Influence of Cy berKnife Prescription Isodose Line on the Discrepancy of Dose Results Calculated by the Ray Tracing and Monte Carlo Algorithms for Head and Lung Plans: A Phantom Study

Incorporation of the Monte Carlo(MC)algorithm in optimizing CyberKnife(CK)plans is cumbersome,and early models unconfigured MC calculations,therefore,this study investigated algorithm-based dose calculation discrepancies by selecting different prescription isodose lines(PIDLs)in head and lung CK plans.CK plans were based on anthropomorphic phantoms.Four shells were set at 2-60 mm from the target,and the constraint doses were adjusted according to the design stratcgy.After optimization,30%-90%PIDL plans were generated by ray tracing(RT).In the evaluation module,CK plans were recalculated using the MC algorithm.Therefore,the dosimetric parameters of different PIDL plans based on the RT and MC algorithms were obtained and analyzed.The discrepancies(mean+SD)were 3.72%+0.31%,3.40%+0.11%,3.47%+0.32%,0.17%+0.11%,0.64%+3.60%,7.73%+1.60%,14.62%+3.21%and 10.10%+1.57%for Djs,Dmeam),Dys,and coverage of the PTV,DGI,V,,V;and V,in the head plans and-6.32%+1.15%,-13.46%+0.98%,-20.63%+2.25%,-34.78%+25.03%,12248%+175.60%,-12.92%+5.41%,3.19%+4.67%and 7.13%+1.56%in the lung plans,respectively.The following parameters were significantly correlated with PIDL:dp98%at the 0.05 level and dpal,dys and dv3 at the 0.01 level for the head plans;dp98e%at the 0.05 level and do1e%,dpmeam,Ccoweange,dool,dvs and dv;at the 0.01 level for the lung plans.RT may be used to calculate the dose in CK head plans,but when the dose of organs at risk is close to the limit,it is necessary to refer to the MC results or to further optimize the CK plan to reduce the dose.For lung plans,the MC algorithm is recommended.For early models without the MC algorithm,a lower PIDL plan is recommended;otherwise,a large PIDL plan risks serious underdosage in the target area.

Numerical Evaluation on the Thermal Performance of the Solar External Cylinder Receiver using Monte Carlo Ray-Tracing Algorithm

The heat receiver is an essential part of the Concentrating Solar Power plant,directly affecting its operation and safety.In this paper,the Monte Carlo ray-tracing algorithm was introduced to evaluate a 50 MW(e)external cylindrical receiver’s thermal performance.The radiation heat flux concentrated from the heliostats field and the view factors between grids divided from the tubes were both calculated using Monte Carlo ray-tracing algorithm.Besides,an in-house code was developed and verified,including three modules of the view-factor calculation,thermal performance calculation,and thermal stress calculation.It was also employed to investigate the 50 MW(e)receiver,and the detailed 3D profiles of temperature and thermal stress in the receiver were analyzed.It was found that the molten salt was heated from 298℃to 565℃and the tube at the 50 MW(e)receiver’s outlet had a high temperature,while the high thermal stress came out at the receiver’s entrance.Finally,the over-temperature of the receiver was discussed,and an optimization algorithm was introduced.The tube wall temperature and film temperature at the overheated area matched the safety criteria,and the outlet molten salt temperature still reached 563℃after the optimization process,with only 2℃dropped.

A survey on deep learning-based Monte Carlo denoising

Monte Carlo(MC)integration is used ubiquitously in realistic image synthesis because of its flexibility and generality.However,the integration has to balance estimator bias and variance,which causes visually distracting noise with low sample counts.Existing solutions fall into two categories,in-process sampling schemes and post-processing reconstruction schemes.This report summarizes recent trends in the post-processing reconstruction scheme.Recent years have seen increasing attention and significant progress in denoising MC rendering with deep learning,by training neural networks to reconstruct denoised rendering results from sparse MC samples.Many of these techniques show promising results in real-world applications,and this report aims to provide an assessment of these approaches for practitioners and researchers.

