Computers & Chemical Engineering最新文献

Online fault detection and classification of chemical process systems leveraging statistical process control and Riemannian geometric analysis 利用统计过程控制和黎曼几何分析的化学过程系统的在线故障检测和分类

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-22 DOI: 10.1016/j.compchemeng.2025.109177

Alireza Miraliakbar , Fangyuan Ma , Zheyu Jiang

{"title":"Online fault detection and classification of chemical process systems leveraging statistical process control and Riemannian geometric analysis","authors":"Alireza Miraliakbar , Fangyuan Ma , Zheyu Jiang","doi":"10.1016/j.compchemeng.2025.109177","DOIUrl":"10.1016/j.compchemeng.2025.109177","url":null,"abstract":"<div><div>In this work, we study an integrated fault detection and classification framework called FARM for fast, accurate, and robust online chemical process monitoring. The FARM framework integrates the latest advancements in statistical process control (SPC) for monitoring nonparametric and heterogeneous data streams with novel data analysis approaches based on Riemannian geometry together in a hierarchical framework for online process monitoring. We conduct a systematic evaluation of the FARM monitoring framework using the Tennessee Eastman Process (TEP) dataset. Results show that FARM performs competitively against state-of-the-art process monitoring algorithms by achieving a good balance among fault detection rate (FDR), fault detection speed (FDS), and false alarm rate (FAR). Specifically, FARM achieved an average FDR of 96.16% while also outperforming benchmark methods in successfully detecting hard-to-detect faults that are previously known, including Faults 3, 9 and 15, with FDRs being 96.03%, 94.83% and 94.20%, respectively. In terms of FAR, our FARM framework allows practitioners to customize their choice of FAR, thereby offering great flexibility. Moreover, we report a significant improvement in average fault classification accuracy during online monitoring from 61% to 82% when leveraging Riemannian geometric analysis, and further to 84.5% when incorporating additional features from SPC. This illustrates the synergistic effect of integrating fault detection and classification in a holistic, hierarchical monitoring framework.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109177"},"PeriodicalIF":3.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel framework for flexibility assessment in design spaces defined by a set of affine bounds 一种由一组仿射界定义的设计空间灵活性评估的新框架

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-21 DOI: 10.1016/j.compchemeng.2025.109189

Diogo A.C. Narciso , Steven Sachio , Maria M. Papathanasiou

{"title":"A novel framework for flexibility assessment in design spaces defined by a set of affine bounds","authors":"Diogo A.C. Narciso , Steven Sachio , Maria M. Papathanasiou","doi":"10.1016/j.compchemeng.2025.109189","DOIUrl":"10.1016/j.compchemeng.2025.109189","url":null,"abstract":"<div><div>A novel framework for flexibility assessment in the context of system design is proposed. We deal with the case when the design space is bounded by a set of affine bounds defining a convex-hull. For this class of problems several flexibility metrics can be calculated, which are related to the minimum/maximum distances between any point in the design space and the less/most distant points at its bounds, respectively. In the first case, the distance functions are obtained via projection to individual bounds, and in the second case, the distance functions are defined via the Euclidean distance to the corners of convex hulls. These two sets of functions can then be used separately to calculate the minimum/maximum of the complete set of minimum/maximum distance functions over the full design space. This approach effectively enables the definition of four multi-parametric programming problems, and deliver four flexibility maps from their solutions. Flexibility maps based on the average of the two sets of distance functions are also delivered. This offers a plethora of complementary metrics for flexibility assessment, which extend beyond the classic approach based on the definition of feasible boxes. From the full set of solutions enabled by this framework, the minimum–minimum and maximum–maximum distance-based flexibility maps stand out as the extreme and most useful cases for flexibility assessment; the initial experimentation with these maps suggest that the average-minimum and particularly the average-maximum distance cases also provide useful information as an overall score on flexibility for any points within the design space.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109189"},"PeriodicalIF":3.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iteration-free cooperative distributed model predictive control through multiparametric programming 基于多参数规划的无迭代协同分布式模型预测控制

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-20 DOI: 10.1016/j.compchemeng.2025.109169

Radhe S.T. Saini , Parth R. Brahmbhatt , Styliani Avraamidou , Hari S. Ganesh

{"title":"Iteration-free cooperative distributed model predictive control through multiparametric programming","authors":"Radhe S.T. Saini , Parth R. Brahmbhatt , Styliani Avraamidou , Hari S. Ganesh","doi":"10.1016/j.compchemeng.2025.109169","DOIUrl":"10.1016/j.compchemeng.2025.109169","url":null,"abstract":"<div><div>Cooperative Distributed Model Predictive Control (DiMPC) architecture employs local MPC controllers to control different subsystems, exchanging information with each other through an iterative procedure to enhance overall control performance compared to the decentralized architecture. However, this method can result in high communication between the controllers and computational costs. In this work, the amount of information exchanged and the computational costs of DiMPC are reduced significantly by developing novel iteration-free solution algorithms based on multiparametric (mp) programming. These algorithms replace the iterative procedure with simultaneous solutions of explicit mpDiMPC control law functions. The reduced communication among local controllers decreases system latency, which is crucial for real-time control applications. The effectiveness of the proposed iteration-free mpDiMPC algorithms is demonstrated through comprehensive numerical simulations involving groups of coupled linear subsystems, which are interconnected through their inputs and a cooperative plant-wide cost function.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109169"},"PeriodicalIF":3.9,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Surrogate model optimization: a comparison case study with pooling problems of CO2 point sources 代理模型优化：与CO2点源池问题的比较案例研究

