Computers & Chemical Engineering最新文献_第9页

A multistage stochastic programming approach for renewable ammonia supply chain network design 可再生氨供应链网络设计的多阶段随机规划方法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-14 DOI: 10.1016/j.compchemeng.2025.109443

Ilias Mitrai , Matthew J. Palys , Prodromos Daoutidis

{"title":"A multistage stochastic programming approach for renewable ammonia supply chain network design","authors":"Ilias Mitrai , Matthew J. Palys , Prodromos Daoutidis","doi":"10.1016/j.compchemeng.2025.109443","DOIUrl":"10.1016/j.compchemeng.2025.109443","url":null,"abstract":"<div><div>This paper considers the effect of ammonia market price uncertainty across multiple years on the deployment of renewable ammonia production facilities in existing ammonia supply chain networks. We use an ammonia supply chain transition optimization model to investigate the effect of this uncertainty. Specifically, we formulate a multistage stochastic programming problem to determine the optimal investment policy for new renewable ammonia production over a multi-year transition horizon such that ammonia demand is satisfied and the total supply chain cost is minimized. The proposed approach is used to analyze the transition of the ammonia supply chain for the state of Minnesota. The results show that the trajectory of the price over time determines the degree to which renewable ammonia production facilities are adopted. In a broad sense, considering the possibility of higher-than-average conventional ammonia market prices through a multistage stochastic problem leads to a wider adoption of renewable production relative to a deterministic problem, which only considers the average market price in an economically optimal supply chain transition. Comparison with a two-stage stochastic programming approach from prior work shows that accounting for price uncertainty across time leads to 4.4% reduction in the cost. For a full transition to renewable production, the multistage stochastic framework results, on average, in a slightly slower transition than the deterministic problem due to scenarios which include lower-than-average market prices.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109443"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145322885","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

Special issue editorial: Selected contributions from foundations of computer aided process design (FOCAPD) 2024 特刊社论：计算机辅助工艺设计基金会（FOCAPD） 2024

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-23 DOI: 10.1016/j.compchemeng.2025.109467

Matt Bassett , Thomas A. Adams II , Selen Cremaschi , Monica Zanfir

引用次数: 0

Interpretable online scheduling for chemical batch plants with attention augmented reinforcement learning agents 基于注意力增强强化学习代理的化工批处理厂可解释在线调度

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-23 DOI: 10.1016/j.compchemeng.2025.109469

Daniel Rangel-Martinez, Luis A. Ricardez-Sandoval

{"title":"Interpretable online scheduling for chemical batch plants with attention augmented reinforcement learning agents","authors":"Daniel Rangel-Martinez, Luis A. Ricardez-Sandoval","doi":"10.1016/j.compchemeng.2025.109469","DOIUrl":"10.1016/j.compchemeng.2025.109469","url":null,"abstract":"<div><div>A method for training Deep Reinforcement Learning agents with self-attention modules is presented to address online scheduling decisions in batch chemical plants. The agent is designed to generate multiple decisions at the same time in a partially observable environment; these decisions can be either discrete or continuous. The use of self-attention modules is justified by their increasing popularity in Natural Language Processing (NLP) methods over Recurrent Neural Networks (RNNs). This method leverages the attention-based models by using the attention matrices generated by the agent to produce a numeric interpretation of the agent’s logic. Additionally, a second attention matrix with fixed parameters was embedded in the architecture to define the relevance of each part of the environment. The information from these matrices is demonstrated to be useful for interpreting the relevance of key aspects in the environment and to track the change of the agent’s focal points in non-stationary environments. The methodology is tested using two batch chemical plant case studies, demonstrating the advantages and limitations in comparison to an agent built with RNNs. The interpretability of the decisions and the logic of the agent showed an option to approach the so called black-box characteristic of data-driven models.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109469"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145413899","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

Novel sufficient conditions for the local stability of non-isothermal continuous homogeneous reaction systems 非等温连续均相反应体系局部稳定性的新充分条件

