Research Initiation Award: Multidisciplinary Design Optimization Development and Application in Electronic Package Design

在这项研究中，两个新的通用算法， 多学科设计优化将得到充分发展， 在电子封装优化的应用中实现。 在 一个算法二阶系统灵敏度将产生 使用产生的局部二阶设计灵敏度 同时进行子系统优化。 并发 子系统优化和局部灵敏度计算将 并行实施，以提高效率。 的 算法提供了一个计算成本低廉的程序， 与之前相比，量化子系统交互 算法提案 第二种算法将使用神经网络 来构建系统设计空间的近似值。 使用 神经网络来表示设计空间， 多学科设计优化策略 在以前的算法提案中使用的设计技术。 神经 网络将使用期间积累的数据进行训练。 并发子空间优化 算法将会 作为通用设计优化工具开发， 应用于多种复耦合多进制 系统. 电子封装设计是一个领域， 可通过应用以下方法实现效益： 多学科设计优化 多学科设计 优化子系统之间的复杂耦合形式上是 在并行设计过程中量化和利用。 //

In this research two new general purpose algorithms for multidisciplinary design optimization will be fully developed and implemented in application to electronic package optimization. In one algorithm second order system sensitivities will be generated using local second order design sensitivities generated concurrently during subsystem optimizations. The concurrent subsystem optimizations and local sensitivity calculations will be implemented in parallel to achieve greater efficiencies. The algorithm provides a computationally inexpensive procedure for quantifying subsystem interactions as compared to previous algorithm proposals. The second algorithm will use neural networks to build approximations of the system design space. The use of neural networks to represent the design space moves the multidisciplinary design optimization strategy away from the point design techniques used in previous algorithm proposals. The neural network will be trained using data that is accumulated during concurrent subspace optimizations. The algorithms will be developed as general purpose design optimization tools for application to a variety of complex coupled multidisiplinary systems. Electronic packaging design is an area where immediate benefits can be realized through the application of multidisciplinary design optimization. In multidisciplinary design optimization the complex couplings between subsystems are formally quantified and exploited in a concurrent design process. //