MDC: A High-Performance Problem-Solving Environment for Optimization and Control of Chemical and Biological Processes

这项研究的主要目标是开发 高性能问题解决环境（PSE）， 化学和生物过程的优化和控制， 强调生物工程应用。 优化与控制 这类过程需要重复的解决方案的时间依赖的部分 在两个或三个空间维度上的偏微分方程（PDE）。 的 这一问题的要求，必须解决 交互地，只能通过使用大规模并行计算机来满足。 这样的 全面而强大的PSE目前还不存在，其发展 提出了重大的计算和计算机科学挑战。 初始 应用是小直径的设计和优化 生物人工动脉 超过600，000例血管置换手术 每年在美国进行，许多涉及合成聚合物替代品 对于由于缺乏生物相容性而失效的小直径血管， 这对于生物人工动脉来说不是问题。 基于连续统的偏微分方程模型 力学理论，描述细胞，纤维和 组织中的应力将被用于模拟 生物人工动脉 生物人工骨最终性能的优化 寻求动脉，特别是承受脉动动脉的能力， 压力 具有类似数学结构的PDE系统通常出现在 作为需要控制的化学过程的模型， 优化. 该项目包括与科学家的合作和投入， 工程师在几个工业和政府实验室的应用， 处理. 优化或控制一个过程， 在偏微分方程中，原始时间间隔被划分为多个子间隔，采用多重激发型方法。 每个子区间上的偏微分方程离散化为 空间通过并行自适应有限元方法，给出了一个大系统， 代数方程组（DAE）。 参数或控制变量 然后优化，受状态和控制变量和连续性 约束（等式和不等式）使用大规模非线性规划 技术. 广泛的知识和研究经验，在适应性方法， PDE、DAE、大规模优化、并行计算、计算 环境，化学和生物过程，需要 成功开发了这样一个PSE。 reaerch团队成员涵盖了这一广泛的范围， 专业知识，并有成功的合作记录 彼此之间

The primary goal of this research is the development of high-performance problem solving environment (PSE) for the optimization and control of chemical and biological processes, with initial emphasis on bioengineering applications. The optimization and control of such processes requires the repetitive solution of time-dependent partial equations (PDEs) in two or three spatial dimensions. The requirements of this problem, which must be solved interactively, can only be met by the use of massively parallel computers. Such a comprehensive and powerful PSE does not currently exist, and its development presents significant computational and computer science challenges. The initial application is the design and optimization of a small diameter bioartificial artery. Over 600,000 surgical procedures for blood vessel replacement are conducted in the U.S. annually, many involving synthetic polymer substitutes for small diameter blood vessels that fail due to lack of biocompatability, which is not an issue for bioartificial arteries. A PDE model based on continuum mechanical theory that describes the distribution of cells, fibers, and stresses in a tissue will be used to simulate the evolving compaction of a bioartificial artery. Optimization of the ultimate properties of the bioartificial artery is sought, in particular the ability to withstand pulsatile arterial pressure. PDE systems of a similar mathematical structure commonly arise as models for chemical processes with a need for their control and optimization. The project includes collaboration with and input from scientists and engineers at several industrial and government laboratories with applications in processing. To optimize or control a process described by PDEs, the original time interval is divided into subintervals in a multiple- shooting type approach. The PDEs on each subinterval are discretized in space via parallel adaptive finite el ement methods to give a large system of algebraic equations (DAEs). Parameters or control variables are then optimized, subject to state and control variable and continuity constraints (equality and inequality) using large-scale nonlinear programming techniques. Extensive knowledge and research experience in adaptive methods for PDEs, DAEs, large-scale optimization, parallel computing, computing environments, and chemical and biological processes, are required to successfully develop such a PSE. The reaerch team members cover this broad range of expertise, and have a successful record of collaboration with each other.