A decision support tool for sustainable and resilient building design

Abstract

In this chapter, an integrated approach for a holistic (involving notions of safety, resiliency and sustainability) building design is presented to select the optimal design alternative based on multiple conflicting criteria under uncertainty. A probabilistic framework of the Multi-Attribute Utility Theory (MAUT) is adopted, where MAUT is developed in conjunction with Performance-Based Engineering (PBE) approach, giving rise to a general framework, namely the PBE-MAUT. In PBE-MAUTdifferentdesignalternatives mayberankedbasedontheexpected utility. The discrepancies from the expected utility theory may be modelled through a risk-averse modelling of the utility functions based on the individual perceptions, or a more detailed description of the consequences valuable to the decision makers. Moreover, a risk-averse decision-maker towards extreme events can consider suitable quantilesorsuperquantiles.Thedistributionoftheutilityfunctionisobtainedfromthe First Order Reliability Method (FORM) which, through the design point, gives also themost critical realizations oftheconsequences fordifferent degrees ofriskaversion. The decision-making process is dynamic, in the sense that the optimal decision changes accordingly when new information is available. Such dynamic behavior is effectively represented using the Bayesian analysis, here modeled by combining PBE-MAUT with the Bayesian Network (BN). In this manner, the proposed framework represents a powerful Decision Support Tool (DST) for holistic building design. The BN, in conjunction with an array of sensors, can also be effectively used to determine the multi-criteria optimal decision considering the building lifecycle for a sustainable and resilient building design. The key features of the DST are demonstrated by an application to an office located on the Create Building, in Singapore.