U.S.-Switzerland Cooperative Research: Stochastic Simulation of Transport Phenomena

9312811 DePablo该奖项支持Juan DePablo博士和威斯康星州大学的两名研究生与Hans C.位于苏黎世的瑞士联邦理工学院聚合物研究所的Oettinger说。 Oettinger教授是随机方法数学方面的世界知名权威，他的机构拥有一些世界上最快的超级计算机。 威斯康星州大学化学工程系是世界上最重要的中心之一，致力于发展和应用传输现象理论来解决化学工程问题。 这些互补的优势非常适合他们的合作目标，这是发展随机方法，使其成为解决运输现象问题的标准工具。他们将通过研究这些方法的数学基础并将其应用于各种工程应用来做到这一点，从不同类型的流动停止后聚合物熔体的流变行为开始。 他们将把他们的理论工作与ETH-Zurich的Oettinger教授的同事产生的实验数据进行比较。 随机方法在解决复杂的多维问题中发挥着越来越重要的作用。 它们首先被开发出来，现在广泛用于物理和数学，但这种复杂的数学方法在化学工程中尚未得到充分利用。 与其他一些方法相比，随机方法非常简单，并且它们似乎可以解决一些难以进行传统分析处理的复杂问题。 另一方面，它们并不总是上级于数值方法。 实质性的工作，如这里提出的，是必要的，以探索在化学工程中的优势和实际应用。 ***

9312811 DePablo This award supports Dr. Juan DePablo and two graduate students of the University of Wisconsin to collaborate in theoretical chemical engineering research with Professor Hans C. Oettinger of the Polymer Institute of the Swiss Federal Institute of Technology in Zurich. Professor Oettinger is a world-renown authority in the mathematical aspects of stochastic methods, and his institution has some of the world's fastest supercomputers. The Department of Chemical Engineering at the University of Wisconsin is one of the world's foremost centers for the development and application of the theory of transport phenomena to the solution of chemical engineering problems. These complementary strengths are well suited to the goal of their collaboration, which is to develop stochastic methods to the point where they become a standard tool for the solution of problems in transport phenomena. They will do this by investigating the mathematical foundations of such methods and by applying these to a wide variety of engineering applications, beginning with the rheological behavior of polymer melts after cessation of different types of flows. They will compare their theoretical work with experimental data generated by colleagues of Professor Oettinger at ETH-Zurich. Stochastic methods are playing an increasingly important role in the solution of complex, multidimensional problems. They were first developed and are now widely used in physics and mathematics, but this sophisticated mathematical approach has not been fully exploited in chemical engineering. Stochastic methods are remarkably simple compared to some other methods, and they appear to work in some complex problems resistant to traditional analytical treatment. On the other hand, they are not always superior to numerical methods. Substantial work, such as that proposed here, is necessary to explore the advantages and practical applications in chemical engineering. ***