• SBMPO sampled

thrusters aligned to body axes (2 inputs).

• Distance was optimized.

• Zero relative velocity at goal enforced. START

GOAL



Results

Motion History Relative to Target (14 sec)

0



Next Steps• Apply collision avoidance to 3D planning environment with

orientation goal.

• Consider moving obstacles.

• Demonstrate minimum time trajectories.

• Develop a spacecraft power consumption model and demonstrate minimum energy consumption.

• Demonstrate rapid replanning to accommodate newly sensed obstacles.

• Implement trajectory constraints based on research of Penny Axelrad (U Colorado).

• Use research of Steve Rock (Stanford) and Norm Fitzcoy (U Florida) to determine final pose constraints.



Contact InformationEmmanuel [email protected]

Griffin [email protected]

Oscar [email protected]

[email protected]

Federal Aviation Administration 1 COE CST First Annual Technical Meeting (ATM1)

November 9 & 10, 2011

Federal Aviation Administration


Task 244: Autonomous Rendezvous & Docking

for Space Debris Mitigation

Norman Fitz-Coy 11-10-2011


November 9 & 10, 2011

Overview • Team Members

• Purpose of Task


• Results

• Next Steps



November 9 & 10, 2011

Team Members • Norman G. Fitz-Coy (PI, University of Florida)

• Takashi Hiramatsu (University of Florida)


November 9 & 10, 2011

Purpose of Task - Motivation • Remediation requires active space debris

removal

• Proliferation of CubeSat form factor satellites leads to

• More spacecraft = more failure

• 52 CubeSats launched since 2003, 23 active (~44% success)

• Disabled spacecraft = debris

• Malfunction in actuator, communication, etc.

• Non-cooperative behavior pre/post docking


November 9 & 10, 2011

Purpose of Task • Objective

• Minimize interaction “forces” between vehicles when docked with a non-cooperative target

• Goals

• Characterize the non-cooperative post-docking with “disabled spacecraft” (i.e., debris)

• Develop necessary control strategy to counteract debris’s motion and maintain a safe docked state


November 9 & 10, 2011

Towing Debris• React to disturbances through rotational motion

• None (cooperative)

• Translational

• Rotational

alalalalal

Debris (leader)

Service vehicle (follower)


November 9 & 10, 2011

Methodology: Game Theory • Game Theoretic Approach

• Multiple players (debris, service vehicle)

• Make an intelligent estimate of the debris’s behavior to compute the reacting control strategy of the service vehicle

• Stackelberg Game

• System with leader-follower hierarchy

• Interaction with a non-cooperative spacecraft (leader)


November 9 & 10, 2011

Methodology: Rotational Dynamics

• SV’s rotational motion

• : control torque input

• : interaction due to non-cooperative behavior

• : interaction due to orientation mismatch

• Design to minimize the interaction

Jω +ω ×Jω = τ + τd + τ s

τd

τ s

τ

τ

τd , τ s

ω

J

Debris (leader)

Service vehicle (follower)


November 9 & 10, 2011

Methodology: Controller Design• Rewrite to get Euler-Lagrange system

• Define errors

• Derive Error dynamics

• Break into two controllers

• Formulate linear error model τ

e1= qd − q e2

= e1+α

1e

1

Jω +ω ×Jω = τ + τd + τ s Mq+ Vmq+ g = τd + τ

Me2= −Vme

2− τ +h+ τd

τ = h−u

e1= −α

1e

1+ e

2

e2= −M−1Vme

2−M−1u+M−1τd


November 9 & 10, 2011

Methodology: Differential Game • 2-player linear quadratic differential game

• s.t.

• Solve using Stackelberg strategy

• Leader-follower hierarchy

• Debris as the leader

J1= 1

2xTQx +uTR

11u+ τd

TR12τd( )

0

∞

∫ dt

J2= 1

2xTNx +uTR

21u+ τd

TR22τd( )

0

∞

∫ dt

x = Ax +B1u+B

2τd x = e

1T e

2T⎡⎣ ⎤⎦

T


November 9 & 10, 2011

Results Attitude Error

Game Controller Feedback Linearizer Total Control Torque

Interaction Debris’s Torque


November 9 & 10, 2011

Summary • Preliminary analysis shows promise for removal

of non-cooperative debris

• Game theory with Stackelberg strategy

• addresses the post-dock interactions

• lowers interactions between service vehicle and debris

• Developed solution preserves nonlinearity of system dynamics (linearity in the error model)


November 9 & 10, 2011

Next Steps: • Add constraints to the control effort

• Extend the controller design to a multiplicative error model

Year 1 Year 2 Year 3

Trajectory Planning

Assessment of the state of the art for active debris removal

Assessment of hardware implementation issues in APFG collision avoidance and SBMPC

Hardware assessment of all developed methodologies

Proximity operation

APFG collision avoidance strategies

Hardware implementation issues in APFG and SBMPC

Post-docking Initial assessment of post-dock scenarios

Continued assessment of post-dock scenarios

Hardware assessment of all developed methodologies


November 9 & 10, 2011

Contact Information • Norman Fitz-Coy

[email protected]

(352) 392-1029

• Takashi Hiramatsu

[email protected]

(352) 846-3020

5/15/2012

1

Task 244: Autonomous Rendezvous and Docking for Space Debris Mitigation

Prof. Steve Rock

COE CST First Annual Technical MeetingBoulder, CO

9 November 2011 1

Overview

Team Members

Purpose of Task


Results, Schedule and Milestones

Next Steps

Contact Information

2

Team Members

Prof. Steve Rock (PI) Jose Padial (PhD student) Marcus Hammond (PhD student)

