Risk Assessment for Performance-Driven Building Design with BIM-Based Parametric Methods

TL;DR

This paper presents BIMProbE, a framework integrating BIM-based parametric tools with probabilistic performance analysis to incorporate uncertainty and risk assessment in building design decision-making.

Contribution

It introduces a novel framework that systematically combines BIM parametrics with probabilistic analysis for risk-aware building design.

Findings

Probabilistic methods alter performance rankings compared to deterministic ones.

The framework enables evaluation of design options based on risk attitudes.

Application demonstrates improved decision-making under uncertainty.

Abstract

A growing demand for handling uncertainties and risks in performance-driven building design decision-making has challenged conventional design methods. Thus, researchers in this field lean towards viable alternatives to using deterministic design methods, e.g., probabilistic methods. This research addresses the challenges associated with conventional methods of performance-driven building design, i.e., ignoring the existing uncertainties and lacking a systematic framework to incorporate risk assessment in building performance analysis. This research introduces a framework (BIMProbE) to integrate BIM-based parametric tools with building probabilistic performance analysis to facilitate uncertainty analysis and risk assessment in performance-based building design decision-making. A hypothetical building design scenario is used to demonstrate the application of the proposed framework. The results show that the probabilistic method leads to a different performance ranking order than the deterministic method. Also, the probabilistic method allows evaluating design options based on different risk attitudes.