A hierarchical design optimization approach for meeting building performance targets

This paper builds on the premise that numerical optimization techniques can improve the decision-making process and structure the use of analysis tools in simulation-based building design. The main goal of this paper is to demonstrate the use of the numerical optimization paradigm for supporting consistency between multiple decisionmaking tasks in simulation-based design scenarios. As an outcome, a set of interrelated design-analysis tasks are posed in a multi-level, multidisciplinary, hierarchical design optimization framework called Analytic Target Cascading (ATC). This paper discusses how ATC functions through the thermal and HVAC design of one floor in a healthcare facility. This thermal and HVAC design problem is based on a survey of an existing healthcare unit and is therefore a realistic representation of a design consulting task. It includes zones that have varying functional requirements and different thermal conditions, and is sufficiently complex for demonstrating both the merits and limitations of the ATC approach in the context of simulation-based decision-making in building design. Decision models formulated for this study incorporate performance targets for AHU capacity, energy consumption, thermal comfort and airflow. Hence, it shows how dependencies between HVAC, energy and thermal comfort, and Computational Fluid Dynamics (CFD) analysis tools can be co-ordinated within the ATC process.