Stanford UniversityAerospace Robotics LaboratoryDepartment of Aeronautics and Astronautics

3

Participants:

Affiliation:

Purpose of Task

4

Goal: Develop new technology to enable safe, autonomous rendezvous and docking with disabled spacecraft or capture of debris

Objectives: Develop and demonstrate robust autonomous rendezvous and docking (AR&D) sensing technology for

Targets undergoing complex, potentially tumbling motion Damaged and/or uncommunicative spacecraft Orbital debris

Retrieval of Westar VI, a stranded communication satellite, courtesy sciencephoto.com

5/15/2012

2


Extend (and fuse) our previous work in feature-based (vision) and range-based (LIDAR) SLAM/SfM to achieve Accurate relative pose

estimation Accurate and dense 3D target

reconstruction Robust performance in the

harsh lighting environment of space

Enable capability for potential use on small satellite missions Low weight, size, and power

budget sensor suite Camera(s) and low-power

LIDAR5

Observer

Target

3D Reconstruction

Estimate of relative position, orientation, translational velocity, angular velocity


Validate algorithms in laboratory demonstrations using existing facilities within the ARL

Rotating base motion simulatorPrescribe complex motion (e.g. torque free) to a target hardware model

6DOF gantry Fly a sensor suite in a prescribed trajectory to observe tumbling target

6

Schedule and Milestones

7

Year 1: Demonstrate rendezvous and docking using a baseline SLAM algorithm Develop a plan to accommodate lighting anomalies Develop a plan to port the SLAM algorithms to low power proessors

Year 2: Modify and extend algorithms to account for lighting anomalies Modify and implement algorithms for low-power computer processors Demonstrate extended algorithms using ground-based simulator

Year 3: Begin development of a small-satellite demonstration

Work to Date: Simulation Environment

Camera-LIDAR simulation environment

Simulated LIDAR range scanning of 3D target models

Simulated images

Environment designed to allow for injection of noise into any point of the measurement and estimation pipeline

8

Project 3D target geometry onto image plane

5/15/2012

3

Estimation Framework: Loose Fusion

9

Vision-only Structure from Motion (SfM)

Relative Pose Estimates

(up to scale factor)

3D Sparse Structure (up to scale factor)

Search Vision-Range

Correspondence

Estimate SfM scale

to truth

Absolute Relative Pose

Estimates

Project Range Scans

ImagesRange scans

Loose Fusion Strategy

Measurements Output

Straightforward approach to fusion of vision and range

Dense 3D Reconstruction and Relative Pose Estimates

Estimation Framework: Tight Fusion

10

SfM-inspired solver that integrates vision data, range data, and vision-range correspondences

for accurate, scale unambiguous estimates

Search Vision-Range

Correspondence

ImagesRange scans

Dense 3D Reconstruction and Relative Pose Estimates

Tight Fusion Strategy

Measurements Output

Hypothesis:

We can do better than the loose integration strategy by folding the vision data, range data, and vision-range correspondences into a new SfM-inspired tightly-integrated formulation

Contact Information

Prof. Steve Rock

[email protected]

1.650.723.3343

11

1





Air Traffic ControlDr. Samuel T. Durrance

ProfessorPhysics and Space Sciences

Florida Institute of Technology



Overview

• Team Members

• Purpose of Task


• Results

• Next Steps


IFR

VFR

NAS



Team Members

• Dr. Nathaniel E. Villaire, Professor Emeritus

• Ms. Nicole Maillet, Research Assistant

• Dr. John Deaton, Professor

• Dr. Samuel T. Durrance, Professor

• Dr. Daniel Kirk, Associate Professor

• Dr. Tristan J. Fiedler, Associate VP for Research



Purpose of Task• Purpose: Identify pertinent questions which must be

answered if Commercial Space Vehicle (CSV) operations are to be integrated into the National Airspace System (NAS) using the existing the Air Traffic Control (ATC)system.

• Objectives: Examine the Airspace Related Federal Air Regulations (FARs) and ATC FAA Orders for Compatibility with CSV Operations.

• Goals: Identify Top Level Questions Which Must be Resolved for CSV Integration Into the NAS.

2



Research Methodology1.Identify the CSV operational parameters affecting the

NAS.

2.Identify the appropriate controlling FAA Orders & Regulations.

3.Assist the FAA and CSV operators by identifying specific questions affecting NAS/CSV integration.

4.Develop top level questions which must be resolved to effect NAS integration.

5.Increase the depth of information required for routine CSV operations in the NAS.




Analyze Applicable FAA Orders and FARs for Questions in the Following Order:

• PREFLIGHT

• TAKEOFF

• DEPARTURE

• EXITING & ENTERING THE AIRSPACE

• ARRIVAL

• LANDING



Examples of ResultsPreflight

Information Required by ATC for Flight in the NAS

• VFR Flight Planning

• Twenty Nine (29) Areas Identified Needing Clarification

• IFR Flight Planning

• Fourteen (14) Areas Needing Clarification Identified

• General Information Required by ATC to Safely Clear CSVs into the NAS

• Fifteen Areas (15) Needing Clarification Identified

• Example: “What will be required on the Minimum Equipment List for CSVs”?

