Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured a...Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.展开更多
The recent works on the development of computational mass transfer （CMT） method and its applications in chemical process simulation are reviewed. Some development strategies and challenges in future research are als...The recent works on the development of computational mass transfer （CMT） method and its applications in chemical process simulation are reviewed. Some development strategies and challenges in future research are also discussed.展开更多
Comparing with continuous production process, unsteady operation process, such as startup and shutdown,tends to abnormal situations due to a large number of operations of operators and dynamic state changes involved. ...Comparing with continuous production process, unsteady operation process, such as startup and shutdown,tends to abnormal situations due to a large number of operations of operators and dynamic state changes involved. To guarantee a safe operation, process hazard analysis(PHA) is very important to proactively identify the potential safety problems. In the chemical process industry, hazard and operability(HAZOP) analysis is the most widely used method. In this paper, based on proposed qualitative simulation and inference method, an automatic HAZOP analysis method for unsteady operation processes is proposed. Mass transfer and relationships among process variables are expressed by Petri net–directed graph model based fuzzy logic. Operating procedure is expressed according to a formal expression. Possible operation deviations from normal operating procedure are identified by using a group of guidewords. Hazards are identified automatically by qualitative simulation and inference when wrong operation process is performed. The method is validated by a rectification column system.展开更多
文摘Large language model-based agent systems are emerging as transformative technologies in chemical process simulation, enhancing efficiency, accuracy, and decision-making. By automating data analysis across structured and unstructured sources—including process parameters, experimental results, simulation data, and textual specifications—these systems address longstanding challenges such as manual parameter tuning, subjective expert reliance, and the gap between theoretical models and industrial application. This paper reviews the key barriers to broader adoption of large language model-based agent systems, including unstable software interfaces, limited dynamic modeling accuracy, and difficulties in multimodal data integration, which hinder scalable deployment. We then survey recent progress in domain-specific foundation models, model interpretability techniques, and industrial-grade validation platforms. Building on these insights, we propose a technical framework centered on three pillars: multimodal task perception, autonomous planning, and knowledge-driven iterative optimization. This framework supports adaptive reasoning and robust execution in complex simulation environments. Finally, we outline a next-generation intelligent paradigm where natural language-driven agent workflows unify high-level strategic intent with automated task execution. The paper concludes by identifying future research directions to enhance robustness, adaptability, and safety, paving the way for practical integration of large language model based agent systems into industrial-scale chemical process simulation.
基金Supported by the National Science Foundation of China（20736005）.ACKNOWLEDGEMENTSThe authors acknowledge the assistance from thestaff in the State Key Laboratories of Chemical Engineering （Tianjin University）.
文摘The recent works on the development of computational mass transfer （CMT） method and its applications in chemical process simulation are reviewed. Some development strategies and challenges in future research are also discussed.
文摘Comparing with continuous production process, unsteady operation process, such as startup and shutdown,tends to abnormal situations due to a large number of operations of operators and dynamic state changes involved. To guarantee a safe operation, process hazard analysis(PHA) is very important to proactively identify the potential safety problems. In the chemical process industry, hazard and operability(HAZOP) analysis is the most widely used method. In this paper, based on proposed qualitative simulation and inference method, an automatic HAZOP analysis method for unsteady operation processes is proposed. Mass transfer and relationships among process variables are expressed by Petri net–directed graph model based fuzzy logic. Operating procedure is expressed according to a formal expression. Possible operation deviations from normal operating procedure are identified by using a group of guidewords. Hazards are identified automatically by qualitative simulation and inference when wrong operation process is performed. The method is validated by a rectification column system.
