An integrated approach for model building, maintenance, reduction and updating in complex dynamic chemical systems

复杂动态化学系统中模型构建、维护、简化和更新的综合方法

• 批准号: RGPIN-2014-06634
• 负责人: Prasad, Vinay
• 金额: $ 1.82万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=612342
• 关键词: integrated; approach; model; building; maintenance

Process systems engineering is concerned with the development and updating of dynamic models, and the use of these models for monitoring, control and optimization. Complex systems present many challenges to the application of standard methods for each of objectives. Complexity itself arises from many sources, including the multiscale or distributed nature of processes, their networked structure, the presence of populations or ensembles of units in the system, or the sheer number of variables in the system. The specific problems complex systems pose are of three kinds: computational and numerical issues in applying standard techniques of analysis (for model updating, estimation, monitoring, optimization and control) to models of such size and scale, incomplete understanding of the physics (and/or chemistry) leading to difficulty in constructing fundamental models in the first place, and the difficulty in obtaining and interpreting meaningful data from sensors for such systems. In the past, our research has addressed examples of these challenges in various application areas, including developing methods for model updating and estimation suitable for large-scale systems, the development of hybrid pseudo-kinetic models for complex chemical systems, and the development of techniques for surrogate modeling and uncertainty propagation in reservoir modeling and prediction. In the research program outlined in this proposal, we take the first steps towards developing a general research framework for addressing the challenges of building hybrid or gray-box models for systems where we have incomplete knowledge to build a fundamental model, for fusing information from multiple sensors and reconciling them with the developed models, and the development of model reduction methods for reducing the difficulty of analysis of system characteristics in complex systems. The expected contributions arising from the proposed program have the potential to significantly advance the state of the art in development of process systems engineering techniques for complex systems; in addition, these techniques will find applicability in a wide variety of application areas under investigation in my research, including froth flotation, coal and petroleum reservoir modeling and estimation, optimization and control of catalysts and catalytic processes, thermal upgrading of bitumen, carbon dioxide fixation and biofuel production using microalgae, and chemometric interpretation of on-line spectroscopic data.

流程系统工程与动态模型的开发和更新有关，以及这些模型用于监视，控制和优化。复杂的系统对每个目标的应用标准方法都带来了许多挑战。复杂性本身来自许多来源，包括流程的多尺度或分布式性质，其网络结构，系统中的人群的存在或单位合奏的存在或系统中的变量数量。特定问题复杂系统姿势分为三种：应用标准技术（用于模型更新，估计，监视，优化和控制）时，对这种尺寸和规模的模型，对物理学（和/或化学）的了解不完整，导致难以在最初构建基本模型以及获得这些系统中的模型中的难度。 过去，我们的研究解决了各种应用领域中这些挑战的例子，包括开发适用于大型系统的模型更新和估计方法，开发用于复杂化学系统的混合伪动光模型以及开发用于Reserveir模型和预测中的替代模型和不确定性繁殖技术的技术。在该提案中概述的研究计划中，我们采取了第一步，开发了一个通用研究框架，以解决为系统建立混合或灰色盒模型的挑战，在这些框架中，我们有不完整的知识来构建一个基本模型，以融合来自多个传感器的信息并将其与已发达的模型进行融合，并使它们与开发的模型和模型的开发方法降低了系统的难度分析系统的模型。 提议的计划产生的预期贡献有可能显着推进复杂系统工艺系统工程技术开发的最新状态； in addition, these techniques will find applicability in a wide variety of application areas under investigation in my research, including froth flotation, coal and petroleum reservoir modeling and estimation, optimization and control of catalysts and catalytic processes, thermal upgrading of bitumen, carbon dioxide fixation and biofuel production using microalgae, and chemometric interpretation of on-line spectroscopic data.