• Multiple Areas Needing Clarification Identified



Examples of ResultsTakeoff• IAW FAR 91.143 – No aircraft may operate in areas specified by NOTAM

for Space Flight Operations except when authorized by ATC.

• Question: What will the specific procedures be for issuing Space Flight NOTAMs?

• Question: What airspace parameters will designated for the multiple types of CSVs?

• Question: What will be the CSV category? (New Category of aircraft?)

• Question: Can CSV operations be conducted under revisions to FAR 91 Subpart D (Special Flight Operations) or will a new Subpart be required?

3



Examples of ResultsTakeoff (Continued)

IAW FAA Order 7110.65T – All takeoff clearances are subject to specific separation standards between similar and dissimilar categories of aircraft.

• Therefore, Integration of CSVs into the NAS will require ATC to provide separation service.

• Under 3-9-1 ATC must provide specific information for separation.

• Question: What kind of weather, runway and atmospheric restrictions will be required?

• Question: Will CSVs have a newly defined priority or will they be subject to the current “First come, first served” system?

• (For example: Will CSVs be subject to Line Up and Wait separation procedures?)



Example of Results

• NOTE-Aircraft same runway separation (SRS) categories are specified in Appendices A, B, and C and based upon the following definitions:

CATEGORY I- small aircraft weighing 12,500 lbs. or less, with a single propeller driven engine, and all helicopters.

CATEGORY II- small aircraft weighing 12,500 lbs. or less, with propeller driven twin-engines.

CATEGORY III- all other aircraft.

• Question: Will CSVs fall under the “CATEGORY III – all other aircraft” group or will their characteristics be distinct enough to warrant different classification?



Example of ResultsDeparture

– WAKE TURBULENCEIAW 7110.65T

• Here is an example of the type of procedures and controls ATC must provide for aircraft operating in the NAS:

• Do not issue clearances which imply or indicate approval of rolling takeoffs by heavy jet aircraft except as provided in para 3-1-4, etc.

• REFERENCE-AC 90-23, Aircraft Wake Turbulence.

• Questions: Will a similar exception be included for spacecraft? What aerodynamic/operating parameters of CSVs will define separation requirements?

• NOTE- There are hundreds of similar questions which must be answered regarding takeoff, climb and standard instrument departures (SIDs) before CSVs can be integrated into the NAS.



Examples of ResultsTransiting the NAS to SpaceIAW AIM-Chapter 1 Specific NAVAIDS are used to transit the NAS.

Participating aircraft can use a vast array of NAVAIDS ranging from basic NDBs to GPS and NextGen Equipment.

• (See Historical Review for a discussion of NAVAIDS, RADAR and current ATC mission statement.)

• Question: What NAVAIDS will be required by ATC for integration of CSVs into the NAS?

• Question: Some models of CSVs are currently unable to react to ADS-B systems. Will CSVs have a separate set of ATC directives to effect separation when conflict with other participating users occur?

• Question: What SIDs will have to be developed through TERPS for the various types of CSVs ?

• Question: How will emergency ABORTs of CSVs affect the safety of other participating users of the NAS?

• Question: Should high speed, high altitude climb corridors dedicated to CSV operations be developed?

• Question: How will ATCT handle the transfer of control to the ARTCC?• This will involve extensive study of current and proposed LOAs between controlling entities.

• This may involve developing new procedures specifically designed for CSVs.

• Specific procedures limited to CSV operations may generate jurisdictional and “customer” conflicts.

4



Examples of ResultsTransiting the NAS to SpaceIAW AIM Chapter 3, Section 2, Controlled Airspace is Defined

• Current airspace classifications include Classes A, B, C, D, E and Special Use.

• Question: Since CSVs will be climbing well above FL600 where normal airspace control is terminated, will the CSVs require a new class of airspace above FL600?

• Question: If a new class of airspace is implemented, what NAVAIDS will be used to define and navigate the airspace?

• Question: What are the details required by ATC for LOA s between impacted ARTCCs?

• Question: What special equipment will the CSVs require to assure positive vehicle separation from all other users of the airspace in transition areas?

• Special Use Airspace

• Each category of Special Use Airspace has specific control parameters and user procedures.

• Question: What will be the operational restrictions of a new category of airspace?

• Question: Which agency(s) will have jurisdiction over a new category of airspace? (FAA, NASA, DOD, Other?)



Examples of ResultsTransiting the NAS from SpaceSEPARATION STANDARDS

• IAW AIM 4-4-11 ATC effects separation of aircraft vertically and longitudinally.

• Question: What will be the separation parameters for the separation of CSVs from the various categories of aircraft using the NAS?

• Question: What kind of adjustments can be used to effect separation of CSVs from other traffic during the reentry phase of flight? (Speed, turns, altitudes, holding, etc.?)

IAW AIM 4-4-16 & 18 Participating aircraft are expected to use TCAS and ASD-B to assist in separation.

• Question: Will the CSVs be equipped with usable TCAS and ASD-B systems which the CSVs can use in assisting ATC in separation of aircraft during reentry?

• Question: If TCAS and ASD-B is used, what special programming of the CSVs’ equipment is required?



Examples of ResultsArrivalIAW AIM chapter 5, section 4: Arrival Procedures

• 5-4-1. Specifies Standard Terminal Arrival (STAR), Area Navigation (RNAV) STAR, and Flight Management System Procedures (FMSP) for Arrivals.

• Question: Will standard instrument approach procedures (STAR) be developed for CSVs to facilitate transition between en route and instrument approach procedures.

