i Building Simulation (not) in the Studio Konferenzraum...

Building Simulation (not) in the StudioSustainable Design Classes 2011 -2013

Digi-Pro @ 3d-Labor (Prof. H. Schwandt)Max Dölling, Dipl.-Ing., Assistant Professor

DIVA Day 2013Solemma LLC @ Thornton Tomasetti

July 15th, 2013, New York City, NY, USA

Building Simulation (not) in the Studio

Dipl.-Ing. Max Dölling 1

Technische Universität Berlin,Germany

Sustainable DesignClasses 2011 - 2013

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Thermal Conditioning & Daylight Zoning Diagram >

Occupancy Hours & Intensity Sketch >

‘Robust’ studio:Karen KrögerPhilip Winkler

Philip Rust

0 2 4 6 8 10 12 14 16 18 20 22

In cooperation with:

Dr. Farshad Nasrollahi 2

Jeffrey Tietze, Cand. BSc 1

1 Digital Processing for Academics (Prof. Schwandt)2 FG Gebäudetechnik und Entwerfen (Prof. Steffan)





Students discussing sintered shading geometry prototypes, summer 2012

Building simulation is commonly taught as a specialty class instead of in a � design-centric but still research-oriented framework �

Common doubts about simulation in design: � simulation usability, feasibility of analysis results to positively (if at all) impact wide-scope design decisions; conflict over contents of core studios �

Initial Thesis: � “Design changes everything” ��(or does it?)

Our classes attempt the � integration of thermal and daylight simulation into the early stages of architectural design �

Throughout the last two years, we held � three seminar types, all concerned with architectural performance optimization �

Main goals: investigate � process, building form & performance impact, design representations � teaching of energy literacy to architecture students to facilitate interdisciplinary processes �

Design research: � reflect on the means, methods and procedures of design in-process; analyse artefacts from a rational, formal and phenomenological perspective �

01 Teaching & Research Goals





A : Parametric Design Climates : 1, 2, 4

02 Class Iterations (chronological)

C : ‘Robust’ Studio Integration 5B : Performative Design 1, 3, 4

� Community Center & Offices � (mechanical conditioning)

� Housing Units & Urban Design � (passive & mech. conditioning)

� Multi - Use Exhibition & Office building ��(mech. cond.)

1 Hollywod, FL, USA 2 Hashtgerd, Iran 3 Yazd, Iran 4 Östersund, Sweden 5 Berlin, GermanyClimate.: Am (Köppen class) Climate: BSk Climate: BWk Climate: Dfc Climate: Dfb

� Geometric optimization� Fixed materials & setpoints� Balance thermal & daylight

� Geometric & material optimization� Fixed setpoints & U-Val., custom mat.� Thermal performance focus

� Geometric & material optimization� Custom setpoints, mat. & behavior� Individualized performance tests

R. Canihuante,

M. El-Soudani

Office Bldg. (FL site)

O. A. Pearl,

D. Gkougkoudi

Housing units (SWE site) B. Suazo, M. Silva (Berlin site)





Student Ralitsa Georgieva presenting daylight simulations, winter 2011/12

03 Metrics & Design / Simulation Tools

Design decisions are guided by energy and comfort metrics, created by DIVA (Daysim, Radiance) & DesignBuilder (E+)

� Total and primary energy demand ��of idealized, best-practice cooling, heating & lighting systems

� Discomfort Hours � Operative Temperature

� UDI 100 - 2000 lux Climate-Based Daylight Metrics ��for all spaces (seasonal & yearly occupancy schedules)

��Daylight Availability � (DAv) 300 lux (office spaces)

� Irradiance images ��grid calculations (seasonal, yearly)

� Point-in-time luminance metrics � Evalglare calculations �

Yet in an unconstrained design process, technical validity of metrics only does not by default provide good design outcomes: � metrics have to be seen in conjunction with design intent & other (architectural) representations �

� The interpretation of technically invariant metrics shifts depending on typology, climate & design goals �





04 Performance Representations (excerpts)a Office / Multi - use building(Ft. Lauderdale, FL, USA)

b Housing development (Yazd, Iran)

Design concepts, Irradiation metrics Overhang study Final performance section with horizontal louversGlare without louvers

Daylight metrics model(UDI, DAv)

Early massing stage Housing UnitsCellular strategy UDI 100 - 2k axonometric Final state (RP irrad. model) Yard perspective (hello, glare... )

C. Kollmeyer,

R. Kölmel

DAv20 %

UDI66 %

C.103

H. 2

L. 6

UDI90 %

DAv84 %

C.64

L. 4

H. .1 DAv 300 lux,UDI 100 - 2000 lux Heating, cooling,lighting energy use development (kWh/m2)Primary energy demand

Initial Variant275 kWh/m2

Final Variant170 kWh/m2





05 Performative Design: Sweden Site

b Design & Simulations:T. Merickova, P. Jardzioch

Variant A

a Design & Simulations: O. A. Pearl, D. Gkougkoudi

UDI 100 - 2000, > 2000 &< 100 lux comparison;Heating energy use

development (kWh/m2)

Test glazing areas, materials, U-values,

and unit overshadowing (conditioned & passive)

Compare two site design variants; pick “best” one.

