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Targeting emergent technologies for D&DAdvances in wireless communications, data sharing technologies and scanning and pattern recognition capabilities could help to speed up and cut the costs of nuclear decommissioning projects. International research efforts are needed to bring promising technologies forward, says Harvey Farr.
The OECD/NEA report “R&D and
Innovation Needs for Decommissioning
Nuclear Facilities” was published in
2014. The report was the culmination of an
effort that began in 2011, which involved
the polling of member countries to identify
decommissioning R&D needs and promising
technologies in five themes:
1. Characterisation and survey prior to
dismantling;
2. Technologies for segmentation and
dismantling;
3. Decontamination and remediation;
4. Materials and waste management;
5. Site characterisation and environmental
monitoring.
The goal of this article is to update the
information in the report with new and
evolving technologies and their potential
D&D applications.
D&D managers are often reluctant to use
new technologies and innovations. But if
we are going to decrease the time and costs
of decommissioning, it is essential that we
start gaining knowledge and experience with
technologies that are already available in
order to capitalise on the rapidly expanding
capabilities of emergent technologies over the
next decade. There are two major objectives
for the near term R&D initiatives: develop
technologies for better, cheaper, faster
D&D; and start and maintain a continuous
improvement cycle.
R&D initiative recommendationsThere are many technologies emerging in
non-nuclear markets that can be adapted
and deployed to benefit decommissioning
efforts now, if the R&D costs are shared.
Based upon the knowledge gained from the
evaluation of emergent technologies, five
“broad spectrum” R&D initiatives and 14
“theme specific” R&D initiatives are proposed
for consideration by member states for
collaborative focus and funding.
The focus of this article is on the five broad
spectrum initiatives. They have application
across themes and provide capabilities
and architecture to support other D&D
innovations. They are centred around five
rapidly emerging technological capabilities
that are being integrated into nuclear reactor
operations and construction projects.
1. Internet of Things – RFID Tags and WiFi
Tags;
2. Location Aware Networks or Real Time
Locating Systems (RTLS);
3. Building Information Models (BIM);
4. Neurosynaptic Artificial Intelligence (AI)
and Pattern Recognition;
5. Expedited 3D CAD.
BIMs are 3D CAD models of the site with
data linked to coordinates. They allow project
management planning and status to be
maintained; users of tablet based work control
systems know where they are within the BIM
and have access to all the information about
structures or components in their vicinity.
These are also essential platforms
for developing interlocks and operator
assistance systems required to safely
and efficiently deploy remotely operated,
autonomous and semi-autonomous heavy
equipment and advanced laser based cutting,
characterisation and decontamination
technologies and to integrate many other
emergent capabilities into D&D.
Neurosynaptic AI can data mine and process
massive amounts of information from plant
drawings, system descriptions, procedures and
manuals and organise it within the BIM. It also
will enable more autonomous equipment use
because the faster, event driven processing
and neurosynaptic architecture has resulted in
robots that learn their environment from video
feeds, spot patterns to identify objects like
pedestrians or other equipment, and learn to
perform tasks from corrections made by human
operators such that over time less intervention
and oversight is required to perform tasks.
Pattern recognition coupled with location
awareness will enable robots and operators in
control centres to know where they are in the
BIM, what objects are they are looking at and
to pull all the information about that object from
the BIM.
Expedited 3D CAD will enable the BIM
to be constantly updated, automating
project management status and situational
awareness and allowing IoT and RFID data
to be tagged to up-to-date 3D CAD models.
This will greatly increase the mapping of
radiation and contaminant data and facilitate
use of geostatistics and kriging to map levels
in 3D. In addition to safety and logistical
considerations, the emergence of these
Plan projectDe�ne objectives & constraints.Bench mark previous experience.Review best available technologies.Project manager led multi-disciplinary integrated work plan &schedule development.
Assess project performanceEvaluate schedule, safety & workperformance.Review suggestions/lessons learned& target those for implementation &further evaluation.
Incorporate experienceResearch & evaluate targetedsuggestions.Document evaluation and lessonslearned results for benchmarkingfuture projects.
Perform projectApprove work instructions,permits & schedule.Perform tasks.Capture negative and postivesuggestions & lessons learned.
D&D continuousimprovement
cycle
Plan projectDe�ne objectives & constraints.Bench mark previous experience.Review best available technologies.Project manager led multi-disciplinary integrated work plan &schedule development.