• 5-4-3. Details Approach Control - Approach control is responsible for controlling all instrument flight operating within its area of responsibility.

• Question: Will Approach Control be able to sequence CSVs in conventional traffic patterns?

• 5-4-8. Special Instrument Approach Procedures - Instrument Approach Procedure (IAP) charts reflect the criteria associated with the U.S. Standard for Terminal Instrument [Approach] Procedures (TERPs) development.

• Question: Will CSVs use Special Instrument Approach Procedures (IAPs)?

• Question: Will CSVs use conventional NAVAIDS or require specialized equipment for dedicated IAPs?

• Question: How will CSVs be controlled during air traffic emergencies involving civil, military and commercial aviation vehicles?



Examples of ResultsLanding

• IAW 7110.65T Landing clearances are governed by a variety of runway separation rules, meteorology conditions and vehicle performance capabilities. Controllers have many tools to assist them in making safe landing decisions. Numerous questions regarding landing the highly specialized CSVs must be addressed before integrating CSVs into the NAS.

• Question: Can CSVs be sequenced in a standard arrival pattern?• Question: Can CSVs be maneuvered to alternate runways or landing pads if conflicts occur?

• 3-10-6. Defines the concept of “ANTICIPATING SEPARATION”. Landing clearance to succeeding aircraft in a landing sequence need not be withheld if you (ATC) observe the positions of the aircraft and determine that prescribed runway separation will exist when the aircraft crosses the landing threshold.

• Question: Can controllers “anticipate separation” with CSVs during normal traffic operations?

• Wake Turbulence and Separation is a concern for landing. Wake turbulence was discussed in the Takeoff section of this presentation, and similar questions arise when identifying pertinent questions that musty be answered if CSVs are to be integrated into the NAS

5



Next Steps• Divide the applicable FARs into smaller groupings for

fine analysis of their effects on CSV operations.

• Divide the applicable FAA Orders on ATC and Airspace into smaller groupings for fine analysis of their requirements in controlling CSV operations.

• Begin construction of a guide for FAA which will help the organization address the problems presented by integration of CSVs into the NAS.



Contact InformationDr. Nathaniel E. Villaire Professor EmeritusCollege of AeronauticsFlorida Institute of TechnologyEmail: [email protected](321) 777-8010

Nicole Maillet(Research Assistant)College of AeronauticsEmail: [email protected] Institute of Technology C/O 2012Cell: (321) 537-4835

1





Ultra High Temperature Composites for Thermal Protection System (TPS)

PI: Jan Gou, Ph.D.Department of Mechanical, Materials

and Aerospace EngineeringUniversity of Central Florida




• Purpose of Task



• Next Steps


• Break



Team Members • Dr. Jan Gou, Department of Mechanical, Materials and Aerospace

Engineering, UCF

- Polymer and ceramic nanocomposites

- Thermal degradation modeling

• Dr. Jay Kapat, Department of Mechanical, Materials and Aerospace Engineering, UCF

- Temperature and pressure measurement, thermal modeling

- Ablation sensing

• Dr. Linan An, Advanced Materials Processing and Analysis Center, UCF

- Polymer derived ceramics, high temperature sensors

• Dr. Ali Gordon, Department of Mechanical, Materials and Aerospace Engineering, UCF

- Thermo-mechanical characterization and modeling

• Students: Jeremey Lawrence, James DeMarco, Jinfeng Zhuge



Research Task #253Objective:

• Develop ultra high temperature, light weight, and cost effective nanocomposites with embedded health monitoring for inherent safety and real-time assessment of thermal protection system applications in hypersonic space vehicles

Goals: Develop light weight and cost effective ablative

materials against solid rocket exhaust plumes with Al2O3 at very high velocity

Provide an analysis tool for the thermal degradation modeling of new ablative materials

Provide ablation sensing to monitor the structural health of the ablative thermal protection system

The Delta II Carries 1,800 Pounds of Ablatives

2



Current Approach• PICA: Phenolic Impregnated Carbon Ablator

• SICA: Silicone Impregnated Carbon Ablator

• Carbon/Carbon Composites



POSS

Clay

The suggested mechanism is that a protective silicate layer onthe surface of condensed phase is formed to function as abarrier to limit O2 supply, flammable gases, heat and masstransfer between the burning surface and underlying polymer atthe elevated temperature.

POSS (polyhedral oligosilsesquioxane) is a cage-like structure,organic groups were attached on each corner; at ~300-350 C,Si-C bond cleavage, and to form ceramic –like char, which actas an insulating barrier and protect the underling subtract.

CNT or CNF

The nanocomposities based on carbon nanotubes are capableof forming a continuous network-structured protective layer,which acts as a heat shield for the virgin polymer below thelayer.

