Hybrid modelling and optimization of process systems

过程系统的混合建模和优化

• 批准号: 341228-2007
• 负责人: Mahalec, Vladimir
• 金额: $ 1.8万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=363960
• 关键词: Hybrid; modelling; optimization; process; systems

Prediction of a process system behaviour (pharmaceutical, chemical, refining or similar plants) via simulation has enabled their optimal design and operation.  These systems are modeled by networks where nodes (equipment) transform energy or material, while arcs are material, energy, or information flows.  Current abilities to model process systems are limited by the accuracy of equipment models, as well as the algorithms for solving the entire network.  First principles equipment models often require a very large effort to achieve desired accuracy.  Models combining the first principles and empirical models (so called hybrid models) have been explored as an alternative.   At present there are no well defined methods that determine what types of equations to include in each part of a hybrid model.   Currently, process networks are simulated or optimized by algorithms that are inherently limited by being single computational processes on single CPUs and do not exploit multi-processor computing capabilities.Goal of the research is to enable an order of magnitude improvement in simulation speed for large process systems and a significant reduction of the effort required to build accurate plant equipment models by:I. Development of typical hybrid model structures for specific types of equipments - thereby providing means for rapid equipment modeling.II. A new class of computational architecture for a process network - simulation via node models that behave autonomously and can run simultaneously (agent-based network computations),  andIII. Algorithms enabling optimization of discrete & continuous variables in such agent-based systems.  The research will provide a basis for a new generation of applications in process design and optimal operation of processes in refining, polymers, pharmaceuticals, or chemicals for bio applications.

通过模拟预测过程系统行为（制药、化工、炼油或类似工厂），使其能够实现最佳设计和操作。​这些系统通过网络建模，其中节点（设备）转换能量或材料，而弧则是材料、能量、当前对过程系统进行建模的能力受到设备模型的准确性以及求解整个网络的第一原理设备模型的算法的限制，以达到所需的模型。目前，还没有明确定义的方法来确定混合模型的每个部分中包含哪些类型的方程。通过算法进行模拟或优化，这些算法本质上受到单个 CPU 上的单个计算过程的限制，并且不利用多处理器计算能力。该研究的目标是使大型过程系统的模拟速度实现一个数量级的提高，并显着提高减少构建所需的工作量准确的工厂设备模型：I. 为特定类型的设备开发典型的混合模型结构 - 提供快速设备建模的方法。 II. 通过自主运行的节点模型进行模拟同时运行（基于代理的网络计算），以及能够在此类基于代理的系统中优化离散和连续变量的算法。该研究将为炼油过程设计和过程优化操作提供基础。聚合物，药品或生物应用化学品。