AAAAssess project performanceEvaluate schedule, safety & workperformance.Review suggestions/lessons learned& target those for implementation &further evaluation.
Incorporate experienceResearch & evaluate targetedsuggestions.Document evaluation and lessonslearned results for benchmarkingfuture projects.
DPerform projectApprove work instructions,permits & schedule.Perform tasks.Capture negative and postivesuggestions & lessons learned.
D&D continuous improvement cycle
Xerafy RFID tags are being used to locate containers
at a French nuclear plant
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capabilities will greatly increase information
sharing and the efficiency of project execution.
Internet of Things In the Internet-of-Things (IoT) sensors and
chips are embedded in devices, and data is
collected and transmitted in real time to onsite
servers or servers in the cloud for storage and
analysis. In a D&D setting, this could be water
processing pump speeds and flow rates; area
radiation monitor dose rates on demineraliser
beds and filters; weights, locations, and dose
rates on waste containers; hours of operation,
fuels use, and location of equipment; or even
personnel identities and locations.
Using IoT capabilities will enable radiological
and hazardous material data to be transmitted
and stored in the cloud in real time from
radiation survey instruments like data loggers
or 3D gamma cameras and from industrial
safety instruments such as oxygen, explosive
gas, volatile organic carbon monitors. IoT
technology was applied during the Japan
nuclear catastrophe, when numerous Geiger
counters owned by individuals were connected
to the Internet to provide a detailed view of
radiation levels across Japan.
Wireless sensors can also be used to monitor
the performance of modular equipment used to
replace the original plant hard-wired systems
such as HEPA units, water processing skids,
and to provide liquid and gaseous effluent
discharge information. Development of an
affordable, adaptable wireless communication
system that is easily deployed and maintained
in a D&D setting is critical to ensure the
technologies discussed in this article can be
brought to bear on decommissioning.
ABB has a modular, solar powered, private
wireless system for use in open pit mining.
The ABB Tropos wireless mesh technology
greatly reduces the need for large towers
and in some cases eliminates it altogether.
Routers, deployed on trailers around the pit,
“discover” each other automatically and
provide coverage for the entire pit. When
the pit topology changes due to new mine
sites, the trailers are simply moved to new
edges, creating coverage for mission-critical
applications within minutes instead of the
months needed for a tower-based design.
Radio Frequency Identification (RFID) tags
can be used to tag information to an object or
person. This allows additional data to be stored
and retrieved in the cloud such as a person’s
training and qualifications, signature authority,
the chain of custody information on samples, or
equipment identification information.
Some nuclear plants are using RFID tags
on containers storing outage equipment to
allow a read out of their contents from a hand
held device. Similarly, information about
equipment can be tagged to an RFID that
uniquely identifies that piece of equipment
and information related to it. Monitors that
sense RFID tagged safety equipment for
personnel accessing construction sites are
already being tested and developed. AREVA is
installing RFID tags on nuclear reactor welds
in France in a building information model
(BIM) application. Nuclear Street reported that
the tags let inspectors identify pipe welds and
their accompanying radiographic images while
calling up quality control data, including the
weld date, serial number, GPS coordinates,
pipe diameter and the welder’s name. The
software that runs the system is hosted on a
local server. The French government’s PACA
labs is testing the project, known as Be-Tag.
Tags that are extremely rugged and resistant
to extremely high radiation doses are also
being developed in the USA.
Building Information Models IoT technologies can be augmented by
technological initiatives related to location
awareness and 4D (x, y, z, time) computer
assisted design (CAD) capabilities.
This technology is currently being used
by control and monitoring systems for heavy
equipment in construction, mining and
agriculture. The coupling of location awareness
of the bulldozers, hauling trucks, etc. within
a 3D CAD model of a mine is being used by
heavy equipment manufacturers to enable
tracking of equipment and personnel locations.
It also allows remote, semi-autonomous and
fully autonomous operation of the equipment
along with command and control tracking from
monitors in a control room.
Systems have been developed to work with
all types of mobile equipment, including trucks,
loading tools and auxiliary equipment as well
as machines from various manufacturers. These
systems can provide monitoring, assignment
and tracking tools to help industry work more
safely, productively and efficiently.
If we can muster the international focus
and collaboration to adapt such systems
to nuclear D&D, it may one day be feasible
to accomplish a major portion of the D&D
activities using heavy equipment remotely,
keeping personnel out of harm’s way. This
would reduce the safety and radiological
coverage requirements and greatly simplify
the planning and execution process.
