Inverse Simulation of Radiative Thermal Transport

Abstract

The early phase of urban planning and architectural design has a great impact on the thermal loads and characteristics of constructed buildings. It is, therefore, important to efficiently simulate thermal effects early on and rectify possible problems. In this paper, we present an inverse simulation of radiative heat transport and a differentiable photon-tracing approach. Our method utilizes GPU-accelerated ray tracing to speed up both the forward and adjoint simulation. Moreover, we incorporate matrix compression to further increase the efficiency of our thermal solver and support larger scenes. In addition to our differentiable photon-tracing approach, we introduce a novel approximate edge sampling scheme that re-uses primary samples instead of relying on explicit edge samples or auxiliary rays to resolve visibility discontinuities. Our inverse simulation system enables designers to not only predict the temperature distribution, but also automatically optimize the design to improve thermal comfort and avoid problematic configurations. We showcase our approach using several examples in which we optimize the placement of buildings or their facade geometry. Our approach can be used to optimize arbitrary geometric parameterizations and supports steady-state, as well as transient simulations.