Presidential Young Investigator Award

总统青年研究员奖

• 批准号: 8657899
• 负责人: Lyle Ungar
• 金额: $ 31.2万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-06-15 至 1992-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8657899&HistoricalAwards=false
• 关键词: Presidential; Young; Investigator; Award

This grant is to provide research support for Dr. Lyle Ungar under the National Science Foundation's Presidential Young Investigator Awards program. Dr. Ungar's research is in two areas: (1) the application of artificial intelligence techniques to automate reasoning about chemical plants and (2) the modelling of transport in systems with moving boundaries and phase transformations. In (1), the area of design and control, he is writing knowledge-based expert systems which use causal models and first principles to gain a "deep" understanding of plant behavior which is applicable to a broad class of processes and problems. The underlying reason for this work is that to be as useful and reliable as possible, expert systems should be able to work from descriptions of processes such as flow sheets, and not need extensive customization for each new process. As part of this project the PI is developing an expert multivariable controller which diagnoses process malfunctions and makes appropriate structural changes to the controller structure, control algorithms and control parameters in order to acheive as tight control of the process as possible. He is working on isolating as much plant-independent knowledge about equipment and control algorithms as possible and on formalizing notions of causality used by engineers i~ design and trouble shooting. In (2), the area of transport through multiphase media, he is using analytical and finite element based perturbation methods to characterize the effect of solidification conditions on melt/solid interface shape and solute segregation and, in particular, to map out the transitions between interfaces of different morphology. A detailed understanding of the solidification process is important for a variety of emerging techniques in electronic materials processing. Pulsed laser annealing is one of these techniques. Pulsed lasers can be used to rapidly melt thin layers (1 micron) of semiconductors and metals which resolidify at rates of up to several meters per second. At these velocities - some 10 times normal crystal growth rates, the melt/solid interface is no longer at equilibrium and dopant segregation is radically altered. Defects can be removed and nonequilibrium (metastable) alloys formed. However, nonuniform solute segregation often limits the usefulness of the alloys. He is incorporating results from atomic scale modelling of rapid solidification into macroscopic transport models, and studying the resulting growth morphologies.

这笔赠款是为莱尔·恩加博士提供研究支持 在国家科学基金会的总统青年 研究者奖计划。 Ungar博士的研究主要集中在两个方面：（1） 人工智能技术自动推理 化学工厂和（2）系统中的运输建模 移动边界和相变。 在（1），设计和控制领域，他写道， 基于知识的专家系统，使用因果模型， “深入”了解植物的首要原则 行为，适用于广泛的过程类别， 问题 这项工作的根本原因是， 尽可能有用和可靠，专家系统应该能够 根据流程图等流程描述进行工作， 不需要为每个新过程进行大量定制。 一部分 PI正在开发一个专家多变量 控制器，诊断过程故障， 对控制器结构进行适当的结构改变， 控制算法和控制参数，以实现 尽可能严格地控制过程。 他正在写 隔离尽可能多的与工厂无关的设备知识， 和控制算法，并对形式化的概念 工程师在设计和解决问题时使用的因果关系。 在（2）中，通过多相介质的传输区域，他是 使用基于分析和有限元的扰动方法 为了表征固化条件对 熔体/固体界面形状和溶质偏析， 特别是，绘制出接口之间的转换， 不同的形态 详细了解 固化过程对于各种新兴的 电子材料加工技术。 脉冲激光 退火是这些技术之一。 脉冲激光可以 用于快速熔化半导体薄层（1微米） 金属的再固化速度可达数米 每秒 在这些速度下--大约是正常速度的10倍 晶体生长速率，熔体/固体界面不再处于 平衡和掺杂剂偏析被彻底改变。 缺陷可以被去除，非平衡（亚稳）合金 形成了 然而，不均匀的溶质偏析往往限制 合金的用途。 他将来自 原子尺度模拟快速凝固成宏观 运输模型，并研究由此产生的增长 形态学