Optimization of Chemical Processes Under Uncertainty

不确定性下的化学过程优化

• 批准号: 9726135
• 负责人: Luke Achenie
• 金额: $ 20.75万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-04-01 至 2001-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9726135&HistoricalAwards=false
• 关键词: Optimization; Chemical; Processes; Under; Uncertainty

Achenie CTS-9726135 The aim of this research is developing novel mathematical support and the associated software for doing simultaneous optimization, and flexibility analysis of chemical processes. Specifically, the following problems will be addressed: (I) estimation of chemical process flexibility, (ii) chemical process optimizaion under uncertainty at the design stage and (iii) optimization of existing chemical processes under uncertainty. The research effort and the resulting software will allow a process engineer to solve the following industrial problems: (1) an estimate of the ability of a chemical process to sustain an acceptable level of performance even when external internal factors change in an unpredictable fashion (for example, a change of catalyst activity in chemical reactors or a change in feed flow rate), (ii) calculation of optimal design margins for process equipment at the design stage, and (iii) calculation of optimal values of control variables (used for example to satisfy environmental and safety requirements) for existing chemical processes under uncertainty. The proposal is being funded under NSF's Cooperative Research Program for Cental and Eastern Europe and the Newly-Independent States. This work is a collaborative effort between the PI and two researchers at the Karpov Institute of Physical Chemistry in Russia.

Achenie CTS-9726135本研究的目的是开发新的数学支持和相关的软件进行同步优化，和灵活性分析的化学过程。 具体而言，将解决以下问题：（一）估计的化工过程的灵活性，（二）化工过程优化下的不确定性在设计阶段和（iii）现有的化工过程的优化下的不确定性。 研究工作和由此产生的软件将允许过程工程师解决以下工业问题：（1）即使外部内部因素以不可预测的方式变化，化学过程维持可接受性能水平的能力的估计（例如，化学反应器中催化剂活性的变化或进料流速的变化），（ii）在设计阶段计算工艺设备的最佳设计裕度，以及（iii）在不确定性下计算现有化学工艺的控制变量的最佳值（例如用于满足环境和安全要求）。 该提案由NSF的中欧和东欧以及新独立国家合作研究计划资助。 这项工作是PI和俄罗斯卡尔波夫物理化学研究所的两名研究人员之间的合作努力。