[Bldg-sim] Statistical method for data from limited parametric runs

[Chris Yates]

Thanks Jeff and Maria,

I need to sharpen up my statistics!

Best / Chris


On Wed, Oct 30, 2013 at 4:04 PM, Maria Karpman <
maria.karpman at karpmanconsulting.net> wrote:

> Jeff, ****
>
> ** **
>
> Is the Fortran toolkit that you mention below an updated / improved
> version of the toolkit released in ~ 2002, or is it the same program? And
> is there a timeframe for when the new version of Guideline 14 will be
> published?   ****
>
> ** **
>
> Thank you,****
>
> ** **
>
> Maria  ****
>
> ** **
>
> *From:* bldg-sim-bounces at lists.onebuilding.org [mailto:
> bldg-sim-bounces at lists.onebuilding.org] *On Behalf Of *Jeff Haberl
> *Sent:* Wednesday, October 30, 2013 11:30 AM
> *To:* Chris Yates; bldg-sim at lists.onebuilding.org
> *Subject:* Re: [Bldg-sim] Statistical method for data from limited
> parametric runs****
>
> ** **
>
> Hello Chris,****
>
>  ****
>
> There is a method and it works like crazy if it is applied correctly to
> certain classes of buildings. ****
>
> ** **
>
> It’s called an "inverse method". However, applying it to houses in mass is
> not yet prime time. ASHRAE has some guidance on inverse methods for
> commercial buildings  in the soon-to-be-published Guideline-14 . When this
> comes out it will include a copy of the FORTRAN RP1050 toolkit and the
> spreadsheet RP1093 toolkit. With the RP1050 toolkit you can apply ASHRAE
> linear and change-point linear models to energy usage data and extract the
> gross parameters that the 3p change-point models yield. ASHRAE's RP1050
> also provides a variable based degree day model, which is the same as
> PRISM, the Princeton Scorekeeping method. These gross parameters have been
> shown to be useful in determining weather-dependent and weather-independent
> parameters for a building. There are even papers where there has been
> speculation that the PRISM parameters could be "mined" to dig further into
> the "inverse description" of a building, such as Ari Rabl's 1980s paper
> published in Energy and Building’s special PRISM volume, and the more
> recent work by Kissock et al. at the University of Dayton on residential.
> ****
>
>  ****
>
> Ongoing work at our lab will soon show that these methods can be further
> extended for certain classes of buildings to approach an automated audit
> that “guesses” the most probably U-value and SHGC for a window, R-value for
> roofs, etc. So far we've had some success using this “blind calibration”
> method. We’re expecting a PhD thesis on this in the Spring 2014.****
>
> ** **
>
> Jeff****
>
>  ****
>
> 8=!  8=)  :=)  8=)  ;=)  8=)  8=(  8=)  8=()  8=)  8=|  8=)  :=')  8=)8=?
> Jeff S. Haberl, Ph.D.,P.E.,FASHRAE,FIBPSA,........jhaberl at tamu.edu<........jhaberl at tamu.edu>
> Professor............................................................Office
> Ph: 979-845-6507
> Department of Architecture.............................Lab Ph:979-845-6065
> Energy Systems Laboratory.............................FAX: 979-862-2457
> Texas A&M University.....................................77843-3581
> College Station, Texas, USA, 77843..................URL:www.esl.tamu.edu
> 8=/  8=)  :=)  8=)  ;=)  8=)  8=()  8=)  :=)  8=)  8=!  8=)  8=? 8=)8=0***
> *
> ------------------------------
>
> *From:* bldg-sim-bounces at lists.onebuilding.org [
> bldg-sim-bounces at lists.onebuilding.org] on behalf of Chris Yates [
> chris.malcolm.yates at gmail.com]
> *Sent:* Wednesday, October 30, 2013 6:48 AM
> *To:* bldg-sim at lists.onebuilding.org
> *Subject:* [Bldg-sim] Statistical method for data from limited parametric
> runs****
>
> Re-posted (Not sure if the original got on the list?)****
>
> ** **
>
> Dear all, ****
>
> ** **
>
> I'm hoping to find a method that can be implemented in Excel for
> extracting a glazing transmittance from two or more sets of temperature
> results.****
>
> ** **
>
> *Our problem:*****
>
> We assess simulated comfort criteria where operative temperatures in a
> zone above 27degC must be in the 1%-ile or less. We extract a *glazing
> transmission* that will 'only just' meet this criterion from two or more
> sets of results. We have limited access to parametric runs, hence only two
> or more sets of thermal modelling results.****
>
> ** **
>
> *What we've used up to now:*****
>
> In order to 'roughly' evaluate the solar transmissivity that helps achieve
> this criterion we have used TREND and other functions for curve fitting in
> excel to interpolate a transmissivity from two or more sets of results.***
> *
>
> ** **
>
> We have two problems with this approach:****
>
> 1. such a narrow band of results are being focused on so the calc is
> subject to inaccuracies****
>
> 2. our modelling software is limited to one hour timesteps and can only
> report temperatures in 1 degree intervals****
>
> ** **
>
> *Possible solution?*****
>
> My gut fee is that we can extract the information more reliably from a
> broader band of data. Is there an approach that looks at the spread of
> temperature distribution from, say, 25 to 28 degC for two or more result
> sets and extracts the transmissivity that matches the 1%-ile. ****
>
> ** **
>
> *Is there such a method?*****
>
> ** **
>
> Minor note: We limit changes to glazing absorptance between our parametric
> runs, aiming for only changes in transmissivity and reflectance. We have
> found operative temperatures to increase with higher glazing absorptance.*
> ***
>
> ** **
>
> Best regards****
>
> ** **
>
> Chris****
>
> ** **
>
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