Computers & Chemical Engineering最新文献_第10页

A computationally efficient policy optimization scheme in feedback iterative learning control for nonlinear batch process 非线性批处理反馈迭代学习控制中一种计算效率高的策略优化方案

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-21 DOI: 10.1016/j.compchemeng.2025.109005

Kaihua Gao , Jingyi Lu , Yuanqiang Zhou , Furong Gao

引用次数: 0

Machine learning-guided space-filling designs for high throughput liquid formulation development 机器学习引导的高通量液体配方开发的空间填充设计

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-18 DOI: 10.1016/j.compchemeng.2025.109007

Aniket Chitre , Daria Semochkina , David C. Woods , Alexei A. Lapkin

{"title":"Machine learning-guided space-filling designs for high throughput liquid formulation development","authors":"Aniket Chitre , Daria Semochkina , David C. Woods , Alexei A. Lapkin","doi":"10.1016/j.compchemeng.2025.109007","DOIUrl":"10.1016/j.compchemeng.2025.109007","url":null,"abstract":"<div><div>Liquid formulation design involves using a relatively limited experimental budget to search a high-dimensional space, owing to the combinatorial selection of ingredients and their concentrations from a larger subset of available ingredients. This work investigates alternative shampoo formulations. A space-filling design is desired for screening relatively unexplored formulation chemistries. One of the few computationally efficient solutions for this mixed nominal-continuous design of experiments problem is the adoption of maximum projection designs with quantitative and qualitative factors (MaxProQQ). However, such purely space-filling designs can select experiments in infeasible regions of the design space. Here, stable products are considered feasible. We develop and apply weighted-space filling designs, where predictive phase stability classifiers are trained for difficult-to-formulate (predominantly unstable) sub-systems, to guide these experiments to regions of feasibility, whilst simultaneously optimising for chemical diversity by building on MaxProQQ. This approach is extendable to other mixed-variable design problems, particularly those with sequential design objectives.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"195 ","pages":"Article 109007"},"PeriodicalIF":3.9,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143360858","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

Systematic design of pulse dosing to eradicate persister bacteria: The case of fluoroquinolones 脉冲给药根除顽固细菌的系统设计：以氟喹诺酮类药物为例

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-18 DOI: 10.1016/j.compchemeng.2025.109010

Garima Singh, Sayed Golam Mohiuddin, Sreyashi Ghosh, Jenet Narzary, Mehmet A. Orman, Michael Nikolaou

{"title":"Systematic design of pulse dosing to eradicate persister bacteria: The case of fluoroquinolones","authors":"Garima Singh, Sayed Golam Mohiuddin, Sreyashi Ghosh, Jenet Narzary, Mehmet A. Orman, Michael Nikolaou","doi":"10.1016/j.compchemeng.2025.109010","DOIUrl":"10.1016/j.compchemeng.2025.109010","url":null,"abstract":"<div><div>A small fraction of infectious bacteria use persistence as a strategy to survive exposure to antibiotics. Pulse dosing of antibiotics, if designed well, has long been considered a potentially effective strategy towards eradication of such bacterial pathogens. In a recent study, we developed a method to systematically design optimal pulse dosing regimens for rapid eradication of persisters with <span><math><mi>β</mi></math></span>-lactam antibiotics, and validated the effectiveness of that method experimentally. In this paper, we extend that method for fluoroquinolones. This is because, in contrast to <span><math><mi>β</mi></math></span>-lactams, fluoroquinolones impart different dynamic behavior on treated bacteria, by inducing persister formation and by triggering a non-negligible post-antibiotic effect. Pulse dosing designed according to the proposed method demonstrated rapid bacterial population reduction compared to constant dosing, underscoring the potential of optimal pulse dosing for efficient use of fluoroquinolone antibiotics. In addition, model fitting and parameter estimation also highlighted differences in persister mechanisms between fluoroquinolones and β-lactams. Overall, our study demonstrates that pulse dosing strategies can be effectively designed with the proposed method, using simple formulas and data derived from basic experiments.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"195 ","pages":"Article 109010"},"PeriodicalIF":3.9,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348530","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

Data-driven contextual robust optimization based on support vector clustering 基于支持向量聚类的数据驱动上下文鲁棒优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-17 DOI: 10.1016/j.compchemeng.2025.109004

