Computers & Chemical Engineering最新文献

The bullwhip effect, market competition and standard deviation ratio in two parallel supply chains 两条平行供应链中的牛鞭效应、市场竞争和标准偏差率

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-12 DOI: 10.1016/j.compchemeng.2024.108916

Xuluo Yin, Wenting Tang

引用次数: 0

CADET-Julia: Efficient and versatile, open-source simulator for batch chromatography in Julia CADET-Julia：高效、通用、开源的 Julia 批次色谱模拟器

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-12 DOI: 10.1016/j.compchemeng.2024.108913

Jesper Frandsen , Jan Michael Breuer , Johannes Schmölder , Jakob Kjøbsted Huusom , Krist V. Gernaey , Jens Abildskov , Eric von Lieres

{"title":"CADET-Julia: Efficient and versatile, open-source simulator for batch chromatography in Julia","authors":"Jesper Frandsen , Jan Michael Breuer , Johannes Schmölder , Jakob Kjøbsted Huusom , Krist V. Gernaey , Jens Abildskov , Eric von Lieres","doi":"10.1016/j.compchemeng.2024.108913","DOIUrl":"10.1016/j.compchemeng.2024.108913","url":null,"abstract":"<div><div>This study introduces CADET-Julia, an open-source, versatile and fast chromatography solver implemented in the Julia programming language. The software offers a platform for rapid prototyping and numerical refinement for a range of chromatography models, including the general rate model (GRM). The interstitial column mass balance was spatially discretized using a strong-form discontinuous Galerkin spectral element method (DGSEM) whereas a generalized spatial Galerkin spectral method (GSM) was applied for the particle mass balance. Three different benchmarks showcased the computational efficiency of CADET-Julia: A baseline benchmark was established by comparing the Julia implementation to a C++ implementation that employed the same mathematical methods and time integrator (CADET-DG). Various Julia time integrators were tested, and with the best-performing settings, the Julia implementation was benchmarked against CADET-DG and a finite volume (FV) based implementation in C++ (CADET-FV). Overall, Julia implementations performed better than C++ implementations and Galerkin methods were generally superior to finite volumes.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108913"},"PeriodicalIF":3.9,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663980","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

Model-based real-time optimization in continuous pharmaceutical manufacturing 基于模型的连续制药实时优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-09 DOI: 10.1016/j.compchemeng.2024.108915

Hazem Damiri , Martin Steinberger , Lisa Kuchler , Atabak Azimi , Stefano Martinuzzi , Peter Sagmeister , Jason D. Williams , Stefan Koch , Markus Tranninger , Jakob Rehrl , Selma Celikovic , Stephan Sacher , C. Oliver Kappe , Martin Horn

引用次数: 0

Computer aided formulation design based on molecular dynamics simulation: Detergents with fragrance 基于分子动力学模拟的计算机辅助配方设计：含香料的洗涤剂

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-09 DOI: 10.1016/j.compchemeng.2024.108919

Yan Qi , Lifeng Zhao , Haiqiu Tang , Lei Zhang , Rafiqul Gani

{"title":"Computer aided formulation design based on molecular dynamics simulation: Detergents with fragrance","authors":"Yan Qi , Lifeng Zhao , Haiqiu Tang , Lei Zhang , Rafiqul Gani","doi":"10.1016/j.compchemeng.2024.108919","DOIUrl":"10.1016/j.compchemeng.2024.108919","url":null,"abstract":"<div><div>Computer-aided formulation design is a methodology that utilizes domain knowledge and selected methods and tools suitable for computer-based applications to assist in formulation (product) design. In this paper, molecular dynamics simulation and Bayesian neural network algorithms are combined with well-known engineering models to help accelerate the development and optimization of formulation-based detergent products with a view to improve product quality and performance. In particular, the mechanism of the behavior of polymers (an active ingredient in the product) to improve the product quality in terms of the fragrance and its residence time is highlighted. Results from molecular dynamic simulation applied to study the molecular interaction mechanism show that the polymers have an attraction effect with fragrance molecules and could adsorb more to make them to stay on the surface of clothes. In addition, the polymer attenuates the diffusion of the fragrance molecules, lengthening the entire process of fragrance diffusion, which is the essence of the ability of the polymer to slow down the release of the fragrance. A Quantitative Structure-Property Relationship (QSPR) model between component proportions and fragrance diffusion is established through Bayesian Neural Network (BNN) and the product formulation is optimized based on this model. Keeping polymer and perfume ingredients unchanged, the surfactant amounts are optimized to provide improved product quality.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108919"},"PeriodicalIF":3.9,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663975","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