These systems already exist, as does
fully capable, remotely operated heavy
construction equipment such as the
excavators, trucks, bulldozers, etc. used to
clear debris from Fukushima Daiichi. There,
heavy equipment was operated remotely
using X-Box™ controllers from command
modules in sea/land containers up to 2km
away. Groupe INTRA - INTervention Robotic
sur Accident, maintained by EDF, CEA, and
AREVA, used remotely operated excavators
and bulldozers to clear up the pathways. The
expansion of similar capabilities is being
vigorously developed and investigated.
Use of this type of system coupled with
location aware networks and building
information models may one day allow
decommissioning to be largely performed
from command centres.
Location Aware Communication NetworksReal Time Locating Systems (RTLS) are
available that use time-of-flight information
between wireless transmitters to triangulate
the location of an active RFID or WiFi tag
to within a few meters. Active RFID tags,
also called WiFi tags, are larger (e.g. wrist
watch size) than passive RFID tags (less than
1cm) because they contain a battery and
transmitter. Miniature power sources and
transmitters are under development promising
to shrink these devices to passive RFID sizes.
New RTLS systems can locate a WiFi tag
to within a few centimetres. This will enable
IoT information to be tagged to physical
coordinates in time and space throughout a
decommissioning facility. This means that
both dynamic and real time data as well as
facility design data can be linked spatially
and made available for download and
analysis in the cloud.
Remotely controlled machinery removes rubble at Fukushima (Source: TEPCO)
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A company is currently testing a
tablet based, paperless, work control and
document control system that enables work
orders, drawings, survey maps, etc. to be
downloaded, completed and updated in
the field. Scanning a bar code on a piece of
equipment allows it to be identified and all
document control information related to it
to be downloaded to the tablet in the field.
This capability is currently being tested at US
operating nuclear plant outages. Construction
based software such as Procore also has
project management, scheduling, and financial
tracking capabilities that can be accessed from
computers, tablets or smart phones. Wireless
location awareness capabilities will eliminate
the necessity of bar coding equipment.
RFID technology together with 3D CAD/
Geographic Information System (GIS) models
are being used to locate and track buried
commodities.
Radiation Safety and Control Services, Inc.
is currently working with Exelon to develop
exactly that kind of system for groundwater
protection and underground asset management
initiatives using GIS/GPS based location
awareness. A complete 3D CAD/GIS model of
the site including outdoor above ground and
underground commodities is being developed.
It shows piping runs, duct banks, storm drains,
pits, pumps, valves and positions them in
3D space linked to each asset’s information,
which is stored as a database. By knowing
the location of a tablet or smart phone,
objects within a certain radius can be tagged.
Data tagged with the 3D coordinates is also
uploaded in real time to the cloud. This could be
well monitoring data, such as water level, pH,
etc. Sample data on a well or systems giving
contaminants and concentrations or inspection
data, is collected real-time in the field. The
facility design and operation data as well as the
IoT data are stored in a GIS database such that
all the information related to systems, samples
etc. within a certain radius of a location can
be retrieved and the exact location of an
underground component can be identified.
The coupling of IoT data, location
awareness, and 3D digital models is
already being used to facilitate information
management and use of autonomous and
semi-autonomous capabilities. This will
enable significant efficiencies and safety
enhancements to be brought to bear on
decommissioning when one thinks about
the value of tagging and mapping data to
a 3D coordinate system and the situational
awareness and safety interlocks for remote
equipment that can be developed from
this. Efficiency gains include elimination
of the intermediate steps to map, survey
and analyse contaminant data; automated
schedule and status update capabilities;
automated inventory of equipment and
waste packages; and remote monitoring of
equipment.
In the construction and architect
engineering realms, systems that capitalise
on these capabilities are being developed.
Capabilities are being developed to tag project
completion information to the 3D digital model
of a facility under construction to enable real
time tracking of progress. This frees resources
from updating status and enables more focus
on predictive scheduling and optioneering.
Physical installation of IoT tagged materials
and items as well as real time tracking of work
order information allows a real time project
status to be maintained. BIM technologies
with sensors are also being used for
constructed buildings to track maintenance
and equipment performance and even usage
patterns of the occupants. The data are
uploaded in real time and can be used to aid in
increasing the efficiency and performance of
future designs.