Xianyu Li , Fenglian Dong , Zhiwei Wei , Chao Shang

{"title":"Data-driven contextual robust optimization based on support vector clustering","authors":"Xianyu Li , Fenglian Dong , Zhiwei Wei , Chao Shang","doi":"10.1016/j.compchemeng.2025.109004","DOIUrl":"10.1016/j.compchemeng.2025.109004","url":null,"abstract":"<div><div>Support vector clustering (SVC) is an effective data-driven method to construct uncertainty sets in robust optimization (RO). However, it cannot appropriately address varying uncertainty in a contextually uncertain environment. In this work, we propose a new contextual RO (CRO) scheme, where an efficient contextual uncertainty set called kNN-SVC is developed to capture the correlation between covariates and uncertainty. Using the k-nearest neighbors (kNN) to select a subset of historical observations, contextual information can be integrated into SVC uncertainty sets, thereby alleviating conservatism while inheriting merits of SVC such as polytopic representability and ease of manipulating robustness. Besides, using only a fraction of data samples ensures low computational costs. Numerical examples demonstrate the performance improvement of the proposed kNN-SVC uncertainty set over conventional sets without considering contextual information. An industrial case of gasoline blending shows the usefulness of the proposed approach in producing robust decisions against linearization errors in nonlinear blending.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"195 ","pages":"Article 109004"},"PeriodicalIF":3.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348529","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

Logic-Based Discrete-Steepest Descent: A solution method for process synthesis Generalized Disjunctive Programs 基于逻辑的离散最陡下降：过程综合广义析取规划的一种求解方法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-17 DOI: 10.1016/j.compchemeng.2024.108993

Daniel Ovalle , David A. Liñán , Albert Lee , Jorge M. Gómez , Luis Ricardez-Sandoval , Ignacio E. Grossmann , David E. Bernal Neira

{"title":"Logic-Based Discrete-Steepest Descent: A solution method for process synthesis Generalized Disjunctive Programs","authors":"Daniel Ovalle , David A. Liñán , Albert Lee , Jorge M. Gómez , Luis Ricardez-Sandoval , Ignacio E. Grossmann , David E. Bernal Neira","doi":"10.1016/j.compchemeng.2024.108993","DOIUrl":"10.1016/j.compchemeng.2024.108993","url":null,"abstract":"<div><div>Optimization of chemical processes is challenging due to nonlinearities arising from chemical principles and discrete design decisions. The optimal synthesis and design of chemical processes can be posed as a Generalized Disjunctive Programming (GDP) problem. While reformulating GDP problems as Mixed-Integer Nonlinear Programming (MINLP) problems is common, specialized algorithms for GDP remain scarce. This study introduces the Logic-Based Discrete-Steepest Descent Algorithm (LD-SDA) as a solution method for GDP problems involving ordered Boolean variables. LD-SDA transforms these variables into external integer decisions and uses a two-level decomposition: the upper-level sets external configurations, and the lower-level solves the remaining variables, efficiently exploiting the GDP structure. In the case studies presented in this work, including batch processing, reactor superstructures, and distillation columns, LD-SDA consistently outperforms conventional GDP and MINLP solvers, especially as the problem size grows. LD-SDA also proves superior when solving challenging problems where other solvers encounter difficulties finding optimal solutions.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"195 ","pages":"Article 108993"},"PeriodicalIF":3.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348531","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 detailed MILP model and an ad hoc decomposition algorithm for the operational optimization of gas transport networks 一个详细的MILP模型和一种气体输送网络运行优化的自组织分解算法

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-17 DOI: 10.1016/j.compchemeng.2025.109006

Lavinia Marina Paola Ghilardi , Francesco Casella , Daniele Barbati , Roberto Palazzo , Emanuele Martelli

{"title":"A detailed MILP model and an ad hoc decomposition algorithm for the operational optimization of gas transport networks","authors":"Lavinia Marina Paola Ghilardi , Francesco Casella , Daniele Barbati , Roberto Palazzo , Emanuele Martelli","doi":"10.1016/j.compchemeng.2025.109006","DOIUrl":"10.1016/j.compchemeng.2025.109006","url":null,"abstract":"<div><div>Nowadays, the management of natural gas networks primarily relies on the expertise gained by operators over the years. Nevertheless, the need to reduce energy consumption and the progressive installation of electric compressors call for the adoption of systematic optimization tools. This study proposes a Mixed Integer Linear Programming (MILP) model for optimizing the operation of complex real-world gas networks to minimize the environmental impact of the compression work in presence of both gas-turbine driven and electric compressors. The operational problem includes the gas transport dynamic equations, detailed modeling of compressor stations and control valves, while handling complex branch and looped networks with possible reverse flow. To address large-scale problems, a graph reduction procedure and a novel bilevel decomposition algorithm are developed. This methodology, validated with real data, enables the optimization of the nationwide Italian network, comprising 51 compressors and 9727 km of pipes.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"195 ","pages":"Article 109006"},"PeriodicalIF":3.9,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348535","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

Optimal sensor placement for contamination detection and identification in water distribution networks under demand uncertainty 需求不确定条件下配水管网污染检测与识别的传感器优化配置

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-13 DOI: 10.1016/j.compchemeng.2025.109003

Venkata Reddy Palleti

引用次数: 0

Process design for plastic waste pyrolysis: Yield analysis and economic assessment 塑料废弃物热解工艺设计：产率分析与经济评价

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-11 DOI: 10.1016/j.compchemeng.2025.109001

