Abstract

The thermal analysis of headlamps and related engineering applications is a key step to ensure their safety, longevity, and can be a driving factor in their overall design process. A comprehensive understanding of the thermal physics in these applications is crucial to analysts and designers. The role of simulation in headlamp design is a fundamental part of this process. The time spent by analysts to evaluate the thermal characteristics of a product design has a fundamental impact on the engineering of headlamps and the entire design process. A significant bottleneck in the thermal analysis is the computationally costly calculation of radiative view factors, which dictate the radiative conductances in headlamp thermal physics. Historically, several approaches have been used to tackle this problem. However, existing methods do not tend to yield the performance and scalability required for optimally efficient thermal analysis. Considering this, we present a GPU-based tool for radiative view factor calculations implemented in the CUDA programming language. We begin by outlining the existing approaches and their pitfalls, including the Hemicube method and Monte Carlo ray tracing methods using conventional CPU-based parallelism. We then discuss our GPU based Monte Carlo view factor calculation method, which is designed to harness the embarrassingly parallel nature of view factor (ray tracing) calculations and the large number of compute cores on GPUs. We show that our implementation is accurate, highly parallel, has been validated against known results, and orders of magnitude faster than existing CPU-based methods run in distributed parallel environments. We then focus on the specific case study of headlamp design and the improvements in the speed of view factor calculations. The new method has the promise to fundamentally change the approach and time needed for design iterations in some engineering applications. We conclude with an outlook for applications in other industries in the near term.