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Parametric study of building variations is perhaps where computer
simulations are at their best in playing the what-if game!<br>
<br>
It's troubling and unfortunate that there was more such studies back
20-30 years ago than now, where the focus has been on developing
ever more complicated building models and ever more detailed
algorithms, with the apparent goal of creating pristine one-time-use
building models.<br>
<br>
I remember when I was first introduced to building energy
simulations at UC Berkeley in 1980, one of my class assignments was
to use Murray Milne's SOLAR-5 program to study the change in loads
for different building orientations. When I first went to LBNL (LBL
in those days :-)), I created a residential building energy data
base for which I created 5 prototypical residential building models
full of macros, which allowed me to do a hundred parametric for each
building model in 45 locations, stepping through common variations
of ceiling and wall insulation, window area/orientation/panes of
glass, infiltration rates, etc., or around 10,000-20,000 runs in
all. These were then reduced to nonlinear equations that drove
simplified programs such as PEAR (Program for Energy Analysis of
Residences, LBNL 1987) or ARES (Automated Residential Energy
Standard, PNNL 1989). <br>
<br>
In 1990, I worked briefly for a East Coast consultant company that
did a lot of utility-supported DSM projects. For those, we would
typically build a base building model, and then ran it through a
dozen or more EEMs requested by the A/E Team. <br>
<br>
In 2004, I had a project to calculate U/SHGC trade-off equations for
DOE's
EnergyStar Windows, for which I wrote a batch process for iterative
DOE-2 simulations varying the U-factor until the building energy use
was within 0.02MBTU of the EnergyStar Window. The same procedure
could also be used to search for the minimum building energy cost,
or automated optimization.<br>
<br>
What I'm trying to say is that parametric analysis has always been
around, and not particularly difficult to do as long as we move away
from using GUI interfaces to writing building input files with
macros, and then add scripts to the batch file to set the macros in
the run stream. <br>
<br>
Joe
<pre class="moz-signature" cols="90">Joe Huang
White Box Technologies, Inc.
346 Rheem Blvd., Suite 205A
Moraga CA 94556
<a class="moz-txt-link-abbreviated" href="mailto:yjhuang@whiteboxtechnologies.com">yjhuang@whiteboxtechnologies.com</a>
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(o) (925)388-0265
(c) (510)928-2683
"building energy simulations at your fingertips"
</pre>
<div class="moz-cite-prefix">On 9/11/2015 7:17 AM, R B wrote:<br>
</div>
<blockquote
cite="mid:CA+f4ixDPm9HT95BAfGYs_vAzaO2k5fDyRZTE5kzFd4xgo4Qo8w@mail.gmail.com"
type="cite">
<meta http-equiv="Context-Type" content="text/html; charset=UTF-8">
<div dir="ltr">Dan,
<div>You are right that most of the 'optimization' happens once
all the massing/shape/room locations/configurations are
finalized. Even now, I dread when I am asked to help with
energy analysis during the early design phase since I have
this at the back of the mind that the architect might come
back with several totally new designs (shape/floors etc.) and
I will have to redo the whole process. This has never happened
in my case, and most decisions are WWR, insulation, glass
types, shading and major system types.</div>
<div>To get back to your question, for the type of analysis that
you have outlined, you might want to look at the expert system
based research in architecture departments where they work on
automatic design generation. Carnegie Mellon comes to mind
since I was involved in this type of work ages back (that was
in the 90's.). Microstation/Autocad might have these kind of
tools inbuilt by now (I havn't really kept up with this
topic), and since they also have energy tools connection -
what you are suggesting seems doable.</div>
<div>-Rohini</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Thu, Sep 10, 2015 at 4:33 PM, Dan
Johnson <span dir="ltr"><<a moz-do-not-send="true"
href="mailto:dan@designandenergy.com" target="_blank">dan@designandenergy.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote">
<div dir="ltr">Aaron and Jason, I like this thread. I
noticed that the curve Aaron presented for WWR vs. Source
Energy shows only a 4% difference in Source Energy over a
range of 0-50% WWR---I would say a negligible difference
from optimizing this component alone. An architect would
shrug this off, despite the thought and computing power
that went into it. This got me to thinking that, as an
architect, the aspect my colleagues most have trouble with
is the arrangement of building elements, rather than the
optimization of each one.