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-18 DOI: 10.1016/j.compchemeng.2025.109199

H.A. Pedrozo , M.A. Zamarripa , A. Uribe-Rodríguez , G. Panagakos , M.S. Diaz , L.T. Biegler

{"title":"Surrogate model optimization: a comparison case study with pooling problems of CO2 point sources","authors":"H.A. Pedrozo , M.A. Zamarripa , A. Uribe-Rodríguez , G. Panagakos , M.S. Diaz , L.T. Biegler","doi":"10.1016/j.compchemeng.2025.109199","DOIUrl":"10.1016/j.compchemeng.2025.109199","url":null,"abstract":"<div><div>In this work, we present a benchmark study to leverage the implementation of surrogate models (SMs) within mathematical optimization problems for the integration of carbon capture technologies within an industrial complex, focusing on the pooling of CO₂ streams to enhance efficiency and reduce capture costs. The SMs are built using data from rigorous process simulations in Aspen Plus, with each data point generated by solving equation-oriented optimization problems. We evaluate five different SMs approaches: Automated Learning of Algebraic Models for Optimization (ALAMO), Kriging, Radial Basis Functions (RBFs), Polynomials, and Artificial Neural Networks (ANNs). We assess their accuracy, computational efficiency, and optimization performance.</div><div>In “one-shot” optimization, ALAMO is the most computationally efficient, while Kriging requires the highest CPU time and may struggle with convergence. To improve solution reliability, we incorporate a trust-region filter (TRF) solution strategy. Within this framework, Kriging and ANN achieve the fastest convergence (two iterations), while ALAMO offers a good balance between efficiency and reliability. The RBF SM presents high accuracy on training data; however, it requires more iterations, increasing computational demand.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109199"},"PeriodicalIF":3.9,"publicationDate":"2025-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modelling and analysis of resilience and reliability in pharmaceutical supply chains 药品供应链弹性和可靠性的建模和分析

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-17 DOI: 10.1016/j.compchemeng.2025.109194

Devesh Kumar , Gunjan Soni , Ajay Pal Singh Rathore , Yigit Kazancoglu

引用次数: 0

An event-based neural partial differential equation model of heat and mass transport in an industrial drying oven 基于事件的工业烘箱热质传递神经偏微分方程模型

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-16 DOI: 10.1016/j.compchemeng.2025.109171

Siddharth Prabhu , Sulman Haque , Dan Gurr , Loren Coley , Jim Beilstein , Srinivas Rangarajan , Mayuresh Kothare

{"title":"An event-based neural partial differential equation model of heat and mass transport in an industrial drying oven","authors":"Siddharth Prabhu , Sulman Haque , Dan Gurr , Loren Coley , Jim Beilstein , Srinivas Rangarajan , Mayuresh Kothare","doi":"10.1016/j.compchemeng.2025.109171","DOIUrl":"10.1016/j.compchemeng.2025.109171","url":null,"abstract":"<div><div>Convective drying is an ubiquitous unit operation in chemical and allied industries; it is energy intensive and a significant contributor to the carbon footprint of a plant. Developing detailed models, a digital twin, of an industrial oven can enable rigorous energy optimization. In this context, we use a neural partial differential equation formalism to train a model of an industrial oven to capture the evolution of the moisture and temperature as a solid passes through. We also use an event function to capture the transition of the moisture and the temperature between the constant rate drying regime and the falling rate drying regime. We show that this hybrid model, even when trained on partially observed and spatially sparse industrial data, accurately captures the system dynamics and generalizes effectively to other spatial locations. We proffer that neural differential equations provide enough flexibility to model complex chemical processes and include domain knowledge to deal with limited and noisy data.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109171"},"PeriodicalIF":3.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144098852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancements in thermal runaway process monitoring: Exploring a novel residual dissimilarity-based Kernel independent component analysis method 热失控过程监测研究进展：基于残差核独立分量分析方法的探索

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-16 DOI: 10.1016/j.compchemeng.2025.109172

