曲面光源蒙特卡罗建模方法
Monte Carlo Modeling Method for Surface Light Source
查看参考文献27篇
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文摘
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光源建模方法是光学仿真算法的核心之一,决定了仿真结果的精度。然而对任意面型的光源建模难度高,建模方法很少被公开讨论。本研究系统地介绍曲面光源建模方法。基于均匀性假设,对曲面光源的空间特性、方向特性进行统计学描述,给出采样光线参数应满足的概率密度函数和采样方法。对两个曲面光源实例进行建模,当采样光线数量在107量级时,建模结果在指定接收器上形成的辐照度分布与理论值间最大相对偏差在1%之内,建模精度很高。同时,分析了两种采样方法对曲面光源建模精度和速度的影响,可为曲面光源建模过程提供一定指导。 |
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其他语种文摘
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Objective Monte Carlo simulations are widely applied in the fields such as imaging evaluations,graphical rendering,scattering analysis,and illumination design. Light source modeling,which directly determines the accuracy of the simulation results,is crucial in Monte Carlo simulation. However,light source modeling,especially surface light source modeling,is difficult and rarely discussed publicly. Surface light sources including extended filaments and curved fluorescent tubes are still commonly employed in general and special lighting. Additionally,the external radiation of the non-transparent components of the mechanical structure can also be considered as surface light sources in stray light analysis of far-infrared optical systems. We provide a Monte Carlo modeling method for surface light sources. In this method,we introduce a statistical model of the surface light source and two ray sampling strategies. Results show that the proposed modeling method has high precision. The influence of different sampling strategies and different random numbers on the modeling accuracy and speed is also discussed to guide balancing the modeling accuracy and speed. Methods Based on the homogeneity assumption,we analyze the spatial and orientational properties of the surface light source separately. We clarify the stochastic ray parameters including the starting point coordinates,direction vectors,energy weights,and their physical implications in the Monte Carlo modeling. Based on the radiation properties of the source,the desired probability density functions for different parameters of the ray are derived. In addition,we describe how to sample the parameters following an arbitrary two-dimensional probability density function based on inverse transform sampling. We introduce two ray sampling strategies of uniform sampling with equal weights and uniform sampling in parameter space. The former strategy samples the rays strictly according to the probability density functions,with equal energy weights. The latter strategy assigns the corresponding weights to the rays and ensures that the weights are proportional to the desired probability density functions,which can considerably improve the computational speed by avoiding numerical integration and interpolation operations. The proposed method can model light sources with arbitrary surfaces,with strong versatility. To verify the accuracy of the modeling results,the integral formula of the irradiance distribution formed by the surface light source on the receiver is derived as the theoretical illuminance distribution(Fig. 1). The accuracy of the modeling method is measured by comparing the relative deviation of the simulated irradiance distribution of the sampled rays from the theoretical value. Results and Discussions Monte Carlo modeling results and precision analysis are implemented for two different surface light sources,which are expressed by XY-polynomial(Fig. 2)and non-uniform rational B-spline(NURBS)(Fig. 6)respectively. The sampled starting points,ray directions,and rays(Figs. 3 and 7)are provided respectively to show the differences between the two sampling strategies. The calculated theoretical irradiance distributions formed by the two surface light sources at the specified receiver have an extremely high spatial resolution,which can be regarded as continuous(Figs. 4 and 8). The maximum relative deviation between the simulated value and the theoretical value is within 1% for 224(≈ 1.6 ×10~7)sampling rays,demonstrating a high modeling accuracy(Figs. 5 and 9). The uniform sampling strategy with equal weights leads to slightly higher modeling accuracy than that of uniform sampling in parameter space. For the NURBS surface light source,we analyze the differences in modeling accuracy and speed between the two sampling strategies under different numbers of rays and the influence of different random numbers on modeling accuracy(Fig. 10). |
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来源
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光学学报
,2023,43(21):2122001 【核心库】
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DOI
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10.3788/AOS230880
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关键词
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光学仿真
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蒙特卡罗
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光源建模
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曲面光源
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均匀采样
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地址
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北京理工大学光电学院, 北京市混合现实与新型显示工程技术研究中心, 北京, 100081
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北京理工大学, 光电成像技术与系统教育部重点实验室, 北京, 100081
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中国科学院西安光学精密机械研究所空间光子信息新技术研究室, 陕西, 西安, 710119
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0253-2239 |
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学科
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物理学 |
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基金
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国家自然科学基金
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中国科学院青年创新促进会项目
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文献收藏号
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CSCD:7619128
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