<div><br>
</div>
<div>Jason's questions related to arrangement---how many
floors? what shape building?---would be the most useful
for conceptual design, in my opinion. I would leave
alone insulation levels and even WWR at the
programming/conceptual stage, and instead run hundreds
of simulations with different *arrangements* of zones. I
would further clarify this point by adding to Jason's
questions list:</div>
<div><br>
</div>
<div>1. Does the conference room go on the east or west
(re: sun exposure)? Under the roof, or in the basement?</div>
<div>2. How deep can floor plates be, and still achieve
adequate daylighting?</div>
<div>3. What aspect ratio of the atrium vs. the floor
plates gives us adequate natural ventilation?</div>
<div>4. If I put the fume hoods in the classroom, I have
to ventilate the whole classroom, but if I put them only
in prep rooms, that is a much smaller air volume...what
difference does this make?</div>
<div>5. If I cluster all my public circulation to one
side, and naturally ventilate this, how much energy do I
save vs. distributed circulation that is conditioned
with fans?</div>
<div>6. Add a giant, beautiful glass staircase---do I save
enough elevator energy to offset the conditioning of the
staircase?</div>
<div><br>
</div>
<div>In typical optimization modeling, the geometry is
fixed and we vary the component parameters. I'd like to
see the opposite.</div>
<div><br>
</div>
<div>If the auto-generating algorithm could produce a 3D
mass diagram of color-coded zone blobs, perhaps as a
Sketchup object, that would communicate well.</div>
<div><br>
</div>
<div>Again, architects tend to have trouble with the
spatial arrangement of zones as something driven by
performance. Perhaps the most useful thing at the
programming/concept design stage is help with
arrangement. Thank you, Dan J</div>
<div>
<div class="gmail_extra"><br>
<div>
<div>
<div dir="ltr">
<div>
<div dir="ltr">Dan Johnson | Design and Energy
| <a moz-do-not-send="true"
href="tel:510.325.5672"
value="+15103255672" target="_blank">510.325.5672</a><span></span>
<div>Assoc. AIA, ASHRAE, LEED AP, CEPE, CPHC
| 907 Ramona Ave. Albany California 94706</div>
</div>
</div>
</div>
</div>
</div>
<br>
<div class="gmail_quote">
<blockquote class="gmail_quote"><br>
---------- Forwarded message ----------<br>
From: Aaron Powers <<a moz-do-not-send="true"
href="mailto:caaronpowers@gmail.com"
target="_blank">caaronpowers@gmail.com</a>><br>
To: Jason Glazer <<a moz-do-not-send="true"
href="mailto:jglazer@gard.com" target="_blank">jglazer@gard.com</a>><br>
Cc: <a moz-do-not-send="true"
href="mailto:bldg-sim@onebuilding.org"
target="_blank">bldg-sim@onebuilding.org</a><br>
Date: Thu, 10 Sep 2015 12:46:16 -0500<br>
Subject: Re: [Bldg-sim] 100 simulations<br>
<div dir="ltr">
<div>
<div>
<div>
<div>Jason,<br>
<br>
</div>
This is something I'm interested in as
well. I think all the preliminary design
factors that you mentioned are great
things to look at. On the later parts of
the design process, control parameters are
also good things to look at (CHW plant
control optimization, air-side control
optimization, etc.).<br>
<br>
</div>
One way to convey the information is through
simple 2D plots. Below is an example of 200
DOE2 simulations while varying the window to
wall ratio and another plot of 81
simulations varying the window shading
coefficient.<br>
<br>
</div>
<img alt="Inline image 1"
src="cid:part6.04060205.08000405@whiteboxtechnologies.com"
height="375" width="525"><img alt="Inline
image 2"
src="cid:part7.04020303.00080405@whiteboxtechnologies.com"
height="375" width="525"><br>
<br>
<br>
<br>
</div>
<div>Unfortunately, this does not convey the
interactive nature of optimization over
multiple variables. Using multidimensional
optimization algorithms can be another useful
tool, but they can be tricky. As an example,