Metrics: average irradiance, H/C energy demand (VIPER)

H. 89 H. 34

> 2k43 %

19 %

100 - 2k38 %

27 %

100 - 2k48 %

> 2k25 %

Baseline (~A) Final Variant

> 2k42 %

H. 37 H. 1818 %

100 - 2k40 %

32 %

100 - 2k45 %

> 2k23 %

Baseline (~B) Final Variant

In parallel to systematic tests,designs continue to developin a heuristic & design-driven fashion, on multiple levels

Variant B

461 114

Summer Winter

Avrg. irradiation (exposed surfaces): kWh/m2

529 135

Summer Winter

Variant A495 117Variant B

Unequal unit performance!

467 116

606 140630 154Final Var.

Final Var.

“Versioning” “Shaping”





06 Performative Design: Sweden Site

Unit perspective section Site perspective (looking East)

Unit section Site perspective (looking West)

b Design & Simulations:T. Merickova, P. Jardzioch

a Design & Simulations: O. A. Pearl, D. Gkougkoudi





07 Detailed Design / Simulation Narrative (Florida Site)

� Design: I. V. Crego, D. Cepeda del Toro �

C.103

H. 2

L. 6

A B C DA B C D

m² m²m²

m²

FormFinding:Volumes

FacadeConcepts:��

Courtyardventilation

(exterior)

Heating (natural gas)

Chiller (electricity)

Useful Daylight Illumi-nance, 100 - 2000 lux

Daylight Availability,��

kWh/m²; Primary

% of occupied hours

Glazing Solar Gains (kWh)

Lighting (electricity)

UDI > 2000, < 100 lux

Glass Sol. Gains (/occ. area)

��

Meeting &Media Halls

AuxiliarySpaces

Foyer

Circulation

25Annual H/C/L energy demand, UDI 100-2000, DAv 300 ��!��!��"��glazing solar gains (all variants)

20

15

10

100

80

60

40

20

NORTH

SOUTH

5

kWh/m2kWh/m2

0 %occ. hrs.

0 kWh)2(/m

Space Use

339

238223

204

153

Nat. Vent.





W. J. Batty & B. Swann (‘97): Integration of Computer Based Modelling and an

Inter-Disciplinary Based Approach to Building Design [...], (Building Simulation ‘97)

“The performance parameters related to the design inquiries are extracted from guidebooks due to their clarity, familiarity and popularity amongst architects. The simulation tasks [...] are then defined with respect to each design stage.”

S. Bambardekar &

U. Poerschke (‘09):

The Architect

as Performer of

Energy Simulation

in the Early

Design Stage,

(Building Simulation

‘09)

08 Design / Simulation Process Observations & Models“The basic procedures involved in the design of acommodity are the same whether it be a toaster, supersonic passenger aircraft or a building.”

Process�Steps Type�of�analysis Shad

ing�Mask

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alysis

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ath�Ana

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se�ana

lysis

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alysis

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lysis

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omy

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ax�Tem

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iatio

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adredu

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Infiltration�ga

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Architectural�design�parameters

A Programming�Stage Climate�analysis o o o o o o o o oBenchmarking oParametric�analysis o o

BSchematic�Design�Stage

1 BUILDING�VLV Orientation o o o o o o o o o o o optimum�orientationMassing o o aspet�ratio,�volumeSite�form�MassingSpace�Zoning o o

2 SPACE�LVLoptimize�envelope Insulation o o o o o o o o o o o o optimum�U,�R�values,�thickness

Materials��opaque o o o o o o o o U,�R�values,�thicknessMaterials��glazed o o o o o o o o o SHGC,�VT,�U�value,�optimum�WWRGreen/Cool�roof o o o o o o o U,R�values,�thickness

3 Passive�heating Thermal�Masso o o o o o o o o

Area,�location,�thickness,�heat�storage�capacityDirect�heat�gain o o o o o o o o o o o o o o o o o WWR,�SHGCIndirect�heat�gain o o o o o o o o o o o o o thickness,�heat�storage�capacity

