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基于优化边界体积层次算法的WRF云产品渲染

谈玲 林疆

南京信息工程大学学报2025,Vol.17Issue(2):215-226,12.
南京信息工程大学学报2025,Vol.17Issue(2):215-226,12.DOI:10.13878/j.cnki.jnuist.20230810003

基于优化边界体积层次算法的WRF云产品渲染

WRF cloud product rendering based on optimized bounding volume hierarchy algorithm

谈玲 1林疆1

作者信息

  • 1. 南京信息工程大学 计算机学院,南京,210044
  • 折叠

摘要

Abstract

As a crucial component of weather systems,3D cloud simulation plays a significant role in various fields such as military and aviation.However,the current mainstream Bounding Volume Hierarchy(BVH)algorithm ex-hibits inefficient rendering performance when dealing with non-uniform and large-volume clouds.Here,a cloud ren-dering approach based on optimized BVH algorithm is proposed.The data points from the WRF(Weather Research and Forecasting)grids are used as cloud primitives,and a Z-order Hilbert curve is employed for spatial sorting.The BVH algorithm based on the Surface Area Heuristic(SAH)is optimized by locally optimizing the cloud primitive density,aiming to enhance computational efficiency.To tackle the data access overhead of overlapping BVH nodes,a novel storage structure called Overlapping Node Sets(ONS)is introduced,which reduces the time complexity.The optimized BVH algorithm reduces unnecessary intersection tests between rays and triangle surfaces,and resolves is-sues related to invalid boundary volume overlaps.Simulation experiments demonstrate that the proposed method a-chieves a 15.6%improvement in SAH cost compared to similar state-of-the-art algorithms,a 10%improvement in EPO(Effective Partial Overlap),and a reduction of over 100%in construction time.The computational efficiency of the optimized BVH algorithm outperforms similar algorithms in any WRF cloud scenario,indicating its capability for rapid rendering of WRF cloud products.

关键词

光线追踪/云仿真/边界体积算法/WRF

Key words

ray tracing/cloud simulation/bounding volume hierarchy(BVH)/weather research and forecasting(WRF)

分类

计算机与自动化

引用本文复制引用

谈玲,林疆..基于优化边界体积层次算法的WRF云产品渲染[J].南京信息工程大学学报,2025,17(2):215-226,12.

基金项目

国家自然科学基金(62271264) (62271264)

南京信息工程大学学报

OA北大核心

1674-7070

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