This document discusses computational design in architecture and building simulation software. It covers the need for environmental building simulation tools, how to select and evaluate such tools, and what the future of building system modeling may look like. Key points include that simulation tools can evaluate energy efficiency, renewable energy, and sustainability in buildings. Selection criteria include the tool's capabilities, ease of use, cost, and support. The document also outlines the steps to develop a simulation model and experiment and stresses the importance of validating models against real data.

1. Computational Design in Architecture
Prepared by: Dr. Nagham Ali Hassan
PhD in environmental design, energy efficiency and renewable energy

2.  The need for Environmental Building Software
Tools
 Aspects of using environmental design tools
 ED-Tools: selection and evaluation criteria
 How to select the best simulation software?
 What a future environment for building system
modeling and simulation may look like?
Dr. Nagham Ali Hasan 2

3.  Spitler (2006) states that “simulation of building thermal
performance using digital computers has been an active
area of investigation since the 1960s, with much of the early
work.
 Over the last 20 years large and continuous increases in
computational development of software tools that designed
to help designers and environmental engineering
consultants make such predictions.
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4. 1. Economic and social pressures
on natural resources globally
2. Climate change is a growing
concern politically
3. Mitigation of greenhouse gas
emissions and adaptation to a
changing climate are priority
issues
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0%
10%
20%
30%
40%
50%
60%
70%
80%
material energy water land timber
50% 45% 40%
60%
70%Currently buildings:
 Consume ~ 37% world energy
 Exploit ~ 40% of world resources
 Produce ~ 40% of world waste

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Dynamic interactions of (continuously changing)
sub-systems in a building context.

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Energy use, indoor air quality and occupant thermal and visual comfort
in buildings are largely influenced by decisions taken in the early stages of
design, often by choices made even before design commences.

7. Purpose of a model is:
1. to enable the analyst to
predict the effect of
changes to the system.
2. a model should be a close
approximation to the real
system and incorporate
most of its salient
features.
A model is a representation of the construction and working of some system of
interest.
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Fig: Designbuilder model interface
Modeling is one way of attaching metrics to
abstract policy and regulatory rhetoric. These
scenarios can augment team-based decision
making and business strategy formulation

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Ways to study a system
 A good model is a
judicious trade-off between
realism and simplicity
 Generally, a model
intended for a simulation
study
 The model should be
flexible and easy of use

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Simulation is used to simulate
everything from games to economic
growth to engineering problems.
Simulation can be one tool used
to examine possible scenarios that
can be followed.
What is simulation?

10. Building Form Optimization for Natural
Ventilation with Using CFD simulation, ISOENV
with MODU Architecture NY, 2014
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Automation simulation

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What tool, which one?
What for, why?
When?
How to (how not to) ?
What does result mean?
Building software tools can evaluate:
1. Energy efficiency,
2. Renewable energy,
3. Sustainability in buildings

12. Current use of performance simulation in
practical building design.
The actual
application is
generally
restricted to the
final phases in
building design
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The application stages:

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Energy Simulation
Load Calculation
Renewable Energy
Retrofit Analysis
Sustainability/Green Buildings
Envelope Systems
HVAC Equipment and Systems
Lighting Systems
Atmospheric Pollution (CO2)
Energy Economics
Indoor Air Quality (IAQ)
Solar/Climate Analysis
Ventilation/Airflow
Water Conservation
Whole Building
Analysis
Materials,
Components,
Equipment, &
Systems
Other Applications
Few of the available tools
deal with all of the tasks
and operations
encompassed by
environmental design.
(Whole Building
Analysis)
Some were designed to
deal specifically with only
one or some of these
processes.
(Codes &
Standards)

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COGNITIVE CRITERIA (what does the tool do ?)
Heuristic Domain (capabilities /
suitability )
Hermeneutic Framework (meaning
and value) what kind of outputs are
provided (form / detail)?
• how does the tool work?
• which physical processes are modelled or
omitted ?
• what simplifications are made?
• what does the tool help find?
• what does the tool does not find?
• what do the outputs mean, how do they
compare with other available data and with
targets and benchmarks?
• can we bypass the tool's modelling or other
limitations and how?

15.  Applicability range of use
(simple - complex)
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PRACTICAL CRITERIA (usability and user-friendliness)
 Ease of Use (how fast to
learn, how easy to use?)
 how fast to get results?
 what communication with user?
 how easy to make changes, re-run
and draw comparisons?
 range of application (single purpose -
multiple)
 range of action (single task -
multitask)
 accuracy
 practical usefulness / comparability

16.  documentation and training available
 technical support from developer?
 further development?
 peer group / community of users
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MARKET CRITERIA (acquire or not ?)
 Cost
Support and Updates
 purchase cost (hardware / software
license )
 speed and ease of learning (time /
knowledge required)

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The tools outputs can
include:
 databases,
 spreadsheets,
 component and systems
analyses,
 and whole-building energy
performance simulation
programs
eQUEST software output

18.  In order to improve predictions and help designing
more robust solutions:
 should We focus on getting all the required “correct” data??
 or should we rather be more realistic and take (sometimes huge)
physical and scenario uncertainties into account??
 What is more relevant:
 Getting the answers right, or
 Getting the right answers ?
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19.  The steps involved in developing a simulation model,
designing a simulation experiment, and performing
simulation analysis are:
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Identify
&
Formulat
e the
problem
Collect and
process real
system data.
&develop the
model
Validate
the
model. Select appropriate
experimental
design
Perform
simulation
runs.

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The problem
can be solved
using
"common
sense
analysis“
it's easier to
change or
perform direct
experiments on
the real
the cost of
the simulation
exceeds
possible
savings
there aren't
proper
resources
available for the
project or there
is no data –
not even
estimates
project
expectati
ons can't
be met
the model
can't be
verified or
validated
Don’t simulate
when …

21. What a future environment for building
system modeling and simulation may look
like???
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23.  The most widely used from among the tools that deal with thermal analysis
have become increasingly more designer-oriented aiming to address both
three-dimensional visualisation (and thus also studies of solar access and
shading design) and the processes of natural ventilation and solar gain that
are of critical importance in contemporary building design.
 With increasing computer power there has been a continuous trend of
integration and greater capability.
 Calculations that needed to be run overnight a few years ago are now
performed in a few minutes.
 Nevertheless, there is still discrepancy between designers' conception of
realism and accuracy and that possible by the application of most of the
current tools.
 Clearly users must have an understanding of the underlying structure and
theoretical basis of the tools they use
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