Quasi-Monte Carlo ray tracing algorithm for radiative flux distribution simulation

Abstract Monte Carlo ray tracing (MCRT) is a fundamental simulation method for central receiver systems(CRSs). MCRT is an effective method to describe the radiative flux distribution on the receiver surface reflected by either a single heliostat or all heliostats in a heliostat field. In this paper, a GPU-based ray-tracing simulation method, namely, quasi-Monte Carlo ray tracing (QMCRT), is proposed to address problems of both efficiency and accuracy. First, QMCRT, as a bidirectional approach, can avoid unnecessary intersection calculations. This method also facilitates sunshape sampling and heliostat surface slope error sampling, which can achieve memory and run-time efficiency. Second, in the traditional approaches, the simulated maximum radiative flux (MaxRF) is randomly higher than the reference value, even if tens of millions of rays are traced. In QMCRT, the problem is solved by applying a trimmed mean smoothing operation to the generated radiative flux distribution. As a result, a stable MaxRF value approaching the reference value is obtained, while the total power remains almost unchanged. The results obtained for both synthetic and real heliostats obtained using QMCRT are substantially in keeping with the results obtained using established computational tools. QMCRT is two orders of magnitude faster than the traditional MCRT method when addressing traditional one-reflection CRS case. Compared with the state-of-the-art GPU-based grid ray tracing (GRT) approach, QMCRT is equally fast but generates a more accurate result. QMCRT also has an advantage in terms of efficiency for CRS compared with two well-known simulation software tools, i.e., SolTrace and Tonatiuh.