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-22 DOI: 10.1016/j.compchemeng.2025.109462

N. Ha Hoang , D. Bonvin

{"title":"Novel sufficient conditions for the local stability of non-isothermal continuous homogeneous reaction systems","authors":"N. Ha Hoang , D. Bonvin","doi":"10.1016/j.compchemeng.2025.109462","DOIUrl":"10.1016/j.compchemeng.2025.109462","url":null,"abstract":"<div><div>This note investigates the stability of non-isothermal continuous homogeneous reaction systems involving <span><math><mi>S</mi></math></span> species, <span><math><mi>R</mi></math></span> reactions, <span><math><mi>p</mi></math></span> inlet streams, and one outlet stream. The analysis, which is based on Lyapunov’s indirect method, is greatly simplified by transforming the reactor model of <span><math><mrow><mi>S</mi><mo>+</mo><mn>1</mn></mrow></math></span> dynamic equations obtained from material and energy balances into <span><math><mrow><mi>R</mi><mo>+</mo><mn>1</mn></mrow></math></span> dynamic equations expressed in terms of vessel extents of reaction and heat exchange. By linearizing this reduced model about the equilibrium point of interest, stability conditions can be established by computing the eigenvalues of a reduced system matrix. Furthermore, for the case of a single reaction of any order that obeys mass-action kinetics, novel sufficient stability conditions have been developed, which do not require computing eigenvalues. These stability conditions are proven to always hold for endothermic reactions using thermodynamical arguments. In addition, it is shown that the proposed stability conditions can be relaxed in the case of exothermic reactions depending on the value of heat-transfer coefficient. Two CSTR examples, with steady-state uniqueness and multiplicity behavior respectively, are used to illustrate the theoretical developments.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109462"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145413889","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 correction symbol Granger causality approach to root cause diagnosis of non-stationary industrial processes 非平稳工业过程根本原因诊断的校正符号格兰杰因果关系方法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-11-12 DOI: 10.1016/j.compchemeng.2025.109479

Rui Chen , Husnain Ali , Shu Liang , Yuanqiang Zhou , Furong Gao

{"title":"A correction symbol Granger causality approach to root cause diagnosis of non-stationary industrial processes","authors":"Rui Chen , Husnain Ali , Shu Liang , Yuanqiang Zhou , Furong Gao","doi":"10.1016/j.compchemeng.2025.109479","DOIUrl":"10.1016/j.compchemeng.2025.109479","url":null,"abstract":"<div><div>Dealing with non-stationary characteristics and revealing the symbol properties of causalities remain obstacles to performing fault root cause diagnosis (RCD) in industrial processes. Existing methods overlook these problems, leading to reduced RCD accuracy and a limited understanding of the dynamic characteristics of fault propagation. To address the above-mentioned problems, this paper proposes a correction symbol Granger causality (CSGC) approach. Firstly, to infer significant Granger causality (GC) from non-stationary processes, the cointegration relationships among variables are utilized to differentiate them and construct an error correction term, enabling the regression model to capture the long-term dependencies among fault variables better. Secondly, the self-explaining neural network is employed to further reveal the symbol properties of the fault variable from the fitted generalized coefficient matrix. Furthermore, two causal criteria of CSGC are established to test the significance level of GC and eliminate bidirectional causalities. Based on CSGC, a causal graph construction strategy containing information on symbol properties is developed for fault RCD and analysis of fault propagation paths. The analysis results of the numerical simulation system indicate that the various metrics of CSGC perform well, demonstrating its potential for accurate RCD and in-depth fault propagation analysis (Accuracy: 0.96, Sensitivity: 1.00, Specificity: 0.95, F1 score: 0.91). Finally, the effectiveness of RCD is validated through its application to the numerical simulation, the Tennessee Eastman process (TEP) and a real-world motor soft-foot fault.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109479"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145517220","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