Nanocomposite Approach



Ablation Performance of Nanocomposite Permeability of the nanopaper Thermal stability of nanoparticles Dispersion of nanoparticles Quality of char formation Thermal conductivity Heat capacity

Conducting heat in one direction, along the alignment of the nanotubes, but reflecting heat at right angles to the nanotubes

High anisotropy of thermal conductivity of the nanopaper: in-plane and through-thickness direction

Ceramic Nanocomposites



3



Startingmaterials

Polymerprecursor

Infusiblepreceramic

network

AmorphousCeramics

Chemicalsynthesis

Crosslinking

Pyrolysis800-1000 oC

Si

C

NSi3N4

SiC

SiCN Ceramics

Thermal Shock FOM

Strength (MPa)

Hardness (GPa)

CTE (x10-6/K)

Poisson’s ratio

E-modulus (GPa)

Density (g/cm3)

500-1000

15-20

~3

0.17

~150-200

2.0-2.3

SiCN

~3000

420

30

3.8

0.14

400

3.17

SiC

250

700

28

2.5

0.24

320

3.19

Si3N4

880

Polymer Derived Ceramics (PDC)



Preform

Infiltrate with liquid precursor

Solidify liquid precursor

Pyrolysis

Carbon Nanopaper/PDC Composite



Nanopaper Manufacturing

Aligned MWNT CNF/POSS CNT/Graphite Nanoplatelets

Microstructural Characteristics

Porosity Thickness (5-10 um) Orientation Permeability Thermal stability Thermal conductivity Heat capacity

CNF/Nanoclay



Prepreg SystemInfiltration System Compressing System

Autoclave ProcessComposite Panel

Process Scalability

4



Heat Release Rates

1 2 3 4 50

150

300

450

600

New

com

posi

tes

GN

P-A

PPla

min

ates

Bas

alt /

glas

s fib

erla

min

ates

CN

F-M

MT

hybr

id p

aper

lam

inat

es

GF

lam

inat

es c

ontr

ol s

ampl

e

?

251KW/m2

291KW/m2370KW/m2

432KW/m2

Hea

t R

elea

se R

ate

(KW

/m2)

Nanopaper Optimization Heat Release Rates (HRRs)

Char Forming

Test Sample (Φ76mm) SEMChar



0 100 200 300 400 500

0

100

200

300

400

500

600

700

800

900

f

Tem

pera

ture

(o C

)

Time (s)

a:control25bottom b:control35bottom c:control50bottom d:control75bottom e:control100bottom f:cxa25bottom g:cxa35bottom h:cxa50bottom i:cxa75bottom j:cxa100bottom

j

hi

g

e d

cb

a

Temperature Profile

Backside Temperature



Next Step - Ablation Testing

Surface Temperature Backside Temperature - backside heat

soaked temperature Ablation rate – peak erosion depth

Ablation Performance

Simulated Solid Rocket Motor (SSRM) is a small scale, liquid-fueled rocket burning kerosene and oxygen.

Heat flux of 700 W/cm2 at 1 inch from the nozzle

Support sample size of 12”x12” Minimum burning time of 10 seconds Particle injection mass flow rate of ~ 20

lb/hr High exhaust velocity



Next Step - Thermal Degradation Modeling and Ablation Sensing• Damage modeling and life prediction under thermal- and

pressure-loading conditions

• Integrated health monitoring with embedded sensors for real-time assessment

5



Industrial Collaboration

• Carbon nanofiber composites are lightweight materials that could be used in rocket applications

• Increases ablation resistance to allow higher temperatures

• Makes nozzles lighter and more durable

Significance of Innovation

Technical Objectives

• Conduct testing on CNF nozzles • Optimize nozzle manufacturing process• Provide reliable and repeatable test rig to subject CNF

nozzle materials to high temperatures and dynamic pressures of liquid and gaseous propellant rocket motors

Applications

• Solid rocket motor nozzle materials (for NASA, DoD, and commercial missile, spacecraft, and launch vehicle applications

• Liquid rocket nozzle and/or throat insert material• Material for other high temperature, long-life applications

Water-cooled workhorse rocket engine with ATK/Plasma processes nozzle test setup

ATK/Plasma processes test with eductor attached to workhorse engine



Contact InformationDr. Jan Gou

Department of Mechanical, Materials & Aerospace Engineering

University of Central Florida

Orlando, FL 32816


Phone: (407) 823-2155



Thank You!

1





Wearable Biomedical Monitoring Equipment for Passengers on Suborbital & Orbital Flightsg

Equipment for PassengightsRichard T. Jennings, MD




• Purpose of Task



• Next Steps




Team Members • Jon Clark, Baylor Center for Space Medicine

• Jimmy Wu, Wyle

• Christine Smith, Wyle

• John B. Charles, NASA-JSC

• Anil Menon, MD, MPH*

• Jennifer Law, MD, MPH*

• Jim Vanderploeg, MD, MPH UTMB (Co-PI)



Objectives

• Determine human physiological parameters and data to be collected

• Identify/set design requirements and procure prototype biomedical monitoring equipment to be incorporated into a wearable vest, harness, or flight suit to support the operational monitoring needs of flight surgeons as well as the research interests of space scientists and physiologists.

2



Research Methodology• Comprehensive review of existing wearable biomedical

monitoring equipment to determine availability of

off-the-shelf equipment.

• Survey flight surgeons, research scientists, and space vehicle

operators to seek input on the features and capabilities

needed from biomedical monitoring.

• The capabilities of existing hardware and software will then be

compared with the needs and desires of the operational and

research community to identify gaps. ce flight crew member medical certification, passenger medical evaluation guidelines, and.



Research Methodology• Using gap analysis, the team will identify new technologies

that are needed to fill these gaps. The gap analysis will explore which existing technologies can be repackaged and incorporated into a wearable system.

• The prototype hardware configurations will be tested under

the expected G profiles in various operator’s launch/landing

systems using the NASTAR Center.





“ I see that you’ve been to NASTAR.”

