Computers & Chemical Engineering最新文献_第10页

Designing a centralized storage hydrogen supply chain network with multi-period and bi-objective optimization 利用多周期和双目标优化设计集中式储氢供应链网络

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-08 DOI: 10.1016/j.compchemeng.2024.108820

Linfei Feng, Hervé Manier, Marie-Ange Maniera

引用次数: 0

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning 利用强化学习开发增强和替代传统过程控制的算法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-08 DOI: 10.1016/j.compchemeng.2024.108826

Daniel Beahr , Debangsu Bhattacharyya , Douglas A. Allan , Stephen E. Zitney

引用次数: 0

End-to-end reinforcement learning of Koopman models for economic nonlinear model predictive control 用于经济非线性模型预测控制的库普曼模型端到端强化学习

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-05 DOI: 10.1016/j.compchemeng.2024.108824

Daniel Mayfrank , Alexander Mitsos , Manuel Dahmen

{"title":"End-to-end reinforcement learning of Koopman models for economic nonlinear model predictive control","authors":"Daniel Mayfrank , Alexander Mitsos , Manuel Dahmen","doi":"10.1016/j.compchemeng.2024.108824","DOIUrl":"10.1016/j.compchemeng.2024.108824","url":null,"abstract":"<div><p>(Economic) nonlinear model predictive control ((e)NMPC) requires dynamic models that are sufficiently accurate and computationally tractable. Data-driven surrogate models for mechanistic models can reduce the computational burden of (e)NMPC; however, such models are typically trained by system identification for maximum prediction accuracy on simulation samples and perform suboptimally in (e)NMPC. We present a method for end-to-end reinforcement learning of Koopman surrogate models for optimal performance as part of (e)NMPC. We apply our method to two applications derived from an established nonlinear continuous stirred-tank reactor model. The controller performance is compared to that of (e)NMPCs utilizing models trained using system identification, and model-free neural network controllers trained using reinforcement learning. We show that the end-to-end trained models outperform those trained using system identification in (e)NMPC, and that, in contrast to the neural network controllers, the (e)NMPC controllers can react to changes in the control setting without retraining.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"190 ","pages":"Article 108824"},"PeriodicalIF":3.9,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424002424/pdfft?md5=b8942e7813913b046ed7ab32d3f23e7e&pid=1-s2.0-S0098135424002424-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141938877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategic and tactical planning model for the design of perishable product supply chain network in Ethiopia 埃塞俄比亚易腐产品供应链网络设计的战略和战术规划模型

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-03 DOI: 10.1016/j.compchemeng.2024.108814

Asnakech Biza , Ludovic Montastruc , Stéphane Negny , Shimelis Admassu

{"title":"Strategic and tactical planning model for the design of perishable product supply chain network in Ethiopia","authors":"Asnakech Biza , Ludovic Montastruc , Stéphane Negny , Shimelis Admassu","doi":"10.1016/j.compchemeng.2024.108814","DOIUrl":"10.1016/j.compchemeng.2024.108814","url":null,"abstract":"<div><p>This article discusses the challenges associated with ensuring food security for a growing global population and emphasizes the critical role of the Agri Fresh Food Supply Chain in addressing these challenges such as mitigating food insecurity and reducing wastes. The economic repercussions of inefficiencies in perishable supply chains impact businesses' profit margins and consumers' access to essential goods. The focus is on the effective management of the complex perishable product supply chains, considering the economic significance of this sector and the need for advanced strategies to optimize the flow of time-sensitive products. The study discusses the limited consideration of product intrinsic characteristics in strategic and tactical planning decisions. The research aims to contribute to supply chain management by proposing a mathematical model (multi echelon, multi product, and multi period) for designing a perishable product supply chain network, considering factors like perishability, quantity discount policy, souring strategies and business continuity. The study explores the impact of these factors on the Agri Fresh Food Supply Chain design and its overall performances. Although the proposed model is designed to be applicable to any country or region, but its capabilities are shown through a real case study in Ethiopia. Results show that a agri-food supply chain design model that considers the intrinsic characteristics of the product, processing capacity level, and quantity discount leads to improved configurations of the food supply chain regardless of adding the associated cost.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"190 ","pages":"Article 108814"},"PeriodicalIF":3.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998015","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

Zonewise surrogate-based optimization of box-constrained systems 基于区域代用的箱形受限系统优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-03 DOI: 10.1016/j.compchemeng.2024.108821

Srikar Venkataraman Srinivas, Iftekhar A. Karimi

引用次数: 0

Data-driven parameterization and development of mechanistic cell cultivation models in monoclonal antibody production processes: Shifts in cell metabolic behavior 单克隆抗体生产过程中数据驱动的参数化和机理细胞培养模型的开发：细胞代谢行为的转变

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-08-02 DOI: 10.1016/j.compchemeng.2024.108822

