Environmental Performance Simulation
From evaluating performance to suggesting new forms
for buildings and neighborhoods
Urban Modeling
Mobility
Rules of Thumb
Microclimate
Cambridge Solar Map
Christoph Reinhart
Royal Academy of Engineering – December 11 2013
Massachusetts Institute of Technology
Department of Architecture
Building Technology Program
What is Building Science?
Wiki says: The collection of scientific
knowledge that focuses on the
analysis and control of the physical
phenomena affecting buildings.
What are key drivers?
Buildings account for roughly a third of carbon
emissions.
We spend 90% of our time indoors.
Research Hypothesis
q Technologies are in place to design and construct affordable, resourceefficient and comfortable buildings.
q Current design practice and education relies on a non-standardized
and mostly not validated design analysis workflows.
Sustainable Design Lab @ MIT
Carlos Cerezo
Timur Dogan
Diego Ibarra (GSD)
Alstan Jakubiec
Aiko Nagano
Christoph Reinhart
Cody Rose
Tarek Rakha
Julia Sokol
“Our research goal is to change current sustainable design practice by
developing, validating and testing workflows and metrics that lead to
improved design solutions as far as occupant comfort and health as well
as building energy use are concerned. The premise of this work is that an
informed decision is a better decision.”
Building Performance Simulation
Building Performance Simulation: An computer-based attempt to model
the various energy and mass flows within a building in order to predict
one or several performance aspects of a design.
Operational Energy
Return on Investment
Solar Radiation
Occupant Comfort
Daylight
Walkability
Today’s Presentation
From evaluating performance to
suggesting new forms
q Environmental performance simulations are now capable of predicting
the physical performance of commonly used building typologies and
technologies.
q Parts of this analysis can be done by architects and planners
themselves. Is this true/desirable?
q We can increasingly expand our analysis to the urban/neighborhood
realm.
Why Environmental Performance Simulation?
q To demonstrate code compliance and to reduce risk.
q To compare different design variants.
Do today’s simulation programs
work?
ASHRAE thinks so.
Purpose of the Standard
q Analyzing and diagnosing building
energy
simulation
software
using
software-to-software and software-toanalytical-solution comparisons.
q Checking a program against a previous
version of itself after internal code
modifications such as an algorithmic
change.
ASHRAE 140 -2007 Standard
Method for the Evaluation of
Building Energy Analysis
Computer Programs
Uncle Sam thinks so, too.
Tax Deduction Information
Under IRS rules, taxpayers' building energy use performance must be
calculated using software that has been tested according to
ANSI/ASHRAE Standard 140 to qualify for tax deductions.
Comparison of measured and simulated
energy use for 97 LEED Buildings
Model uncertainty from weather, infiltration rate, usage schedule
and occupant behavior.
Paper
H W Samuelson, A Lantz and C F Reinhart, "Non-technical barriers to energy model sharing and reuse", Building
and Environment, 54, pp. 71-76, 2012.
But, models can be calibrated…
H W Samuelsona, A Ghorayshib and C F Reinhart, Analysis of a Simplified Building Energy Model
Calibration Procedure for 18 Real-World Case Studies (in preparation)
Accuracy of Daylight Simulations
60
Daylight Autonomy [%]
measured
50
simulated
40
climate Data: i
30
20
10
0
0
200
400
600
800
1000
illuminance threshold [lux]
Light. Res. & Technology
Mardaljevic, 1995
Energy & Buildings
Reinhart, Walkenhorst 2001
Energy & Buildings
Reinhart, Andersen 2006
The Radiance/Daysim daylight simulation program can efficiently and
reliably model annual illuminance time series with a mean relative error
of 20%.