3



Results and Schedule• Initial Team Meeting April 27, 2011

• Market Survey Completed(NASA Partnership)

• Draft Document and Gap Analysis Underway

Year 1 Year 2

Major Milestone Intermediate Milestone

Integrated Full-System SimulationsWearable Biomedical Monitoring Equipment

• Review of existing equipment and alternative concepts• Survey of needs and requirements / perform gap analysis• Procure / develop prototype hardware• Equipment testing and verification in centrifuge

M1 – Hardware procurement / development for testing

M2

M2 – Results of centrifuge testing

M1

Schedule:



Contact Information• Richard Jennings

University of Texas Medical Branch

301 University Blvd

Galveston, TX 77555-1110

409-747-6131

[email protected]

1




3. Tolerance of Centrifuge-induced G-force by Disease State


November 10, 2011





• Purpose of Task



• Next Steps




Team Members • PI: Jim Vanderploeg, MD (UTMB Aerospace Med.)

• Student: Becky Blue, MD (UTMB Aerospace Med.)

• Student: James Pattarini, MD (UTMB Aerosp. Med.)

• Co-I: Richard Jennings, MD (UTMB Aerospace Med)

• Brienna Henwood (NASTAR Center)

• Julia Tizard, Ph.D. (Virgin Galactic)



NASTAR Center

2



Purpose of Task• Purpose:

• Use centrifuge-induced G-force to evaluate subjects with defined disease states under the G-loads expected during commercial space flights

• Disease States• Controlled hypertension

• Controlled diabetes

• Controlled cardiovascular/coronary disease

• Respiratory disease

• Spinal disease or injury



Objectives• Conduct training and evaluation of future passengers with a range of

medical conditions so we can characterize their responses to the G environment

• Evaluate biomedical monitoring equipment under the G profiles of commercial space flights to ascertain the suitability of proposed wearable biomedical monitoring equipment and to verify that the quality of the data captured by the devices provides the information needed by the operational and research personnel

• Develop optimal training protocols for passengers so they can be trained efficiently and effectively in countermeasures to the G forces they will experience

• Conduct training and evaluation of flight crew members in the G profiles of various operators vehicles to verify that the G environment does not adversely impact on their ability to control the vehicle.



Goals• The expected benefits from this project include:

• Characterization of responses of individuals with several common medical conditions

• Development of risk mitigation strategies for individuals with those medical conditions

• Validation of wearable biomedical monitoring equipment for use during commercial space flights.




3



Next Steps• Finalize IRB approval

• Finalize NASTAR arrangements

• Recruit subjects

• Conduct training and evaluation in centrifuge

• Evaluate biomedical monitoring equipment



Contact Information





Phone: 1-409-747-5357

Fax: 1-409-747-6129


1



Federal AviationAdministrationCOE CST First Annual

Technical Meeting:

Commercial Spaceflight Operations Curriculum

Development

Task 257:Masters’s Ops LabGeorge H. Born

11.09.2011 Federal AviationAdministration 2



• Task Purpose/Objectives

• Process

• Results and Output

• Feedback

• Next Steps




Team Members • George H. Born – Director, Colorado Center for

Astrodynamics Research

• Bradley Cheetham – Graduate Research Assistant, Aerospace Engineering Sciences

• Jules Feldhacker – Graduate Research Assistant, Aerospace Engineering Sciences

• Emil Heeren – Visiting Scholar

• Jon Herman – Visiting Scholar/Graduate Research Assistant



Partnering Organizations

2



Purpose of Task• Objectives:

• Develop one-semester course

• Develop one-semester lab

• Refine content based on student and industry feedback

• Standardize and establish Graduate Certificate

• Increase collaboration between academia and industry



FAA COE CST Objectives• Research

• Student research projects investigate current constraints and explore potential solutions

• Training• Preparing students to enter industry with

commercial perspective

• Outreach• Educating academia about developments in

commercial space



Process/Approach• Draft academic objectives based on industry

discussion

• Solicit feedback on academic objectives• AIAA Spaceflight Operations Meeting

• Over 21 industry/partner organizations

• Define curriculum topics and solicit feedback

• Identify subject matter experts to develop and deliver content



Academic Objectives - Overall

Course shall serve as a bridge between theoryand application to prepare real world problem

solvers

3



Academic Objectives • Comprehension of total mission sequence

• Mission initiation to end of mission

• Course = overview

• Lab = implement

• Constraints on design and operations (both understand and identify)

• Technical – what can you do

• Policy/Legal – what are you allowed to do

• Business – what can you afford to do

• Practical – how do you adapt



Academic Objectives• Understanding of and insight into current industry practices

• Comprehension of current industry practices

• Past to present

• Keep vs Change?

• Critical review of potential improvements

• Overview of project management and team dynamics

• Cross cutting theme (through all objectives): RISK• Quantify and understand risk vs cost



Course ScheduleTheme Topic/Subject Speaker Date

Background

Lecture 1 Course introduction Cheetham/Born - CU 8.23.2011

Lecture 2 Industry & Government intro Steve Lindsey - SNC 8.25.2011

Lecture 3 Industry & Government Challenges Mike Gold – Bigelow Aerospace 8.30.2011