R&D initiatives to bring IoT and BIM
technologies to bear on decommissioning
will provide the framework for integration of
robotic capabilities, data management (such
as geostatistical), and project management
capabilities that can improve the cost and
efficiency of decommissioning. 4D CAD
models are starting to be used to design, plan,
schedule and operate construction projects
in order to more efficiently plan and manage
complex projects where safety hazards
and conflicts between work groups have a
high potential. These technologies are also
being applied to planning deconstruction or
demolition projects. Électricité de France has
initiated a plant lifecycle management (PLM)
project for new build and existing nuclear
facility models, methodologies and tools able
to ensure that these construction requirements
are fulfilled. 3D data aims, in this context, to
provide not only the as-designed but also the
as-built representation of the geometry of the
facility components (HVAC, cable trays, pipes,
valves etc.) as well as their relative positions.
The PLM includes a database on information
related to the 3D CAD model. The goal is to
take into account the whole plant lifecycle:
engineering, building, operating, maintaining
and decommissioning. Algorithms and
computer modelling can be used within these
frameworks to determine the most efficient
sequences for specific activities.
Neurosynaptic pattern recognition Dynamic pattern recognition and 3D
CAD capabilities are rapidly developing
technologies that augment those discussed
above, especially in a changing construction
or decommissioning environment. Pattern
recognition is the ability to identify objects
from photographs or video feeds or to identify
correlations or relationships in data.
There have been initiatives to develop
neurosynaptic algorithms, computers, and
chips whose design is based upon studies
of the neural networks of mammalian
brains. The neurosynaptic architecture
has the potential to revolutionise the
computer industry by integrating brain-like
capability into devices where computation is
constrained by power and speed.
Systems of Neuromorphic Adaptive Plastic
Scalable Electronics (SyNAPSE) is a U.S.
Defense Advanced Research Projects Agency
(DARPA) funded programme that started
in 2008 to develop electronic neuromorphic
machine technology that scales to biological
levels. These efforts have developed several
different neurosynaptic chips that process
data much faster and more efficiently than
conventional chips ,resulting in vastly improved
pattern recognition and artificial intelligence
capabilities. The final phase of the DARPA
initiative, targeted to be completed in 2017, is
the fabrication of a multi-chip neural system
of 108 neurons (100 million) for installation
in a robot that performs autonomously at a
cat’s level of cognition. The ultimate vision is
to build a cognitive computing architecture
that approximates the number of neurons and
synapses estimated in the human brain.
These capabilities promise to speed the
introduction of robots into new areas of use
beyond the fixed position applications on
factory floors. A second wave of robotically
performed work is coming and it will be as
revolutionary for construction and material
handling applications as the first wave of
fixed position robotics was for manufacturing.
In August 2014 IBM announced the
release of its TrueNorth neurosynaptic
“ Pattern recognition and neuromorphic programing should be a high priority R&D initiative for the global D&D community ”
IBM unveiled its TrueNorth neurosynaptic chip in August 2014(Source: IBM)
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chips. Each TrueNorth chip consists of 4096
neurosynaptic cores arranged in a 64×64 grid
and is based on a brain-inspired computer
architecture. It is powered by one million
neurons and 256 million synapses.
In the near term TrueNorth can provide
an extremely efficient coprocessor to handle
sensor input, computer vision, AI (self-driving
cars), and other emerging spheres in personal/
wearable computing. These attributes will
surely rapidly expand the capabilities of
autonomous equipment and tracking and
control like systems. TrueNorth is also energy
efficient, consuming only 70mW during
real-time operation. At 400 billion synaptic
operations per second per watt this is about
176,000 times more efficient than a modern
CPU running the same brain-like workload,
and 769 times more efficient than other state-
of-the-art neuromorphic approaches.
In the UK, Stephen Furber of the University
of Manchester is working on a supercomputer
constructed from conventional digital-
based low-power computer chips. So-called
SpiNNaker now consists of 20,000 chips, each
of which represents 1000 neurons. Furber
expects that number will rise eventually to a
1-million-chip system representing 1 billion
neurons—about 1% of the neurons in the
human brain.
“Core”-type self-contained neural networks
operate in parallel, without a clock, in an
event-driven fashion and they integrate
memory, computation, and communication.
Individual cores can fail and yet, like the brain,
the architecture can still function. Cores on the
same chip communicate with one another via
an on-chip event-driven network via an inter-
chip interface leading to seamless scalability
like the cortex, enabling creation of scalable
neuromorphic systems. This technology is
already being used for pattern recognition in
live video feeds. IBM has a monitor streaming
video of Hoover Tower at Stanford University
looking down at the plaza, below. The system
is trained to recognise buses, cars, people, and
cyclists in the live video feed. As each shape
enters the scene, it’s briefly surrounded by a
splash of colour: purple for cyclists; green for
pedestrians; dark blue for cars; sky blue for
trucks; and yellow for buses.