Papers:
§ Reinhart C F, Andersen M, “Development and validation of a Radiance model for a translucent panel”, Energy and Buildings 38:7
pp. 890-904, 2006
§ Reinhart C F, Walkenhorst O, “Dynamic RADIANCE-based daylight simulations for a full-scale test office with outer venetian
blinds.” Energy & Buildings, 33:7 pp. 683-697, 2001
Today’s Presentation
From evaluating performance to
suggesting new forms
√q Environmental performance simulations are now capable of predicting
the physical performance of commonly used building typologies and
technologies.
q Parts of this analysis can be done by architects and planners
themselves. Is this true/desirable?
q We can increasingly expand our analysis to the urban/neighborhood
realm.
Teaching Simulations
How close do ‘simulation novices’ get?
McGill – School of Architecture
Crit Room 102- Best Practice Model
- error analysis of 69 student models of a sidelit space
- comparison of simulation results using Ecotect-Split-Flux and Radiance
Paper: Ibarra D, Reinhart C F, "Daylight factor simulations - 'How close do simulation beginners 'really' get?“, Proceedings
Building Simulation 2009.
69 Student Models
q Ecotect results lie over and under Radiance results
q Enormous range of results.
Simulation
Checklist
Book Chapter: Reinhart C F,
“Simulation-based Daylight
Performance Predictions“ in
Building Performance
Simulation for Design and
Operation, Editors J Hensen
and R Lamberts, Taylor &
Francis, 2011
Spring 2012 MIT 4.430 Daylighting
Spring 2012 MIT 4.430 Daylighting
q Simulation of 10.485.
q Practicing good simulation habits.
q Building trust in one’s own modeling skills.
How do we reach the architects not
interested in taking electives on
simulation?
Simulation Games
Hypothesis
Being able to read thermal simulation results and to adapt one’s
design accordingly has become an essential skill for graduating
and practicing architects.
Why?
The alternatives for architects are to effectively ignore simulation
output or to have the modeler take over key design aspects of the
building. (Both alternatives are undesirable for architects.)
Note
Engineers, this does not mean that the architects know how to do
the simulations themselves.
The Game …
Human Cluster [Experts]
Simulation Queue
Searching for the winning combination…
C F Reinhart, T Dogan, D Ibarra and H W Samuelson, "Learning by doing - Teaching energy
simulation as a game", Journal of Building Performance Simulation, October 2011.
Simulation Order Form
Provided by Modeler
Results: Final Designs
q EUIs of the 10 final designs were 22–31% below the base variant.
q Building massings chosen by the different groups diverged.
“Today building science was definitely not boring.”
Today’s Presentation
From evaluating performance to
suggesting new forms
√q Environmental performance simulations are now capable of predicting
the physical performance of commonly used building typologies and
technologies.
√q Parts of this analysis can be done by architects and planners
themselves. Is this true/desirable?
q We can increasingly expand our analysis to the urban/neighborhood
realm.
Framework for Daylighting
Figure from Daylighting Handbook (Reinhart)
Paper: C F Reinhart and J Wienold, "The Daylighting Dashboard - A Simulation-Based Design Analysis
for Daylit Spaces", Building and Environment, 2011.
Daylighting Dashboard
Question: Should I specify blinds or not?
% Occupied hours
Daylit Area:
73% of the space
Potential glare: 50% of the year
44% of the space
no glare
View: 100% 50%
Paper
§ Reinhart C F, J Wienold, “The Daylighting Dashboard - A Simulation-Based Design Analysis for Daylit Spaces”. Building and
Environment, 2011 46:2 386-396
DIVA for Rhino
Grasshopper
Rhino Model
Visualizations
Radiance
Visual Comfort
Evalglalre
Climate-based Metrics
Daysim
Radiation Maps
GenCumulativeSky
Annual Glare Maps
Daysim
Paper:
§ K Lagios, J Niemasz and C F Reinhart, "Animated Building Performance Simulation (ABPS) - Linking Rhinoceros/Grasshopper with
Radiance/Daysim", SimBuild 2010, New York City, August 2010
§ J A Jakubiec and C F Reinhart, DIVA-for-Rhino 2.0: Environmental parametric modeling in Rhinoceros/Grasshopper using
Radiance, Daysim and EnergyPlus, Building Simulation 2011, Sydney, November 2011
Thermal Loads
EnergyPlus
Animated Building Performance Simulation
Simulation: J Niemasz and K Lagios
Environmental Performance
combined with a Genetic Algorithms
Determine a box shape with maximum enclosed volume and annual solar radiation
exposure in Boston (Niemasz)
This looks a bit like trying to have monkeys play
Shakespeare. Can we do better?
