[Bldg-sim] 100 simulations

R B slv3sat at gmail.com
Fri Sep 11 07:17:11 PDT 2015


Dan,
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.
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.
-Rohini

On Thu, Sep 10, 2015 at 4:33 PM, Dan Johnson <dan at designandenergy.com>
wrote:

> 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.
>
> 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:
>
> 1. Does the conference room go on the east or west (re: sun exposure)?
> Under the roof, or in the basement?
> 2. How deep can floor plates be, and still achieve adequate daylighting?
> 3. What aspect ratio of the atrium vs. the floor plates gives us adequate
> natural ventilation?
> 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?
> 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?
> 6. Add a giant, beautiful glass staircase---do I save enough elevator
> energy to offset the conditioning of the staircase?
>
> In typical optimization modeling, the geometry is fixed and we vary the
> component parameters. I'd like to see the opposite.
>
> 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.
>
> 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
>
> Dan Johnson | Design and Energy | 510.325.5672
> Assoc. AIA, ASHRAE, LEED AP, CEPE, CPHC | 907 Ramona Ave. Albany
> California 94706
>
>
>> ---------- Forwarded message ----------
>> From: Aaron Powers <caaronpowers at gmail.com>
>> To: Jason Glazer <jglazer at gard.com>
>> Cc: bldg-sim at onebuilding.org
>> Date: Thu, 10 Sep 2015 12:46:16 -0500
>> Subject: Re: [Bldg-sim] 100 simulations
>> Jason,
>>
>> 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.).
>>
>> 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.
>>
>> [image: Inline image 1][image: Inline image 2]
>>
>>
>>
>> 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.
>>
>> [image: Inline image 5]
>>
>> [image: Inline image 4]
>> Aaron
>>
>> On Wed, Sep 9, 2015 at 4:33 PM, Jason Glazer <jglazer at gard.com> wrote:
>>
>>> 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:
>>>
>>>  - number of occupants
>>>
>>>  - amount of area needed for different types of spaces
>>>
>>>  - location of the lot lines
>>>
>>>  - building location
>>>
>>> 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.
>>>
>>>  - How many floor building uses the least energy?
>>>
>>>  - What shape building uses the least energy?
>>>
>>>  - What is the impact of more roof insulation?
>>>
>>>  - What is the impact of more or less fenestration on loads and
>>> daylighting?
>>>
>>> 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.
>>>
>>>  - So what questions do you think could be answered by such an automated
>>> system during early conceptual design?
>>>
>>>  - How would you best convey that information to the building design
>>> team?
>>>
>>>  - Are there other times that a suite of automated simulations would
>>> make sense?
>>>
>>> A lot of useful information could be generated with a hundred automated
>>> simulations!
>>>
>>> Jason
>>>
>>> --
>>> Jason Glazer, P.E., GARD Analytics, 90.1 ECB chair
>>> Admin for onebuilding.org building performance mailing lists
>>>
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>>
>>
>>
>> --
>> Sent from my DynaTAC 8000x
>>
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