EAGER: Impact on Scientific Discovery using Simulation-Based Engineering & Science

工业界对高质量科学和工程的需求和使用没有很好的记录。在某些情况下，它没有得到很好的理解。然而，由于各种因素，对基于仿真的工程和科学（SBE& S）的需求有所增加：减少上市时间的经济压力;解决产品复杂性和安全性所需的多学科物理学;现代生产方法和能源创新和保护;由于小型化，复杂的材料操作和安全性，一般无法进行物理原型设计;以及高性能计算（HPC）以高保真度和物理精度运行模型的能力。在所有这些情况下，SBE S必然严重依赖学术和工业研究。这项研究将通过记录工业计算社区对科学的使用，使学术和工业科学社区受益。目标公司是财富50强，在SBE S方面有丰富的经验，并定期投资于学术研究。他们每个人都将在使用HPC进行计算建模方面拥有丰富的经验--名副其实的高级用户，代表了科学理解和发现的计算需求的最佳实践，并具有将科学转化为改进的生产方法和经济发展的额外能力。这项研究预计i）帮助理解联邦政府支持的大学研究和工业研发之间的相互作用，以及学术和工业科学之间的相互依赖程度，ii）将美国大型公司的HPC工作与大学研究联系起来，iii）确定推动行业对高质量研究需求的用例，iv）可能与一些联邦机构和部门的活动建立联系，v）确定可能促进高级软件开发联盟的实践，包括千万亿次计算。

Industry's demand for and use of high-quality science and engineering is not well documented. In some instances it is not well understood. Demand for simulation-based engineering and science (SBE&S), however, has increased due to a variety of factors: economic pressure to decrease time-to-market; multi-disciplinary physics needed to address product complexity and safety; modern production methods and energy innovation and conservation; a general inability to conduct physical prototyping due to miniaturization, complex materials manipulation and safety; and the capability of high-performance computing (HPC) to run models with high fidelity and physical accuracy. In all these instances, SBE&S necessarily relies heavily on academic and industrial research. This research will benefit both the academic and industrial science communities by documenting the use of science by the industrial computational community. Target companies are in the Fortune 50 and have deep experience in SBE&S and invest regularly in academic research. They will each have significant experience in computational modeling using HPC - veritable power users that represent best practices in computational demand for scientific understanding and discovery with an additional ability to convert science into improved production methods and economic development. This research is expected to i) aid understanding of the interplay between federally-supported university-based research and industrial R&D and how interdependent academic and industrial science are, ii) relate HPC efforts within large U.S. companies to university-based research, iii) identify use cases that drive industry demand for high-quality research, iv) potentially create linkages to activities at a number of federal agencies and departments, v) identify practices that could potentially foster alliances in advanced software development, including petascale computing.