Hyojin Jung, Yuchan Ahn

{"title":"Process design for plastic waste pyrolysis: Yield analysis and economic assessment","authors":"Hyojin Jung, Yuchan Ahn","doi":"10.1016/j.compchemeng.2025.109001","DOIUrl":"10.1016/j.compchemeng.2025.109001","url":null,"abstract":"<div><div>The widespread use of plastic products and inadequate waste management systems have rendered plastic waste a major source of environmental pollution, thereby necessitating effective plastic recycling methods. In this study, we propose two pyrolysis processes for recycling plastic waste using Aspen Plus: a base process and an alternative process. The main difference lies in the condensation and separation methods used to produce pyrolysis oil. In the base process, condensation is carried out using a cooler, followed by decomposition with a flash drum. In contrast, the alternative process utilizes a distillation column for both condensation and separation. The results showed that PS achieved the highest oil yield of 81.3 %, while PS/PE exhibited the greatest improvement, with a 27.34 % increase in oil production yield in the alternative process compared to the base process. However, the alternative process incurs higher operating and capital costs due to the precise control requirements, particularly for feedstocks like PS/PE/PP/PET, which had the highest energy production cost at 31.07×10 <sup>−4</sup> $/ MJ compared to 27.85×10 <sup>−4</sup> $/ MJ in the base process. Despite these higher costs, the alternative process significantly improved oil production, especially for plastics such as PS and PS/PE. These findings underscore the importance of selecting pyrolysis processes based on feedstock composition and specific recycling goals, highlighting the trade-off between higher yields and increased energy production costs and emphasizing the need for balance.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"194 ","pages":"Article 109001"},"PeriodicalIF":3.9,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136738","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

Ensemble transfer learning assisted soft sensor for distributed output inference in chemical processes 集成迁移学习辅助软传感器在化工过程分布式输出推理中的应用

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-09 DOI: 10.1016/j.compchemeng.2025.109002

Jialiang Zhu, Wangwang Zhu, Yi Liu

{"title":"Ensemble transfer learning assisted soft sensor for distributed output inference in chemical processes","authors":"Jialiang Zhu, Wangwang Zhu, Yi Liu","doi":"10.1016/j.compchemeng.2025.109002","DOIUrl":"10.1016/j.compchemeng.2025.109002","url":null,"abstract":"<div><div>Chemical processes with distributed outputs are characterized by various operating conditions, and the scarcity of labeled data poses challenges to the prediction of product quality. An ensemble transfer Gaussian process regression (ETGPR) model is developed for prediction of different quantities of distributed outputs. First, for each test instances from target domain, just-in-time learning is adopted to select distance-based similar instances from source domain in related operating conditions. Mutual information helps create various local models by building diverse input variable sets. Subsequently, Bayesian inference is used to produce the posterior probabilities relative to the test instance, then set as the weights of local prediction. The instance transfer is thus completed via distance-based similar instance selection from source domain for local model construction, and the model performance is improved by the ensemble weighting strategy, concerning the target domain, under diverse operating conditions. Therefore, by utilizing and transferring information from source domain, unsupervised transfer can be implemented with available unlabeled target data. The superiority of ETGPR model is confirmed in the case of modeling the polymerization process with distributed outputs.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"194 ","pages":"Article 109002"},"PeriodicalIF":3.9,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136597","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

Multi-objective reaction optimization under uncertainties using expected quantile improvement 基于期望分位数改进的不确定条件下多目标反应优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2025-01-09 DOI: 10.1016/j.compchemeng.2024.108983

Jiyizhe Zhang , Daria Semochkina , Naoto Sugisawa , David C. Woods , Alexei A. Lapkin

{"title":"Multi-objective reaction optimization under uncertainties using expected quantile improvement","authors":"Jiyizhe Zhang , Daria Semochkina , Naoto Sugisawa , David C. Woods , Alexei A. Lapkin","doi":"10.1016/j.compchemeng.2024.108983","DOIUrl":"10.1016/j.compchemeng.2024.108983","url":null,"abstract":"<div><div>Multi-objective Bayesian optimization (MOBO) has shown to be a promising tool for reaction development. However, noise is usually inevitable in experimental and chemical processes, and finding reliable solutions is challenging when the noise is unknown or significant. In this study, we focus on finding a set of optimal reaction conditions using multi-objective Euclidian expected quantile improvement (MO-E-EQI) under noisy settings. First, the performance of MO-E-EQI is evaluated by comparing with some recent MOBO algorithms <em>in silico</em> with linear and log-linear heteroscedastic noise structures and different magnitudes. It is noticed that high noise can degrade the performance of MOBO algorithms. MO-E-EQI shows robust performance in terms of hypervolume-based metric, coverage metric and number of solutions on the Pareto front. Finally, MO-E-EQI is implemented in a real case to optimize an esterification reaction to achieve the maximum space-time-yield and the minimal E-factor. The algorithm identifies a clear trade-off between the two objectives.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"194 ","pages":"Article 108983"},"PeriodicalIF":3.9,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136740","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