Kozue Okamura, Kota Oishi, Sara Badr, Akira Yamada, Hirokazu Sugiyama

{"title":"Data-driven parameterization and development of mechanistic cell cultivation models in monoclonal antibody production processes: Shifts in cell metabolic behavior","authors":"Kozue Okamura, Kota Oishi, Sara Badr, Akira Yamada, Hirokazu Sugiyama","doi":"10.1016/j.compchemeng.2024.108822","DOIUrl":"10.1016/j.compchemeng.2024.108822","url":null,"abstract":"<div><p>Representative kinetic models to describe monoclonal antibody (mAb) production processes are needed for effective process design. The development of mechanistic models can be impeded by the lack of complete understanding of changes in cell metabolism, e.g., lactate metabolic shifts. State-estimation-based methods were applied to assess the fit of available kinetic models over experimental runs. The results indicated the regions where model parameter updates were required. Different clustering strategies were applied to isolate the variations in the culture environment and correlate them to the lactate shifts. Alternative formulations for the specific lactate consumption/production term were provided for each identified phase. Two case studies are presented for pilot-scale data in different reactor types. The results show the improvement in modeling accuracy and highlight the role of oxygen and nutrient levels on the shifts. The approach showcases the use of data-driven insights to effectively utilize limited experimental data to develop robust mechanistic models.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"191 ","pages":"Article 108822"},"PeriodicalIF":3.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424002400/pdfft?md5=7997adf5ee2030eb9c80b9ddacea1b76&pid=1-s2.0-S0098135424002400-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Novel terminal region computation method for quasi-infinite horizon NMPC 准无限视界 NMPC 的新型终端区域计算方法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-07-30 DOI: 10.1016/j.compchemeng.2024.108819

Guilherme Augusto Silva de Souza, Darci Odloak

引用次数: 0

Operating condition design with a Bayesian optimization approach for pharmaceutical intermediate batch concentration 采用贝叶斯优化方法设计制药中间批浓度的操作条件

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-07-28 DOI: 10.1016/j.compchemeng.2024.108813

Chong Liu , Chengyu Han , Chenxi Gu , Wei Sun , Jingde Wang , Xun Tang

引用次数: 0

Recurrent neural network-based prediction of O-GlcNAcylation sites in mammalian proteins 基于循环神经网络预测哺乳动物蛋白质中的 O-GlcNAcylation 位点

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-07-26 DOI: 10.1016/j.compchemeng.2024.108818

Pedro Seber, Richard D. Braatz

{"title":"Recurrent neural network-based prediction of O-GlcNAcylation sites in mammalian proteins","authors":"Pedro Seber, Richard D. Braatz","doi":"10.1016/j.compchemeng.2024.108818","DOIUrl":"10.1016/j.compchemeng.2024.108818","url":null,"abstract":"<div><p>O-GlcNAcylation has the potential to be an important target for therapeutics, but a motif or an algorithm to reliably predict O-GlcNAcylation sites is not available. Current predictive models are insufficient as they fail to generalize, and many are no longer available. This article constructs recurrent neural network models to predict O-GlcNAcylation sites based on protein sequences. Different datasets are evaluated separately and assessed in terms of strengths and issues. Within a given dataset, results are robust to changes in cross-validation and test data as determined by nested validation. The best model achieves an F<span><math><msub><mrow></mrow><mrow><mn>1</mn></mrow></msub></math></span> score of 36% (more than 3.5-fold greater than the previous best model) and a Matthews Correlation Coefficient of 35% (more than 4.5-fold greater than the previous best model), and, for the F<span><math><msub><mrow></mrow><mrow><mn>1</mn></mrow></msub></math></span> score, 7.6-fold higher than when not using any model. Shapley values are used to interpret the model’s predictions and provide biological insight into O-GlcNAcylation.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108818"},"PeriodicalIF":3.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963120","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

Toward understandable semi-supervised learning fault diagnosis of chemical processes based on long short-term memory ladder autoencoder (LSTM-LAE) and self-attention (SA) 基于长短期记忆梯形自动编码器（LSTM-LAE）和自我注意（SA）的化学过程故障诊断的可理解半监督学习

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-07-26 DOI: 10.1016/j.compchemeng.2024.108817

Yang Jing , Xiaolong Ge , Botan Liu

{"title":"Toward understandable semi-supervised learning fault diagnosis of chemical processes based on long short-term memory ladder autoencoder (LSTM-LAE) and self-attention (SA)","authors":"Yang Jing , Xiaolong Ge , Botan Liu","doi":"10.1016/j.compchemeng.2024.108817","DOIUrl":"10.1016/j.compchemeng.2024.108817","url":null,"abstract":"<div><p>Fault diagnosis and localization play vital role in chemical process monitoring. Finding the root cause of fault accurately and timely is the key to avoid serious accidents and ensure process safety. Unfortunately, most deep learning-based models only involves in predicting fault state and interpretability is still not fully explored. Besides, lack of labeled samples in practical situations makes supervised learning difficult to implement. To circumvent the obstacle, semi-supervised learning based on long short-term memory ladder autoencoder is combined with self-attention mechanism, which is intended to establish interpretable model by explicitly clarifying the corresponding relationship between abnormal variables and faults. Using Tennessee Eastman process and practical high-purity carbonate production process as benchmark, fault diagnosis and identification performance of proposed LSTM-LAE-SA is validated, and interpretability analysis is performed to demonstrate its capabilities in abnormal variable locations. The developed understandable model could improve operator's trust and industrial application in fault diagnosis system.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108817"},"PeriodicalIF":3.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950332","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