These chips not only allow robots to
perceive their environment through pattern
recognition image processing, but to learn by
performing tasks while remotely controlled.
IBM’s neuromorphic team leader Dharmendra
Modha stated that neuromorphically
heightened perception will give robots
the wherewithal to navigate hazardous
environments, such as a damaged nuclear
reactor, “without guidance from a human
operator, beaming back data on radiation and
other conditions in real time.”
HRL Laboratories LLC is also working
on a neuromorphic chip, which can process
visual data fast enough to pilot a palm-sized
helicopter inside an office building and
recognise and explore rooms it has never
seen before. Another robot uses its video feed
to avoid furniture and make laps around an
office. If it bumps into someone’s leg and an
operator intervenes with a remote joystick to
steer it around legs, it learns and avoids them
on its own without intervention.
The same neurosynaptic architectures
that allow rapid pattern recognition from
images are being used to mine and organise
information. This technology has next
generation cloud and big data processing
applications as well. AI systems are being
used by DARPA to read thousands of peer
reviewed journals and formulate hypotheses
for investigation by researchers.
Examples of how neurosynaptic pattern
recognition technologies can be used in D&D
are:
1. Data mining applications such as
processing of blueprint and document
information to tag it to the 3D CAD/GIS
model of the BIM;
2. D&D pattern recognition capabilities
that will allow autonomous equipment
and their video feeds to control rooms to
identify objects, people, and equipment
to provide situation awareness, safety
interlocks, and progress updates;
3. Programming to train AI systems to
recognise components and equipment
using pattern recognition and BIM
coordinates. This will enable download of
information from the GIS database such as
drawings, material type, like component
weight, centre of gravity, etc.
In the same way that pattern recognition
technologies are being used to inventory
roadway assets, inventories of containers,
construction equipment, systems, and
structures can be developed using pattern
recognition algorithms for nuclear D&D
objects.
When these capabilities are coupled with
systems such as the Fukushima remotely
operated construction equipment, it is
easy to see why pattern recognition and
neuromorphic programming should be a high
priority R&D initiative for the global nuclear
decontamination and decommissioning
community. The use of remotely operated
or autonomous equipment will reduce the
planning and coverage required by removing
workers from the decommissioning work
zones. Intelligent autonomous equipment
with neurosynaptic processors could perform
many routine repetitive tasks.
IBM Research has built SyNAPSE University
to help interested parties build and program
complex neurosynaptic systems. It would be
worthwhile for the member states to consider
an R&D initiative that adapts the use of this
technology. The goal would be to develop
robotics capable of removing commodities
autonomously, eliminating the requirement
for scaffolding, tenting, local HEPA ventilation
radiation protection and industrial safety
coverage as well as all of the planning and
monitoring required to maintain compliance
with regulations to protect workers.
3D laser scanning of a nuclear plant by Russia’s NEOLANT
3D CAD model of Russia’s Rostov 3
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NUCLEAR ENGINEERING INTERNATIONAL | www.neimagazine.com May 201532
Expedited 3D CAD3D scanning technologies are also being used
to identify construction equipment patterns
that can be applied to pattern recognition
from video streams and are being developed
to automate updates of construction progress.
Developing such capabilities builds in
redundancy to RFID based and location
aware based BIM technologies for project
management, safety interlocks and for
deploying autonomous robots that will know,
for example, they are looking at a valve from
the live video feed, know which valve it is
based on the x, y, z, coordinates, and be able
to access all the information about it from the
BIM database in the cloud.
The ability to dynamically update the 3D
CAD/GIS BIM will be critical for efficient use
and deployment of the capabilities discussed
in this article. Current technologies such as
3D laser scanning are available and currently
being used. Russia has developed a BIM
system called Multi-D for nuclear facilities,
which uses 3D laser scanning (see NEI June
2014, p19). LED based scanning technologies
are being developed as an alternative to
laser scanning in order to provide smaller,
more dynamic 3D CAD imaging systems.
Photograph based 3D CAD modelling
capabilities are also being developed and
could facilitate the update of BIM CAD models
through video feeds and cameras on remotely
operated equipment, such as robots and
aerial drones. It may also be feasible to outfit
equipment with devices such as a Google
Project Tango tablet to more precisely update
and build 3D CAD environments.