Launch Topic/Subject Speaker Date

Lecture 1 Launch Overview - Technical Review

Matt Cannella - CU 9.1.2011

Lecture 2 Launch Vehicle Overview Emil Heeren - CU 9.6.2011

Lecture 3 Launch constraints Col. David Goldstein – Vandenberg AFB 9.8.2011

Lecture 4 Human launch considerations John Reed - ULA 9.13.2011

Lecture 5 Suborbital flight Jon Turnipseed – Virgin Galactic 9.15.2011



Course ScheduleOperations Topic/Subject Content Date

Lecture 1On-Orbit -

Attitude/Rendezvous & Docking

Cancelled 9.20.2011

Lecture 2 Operations Overview Bill Possel - LASP 9.22.2011

Lecture 3 S&MA George Gafka – NASA JSC 9.27.2011

Lecture 4 Spacecraft Subsystems Michael Begley - LMCO 9.29.2011

Lecture 5 Spacecraft Subsystems II Scott Mitchell – Ball Aerospace 10.4.2011

Lecture 6 Industry OverviewAlan Stern - SwRI 10.6.2011

Lecture 7 Payloads Martin Taylor/Michael Mahoney - GeoEye 10.11.2011

Lecture 8 Human Factors Jim Voss - SNC 10.13.2011

Lecture 9 On-Orbit - ODJeff Parker - JPL 10.18.2011

Lecture 10 Conjunction/Debris Dave Vallado - AGI 10.20.2011

Lecture 11 Ground station operations/design

Byron Miller – Clear Channel Satellite 10.25.2011

End-of-Mission Topic/Subject Content Date

Lecture 1 Re-entry Overview/Review Cancelled 10.27.2011

Lecture 2 End-of-mission options Larry Williams/Scott Henderson - SpaceX 11.1.2011

Lecture 3 Quality Sciences/Cost-Plusvs. Commercial Contracting

Jeff Luftig - CU 11.3.2011

4



Course ScheduleMission Planning Topic/Subject Content Date

Lecture 1 Mission design Mike McGrath - LASP 11.8.2011

Lecture 2 Construction/Integration Overview David Termohlen – Orbital Sciences Corp. 11.10.2011

Lecture 3 Mission Assurance/Contingency Plans/Risk reduction

Wayne Hale - SAS 11.15.2011

Lecture 4 Financial/Contracting Overview Clay Mowry - Arianespace 11.29.2011

Misc. Topics Topic/Subject Content Date

Lecture 1 On-orbit Fuel Depots/Satellite Servicing Jon Goff – Altius Space Machines 11.17.2011

Conclusions Topic/Subject Content Date

Lecture 1 Overview/Summary/Current issues Mark Sirangelo - SNC 12.1.2011

Lecture 2 Space Policy Overview Bill Possel - LASP 12.6.2011

Lecture 3 Course Summary Cheetham - CU 12.8.2011

Student Presentations Individual research projects

Selected by students and assisted by industryFINALS



Student Products• Total students enrolled: 28

• 19 on-campus

• 9 off-campus (enabled by distance technology)

• Assignments• Weekly discussion

• 4 Open Ended Assignments

• 4 Labs

• 1 Research Paper



Student FeedbackCourse Content

OverallVery - 42%

Somewhat - 54%

Neutral - 4 %

LecturesVery - 50%

Somewhat - 42%

Neutral/Below -8%

ComparisonExceeds - 46%

Same - 42%

Below - 12%

“I really enjoy this course. It is information that every aerospace engineer should know”

“It is extremely valuable to gain insight from professionals, as opposed to the usually somewhat-limited academic presentation of material”

“I am finishing my Master’s degree this semester and a lot of this information is useful to me in understanding how the industry works”

“I like the variety of topics that are covered”

“This course has really stood out to me so far in how everything is very investigative.”



Next Steps• Spring-Summer 2012:

• Continued development/revision of course

• Initiate development of lab portion

• Fall 2012• Offer lecture for second time

• Spring 2013• Offer lab for first time

• Continue alternating course/lab• Formalize Certificate program

5



Contact Information

George H. [email protected]

Bradley [email protected]



Questions

1



Federal AviationAdministrationAnalysis Environment for

Safety Assessment of Launch and Re-Entry

Vehicles

Juan J. Alonso and Francisco CapristanDepartment of Aeronautics & Astronautics

Stanford University

FAA COE for CST Technical MeetingBoulder, CO




• Purpose of Task


• Results / Progress to Date

• Next Steps



Team Members • PI: Juan J. Alonso, Aero & Astro

• Francisco Capristan, Aero & Astro, Graduate Student

• Exploratory discussions with:

• ULA

• Boeing

• SpaceX



Purpose of Task / Goals• To provide the FAA and the community with an independent

multi-disciplinary analysis capability based on tools of the necessary fidelity.

• To develop and establish quantitative safety metrics appropriate for commercial space transportation (launch and re-entry).

• To validate the resulting tool with existing and proposed vehicles so that the resulting tool/environment can be confidently used.

• To increase the transparency of the safety assessment of future vehicles via a common analysis tool that is entirely open source and, thus, streamline the licensing process for a variety of vehicle types

2



Research Methodology• Currently the FAA uses a number of procedures and tools to assess the

safety of future commercial launch and re-entry vehicles (including maximum probable loss determination) that are based on traditional launch systems. There are concerns with potential diversity of future systems.

• Industry has asked for further clarity/transparency regarding the necessary proof for obtaining a license

• Safety issues include:• Human rating.

• Acceptable probability of failure.

• How to account safety risks not associated with component, sub-system, and system failure (unknown unknowns).

• Reliability does not equal safety: a reliability analysis tool is not sufficient.

• Mathematical models do not accurately represent reality, numbers obtained are not necessarily indicators of safety



FAA Existing Licensing Requirements• Mostly based on NASA heritage for ELVs.

