CAD-Centric Attribution Methodology for Multidisciplinary Optimization Environments: Enabling Parametric Attribution for Efficient Design Space Formulation and Evaluation

Abstract

Multidisciplinary design optimization (MDO) processes that automate the workflow between a parametric product model and performance simulation engines can compress design cycle time, increase design knowledge, and yield substantive product quality and performance gains. However, the accuracy and cost-effectiveness of an MDO process is highly dependent on designers’ ability to structure the optimization problem for specific challenges, particularly when specifying how building attributes and their associated geometry are configured for an optimization process. This research fills these gaps in MDO literature by developing a computer-aided design (CAD)-centric attribution methodology for multidisciplinary optimization environments (CAMMOE). CAMMOE enables designers to improve the accuracy of their optimization processes by helping them develop and analyze alternative spaces that are of just the right size and composition to meet their design intent. The writers demonstrate the potential power and generality of CAMMOE to enable designers to formulate MDO problems that can be executed efficiently and effectively with two industry case studies.