Scholarlink

To develop a more realistic virtual reality firefighting training platform, this study utilizes fire spread data, including smoke and heat, obtained from numerical simulations using the Fire Dynamics Simulator (FDS). FDS employs MPI and OpenMP for large-scale fire simulations by dividing computational domains into sub-domains, with OpenACC applied to support heterogeneous hardware architectures. Performance tests using CSIRO Grassland Fires demonstrated a 1.89 × speedup with combined CPU-GPU computation and a 21 × speedup with 1 GPU and 16 CPUs, validating enhanced fire analysis capabilities. Additionally, existing VR engines were improved by integrating WFDS data into Unreal Engine for realistic smoke and heat visualization using FGA files. The program dynamically visualizes flame and smoke movements based on wind speed and direction, achieving a 100% match between WFDS data and Unreal Engine output, with combustion stages rendered in real-time through mass-based material updates.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Development of a Virtual Reality Training Program: Integrating FDS Simulation and Performance Optimization with Unreal Engine on Heterogeneous Hardware

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

查看全文
  • D. Kim

摘要

To develop a more realistic virtual reality firefighting training platform, this study utilizes fire spread data, including smoke and heat, obtained from numerical simulations using the Fire Dynamics Simulator (FDS). FDS employs MPI and OpenMP for large-scale fire simulations by dividing computational domains into sub-domains, with OpenACC applied to support heterogeneous hardware architectures. Performance tests using CSIRO Grassland Fires demonstrated a 1.89 × speedup with combined CPU-GPU computation and a 21 × speedup with 1 GPU and 16 CPUs, validating enhanced fire analysis capabilities. Additionally, existing VR engines were improved by integrating WFDS data into Unreal Engine for realistic smoke and heat visualization using FGA files. The program dynamically visualizes flame and smoke movements based on wind speed and direction, achieving a 100% match between WFDS data and Unreal Engine output, with combustion stages rendered in real-time through mass-based material updates.