SHADERADE - Generating the Next
Generation of Shading Systems
Conventional Shading
Design: Jeff
Niema
sz
Static Exterior Shading: SHADERADE
Surround Shade
Paper: J Sargent, J Niemasz, C F Reinhart, “SHADERADE: Combining Rhinoceros and EnergyPlus for the design of static exterior shading
devices”, Building Simulation 2011, Sydney, November 2011.
Static Exterior Shading: SHADERADE
Once the volume has been assessed, any surface
within its bounds can be visualized:
Surround Shade
The Shaderaded Aquatower
J Sargent & J Niemasz
Climate Change Predictions
A General Circulation Model (GCM) is a mathematical model of the general
circulation of a planetary atmosphere or ocean. [Wikipedia]
The IPCC Working Group III developed storylines which represent a potential
range of different demographic, social, economic, technological and
environmental developments (IPCC 2000).
How large is the Effect?
Harvard University – Gund Hall
DesignBuilder model
Gund Hall now
Samuelson, Holmes, Reinhart 2011
q 33 Zone E+ model
q 1990 TMY2 weather
data for Boston
Case Study: Gund Hall now and then
36% less heating
45% more cooling
q 33 Zone E+ model
q 1990 TMY2 weather
data for Boston
q predicted 2080 weather
data for the IPCCCA2
scenario (medium to high
emissions scenario).
Linking Future Climate Files with Future Prices
Data Source: Economic Insights from Modeling Analyses of
H.R. 2454 — the American Clean Energy and Security Act
(Waxman-Markey); Pew Center for Global Climate Change
q The basic idea of the paper is to link 7 of the 22 energy price projections
from the 2009 Energy modeling Forum (EMF-22) to the four climate
change projections from the 3rd IPCC Assessment Report (TAR).
q The matching is realized via the Radiative Forcing (RF) of the different
scenarios. RF is the change in net irradiance at the top of the tropopause
compared to the year 1750.
Case Study: Office Building in Boston
Generic 1980s office building, floor area 5000m 2, 3
stories.
q Baseline: Building left as is.
q Minimum: Upgrade so that the building meets
ASHREA 90.1-2004 (more efficient HVAC and
windows (inoperable).
$89,000
upgrade ∆ cost
q Medium: Same as previous but add mixed-mode
ventilation & solar shading.
$183,000
upgrade ∆ cost
q Advanced: Same as previous but double all
insulation levels.
$255,000
upgrade ∆ cost
Case Study: Cumulative Energy Costs
Paper: S H Holmes and C F Reinhart, Assessing future climate change and energy price scenarios for
institutional building investment and HVAC operation, Building Research and Information, 41:2, pp.
209-222, 2013.
Case Study: Cumulative Energy Costs
q IRR highest for minimum upgrade. (It is tough, energy is cheap in this
country.)
q Cooling dominated climates have higher IRRs. This does not necessarily
translate into actions today.
Urban Modeling
C Reinhart, C Cerezo, J A Jakubiec, T Dogan, T Rakha
Context - From homo sapiens to homo urbanus
Source: WIKI UN 2010 Projections
q Industrial Revolution - 3% city dweller
q 2008 - 50% city dweller
q 2030 60% city dweller 1.7 billion more than today
Grimond, J, 2007, The world goes to town, The Economist, May 5th 2007
Our task is to house 1.7 billion new
city dwellers in 17 years or two
million a week.