• Comprehensive set of flight safety analysis requirements for ELVs:• Trajectory Analysis

• Malfunction Turn Analysis

• Debris Analysis

• Flight System Safety Analysis

• Straight-up Time Analysis

• Data Loss Flight Time and No Longer Terminate Time Analysis

• Time Delay Analysis

• Flight Hazard Area Analysis

• Probability of Failure Analysis

• Debris Risk Analysis

• Toxic Release Hazard Analysis

• Far-Field Overpressure Effects Analysis

• Collision Avoidance Analysis

• Overflight Gate Analysis and Hold and Resume Gate Analysis



Current Approach• Long term goal is to look at all possible licensed activities (in the following order):

• ELV

• Suborbital

• Single craft

• Multi craft

• RLV

• SSTO

• TSTO

• Various options

• Develop safety metrics.

• Not looking at certification, only licensing.

• Not trying to solve design practices (existing standards must be followed).

• We are trying to answer big picture questions about safety assessment of current and future launch and re-entry systems. How can we set appropriate safety levels rationally?



Current Approach

3



Current Approach• Typically deterministic inputs result in a deterministic output. We are

considering outputting ranges and understanding the input parameter combinations that lead to worst case scenarios (tails of distribution)

• Results obtained by solving the reverse problem could be used to inform licensing restrictions, or influence designs.



Research Questions• What are the operating margins?

• How large can the epistemic uncertainty intervals be before losing confidence in safety estimates?

• What is the risk of affecting the surrounding population/protected area?

• How much data of each kind (simulation, experimentation, flight) is needed to guarantee accuracy of safety assessment to a certain degree in a certain envelope?

• By solving the reverse problem, what are the licensing requirements that help obtain the desired outputs/safety metrics?



Analysis Environment



Analysis Environment: Debris Propagation

4



Debris Propagation Details



Debris Propagation Results• Debris simulation for fictitious launch vehicle of approximately the size of a

Falcon 9

• Randomly generated debris catalog. Probabilistic CD and initial velocities

• Intent was to verify trajectory and debris propagation portion of environment



Sophisticated Debris Models• Prior work includes LARA (USAF) and CRTF (ACTA) with

many needed components. Attempting to improve on these models by including uncertainty directly in the modeling and ensuring open access

• Assumptions in new debris dispersion tool :• Spherical rotating Earth.

• Debris pieces are not allowed to change mass or collide during propagation.

• Debris pieces treated as point masses.

• Lift and drag coefficients constant throughout all speed regimes.

• Explosion effects simulated by giving impulse velocities to the debris.

• Wind effects in all 3 orthogonal directions are considered.

• Malfunction turns not implemented yet.



Sophisticated Debris Models (II)• Assumptions in the Expected Casualty (safety metric #1)

calculation:• No sheltering.

• A normal bivariate distribution assumed for the affected areas.

• Population divided in square grid cells, and uniformly distributed within a cell.

• All debris (regardless of size or kinetic energy) consider lethal.

• Debris pieces assumed to reach the ground at their terminal speed.

• No bouncing or explosive debris considered.

5



Columbia Accident Simulations• More than 80 000 debris pieces recovered over more than 10 counties.

• 11 debris groups considered.

• There is a considerable amount of uncertainty in the input parameters, for example:• Number of debris pieces

• Main vehicle's state vector

• Impulse velocities due to explosions

• Lift to drag ratio



Columbia Accident Simulations• More than 80 000 debris pieces recovered over more than 10 counties.

• 11 debris groups considered.

• There is a considerable amount of uncertainty in the input parameters, for example:• Number of debris pieces

• Main vehicle's state vector

• Impulse velocities due to explosions

• Lift to drag ratio



Columbia Accident Simulations



Columbia Accident Simulations

6



Conclusions & Future WorkConclusions

• Initial framework architecture developed, modular components being added

• Initial focus on damage to the ground on ELV ascent trajectory

• Initial trajectory and debris dispersion tools have been implemented, and successfully automated to generate thousands of Monte Carlo evaluations.

• The current debris dispersion tool seems to capture the basic physical effects of falling debris.

• Despite the considerable amount of uncertainty in the input parameters, the debris dispersion model does an acceptable job in locating the risk areas.

Future work

• Validate the dispersion tool against other well accepted debris analysis tools (help is needed from industry to define realistic debris catalogs).

• Add malfunction turns to the simulation.

• Implement other random distributions (e.g Kernel density estimation) to calculate casualty expectation.

• Begin theoretical development for probabilistic inversion of safety requirements.

1




Plans for a Flight Software V&V Workshop

Juan J. AlonsoDepartment of Aeronautics & Astronautics

Stanford University

FAA COE for CST Technical MeetingBoulder, CO



Overview• This is a minor task that, at the moment, includes no

research or graduate students

• Flight software V&V was identified as a critical technology to improve safety and reduce costs

• Outcome of this effort is meant to be a workshop to outline a plan of research in this area

• The intent is to hold this workshop during the early Spring of 2012



Overview• Initial contacts with NASA, Industry, Academe are

helping generate:• A database of possible participants

• A short number of presentations

• An agenda for the workshop

• Your help in identifying all relevant parties is greatly appreciated.

• Possibility of adding the output of workshop to roadmapping activity sublevels?

Year 1 Annual Report – Volume 2 - PBworks

Documents

Transcript of Year 1 Annual Report – Volume 2 - PBworks