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Design and Operation of High Performance Chemical Processes

Design and Operation of High Performance Chemical Processes
高性能化学工艺的设计和操作
批准号:
9114080
负责人:
Warren Seider
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing grant
财政年份:
1991
资助国家:
美国
项目状态:
已结题
起止时间:
1991-08-15 至 1995-01-31

项目摘要

项目成果

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中文摘要
翻译
该项目延续了首席研究员对难以操作和控制的复杂过程设计的算法方法的实验;也就是说,过程经常被过度设计,因为过程工程师不愿意在复杂操作制度附近或内部进行设计,因为这些过程通常在经济上是最优的。为了实现更好的设计,将继续研究设计方法的发展,包括设计、操作和控制优化的协调。原型软件系统PRODOC将得到扩展,以允许在更广泛的化学过程中使用新的方法来消除过度设计。在这些新方法中,设计和控制模型随着设计的发展以协调的方式得到改进。先前开发的模型预测控制器(MPC)能够在复杂非线性区域附近或内部运行所需的改进控制。MPC优化与经济优化相协调,随着经济优化的进行,有效地评价最有希望的设计的可控性。该项目涉及两种典型的化学过程,以实验新的算法和设计方法。它扩展和完善了定位所有解决方案的优化技术,包括全局最优,复杂的非线性程序,如在实施新的设计方法时出现。这些贡献,可以被期望为所有设计工程师推进最先进的技术,开始对化学过程工程师产生影响,他们正在获得可靠地设计更多高度集成的化学过程的能力,这些过程更节能,更有利可图。
英文摘要
This project continues the principal investigator's experimentation with algorithmic methods for the design of complex processes that are difficult to operate and control; that is, processes that are often overdesigned because process engineers are reluctant to design near or within regimes of complex operation, where these processes are often economically optimal. To achieve better designs, work will continue to investigate development of design methodologies that involve the coordination of design, operations, and control optimizations. The prototype software system, PRODOC, will be extended to permit experimentation with new methodologies for eliminating overdesign in a broader class of chemical processes. In these new methodologies, models for design and control are refined in a coordinated fashion as the design evolves. A Model Predictive Controller (MPC) developed previously, enables the improved control needed to operate near or within complex nonlinear regimes. MPC optimization is coordinated with economic optimization to efficiently evaluate the controllability of the most promising designs as the economic optimization proceeds. The project is concerned with two typical chemical processes for experimentation with the new algorithms and design methodologies. It extends and perfects the optimization techniques for locating all solutions, including the global optimum, of complex nonlinear programs, such as arise when implementing the new design methodologies. The contributions, which can be expected to advance the state-of-the-art for all design engineers, are beginning to have an impact on chemical process engineers, who are gaining the ability to reliably design more highly-integrated chemical processes that are more energy- efficient and profitable.
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Path Sampling and Dynamic Risk Analysis
  • 批准号:
    2220276
  • 项目类别:
    Standard Grant
  • 资助金额:
    $35.0万
  • 财政年份:
    2022
  • 负责人:
    Warren Seider
  • 依托单位:
EAGER: GOALI: REAL-D Path-Sampling Algorithms to Understand Rare Safety Events and Improve Alarm Systems
  • 批准号:
    1839535
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.0万
  • 财政年份:
    2018
  • 负责人:
    Warren Seider
  • 依托单位:
GOALI: Collaborative Research: Model-Predictive Safety Systems for Predictive Detection of Operation Hazards
  • 批准号:
    1704833
  • 项目类别:
    Standard Grant
  • 资助金额:
    $10.77万
  • 财政年份:
    2017
  • 负责人:
    Warren Seider
  • 依托单位:
Collaborative Research: GOALI: Synergistic Improvement of Process Safety and Product Quality Using Process Databases
  • 批准号:
    1066475
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $35.2万
  • 财政年份:
    2011
  • 负责人:
    Warren Seider
  • 依托单位:
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