Parametric modeling strategies for efficient annual analysis of daylight in buildings

Open Access
Author:
Subramaniam, Sarith
Graduate Program:
Architectural Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
February 27, 2018
Committee Members:
  • Richard George Mistrick, Dissertation Advisor
  • Richard George Mistrick, Committee Chair
  • Kevin William Houser, Committee Member
  • Donghyun Rim, Committee Member
  • Ute Poerschke, Outside Member
Keywords:
  • Daylighting
  • Lighting
  • Software Development
  • Architecture
  • Building Science
Abstract:
Daylighting simulations are an essential part of the modern building design process. Results generated from such simulations influence various aspects of building design such as facade orientation, design of electric lighting and lighting control systems, selection and sizing of glazing, and choice of internal or external shading systems for glare control. Recent advances in the development of visual scripting mediums for popular 3D modeling platforms have made it possible to easily set up hundreds of such simulations for the design of a single building. Most contemporary mainstream daylight simulation tools, however, are not conducive to such large-scale studies. These tools are based on nearly two-decade old raytracing algorithms, which in addition to being computationally inefficient, also rely on simplifying assumptions that compromise the precision of the simulations. This dissertation research investigates simulation workflows which can improve the computational efficiency and precision of parametric daylighting simulations. These workflows leverage newly introduced tools within the Radiance raytracing system. The principal research is documented in five separate chapters that cover four hypothesis-driven numerical studies and an open source software development initiative. The first two studies focus on novel approaches to employ daylight coefficients as a means of calculating precise values of illuminance and luminance for annual climate-based simulations. The remaining studies investigate the potential of employing multi-phase simulations as a means of reducing the computational runtime for illuminance-based simulations. The workflows employed for organizing and automating the simulations for the numerical studies were scripted using a custom-written software. This software, written in the Python programming language, was eventually assimilated within an open source building simulation library that has now been publicly released.