STTR Phase I: Nanoscale Transport Processes Prediction/Design/Analysis Tool for NEMS Applications

这个小企业技术转让第一阶段项目将产生一个独特的计算工具，用于预测纳米系统中的传输。这里使用的新方法是基于格子玻尔兹曼方法（LBM），它将使纳米器件的虚拟原型使用高达一亿个计算单元的网格，从而开辟了计算机辅助设计和分析NEMS设备在数据存储行业的方式。现有的LBM代码将被扩展以处理适用于计算机磁盘驱动系统中的磁头磁盘接口的高Knudsen数范围。这种新的分析模型将在商业软件包PowerFLOW中实现，该软件包目前用于全球汽车应用，并在数据存储行业中具有早期应用。通过该平台，将获得最高标准的数值精度、并行效率和几何灵活性（包括与商业CAD工具的完全集成）。在对该算法进行基准测试时，将模拟工业级复杂性的纳米级运输问题，目标是解决滑块的所有相关几何细节，并获得详细的压力和剪切（头部）应力分布。 在商业上，这种纳米级的运输预测工具将打开新的模拟市场，特别是在工程设计层面。其次，这种新技术应该打开广阔的新的市场，计算机辅助工程（CAE），特别是在NEMS和相关行业，使纳米级传输预测设备的真实的世界的复杂性，现在设计/优化使用实验或半经验的规则。市场分析表明，通过在工程设计层面引入新的预测技术，每年约1.5亿美元的CAE市场将增长10至100倍。

This Small Business Technology Transfer Phase I project will produce a unique computational tool for predicting transport in nanoscale systems. The novel approach to be used here is based on Lattice Boltzmann Methods (LBM) which will enable virtual prototyping of nanodevices using grids of up to a hundred million computational cells thus opening the way for computer aided design and analysis of NEMS devices in the data storage industry. Existing LBM codes will be extended to handle the high Knudsen number range applicable for the head disk interface in computer disk drive system. This new analytical model will then be implemented in a commercial software package, PowerFLOW, which is now used for automotive applications worldwide and has early applications in the data storage industry. With this platform, the highest standards of numerical accuracy, parallel efficiency, and geometric flexibility (including full integration with commercial CAD tools), will be obtained. Upon benchmarking this algorithm against simplistic flow data, a nanoscale transport problem of industrial level complexity will be simulated, with the goal to resolve all the relevant geometric details of the slider and to obtain detailed pressure and shear (head) stress distributions. Commercially, this nanoscale transport prediction tool will open new simulation markets, especially at the engineering design level. Secondly, this new technology should open broad new markets for computer aided engineering (CAE), especially in NEMS and related industries, by enabling nanoscale transport prediction in devices of real world complexity which are now designed/optimized using either experimentation or semi-empirical rules. Market analysis shows that the existing CAE market of about $150 MM per year should increase 10- to 100-fold by introducing new prediction technologies at the engineering design level.