Metrics for evaluating stochastic outputs in machine learning models: Addressing accuracy and uncertainty 评估机器学习模型中随机输出的度量：处理准确性和不确定性

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-29 DOI: 10.1016/j.compchemeng.2025.109474

Yushi Deng, Mario R. Eden, Selen Cremaschi

{"title":"Metrics for evaluating stochastic outputs in machine learning models: Addressing accuracy and uncertainty","authors":"Yushi Deng, Mario R. Eden, Selen Cremaschi","doi":"10.1016/j.compchemeng.2025.109474","DOIUrl":"10.1016/j.compchemeng.2025.109474","url":null,"abstract":"<div><div>Chemical processes are modeled and designed considering uncertainties in system parameters, operating conditions, and environmental factors. Models with stochastic outputs are commonly employed to make decisions in chemical engineering designs. Evaluating models with stochastic outputs requires assessing both prediction accuracy and precision. The area metric measures the overall mismatch between the prediction and observation, but does not provide a metric to assess precision and accuracy separately. Previously, we introduced uncertainty width, which decomposes the area metric into precision and bias components for model outputs whose distributions are symmetric. In this work, we investigate the applicability and effectiveness of the uncertainty width to asymmetric output distributions through a series of computational experiments. We then further study the application of the uncertainty width to evaluate the performance of eight distinct machine learning techniques, each integrated within a hybrid modeling framework, for predicting liquid entrainment with its uncertainty across three different flow orientations. The results of the computational experiments suggest that the uncertainty width is effective for asymmetric cases, especially when bias is small. Further studies are needed to understand the effectiveness of uncertainty width in cases of large bias and extreme asymmetry. The results for the hybrid models support the effectiveness of uncertainty width. They reveal that the Gaussian Process model has the best overall prediction accuracy. The remaining models exhibit diverse trade-offs between precision and accuracy, indicating that model selection should be guided by the specific accuracy and precision requirements for the application.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109474"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145517221","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

Pipeline pressure drop modeling and compression power minimization for nonideal, compressible, gas mixture flows with application to pipeline flow of natural gas-hydrogen blends 非理想可压缩气体混合流的管道压降建模和压缩功率最小化及其在天然气-氢混合物管道流中的应用

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-16 DOI: 10.1016/j.compchemeng.2025.109455

Jeremy Conner, Vasilios I. Manousiouthakis

{"title":"Pipeline pressure drop modeling and compression power minimization for nonideal, compressible, gas mixture flows with application to pipeline flow of natural gas-hydrogen blends","authors":"Jeremy Conner, Vasilios I. Manousiouthakis","doi":"10.1016/j.compchemeng.2025.109455","DOIUrl":"10.1016/j.compchemeng.2025.109455","url":null,"abstract":"<div><div>This work presents a novel, dimensionless model that results in a dimensionless algebraic equation that can be used to quantify the pressure drop associated with the steady state, isothermal flow through a straight, horizontal pipeline, of a compressible gas mixture whose thermodynamic behavior is described for comparison purposes by ideal gas (IG) and nonideal gas generic cubic (GC) equation of state (EOS) models. A solution strategy, that uses the aforementioned dimensionless algebraic equation, is then presented that quantifies the pipeline pressure drop for hydrogen containing mixtures. A novel power minimization formulation for pipeline gas compression is then presented, which utilizes the aforementioned dimensionless pipeline pressure drop model for a fluid with GCEOS thermodynamics. Several case studies are then presented to illustrate the pipeline pressure drop dependence on the hydrogen mole fraction of a binary, methane hydrogen mixture, and a natural gas hydrogen mixture with a real life natural gas composition containing eight species, and the optimum power of compression for a pipeline used to deliver constant power for various methane-hydrogen composition blends.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109455"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360334","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

Visual process monitoring of biomass conversion reactors using transfer learning and generative AI 基于迁移学习和生成式人工智能的生物质转化反应器视觉过程监测

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-23 DOI: 10.1016/j.compchemeng.2025.109464