4 Passive�cooling Cross�Ventilation o o o o o o o o o o o o o o o Inlet/outlet�opening�area,�locationStack�ventilation o o o o o o o o o o o o o stack�height,�location,�opening�areaMass+night�cooling o o o o o o o o o o o o o o o o o area�of�thermal�mass�&�openings

5 Shading Shading o o o o o o o o geometry,�location

6 Daylighting Daylighting o o o o o o o o o o o o optimum�DF,�WWRLight�shelves o o o o o Glare�controlDaylight�zoning o oSkylights o o o o o optimum�DF

Daylight�dimming o o o oOccupancy�sensors o o o sensor�location

7 Renewables Solar�power o o o panel�sizingWind�PowerGeothermal�powerSolar�DHW o o o panel�sizing

Miscellaneous Lighting Thermal Energy

� Knowledge of architectural design processes (and the implications of full “integration”) advances only slowly in the BPS community, compared to technological innovation �

Instead of aiming to standardize processes, attention is given to recurring patterns in design - specific workflows:

� Processes are not linear � but concurrently erratic, iterative, case-specific and linked to performance / design intent

� Simulation scope ��improves through time, usually in phases:��a Heuristic design-seed generation��b Partial / explorative simulations (single / multi-domain)�� c Whole-building multi-domain interdependent simulations

� Form / Performance knowledge � steadily accretes throughout individual design steps taken by students

� Individual / tacit knowledge constructed through designerly making � coexists with � quantified, multi-domain performance behaviours (which are objective within their evaluatory scope and, in the case studies, geometrically defined) �





Design

AB

DC

Intent

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M. C. Doelling &.......................

F. Nasrollahi (‘13)

Parametric Design :

A Case - Study in Design-Simulation Integration, (Building Simulation’13)

��!��"�#�$��

� Hence, linear descriptions of design/simulation processes obfuscate their real inherent complexity - but awareness of this problem is increasing in the literature �

Elements of an adapted process model (Doelling & Nasrollahi, Building Simulation 2013):

� Design intent � is intersubjectively constructed and encapsulates (performance) domains (A - D plus many more)

� Design Synthesis � is achieved by continuously overlapping domain states (e.g., through “multivalent” representations)

Domain crosstalk influences design intent; intent modifies domains � resulting in a non-linear process field �

What are the benefits of thinking in such a model?

� The model unburdens design processes from constant rational analysis synchronicity demands �

� It supports holistic knowledge achieved through complex, physically accurate, output-flexible tools (e.g., DIVA) �

“The focus of simulation is to solve design dilemmas. [...] The identification of three main design stages is not neccessarily a reproduction of the [design] process. ”

R. Venancio,

A. Pedrini, A.C.

van der Linden, E. van

den Ham & R. Stouffs (‘11):

Think Designerly! Using Multiple Simulation Tools to

Solve Architectural Dilemmas, (Building Simulation ‘11)Chermayeff & Alexander (‘63):

Design Interdependencies

“An integrated process is ......a dynamic field of........related design states ...........and should not be ..............represented...................linearly. ”





SAMPLE building, Ft. Lauderdale, Florida, USA (office int. loading)

01 Annual average Zone Air Temperature (C°), non-conditioned, non-ventilated (inf. 0.7 ac/h)

02 Annual averagecooling rate (W) of v. 01if cooling were enabled

03 Annual average of ZoneTransmitted Solar (W), base state, no shadingmax. gains S/E, S/W

04 Addition of overhangs &shading reduces zone air temp. & absolute difference

05 Addition of calculated natural ventilation plus shadingyields 13° avrg. temp. reduction

10 Results : Space - Based Thermal Metrics Mapping

� Derived from experiments with combined design & data-visualization in class and the benefits of space-based metrics shown by DIVA and in the literature, the GHpython tool Mr. Comfy spatially displays energy simulation data �

� Multi-zone mapping � of hourly / daily / monthly / annual / arbitrary range performance data generated by EnergyPlus

� Co-display of several report variables � by duplicating components; unlimited no. of variables & zones per *.csv (Until it crashes - beware of Alpha releases)

How is this useful and related to design processes?

� Where in a building significant events occurr can be hard to gauge from chart data, requiring other representations �

� Spatial zone relationships & adjacencies influence thermal performance, at times making it behave counter-intuitively �

��Long - term goal ��custom design - supportive metrics

��Release date ��~ September ‘13 (v. 0.1)

N





Student Alan Patrick discussing simulations, ’Robust’ studio, Summer 2013

11 Results : Building Simulation in the Studio

� Continuing success in the stand-alone classes led to an invitation to participate in the ‘Robust’ design studio held by the department of Prof. Regine Leibinger, TU Berlin �

� Goal � Perform design-driven simulations of individualized scope, to aid realization of ‘robust’, heavy bldg. envelopes

� Studio benefits & possibilities �� Students have more time to work on design variants� Interest by design departments is a prerequisite to move� sustainability simulations into the mainstream of practice� More realistic test environment of conflicting influences� Results can be more representative of integrated design &� of high architectural quality (successful in this class!)