A numerical and experimental comparison of heat transfer in a quasi two-dimensional packed bed

Heat transfer plays a major role in many industrial processes taking place in packed beds.An accurate and reliable simulation of the heat exchange between particles is therefore crucial for a reliable operation and to optimize the processes in the bed.The discrete ordinates method(DOM)provides an established numerical technique to model radiative heat transfer in granular media that offers the possibility to consider the directional dependence of the radiation propagation.In this work,DOM is compared with Monte Carlo ray tracing,which provides an alternative method for heat transfer simulations.Geomet-rically simple configurations are used to investigate the influence of the angular discretization on the accuracy of the results and the computation time in both methods.The obtained insights are then transferred to a more complex configuration of a quasi two-dimensional test rig consisting of metal rods for which also experimental results are available.Our results show that both DOM and Monte Carlo ray tracing allow for an accurate simulation of heat transfer in packed beds.Monte Carlo ray tracing requires thereby computation times that are surprisingly competitive(although still somewhat slower)compared to DOM and allows for an easier computation of highly accurate reference solutions.In our preliminary comparison to the experimental test rig,Monte Carlo ray tracing also provides the advantage that it can more easily model highly specular materials such as stainless steel.Both methods are comparable for diffuse materials such as magnesium oxide.

线性菲涅尔太阳能系统光学性能研究与优化

为研究与优化线性菲涅尔太阳能系统的光学性能,本文采用蒙特卡罗光线追迹法（MCRT）自编程建立了整个系统的三维光学模型。基于此,分析了不同反射镜型式、瞄准位置、形面误差以及地理位置等对系统光学性能的影响规律,优化了反射镜几何参数与瞄准位置。结果表明,不同镜面型式下系统性能均存在最优值,此时圆柱面与抛物面镜光学性能几乎一样。对于吸热管热流分布,可通过优化设计反射镜瞄准线来提高热流分布均匀性,一定的形面误差也会改善其均匀性。在地理上,该系统在北纬20°~50°的范围内年均光学效率在52%~37%之间,可在我国大部分地区应用。

Heat Transfer Enhancement in a Parabolic Trough Solar Receiver using Longitudinal Fins and Nanofluids

In this paper,we present a three dimensional numerical investigation of heat transfer in a parabolic trough collector receiver with longitudinal fins using different kinds of nanofluid,with an operational temperature of 573 K and nanoparticle concentration of 1% in volume.The outer surface of the absorber receives a non-uniform heat flux,which is obtained by using the Monte Carlo ray tracing technique.The numerical results are contrasted with empirical results available in the open literature.A significant improvement of heat transfer is derived when the Reynolds number varies in the range 2.57×104≤ Re≤ 2.57×105,the tube-side Nusselt number increases from 1.3 to 1.8 times,also the metallic nanoparticles improve heat transfer greatly than other nanoparticles,combining both mechanisms provides better heat transfer and higher thermo-hydraulic performance.

A practical path guiding method for participating media

Rendering translucent materials is costly:light transport algorithms need to simulate a large number of scattering events inside the material before reaching convergence.The cost is especially high for materials with a large albedo or a small mean-freepath,where higher-order scattering effects dominate.In simple terms,the paths get lost in the medium.Path guiding has been proposed for surface rendering to make convergence faster by guiding the sampling process.In this paper,we introduce a path guiding solution for translucent materials.We learn an adaptive approximate representation of the radiance distribution in the volume and use it to sample the scattering direction,combining it with phase function sampling by resampled importance sampling.The proposed method significantly improves the performance of light transport simulation in participating media,especially for small lights and media with refractive boundaries.Our method can handle any homogeneous participating medium,with high or low scattering,with high or low absorption,and from isotropic to highly anisotropic.

Variance reduction using interframe coherence for animated scenes

In an animated scene,geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However,Monte Carlo methods typically take a long time to produce a noise-free image. In this paper,we propose a variance reduction technique for Monte Carlo methods which exploits coherence between frames. Firstly,we introduce a dual cone model to measure the incident coherence intersecting camera rays in object space. Secondly,we allocate multiple frame buffers to store image samples from consecutive frames. Finally,the color of a pixel in one frame is computed by borrowing samples from neighboring pixels in current,previous,and subsequent frames. Our experiments show that noise is greatly reduced by our method since the number of effective samples is increased by use of borrowed samples.