BS2017_Nikolaidou_Wright_Hopfe.pdf (2.93 MB)

Robust building scheme design optimization for uncertain performance prediction

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conference contribution
posted on 27.04.2017 by Elli Nikolaidou, Jonathan Wright, Christina Hopfe
Design exploration is a vital part of the building design process that aims at identifying the best-performing design with regard to the requirements of the client and building regulations. Building performance simulation can support this “explorative” process, its potential however being restricted by the fact that all design parameters are subject to uncertainty. In addition, while the need for an efficient exploration of the design space has resulted in the integration of optimization into the design process, the majority of existing research treats uncertainty quantification and optimization as separate processes. Finally, candidate designs are commonly evaluated with respect to only one or two design criteria, while the multi-dimensionality of real-world problems calls for integrated design solutions that meet several – often-conflicting – objectives. A new approach is thus developed that aims to help designers identify robust Pareto-optimal solutions that satisfy several design criteria, while remaining optimal regardless of the uncertainty in boundary conditions. Through its implementation to a real-world case-study building, the novel approach is found to be able to identify optimum solutions that preserve their optimality over the entire range of uncertain performance scenarios.

Funding

This research is supported through a studentship funded by the UK Engineering and Physical Sciences Research Council (EPSRC).

History

School

  • Architecture, Building and Civil Engineering

Published in

Building Simulation 2017

Citation

NIKOLAIDOU, E., WRIGHT, J.A. and HOPFE, C.J., 2017. Robust building scheme design optimization for uncertain performance prediction. Presented at the Building Simulation 2017: The 15th International Conference of IBPSA, San Francisco, August 7-9th.

Publisher

IBPSA

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

14/02/2017

Publication date

2017

Notes

This is a conference paper.

Language

en

Location

San Francisco, USA

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