ITR: An Interactive Experimental/Numerical Simulation System with Applications in MEMS Design

ITR：交互式实验/数值仿真系统在 MEMS 设计中的应用

• 批准号: 0083004
• 负责人: Elizabeth Bradley
• 金额: $ 47万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0083004&HistoricalAwards=false
• 关键词: ITR; Interactive; Experimental; Numerical; Simulation

This project will build a new generation of numerical simulation systems by creating a feedback path between physical experiments and numerical solvers. There are a number of exciting implications of this data-adaptive simulation idea. Engineering fluid flows are inherently complex. This complexity limits measurement and precision, so engineers are forced to work with fluid flows based on very sparse information. Numerical solvers, on the other hand, can resolve tiny flow structures, but they generally run in an open-loop mode and are thus unverified. Coupling the two forms of technology offers powerful advantages to each. Comparisons against live experimental data will allow simulation algorithms to be verified quantitatively, in detail, and in-line. Once it is verified in this fashion, one can use the simulation with confidence on related problems. Once can also use the sensor information to correct the solver's data, or even to adjust the solver parameters on the fly. Moreover, once the solver is properly synchronized with the real system, one could use the former to explore the physics of the latter in more detail than sensors would allow - and still trust the results.A particularly compelling application area for data-adaptive simulation techniques is microelectromechanical systems (MEMS). This emerging technology is driving a revolution in engineering design that is placing new demands on numerical simulation. Accurate modeling of the interaction of tiny, flexible, moving structures with high-speed chaotic fluids is challenging. To resolve the fine details in this kind of simulation, computational fluid dynamics technology requires extremely fine meshes and the solution of very large systems of nonlinear equations. This makes it difficult to build production-quality computer-aided design (CAD) tools for MEMS, which in turn forces engineers to fabricate devices without testing them. Functional CAD tools would allow MEMS designers to achieve one-pass design, much as VLSI does now.

该项目将通过在物理实验和数值求解器之间创建反馈路径来构建新一代数值模拟系统。这种数据自适应模拟的想法有许多令人兴奋的含义。工程流体流动本质上是复杂的。这种复杂性限制了测量和精度，因此工程师被迫根据非常稀疏的信息处理流体流动。另一方面，数值求解器可以解决微小的流动结构，但它们通常以开环模式运行，因此未经验证。将这两种形式的技术结合起来，为每一种技术提供了强大的优势。与现场实验数据的比较将允许模拟算法进行定量，详细和在线验证。一旦以这种方式验证，人们就可以放心地将模拟用于相关问题。还可以使用传感器信息来校正求解器的数据，甚至动态调整求解器参数。此外，一旦求解器与真实的系统正确同步，人们就可以使用前者来探索后者的物理特性，比传感器所允许的更详细，并且仍然可以信任结果。数据自适应仿真技术的一个特别引人注目的应用领域是微机电系统（MEMS）。这项新兴技术正在推动工程设计的革命，对数值模拟提出了新的要求。微小的，灵活的，移动的结构与高速混沌流体的相互作用的精确建模是具有挑战性的。为了解决这种模拟中的细节问题，计算流体动力学技术需要非常精细的网格和非常大的非线性方程组的解。这使得很难为MEMS构建生产质量的计算机辅助设计（CAD）工具，这反过来又迫使工程师在不进行测试的情况下制造设备。功能CAD工具将允许MEMS设计人员实现一次通过设计，就像现在的VLSI一样。