Qiangqiang Mao , Boris Yip , Chuanhao Xu , Sagar Garg , Pengcheng Guo , Yankai Cao

{"title":"Visual process monitoring of biomass conversion reactors using transfer learning and generative AI","authors":"Qiangqiang Mao , Boris Yip , Chuanhao Xu , Sagar Garg , Pengcheng Guo , Yankai Cao","doi":"10.1016/j.compchemeng.2025.109464","DOIUrl":"10.1016/j.compchemeng.2025.109464","url":null,"abstract":"<div><div>Thermochemical reaction system, particularly in the form of small-scale, low-cost bioreactor, offers a promising solution for efficient biomass-to-bioproduct conversion. The bioreactor potentially revolutionizes biomass conversion and keep rural communities into the loop of biomass-based circular economy. However, its continuous operation remains a significant concern. A primary concern arises from the unexpected reaction condition, which is typically indicated by smoke emanating from the bioreactor. This expected issue can be resolved by minor adjustments to ensure proper reaction environment. In this regard, an automated visual process monitoring for smoke detection is crucial. This can be achieved by developing a convolutional neural network (CNN)-based smoke classifier. However, shuffled video-based smoke classification, where a model trained on video recordings from field experiments is applied to monitor new biomass reaction processes with unseen scenarios, poses great challenges due to limited number of field experiments, particularly given the diversity of field backgrounds. Considering the limited diversity issue, this study explore the potential of generative artificial intelligence (GenAI) to generate virtual training images with smoke and without smoke. With augmented training data, a tailored transfer learning strategy is applied to fine tune the CNN model for smoke detection. To assist field operators in understanding classifier decisions and correcting erroneous predictions, an explainable visual representation is provided by smoke localization heatmaps. The results show that the proposed method significantly improve smoke detection accuracy and prediction reliability, which is essential for the continuous operation of biomass conversion reactors and the success of decarbonization within biomass-based circular economy.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109464"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360336","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 grid-scale study of demand bidding by large industrial users 大型工业用户需求竞价的电网规模研究

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-14 DOI: 10.1016/j.compchemeng.2025.109442

Xin Tang , Cosmin G. Petra , Michael Baldea , Ross Baldick

{"title":"A grid-scale study of demand bidding by large industrial users","authors":"Xin Tang , Cosmin G. Petra , Michael Baldea , Ross Baldick","doi":"10.1016/j.compchemeng.2025.109442","DOIUrl":"10.1016/j.compchemeng.2025.109442","url":null,"abstract":"<div><div>A demand bidding mechanism for engaging large industrial electricity users in the operation of the power grid is presented. Demand bidding is formulated as an optimization problem based on a modified version of the alternating current optimal power flow problem, and can be interpreted as a tâtonnement process between the grid operator and electricity users. The work provides the first – to the authors’ knowledge – grid-scale case study of demand bidding, using a synthetic grid structure in the footprint of the grid of Texas. Results reveal that the demand bidding lowers overall power generation costs, but economic benefits plateau as the number of participants increases. Transmission line and transformer capacity constraints become the limiting factors, revealing that expanding and fortifying the transmission infrastructure is key to expanding demand-side participation. Demand bidding does not substantially alter the optimal operation of existing bidding entities when the number of bidders increases, thereby supporting existing bidders to stay in the system and encouraging new ones to join.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109442"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360248","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

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems 基于仿真设计的表后能源系统并行无导数优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-03 DOI: 10.1016/j.compchemeng.2025.109422

Gustavo Campos, Weslley da Silva Pereira, Roberto Vercellino, Juliane Mueller, Margaret Mann

{"title":"Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems","authors":"Gustavo Campos, Weslley da Silva Pereira, Roberto Vercellino, Juliane Mueller, Margaret Mann","doi":"10.1016/j.compchemeng.2025.109422","DOIUrl":"10.1016/j.compchemeng.2025.109422","url":null,"abstract":"<div><div>In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109422"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360249","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