SBIR Phase I: Visualization of Massive Multivariate Adaptive Mesh Refinement (AMR) Data

SBIR 第一阶段：海量多元自适应网格细化 (AMR) 数据的可视化

• 批准号: 0441564
• 负责人: Lisa Avila
• 金额: $ 10万
• 依托单位: KITWARE INC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-01-01 至 2005-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0441564&HistoricalAwards=false
• 关键词: SBIR; Phase; Visualization; Massive; Multivariate

This Small Business Innovation Research (SBIR) Phase I project addresses the lack of visualization technology for hierarchical overlapping structured grids created through a process known as Adaptive Mesh Refinement (AMR). Although the AMR structure makes possible simulations that would have otherwise been too computationally and memory expensive using a uniform grid approach, it leaves the scientist with a lack of visualization tools to properly render the resulting volumetric data. Therefore, there is a need for visualization tools that are focused on volume rendering the large, multivariate, time-varying data produced by simulations using the AMR technique. In this project, a volume rendering approach is described that will enable scientists to effectively visualize the results of their simulations. A ray casting algorithm will be implement allowing for accurate visualization with the ability to trade quality for speed, flexible compositing of multivariate data, and adaptability across a variety of computational platforms from massively parallel to a desktop computer. A prototype visualization system will be created which will demonstrate interactivity through the use of level of detail techniques, advanced transfer function editing for multivariate data, and intermixing of the volume rendering solution with standard geometric techniques.Early in the development cycle, the core AMR visualization technology will be incorporated into the open source Visualization Toolkit in order to gain valuable feedback and to gain recognition in this field. This inclusion will provide researchers with early access to these visualization techniques, freeing up valuable time currently spent implementing custom solutions. The availability of these AMR visualization methods as source code will enable future research in the area of AMR visualization to be based upon the results obtained through this effort. The documentation (including a commercially available textbook and users' guide) and the training classes for the Visualization Toolkit will be updated to include AMR visualization, providing educational opportunities for new researchers in the area. In addition to the availability of this technology as part of an open-source toolkit, a commercial application will be developed to provide AMR visualization in a turn-key application. AMR visualization provided in an end-user application will eliminate the need for most researchers to develop their own visualization solutions, allowing more time to be focused on the core science.

这项小型企业创新研究（SBIR）I阶段项目解决了缺乏可视化技术，用于通过称为自适应网格改进的过程（AMR）创建的层次重叠结构网格。 尽管AMR结构使可能的模拟可能过于计算，并且使用统一的网格方法昂贵，但它使科学家缺乏可视化工具，无法正确渲染所得的体积数据。 因此，需要可视化工具，这些工具专注于使用AMR技术通过模拟产生的大型，多变量，时变的数据。 在该项目中，描述了一种量渲染方法，该方法将使科学家能够有效地看到其模拟结果。 射线铸造算法将实现，允许以速度交易质量，灵活的多元数据合成以及从大量平行到台式计算机的各种计算平台进行适应性的能力进行准确的可视化。 将创建一个原型可视化系统，该系统将通过使用详细技术级别的使用，高级传输功能编辑多变量数据来证明交互性，以及与标准的几何技术相互混合的量渲染解决方案。在开发周期中，核心AMR可视化技术将在为了获得价值的反馈和获得价值的识别中，将核心AMR可视化技术纳入为开源的可视化工具kit。 此包含将为研究人员提供早期访问这些可视化技术的机会，从而腾出目前在实施自定义解决方案上花费的宝贵时间。 这些AMR可视化方法作为源代码的可用性将使AMR可视化领域的未来研究得以基于通过这项工作获得的结果。 该文档（包括商业上可用的教科书和用户指南）和可视化工具包的培训课程将进行更新，以包括AMR可视化，为该地区的新研究人员提供教育机会。 除了作为开源工具包的一部分的该技术的可用性外，还将开发商业应用程序，以在交钥匙应用程序中提供AMR可视化。 最终用户应用程序中提供的AMR可视化将消除大多数研究人员开发自己的可视化解决方案的需求，从而使更多的时间专注于核心科学。