Show simple item record

dc.creatorshahsavari, Fatemeh
dc.creatorYan, Wei
dc.creatorKoosha, Rasool
dc.date.accessioned2019-05-30T21:29:12Z
dc.date.available2019-05-30T21:29:12Z
dc.date.issued2019-05-26
dc.identifier.citationShahsavari, F., Yan, W., & Koosha, R. (2019). A Case Study for Sensitivity-Based Building Energy Optimization. ARCC Conference Repository, 1(1). Retrieved from https://www.arcc-repository.org/index.php/repository/article/view/644en
dc.identifier.urihttps://hdl.handle.net/1969.1/175379
dc.description.abstractBuilding design optimization process is associated with uncertainties due to climate change, unpredictable occupant behavior, and physical degradation of building material over time. The inherent uncertainties in the design process reduce the reliability and robustness of the optimal design solution(s) and affect design decision-making results. This research studies the capabilities of parametric design tools in adopting probabilistic methods to handle uncertainties in building performance optimization. Variance-based methods, e.g., Monte Carlo sensitivity analyses are implemented to identify the most critical parameters in design optimization problems and improve the efficiency of design optimization. The optimal solutions achieved with variance-based methods are satisfying the design objectives more efficiently, also remain robust to changes and uncertainties.en
dc.language.isoen_US
dc.publisherARCC Conference Repository
dc.subjectBuilding design optimizationen
dc.subjectVariance-based methodsen
dc.subjectParametric designen
dc.subjectSensitivity analysisen
dc.subjectMonte Carloen
dc.titleA case study for sensitivity-based building energy optimizationen
dc.typeArticleen
local.departmentArchitectureen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record