An integrated approach to discovery and optimal operation in process and reaction engineering

过程和反应工程中发现和优化操作的综合方法

• 批准号: RGPIN-2019-04600
• 负责人: Prasad, Vinay
• 金额: $ 3.35万
• 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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715060
• 关键词: integrated; approach; discovery; optimal; operation

The focus of this proposal is on an integrated approach to discovery and optimal operation in process and reaction engineering. It addresses the various issues presented by complexity in chemical processes: a large number of species/reactions, spatial heterogeneity, and tightly coupled and networked interacting subsystems. The first cause arises from the use of complex feeds, the second from spatial heterogeneity of the processes, and the third because of tightly coupled heat and mass transfer operations that are a natural consequence of process intensification and attempts to improve the efficiency of operation. Complexity presents many challenges to optimal dynamic operation. In systems like biomass conversion and bitumen upgrading, the inability to even identify all species presents a significant challenge to determining optimal operation and understanding the underlying chemistry. We propose a method to hypothesize and discover the dominant chemistry in such systems based on statistical, machine learning and graph-theoretic methods. A method is developed to incorporate information from multiple spectroscopic sources to improve identification of the chemistry. The identification of chemistry and reaction mechanism enable the development of accurate process models and advanced process control. The issues presented by spatial heterogeneity of petroleum reservoirs are addressed by transforming the process models to network or graph-based models. Concepts of reachability of nodes in graphs are invoked to identify the sensor and actuator locations that will result in optimal operation and control. In the case of tightly coupled networks of chemical processes and their units, a thermodynamics-based framework for the process models and controllers is combined with the network models to develop a framework for optimally reconfiguration of the plantwide control system. The integrated network or graph-based approach described in the proposal has the potential to address two major issues: smart and adaptive optimal operation of process systems under uncertainty, and sustainable and optimal process operation. The application to energy-related processes also ensures significant impact when the results of the research are implemented.

该提案的重点是在过程和反应工程中的发现和最佳操作的综合方法。它解决了化学过程中复杂性提出的各种问题：大量物种/反应，空间异质性以及紧密耦合和联网的相互作用子系统。第一个原因是使用复合饲料的使用，第二个原因是过程的空间异质性，第三个原因是由于加热和传质操作紧密耦合，这是过程加强的自然结果，并试图提高操作效率。复杂性给最佳动态操作带来了许多挑战。 在诸如生物量转化和沥青升级之类的系统中，甚至无法识别所有物种对确定最佳操作和理解潜在化学的挑战构成了重大挑战。我们提出了一种基于统计，机器学习和图理论方法的系统中假设和发现此类系统中的主要化学方法的方法。开发了一种方法来合并来自多个光谱源的信息，以改善化学的识别。化学和反应机制的鉴定可以开发准确的过程模型和高级过程控制。 通过将过程模型转换为基于网络或基于图的模型，可以解决石油储层的空间异质性提出的问题。调用节点在图中的可及性概念，以识别传感器和执行器位置，从而导致最佳操作和控制。 在化学过程及其单元的紧密耦合网络的情况下，将基于热力学的过程模型和控制器的框架与网络模型相结合，以开发一个框架，以最佳地重新配置植物园控制系统。 提案中描述的基于集成的网络或基于图的方法具有解决两个主要问题的潜力：不确定性下的过程系统的智能和适应性最佳操作以及可持续且最佳的过程操作。在实施研究结果时，与能源相关的过程的应用还确保了重大影响。