Risk-averse supply chain management via robust reinforcement learning 通过稳健强化学习规避风险的供应链管理

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-06 DOI: 10.1016/j.compchemeng.2024.108912

Jing Wang , Christopher L.E. Swartz , Kai Huang

{"title":"Risk-averse supply chain management via robust reinforcement learning","authors":"Jing Wang , Christopher L.E. Swartz , Kai Huang","doi":"10.1016/j.compchemeng.2024.108912","DOIUrl":"10.1016/j.compchemeng.2024.108912","url":null,"abstract":"<div><div>Classical reinforcement learning (RL) may suffer performance degradation when the environment deviates from training conditions, limiting its application in risk-averse supply chain management. This work explores using robust RL in supply chain operations to hedge against environment inconsistencies and changes. Two robust RL algorithms, <span><math><mover><mrow><mi>Q</mi></mrow><mrow><mo>ˆ</mo></mrow></mover></math></span>-learning and <span><math><mi>β</mi></math></span>-pessimistic <span><math><mi>Q</mi></math></span>-learning, are examined against conventional <span><math><mi>Q</mi></math></span>-learning and a baseline order-up-to inventory policy. Furthermore, this work extends RL applications from forward to closed-loop supply chains. Two case studies are conducted using a supply chain simulator developed with agent-based modeling. The results show that <span><math><mi>Q</mi></math></span>-learning can outperform the baseline policy under normal conditions, but notably degrades under environment deviations. By comparison, the robust RL models tend to make more conservative inventory decisions to avoid large shortage penalties. Specifically, fine-tuned <span><math><mi>β</mi></math></span>-pessimistic <span><math><mi>Q</mi></math></span>-learning can achieve good performance under normal conditions and maintain robustness against moderate environment inconsistencies, making it suitable for risk-averse decision-making.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108912"},"PeriodicalIF":3.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663977","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

Jaynes machine: The universal microstructure of deep neural networks 杰恩斯机器深度神经网络的通用微观结构

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-04 DOI: 10.1016/j.compchemeng.2024.108908

Venkat Venkatasubramanian , N. Sanjeevrajan , Manasi Khandekar , Abhishek Sivaram , Collin Szczepanski

{"title":"Jaynes machine: The universal microstructure of deep neural networks","authors":"Venkat Venkatasubramanian , N. Sanjeevrajan , Manasi Khandekar , Abhishek Sivaram , Collin Szczepanski","doi":"10.1016/j.compchemeng.2024.108908","DOIUrl":"10.1016/j.compchemeng.2024.108908","url":null,"abstract":"<div><div>Despite the recent stunning progress in large-scale deep neural network applications, our understanding of their microstructure, ‘energy’ functions, and optimal design remains incomplete. Here, we present a new game-theoretic framework, called statistical teleodynamics, that reveals important insights into these key properties. The optimally robust design of such networks inherently involves computational benefit–cost trade-offs that physics-inspired models do not adequately capture. These trade-offs occur as neurons and connections compete to increase their effective utilities under resource constraints during training. In a fully trained network, this results in a state of arbitrage equilibrium, where all neurons in a given layer have the same effective utility, and all connections to a given layer have the same effective utility. The equilibrium is characterized by the emergence of two lognormal distributions of connection weights and neuronal output as the universal microstructure of large deep neural networks. We call such a network the Jaynes Machine. Our theoretical predictions are shown to be supported by empirical data from seven large-scale deep neural networks. We also show that the Hopfield network and the Boltzmann Machine are the same special case of the Jaynes Machine.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108908"},"PeriodicalIF":3.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663974","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

Physics-informed neural networks for state reconstruction of hydrogen energy transportation systems 用于氢能运输系统状态重构的物理信息神经网络