Similarly the Fraunhofer Institute for
Applied Optics and Precision Engineering
IOF in Jena Germany is spearheading a
consortium whose goal is the combination
of competencies in optics/photonics, IT/
software engineering and electronics with
those from design, neuroscience, cognitive
science and human factors science. It may
one day be possible to use WiFi signals to
develop 3D CAD maps and sense changes
within the areas including human gestures
and falls, changes in equipment positions,
etc. These devices are also shrinking to chips
that process photos in an iPhone so that exact
replicas of small objects can be printed out on
a 3D printer.
Cheap, miniature 3D CAD mapping
together with pattern recognition and data
processing capabilities built on neurosynaptic
chips will unleash robotic technologies from
fixed position manufacturing applications
to dynamic complex applications such as
construction sites. Pattern recognition and
image processing coupled with location
aware BIM technologies will also be used to
automatically track and monitor construction
progress and schedule status.
A path forward for R&D initiativesExciting new technologies are emerging.
The next step is to adapt and develop
them, and integrate them for use in
decommissioning. This will require industry
consensus, collaboration, and focus. Broad
spectrum initiatives are necessary to lay the
groundwork. These capabilities must then be
paired with better project management and
interpretation tools such as paperless work
controls, geostatistics, and digital spatial
models. Developing such platforms now will
greatly assist in deploying and testing the
next generation of robotics and autonomous
equipment and other evolving technologies,
which need to be safely integrated into active
decommissioning projects.
The path forward to implement these
initiatives requires consensus among member
countries and sponsoring organisations
such as the OECD, IAEA, NDA, DOE and
EPRI. It would be advisable to assemble
a multinational team of seasoned D&D
specialists to identify lead technical experts
and companies on the applicable technologies
for each R&D initiative. Host DECON or
SAFSTOR facilities for field testing initiatives
should be solicited by the team and sponsors.
Personnel with experience in several
countries or on different continents could
lead multi-national teams of experts and
develop technologies that encompass
challenges unique to member countries,
such as waste minimisation, recycling and
reuse of materials. Organising such a team
and implementing the initiatives may be
better suited to a contractor or several such
firms in order to maintain focus and develop
technologies that integrate with one another.
Approved projects should be managed
and planned using an integrated multi-
disciplinary project planning process similar
to the ones adopted for outage management
and modification review and approvals
at commercial nuclear power plants (see
diagram above).
Project management personnel should
assemble and lead experts on the
technologies being developed and/or tested
to put together a scoping phase project,
plan, schedule, and budget that will meet
the needs of both the sponsors and the
host facility and if necessary provide a
basis for seeking additional sponsors for
funding. Upon approval and securing of
adequate funding, a detailed planning phase
resulting in a plan that integrates into the
host facilities decommissioning process will
be implemented. This plan will include an
implementation schedule/work breakdown
structure and provide metrics and details
by which performance can be measured for
meeting R&D objectives. ■
AcknowledgementsThe author would like to thank Gerard Laurent, Eric Darois, Greg Babineau, Mathew Darois, Nick Williams and Dave Fauver for their invaluable review and comments on this article.
About the authorHarvey Farr is Senior Project Manager & Health Physicist at Radiation Safety and Control Services. He was also a co-author of the OECD/NEA report “R&D and Innovation Needs for Decommissioning Nuclear Facilities.”
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assigned
Target andcontact host
facilities
Prepareschedule
Draft R&Dreport
Sponsor andstakeholders
commentR&D report
Prepare workbreakdown
structure andcost estimate
Draft detailedR&D plan,
WBS,schedule,
deliverables
Sponsorcomment ondetailed R&D
plan
Teamincorporates
sponsorcomments
and submitsto EDF
Perform R&Dimplementcontinuous
improvement
Review R&Dproject capturelessons learned
Identifypotentialfundingsource
OECD/NEAIAEANDADOEEPRI
Prepare R&Dproposals
Submit tofundingsources
Sponsorreview andcomment
Determine�nancial
assurancesand incentives
required
Obtain hostfacility
authorizationto proceed
Teamincorporates
sponsorcomments
and submitsto sponsor
Teamincorporates
sponsorcomments
and submitsto sponsor
Yes
Yes
Yes
Yes
No
No
No
No
How the multi-disciplinary project management process for R&D initiatives might work