Kim, Hyoungsub (2017-12). A Model for Performance Evaluation of Climate-Adaptive Building Envelopes Using Parametric Models and Multi-Criteria Optimization. Doctoral Dissertation. Thesis uri icon

abstract

  • The goal of this research is to enable designers to evaluate the performance of Climate-Adaptive Building Envelopes (CABE) to make better decisions at the conceptual design stage. This goal was accomplished by delivering three contributions to the fields of parametric modeling, building performance simulation, and multi-criteria optimization. There are three main challenges in CABE performance evaluation that cannot be overcome by conventional methods: 1) defining a suitable relationship between environmental factors and their thresholds by focusing on a given condition in CABE behavior control; 2) representing a CABE's time-series behavior by using a single Building Performance Simulation (BPS) model; and 3) managing information related to a CABE's performance and behavior for use in design decisions. To overcome these issues, this research developed a new CABE performance evaluation method called Parametric Behavior Maps (PBM), which makes three key contributions. First, the PBM method is able to generate a CABE operation schedule as an Hourly Behavior of Openness (HBOO) scenario to evaluate CABE performance using a single BPS model. Second, the PBM method produces more reliable outcomes than the conventional process, especially in terms of the time-lag effect of thermal performance. Third, the use of a Function-based Behavior Control System (FBCS) for the CABE efficiently facilitates a multi-criteria optimization process by progressively simulating alternative HBOO scenarios, allowing designers to choose the best scheme. These three contributions offer logical proof that the use of parametric modeling and simulation tools can help designers make better decisions regarding CABE alternatives. The PBM method was validated by investigating several test cases. First, static shading scenarios were developed using the PBM; the amount of incoming solar radiation was then compared with outcomes from the BPS with static shading. Second, indoor temperature profiles were simulated using the PBM method and an HBOO scenario; the results were compared with the outcomes obtained from the existing method, in order to determine the PBM's reliability. Third, the integration of the PBM method and evolutionary multi-objective optimization technique illustrates the usefulness of the FBCS in CABE performance optimization.

publication date

  • December 2017