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4 results for “building performance simulation”
HeatResilientCity II - work package 2.2: Influence of regional and urban climate on indoor overheating - Results of building performance simulation
<p>This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.2 Influence of regional and urban climate on indoor overheating of the project <a href="http://heatresilientcity.de/">HeatResilientCity II</a>. The buildings under consideration are a multi-residential so-called ‘Gründerzeithaus’ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms on the top floor/attic of each building and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoors and outdoors. Further information can be found in the README of this repository. The simulations were performed for five <strong>different</strong> <strong>regions</strong> in Germany (Dresden, Hamburg, Köln, Stuttgart and Potsdam) for <strong>average present</strong> and <strong>future</strong> <strong>summers</strong> based on meteorological measurement data and under consideration of <strong>urban</strong> <strong>climate</strong>.</p> <p>In addition to the ‘plain’ simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in the files <em>Calculated_Variables.txt</em>. The calculated quantities include temperature-weighted exceedance hours (TWEH) for the limits of 25, 26 and 27 °C (defined in DIN 4108-2:2013 as ‘Übertemperaturgradstunden’) and the maximum operative temperature calculated for the period from April to September.</p> <p>The used <strong>input data</strong> and <strong>building models</strong> can be found in the related repository.</p>
HeatResilientCity II - work package 2.3: Interactions between buildings and open space adaptation measures – Meteorological input data for building performance simulation
<p>This repository contains <strong>meteorological</strong> <strong>data</strong> from urban climate simulations that were carried out in districts of the cities of Dresden and Erfurt as part of the <a href="http://heatresilientcity.de/">HeatResilientCity II</a> project. The data was extracted at specific points (receptors) of the urban climate model. In addition to the data, a <strong>script </strong>is attached that can be utilized to generate a time series for IDA ICE building performance simulations using IceWeather.exe. Therefore, a Microsoft Windows operating system is required. To create a time series, simply use the function <em>createIdaIceInput()</em> at the end of the script <em>createTimeSeries.py</em>. Further explanations can be found at the beginning of the script. Information about the ENVI-met data used to create the IDA ICE input can be found in <em>README_RawENVImetOutput_DD.txt</em> and <em>README_RawENVImetOutput_EF.txt</em>.</p> <p>Some input <strong>data files have already been generated</strong><strong> </strong>and can be directly used for<strong> thermal building performance simulations with IDA ICE</strong>. These files can be found in the folder <em>0.3_Input_Timeseries (Climate) for IDA ICE</em>.</p> <p>The <strong>naming convention</strong> of the final input data files for IDA ICE is as follows:</p> <ul> <li>TOWN_SCENARIO_RECEPTOR_AVERAGING_INTERFACE_LATITUDE_LONGITUDE_VERSION</li> <li>TOWN: Choose between 'Erfurt' and 'Dresden'</li> <li>SCENARIO: See further information in <em>README_RawENVImetOutput_DD.txt</em> and <em>README_RawENVImetOutput_EF.txt</em></li> <li>RECEPTOR: Location in the modelled area (ENVI-met simulation) where data was extracted.</li> <li>AVERAGING: Information about averaging the hourly values of the urban climate simulation (see <em>createTimeSeries.py and READMEs)</em></li> <li>INTERFACE: Information on how single days were joined together (see <em>createTimeSeries.py</em>).</li> <li>LATITUDE: Default values for Dresden and Erfurt are set in the script. Add additional values in the function <em>setIceWeatherParams()</em> if you are using other cities/custom ENVI-met simulation data.</li> <li>LONGITUDE: Default values for Dresden and Erfurt are set in the script. Add additional values in the function <em>setIceWeatherParams()</em> if you are using other cities/custom ENVI-met simulation data.</li> <li>VERSION: The version number can be set in the script.</li> </ul> <p>Example: <em>Dresden_2y_A1_a_timeSeries_24-24_51.0468_13.6707_v11.prn</em></p> <p><strong>Folder overview:</strong></p> <ul> <li>The ENVI-met raw data is stored in <em>0.1_Input_RawENVImetOutput</em>.</li> <li>The script is stored in <em>0.2_Input_ScriptsToCreateTimeSeries</em>.</li> <li>The final datasets ready for simulation with IDA ICE are stored in <em>0.3_Input_Timeseries(Climate)ForIDAICE</em>. This folder also contains some weather data time series that have already been created and can be used for IDA ICE (subfolders Erfurt_v11 and Dresden_v11).</li> </ul>
Data for Gaussian-Process-Based Emulators for Building Performance Simulation
<p>The ZIP folder contains the MAT files you need to rerun the experiment described in</p> <p>Rastogi, Parag, Mohammad Emtiyaz Khan, and Marilyne Andersen. 2017. “<strong>Gaussian-Process-Based Emulators for Building Performance Simulation</strong>.” In <em>Proceedings of BS 2017</em>. San Francisco, CA, USA: IBPSA.</p> <p>-------------------------------------------------------------</p> <p>The two m-scripts (MATLAB) help you to load the results reported in the paper. Make sure to CHECK the file paths inside the scripts, especially to the MAT files. Usually, the paths should be fine if you update the variable <em>pathMATfolder</em> inside the script <em>RunThis.m</em> .</p> <p>There are two types of MAT files inside the folder called "Data" :</p> <p>1. Original data (building simulations) --> gpdata_BaseSimulation.mat</p> <p>2. Errors and predictions - errs_BaseSimulation_N_M.mat and ystore_BaseSimulation_N_M.mat --> The first contains all the error quantities and the second the 'y' predictions. The number N represents the run number (subset of master training data set sampled for the given run). The number M can take only two values - 1 or 2. The models for heating load are represented by 1 and for cooling by 2.</p> <p>3. Metadata - trainN* --> These files contain metadata for setting up the plots.</p> <p>See github repository <strong>https://github.com/paragrastogi/GPregressionInBS.git</strong> for more scripts. See <strong>www.paragrastogi.com</strong> or <strong>www.ibpsa.org</strong> for the conference paper.</p>
HeatResilientCity II - work package 2.3: Interactions between buildings and open space adaptation measures – Results of building performance simulations
<p>This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.3: Interactions between buildings and open space adaptation measures of the project <a href="http://heatresilientcity.de/">HeatResilientCity II</a>. The buildings under consideration are a multi-residential so-called „Gründerzeithaus“ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms of each building on the top floor/attic and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoor and outdoor. Further information can be found in the README of this repository.</p> <p>In addition to the “plain” simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in <em>Calculate_Indicators_Dresden.txt </em>and<em> Calculate_Indicators_Erfurt.txt</em>. The calculated quantities include temperature weighted exceedance hours for the limits of 25, 26 and 27 °C, the maximum operative temperature occurring during the simulation and the operative indoor temperature and outdoor air temperatures at 4 am and 6 pm on the last day of the heat period/simulation.</p> <p>The used <strong>input data</strong> and <strong>building models</strong> can be found in the related identifiers.</p>
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