How can we do this?
Housing for 2 million in Boston corresponds to about 80,000 buildings
week.
q Dramatically increase the number of qualified simulationists
q Introduce significant economies of scale = urban modeling
How do we live?
Goal
To develop an urban modeling platform to design and
improve new and existing neighborhoods regarding multiple
measures of urban sustainability including operational
energy use, daylighting, outdoor comfort and sustainable
transportation.
Informal Settlement
in Rio
Suburbs in Shanghai
Operational Energy
Operational Energy
Mobility
Mobility
Comfort
Comfort
Back Bay, Boston
Daylight
Daylight
Costs
Costs
Embodied Energy
Embodied Energy
Forum Vaubin, Freiburg, Germany
Combining Big Data and BPS
Photo of the MIT Campus (Google Maps).
LiDAR Data of the MIT Campus
3 dimensional point cloud (126 million points).
3D Model of the MIT Campus
Generation of a 3D model through surface triangulation.
Solar Radiation Map
Cumulative annual solar radiation.
Mapdwell – MIT spinoff
umi
Workflow
Plug-in for NURBS Modeler Rhinoceros 5
Download at
www://UrbanModeling.net
Massing Model
How does it work? User Perspective
1. Design a building form
2. Assign energy templates and 3. Simulation model constructed
fenestration information
Visualizing umi-Thermal Simulation
Results
Export and simulation time: ~20 minutes with parallel processing (8 GHz-hours).
Whole city electricity, gas and
carbon emissions
Valuable input for district heating and cooling providers.
umi - Outdoor Comfort
Hourly Solar Radiation:
-> Daysim/Radiance
-> E+ Weather File
umi - Outdoor Comfort
Tair > 28 °C & dir solar
Tair < 5 °C & without dir solar
hours / yr
hours / yr
Source: Timur Dogan
umi - Mobility
Source: Tarek Rakha
umi - Daylighting
Hourly Exterior Solar
Radiation*
Interior light solver **
Dogan, Reinhart, Michalatos, URBAN DAYLIGHT SIMULATION CALCULATING THE
DAYLIT AREA OF URBAN DESIGNS, SimBuild2012
Umi - Daylighting
Calculated in less than 30 minutes including model setup.
Source: Timur Dogan
umi – Embodied Energy
Source: Carlos Cerezo
Today’s Presentation
From evaluating performance to
suggesting new forms
√q Environmental performance simulations are now capable of predicting
the physical performance of commonly used building typologies and
technologies.
√q Parts of this analysis can be done by architects and planners
themselves. Is this true/desirable?
√q We can increasingly expand our analysis to the urban/neighborhood
realm.
Closing Thoughts
q Building Science and BPS have reached a level of professional
maturity and the results of BPS increasingly draw attention form
outside of the traditional AEC community.
q More comprehensive teaching of Building Science is required that
combines validated rules of thumb with simulations and case study
analysis.
q We need to collect and publicize the energy use of all buildings and
rate a building according to its performance with respect to its peers.
Thank you
Contact
Christoph Reinhart
Associate Professor
MIT
Email: creinhart@mit.edu
Today – Launch of the
Washington DC Solar Map
MIT Sustainable Design Lab
Carlos Cerezo
Timur Dogan
Diego Ibarra (GSD)
Alstan Jakubiec
Nathaniel Jones
Aiko Nagano
Krista Palen
Tarek Rakha
Julia Sokol
Solemma
Alstan Jakubiec
Kera Lagios
Jeff Niemasz
Christoph Reinhart
Jon Sargent
Alumni
Seth Holmes, Karthik Dondeti, Elliot Glassman, Cynthia Kwan, Rohit Manudhane, Rashida Mogri,
Azadeh Omidfar, Debashree Pal, Tiffany Otis, Holly W Samuelson, Jennifer Sze, John Sullivan, Nari
Yoon