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-11-02 DOI: 10.1016/j.compchemeng.2024.108898

Lu Zhang , Junyao Xie , Qingqing Xu , Charles Robert Koch , Stevan Dubljevic

{"title":"Physics-informed neural networks for state reconstruction of hydrogen energy transportation systems","authors":"Lu Zhang , Junyao Xie , Qingqing Xu , Charles Robert Koch , Stevan Dubljevic","doi":"10.1016/j.compchemeng.2024.108898","DOIUrl":"10.1016/j.compchemeng.2024.108898","url":null,"abstract":"<div><div>Hydrogen energy, as one of the promising future energy forms, has attracted attentions from academia and industry due to its cost-effective and low-carbon nature. Compared with oil and gas transportation, its transportation is more challenging due to its complex blending mechanism. Inferring the internal states during transportation is essential for condition monitoring and operational planning of hydrogen-blending natural gas pipelines. Considering the nonlinear spatiotemporal dynamics and limited sensor information, reconstructing infinite-dimensional pipeline state variables is challenging. This paper addresses the state reconstruction of nonlinear infinite-dimensional hydrogen-blending natural gas pipeline systems using physics-informed neural networks. The proposed design combines neural networks with nonlinear partial differential equations that govern the pipeline systems. With limited measurements, the trained model is capable of predicting the state evolutions of pressure, flow, and mass flux ratio of hydrogen during transient transportation at any location. The proposed design is demonstrated through detailed numerical simulations and sensitivity analyses.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108898"},"PeriodicalIF":3.9,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663973","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

Multiproduct pipeline scheduling: A comprehensive bibliometric analysis and a systematic literature review 多产品流水线调度：综合文献计量分析和系统文献综述

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2024-10-28 DOI: 10.1016/j.compchemeng.2024.108911

Mouad Sidki , Nikolay Tchernev , Pierre Féniès , Libo Ren , Selwa Elfirdoussi

{"title":"Multiproduct pipeline scheduling: A comprehensive bibliometric analysis and a systematic literature review","authors":"Mouad Sidki , Nikolay Tchernev , Pierre Féniès , Libo Ren , Selwa Elfirdoussi","doi":"10.1016/j.compchemeng.2024.108911","DOIUrl":"10.1016/j.compchemeng.2024.108911","url":null,"abstract":"<div><div>Multiproduct pipeline scheduling problem has garnered increasing attention over the past few decades due to potential economic savings and increased operational efficiency. This paper presents a comprehensive bibliometric analysis and systematic literature review on multiproduct pipeline scheduling, focusing on works published from 2000 to 2023. Using three reputable bibliographic databases, the research gathers and examines metadata to provide an understanding of research evolution, key themes, relevant authors, and journals, as well as the country-wise distribution of authors’ affiliations. The selected articles were refined for a systematic literature review. A research framework was developed to classify the literature into common themes for easier navigation. The classification criteria include industry sectors, pipeline systems’ topologies, scheduling accuracy, parameter certainty, operation constraints, time and volume representations, solution strategies, and objectives. The results provide a comprehensive understanding of the field's current state and highlight promising directions for future research.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"192 ","pages":"Article 108911"},"PeriodicalIF":3.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663978","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

Robustness in optimal design of Eco-Industrial Parks under the lens of two-stage stochastic optimization 两阶段随机优化视角下生态工业园区优化设计的稳健性

IF 4.3 2区工程技术

Computers & Chemical Engineering Pub Date : 2023-09-09 DOI: 10.1016/j.compchemeng.2023.108399

Gianfranco Liberona , Alessandro Di Pretoro , Stéphane Negny , Ludovic Montastruc , David Salas

引用次数: 1

Analytical solutions for the modeling, optimization, and control of microwave-assisted freeze drying 微波辅助冷冻干燥的建模、优化和控制的解析解

IF 4.3 2区工程技术

Computers & Chemical Engineering Pub Date : 2023-09-01 DOI: 10.1016/j.compchemeng.2023.108318

Prakitr Srisuma , George Barbastathis , Richard D. Braatz

引用次数: 2