� Studio difficulties & pitfalls �� Design staff and students must both be educated� Conflicts of interest can erode intensity benefits� Influencing whole-building morphology can cause friction� If the studio is not primarily sustainability-driven, � performance concerns might become mere addenda

� Process, technology are “ready”. We need positive results!





(Seasonal) UDI100 - 2000 lux& DAv 300 luxdaylight studiesfor alternatingzones of light /

dark

Cross Sections

LateralSection

Light intent & Sim.


UDI 100-2000 Lux UDI 100-2000 Lux Sommer UDI 100-2000 Lux Winter Daylight Avilability 500 Lux

Exhibition

Multi-Purpose

Research Center

Exhibition

Event

+24,00

+20,00

+14,00

+10,00

+6,00

+0,00

4,35 9,00 3,351234

Section North-South 1:200 Section North-South 1:200

Elevation Friedrichstraße 1:200

Section East-West 1:200

114

113

112

111

110

109

108

107

106

OPENINGS [%]

605040302010

HEAT

GEN

ERAT

ION

[kW

h/m

2] SOUTH

NORTH

� Design / Sim.:� L. de Pedro,��C. Sitzler �





Multi-metric daylight study of different facade

configurations for maximum

daylight depth & uniformity(500 lux)

Sommer

Winter

Initial LightShelf Concepts

sommer

equinox

winter

sommer

equinox

winter

Seasonal Facade Overshadowing

Daylight Autonomy

UDI < 100 lux

UDI 100 - 2k lux

UDI > 2k lux

Daylight

Availability

A B C D

Regular facade ALight shelf only B

Shelf + plate cut CShelf 10° rotated D

Final South Facade (configuration C) South FacadeCutaway (conf. C)


� Design / Sim.:� K. Kröger��P. Winkler

P. Rust �





Student Majd Murad discussing simulations, ’Robust’ studio, Summer 2013

14 Conclusion

� Simulation, if used properly, has a massively positive influence on ‘integrated’ processes designers undertake; it also is craft �

� ‘Designerly’ simulations do not weaken form and can be� applied even in a non-sustainability driven creative context �

� Inclusive performance research must happen in a strongly � design-driven framework, to stay generally applicable �

� In this context, individual domains should adapt:� Tools: complex & usable, not simple, to mirror design reasoning� Process: Fluid, adaptable, individual; with rational components� Representations, Metrics: Problem-specific, spatially defined

� “Design changes everything” ...? ��Not quite.

Design changes simulation, which in turn influences design.

Architects deal with early-stage unstructured information in a synthetic manner, which shapes design intent and is used to gauge the social and behavioural impacts of space; this gives BPS performed by designers great future potential.





Student Philip Rust co-presenting, final crit of ’Robust’ studio, Summer 2013

A special “Thank You!” to all the students who participated in our classes throughout the last 2.5 years. None of this would have been possible without you.

With deep thanks to:Cecilia, Farshad Nasrollahi, Jeffrey Tietze, Alstan Jakubiec, Christoph Reinhart, Matthias Graf v. Ballestrem, Bogdan Strugar, Jan Kunze, Regine Leibinger (everyone I forgot, apologies)

Thank you, DIVA DAY! Off-conference questions? [email protected]

References

Doelling, M.C. & Nasrollahi, F. 2012. Building Performance Simulation in Non-Simplified

Architectural Design. Proceedings of the 30th eCAADe conference, Prague, Czech Republic.

Doelling, M.C. 2012. Hybrid Daylight Models in Architectural Design Education. Proceedings of

DIVA Day 2012, Massachusetts Institute of Technology, Boston.

Doelling, M.C. & Nasrollahi, F. 2013. Architektur, Simulation und Intention. In: Claus Steffan (Hrsg.),

Parameter des Entwerfens: Architektur und Nachhaltigkeit. Universitätsverlag der TU Berlin.

Doelling, M.C. & Jastram, B. 2013. Daylight Prototypes: From Simulation Data to Four-Dimensional

Artefact. Proceedings of the 18th CAADRIA conference, National University of Singapore, Sing.

Doelling, M.C. & Nasrollahi, F. 2013. Parametric Design: a Case Study in Design-Simulation

Integration. Proceedings of Building Simulation 2013, Lyon, France.

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