Implementing Surrogate Modeling Techniques for Designing Optimal Building Envelops: A Case Study

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dc.contributor.authorMonshet, Shahrzad
dc.contributor.authorFroese, Thomas M.
dc.contributor.authorEvins, Ralph
dc.date.accessioned2022-08-19T18:33:25Z
dc.date.available2022-08-19T18:33:25Z
dc.date.copyright2022en_US
dc.date.issued2022-05-25
dc.description.abstractBuildings are known to have significant environmental impacts. The life cycle approach to measuring CO2 emission and life cycle costs of buildings is getting more important in the building design process. However, due to the complexity of the design process and the computational time of simulations and data processing, such methods are difficult to implement within optimization processes. This paper aims to apply surrogate modeling techniques as a solution to resolve the computational difficulties in the optimization process of building envelopes. The paper will describe the methods applied and will evaluate several aspects of the process, including the impact of the size of the training set on the prediction accuracy and the impact of different energy system efficiencies on the final optimum envelope design concerning seven objectives related to the economic and environmental performance of the building. The results showed that the size of the sampling test has a significant effect on the prediction accuracy; however, a balance between increasing the precision and computational time can be found to select an adequate number of samples. Moreover, it is found that to achieve the lowest total equivalent cost corresponding to the highest economic and environmental performance of the building, the minimum allowed the window to wall ratio (15 %) and the maximum permitted wall insulation thickness (0.02 m) is realized to be the final optimal solution and, therefore, recommended in design. The surrogate model was also shown to be efficiently capable of finding the optimum results according to the other objectives, including both economic and pure environmental aspects. Furthermore, the results provide insightful information on how the variation of energy systems' efficiency might affect the optimum solutions in the optimization process.en_US
dc.description.embargo2024-06-30
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.identifier.citationS. Monshet, T.M. Froese, and R. Evins, Implementing Surrogate Modeling Techniques for Designing Optimal Building Envelops: A Case Study, CSCE 2022 Annual Conference, Whistler, Canada, May 25-28, 2022.en_US
dc.identifier.urihttp://hdl.handle.net/1828/14104
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Canada*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/ca/*
dc.subjectSurrogate Models
dc.subjectBuilding Envelope
dc.subjectOptimization
dc.subjectEconomic and environmental performance
dc.subject.departmentDepartment of Civil Engineering
dc.titleImplementing Surrogate Modeling Techniques for Designing Optimal Building Envelops: A Case Studyen_US
dc.typePreprinten_US

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