below is a case of looking for the optimal
minimum condenser water flow in a variable
flow condenser system. From looking at the
first plot, the function seems relatively
smooth and it's obvious that there's an
optimal in the neighborhood of 0.6. However,
if you zoom in (second plot), you can see that
the data is not very smooth, and there are all
kinds of jagged local minima/maxima. These
will tend to throw off most optimization
algorithms, which is why I think it's helpful
to consider looking at automated mass
simulations before taking on the problem of
optimization.<br>
<br>
<img alt="Inline image 5"
src="cid:part8.01090606.00000803@whiteboxtechnologies.com"
height="380" width="525"><br>
<br>
</div>
<div><img alt="Inline image 4"
src="cid:part9.03030602.05030008@whiteboxtechnologies.com"
height="377" width="525"><br>
</div>
<div>Aaron<br>
</div>
</div>
<div class="gmail_extra"><br>
<div class="gmail_quote">On Wed, Sep 9, 2015 at
4:33 PM, Jason Glazer <span dir="ltr"><<a
moz-do-not-send="true"
href="mailto:jglazer@gard.com"
target="_blank"><a class="moz-txt-link-abbreviated" href="mailto:jglazer@gard.com">jglazer@gard.com</a></a>></span>
wrote:<br>
<blockquote class="gmail_quote">I am just
finishing up a project that performed about
60 automated simulations (using Python with
EnergyPlus and Eppy) for a series of
buildings in a bunch of cities. The power of
automating simulations to understand the
energy savings of different measures is very
impressive no matter what tools are being
used. It has made me wonder about when does
automation make the most sense during the
design process and what information can be
provided to an architect or entire building
design team to encourage low energy building
design. I am thinking one of the most
influential times might be during the
architectural programming and early
conceptual design steps. At this point the
number of separate pieces of information is
probably low enough that it could be filled
out on a web form:<br>
<br>
- number of occupants<br>
<br>
- amount of area needed for different types
of spaces<br>
<br>
- location of the lot lines<br>
<br>
- building location<br>
<br>
Conceivably, with that information, all
sorts of various building configurations
could be created automatically by a clever
script then simulated and the resulting
answers summarized.<br>
<br>
- How many floor building uses the least
energy?<br>
<br>
- What shape building uses the least
energy?<br>
<br>
- What is the impact of more roof
insulation?<br>
<br>
- What is the impact of more or less
fenestration on loads and daylighting?<br>
<br>
I would not expect the design team to use
any of the automatically created building
models directly but it might influence the
design process in a good way if it was easy
to get and easy to understand. I understand
people have been researching the
optimization of these kinds of factors but I
am not sure that is necessary. Maybe just
several different series of simulations
illustrating various building options and
their impact onenergy might be enough to get
the discussion going.<br>
<br>
- So what questions do you think could be
answered by such an automated system during
early conceptual design?<br>
<br>
- How would you best convey that
information to the building design team?<br>
<br>
- Are there other times that a suite of
automated simulations would make sense?<br>
<br>
A lot of useful information could be
generated with a hundred automated
simulations!<span><br>
<br>
Jason<span class="HOEnZb"><br>
<br>
-- <br>
Jason Glazer, P.E., GARD Analytics, 90.1
ECB chair<br>
Admin for <a moz-do-not-send="true"
href="http://onebuilding.org"
rel="noreferrer" target="_blank">onebuilding.org</a>
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<br>
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