|Title||BIM-Centric Daylight Profiler for Simulation (BDP4SIM): A Methodology for Automated Product Model Decomposition and Recomposition for Climate-Based Daylighting Simulation|
|Publication Type||Technical Report|
|Authors||Welle, B., Z. Rogers, and M. Fischer|
Flexible problem formulation is required for product model-based thermal analysis using multidisciplinary design optimization (MDO) environments for cost-effectiveness, accuracy, and scalability in the Architecture, Engineering, and Construction (AEC) industry. The integration of daylighting simulation into an MDO process, however, presents several implementation challenges. In current practice, the process of an architect, engineer, or daylighting consultant to determine how to analyze a given building design for daylighting performance is frequently subjective, time-consuming, and inconsistent. Furthermore, long simulation time requirements for daylighting significantly hinder the realization of many benefits from MDO. The determination of which spaces in a building are sufficiently different to warrant an independent daylighting analysis is based primarily on building physics, building design criteria, and operating schedules (e.g. occupancy schedules). This characteristic of daylighting analysis creates the opportunity to develop intelligent mechanisms to automate the identification of the building spaces for analysis using performance-based methods, simulation of spatial results, and the scaling of spatial simulation results to whole building performance metrics in a fraction of the time it takes in current practice. Such methods would result in enhanced problem formulation and evaluation capabilities for daylighting simulation, and improved cost-effectiveness, accuracy, and scalability for MDO-based daylighting simulation. Currently, no such methods exist in literature or in practice. This paper fills these gaps by presenting a methodology for automated product model decomposition and recomposition for climate-based daylighting simulation using Radiance. The authors validate the research with the method’s application to several test cases and a large federal office building industry case study.
|Keywords||Conceptual Building Design, daylighting simulation, design decomposition, distributed and parallel computing, MDO, Multidisciplinary Design Optimization, process integration and design automation|
|Year of Publication||2012|
Last modified Thu, 19 Apr, 2012 at 13:51