Simin Li , Shuang-hua Yang , Yi Cao , Xiaoping Jiang , Chenchen Zhou

{"title":"Advancements in thermal runaway process monitoring: Exploring a novel residual dissimilarity-based Kernel independent component analysis method","authors":"Simin Li , Shuang-hua Yang , Yi Cao , Xiaoping Jiang , Chenchen Zhou","doi":"10.1016/j.compchemeng.2025.109172","DOIUrl":"10.1016/j.compchemeng.2025.109172","url":null,"abstract":"<div><div>Thermal runaway faults typically develop gradually within complex systems at a relatively low rate, often remaining imperceptible during their initial phases. If not detected by adequate monitoring systems, these faults may go unnoticed until their consequences escalate to a critical level, potentially resulting in significant system degradation or failure. To address the limitations of traditional monitoring methods, this paper introduces a novel non-linear dynamic and non-Gaussian fault detection approach, termed residual dissimilarity-based kernel independent component analysis (RDKICA). RDKICA employs canonical variate dissimilarity analysis to construct both a state space and a residual space, effectively reducing dimensionality while preserving essential features for fault identification. In these spaces, state dissimilarity captures small drifts in linear components, whereas residual dissimilarity captures small drifts in nonlinear components. Kernel independent components are then extracted from the residual dissimilarity to effectively characterize small drifts in nonlinear components and account for non-Gaussian noise. The efficacy of the proposed algorithm is demonstrated through a comprehensive case study of a thermal runaway benchmark, complemented by an ablation study. The results showcase the superior detection performance of RDKICA in comparison to existing algorithms.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109172"},"PeriodicalIF":3.9,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and optimization of circular economy networks—A case study of PET 循环经济网络的设计与优化——以PET为例

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-14 DOI: 10.1016/j.compchemeng.2025.109164

Abdulhakeem Ahmed, Akhil Nair, Ana Ines. Torres

{"title":"Design and optimization of circular economy networks—A case study of PET","authors":"Abdulhakeem Ahmed, Akhil Nair, Ana Ines. Torres","doi":"10.1016/j.compchemeng.2025.109164","DOIUrl":"10.1016/j.compchemeng.2025.109164","url":null,"abstract":"<div><div>Circular design is a potential means of achieving holistic sustainability. However, doing so requires systematic solution approaches to ensure proper design, evaluation, and implementation. This work proposes a generalized optimization framework for designing and optimizing circular economy (CE) networks under multi-criteria decision-making. We apply the proposed framework to a case study of the polyethylene terephthalate (PET) supply chain, considering various waste valorization pathways. A holistic process superstructure is defined and solved as a mixed integer linear program (MILP) in Pyomo. The optimized objective functions include total annualized cost (TAC), greenhouse gas emissions (GHG), and virgin material consumption. A Pareto analysis serves to elucidate trade-offs between competing objectives. Results show that designing for circularity at inception is favorable over linear network design. Trade-offs are significant between cost and emissions and cost and consumption. Furthermore, chemical and mechanical recycling combined proved to be a dominant strategy for all objectives with high tolerance to cost uncertainty, but lower tolerance to yield uncertainty.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109164"},"PeriodicalIF":3.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid semi-supervised fault detection framework under limited high-confidence data scenarios 有限高置信度数据场景下的混合半监督故障检测框架

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-14 DOI: 10.1016/j.compchemeng.2025.109186

Selorme Agbleze , Lawrence J. Shadle , Fernando V. Lima

{"title":"Hybrid semi-supervised fault detection framework under limited high-confidence data scenarios","authors":"Selorme Agbleze , Lawrence J. Shadle , Fernando V. Lima","doi":"10.1016/j.compchemeng.2025.109186","DOIUrl":"10.1016/j.compchemeng.2025.109186","url":null,"abstract":"<div><div>In the broad field of fault detection, approaches utilizing process conditions are established for systems with adequate datasets. However, systems including recently commissioned and novel processes have limited datasets available for model-based fault detection. Moreover, these systems have far greater proportions of normal operating data than adequate fault examples due to the time for which they have been operated. In this work, a combined hybrid framework for fault detection is developed that enables augmentation of the limited dataset available with HAZOP data, allowing for the utilization of both human expert knowledge and generated pseudo-process data. Additionally, the generation of artificial data is performed for reducing false positives in adversarial training. A semi-supervised distance variant of center loss is used to improve the consistency of deep feature activations from paired and unpaired data. A comparison between the proposed approach and an approach utilizing only process data in the limited data case is presented. Overall, the proposed approach shows 4.1 % and 8.8 % improvements in average detection rate when compared to the state-of-the-art supervised method for the Tennessee Eastman process and subcritical coal-fired power plant case studies, respectively, enabling the use of unlabeled data to supplement labeled process data for fault detection.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"200 ","pages":"Article 109186"},"PeriodicalIF":3.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144115693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Encrypted machine learning-based model predictive control architectures for nonlinear systems 基于加密机器学习的非线性系统模型预测控制体系结构

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-05-13 DOI: 10.1016/j.compchemeng.2025.109166

Arthur Khodaverdian , Guoquan Wu , Zhe Wu , Panagiotis D. Christofides

引用次数: 0