Computers & Chemical Engineering最新文献_第8页

Multi-scale residual attention networks with spatio-temporal attention co-optimization for industrial fault diagnosis 基于时空关注协同优化的多尺度剩余关注网络工业故障诊断

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-11-17 DOI: 10.1016/j.compchemeng.2025.109482

Youqiang Chen , Ridong Zhang , Furong Gao

{"title":"Multi-scale residual attention networks with spatio-temporal attention co-optimization for industrial fault diagnosis","authors":"Youqiang Chen , Ridong Zhang , Furong Gao","doi":"10.1016/j.compchemeng.2025.109482","DOIUrl":"10.1016/j.compchemeng.2025.109482","url":null,"abstract":"<div><div>Traditional fault diagnosis has limitations in dynamic condition adaptation and multimodal feature decoupling, while existing deep learning methods are limited by the localization of time series modeling, noise sensitivity and insufficient efficiency of multiscale feature fusion. Aiming at the above challenges, this paper proposes a multi-scale residual attention fault diagnosis network (MRAFDN) through hierarchical dynamic feature enhancement and spatio-temporal attention co-optimization mechanism. The innovation of this study lies in constructing a dual fusion framework integrating Dynamic Multi-Scale Channel Attention (MSCA) and Dilated Spatial Attention (DSA). Employing a 1D Residual Network (1D-ResNet) as the backbone architecture, residual connections preserve low-level information from raw signals, while cascaded optimization with dual attention mechanisms forms a comprehensive lifecycle fault characterization system spanning from micro fluctuations to macro drifts. This methodology theoretically addresses fundamental challenges including noise-feature coupling, coexistence of multiple fault modes and adaptability to dynamic operational conditions. The proposed method demonstrates significant robustness under strong noise for multi-class fault modes in TE chemical processes and industrial coke furnaces.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109482"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145620086","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 machine learning-fueled modelfluid for flowsheet optimization 用于流程优化的机器学习驱动的模型流体

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-11-24 DOI: 10.1016/j.compchemeng.2025.109486

Martin Bubel, Tobias Seidel, Michael Bortz

{"title":"A machine learning-fueled modelfluid for flowsheet optimization","authors":"Martin Bubel, Tobias Seidel, Michael Bortz","doi":"10.1016/j.compchemeng.2025.109486","DOIUrl":"10.1016/j.compchemeng.2025.109486","url":null,"abstract":"<div><div>Process optimization in chemical engineering may be hindered by the limited availability of reliable thermodynamic data for fluid mixtures. Remarkable progress is being made in predicting thermodynamic mixture properties by machine learning techniques. The vast information provided by these prediction methods enables new possibilities in process optimization. This work introduces a novel modelfluid representation that is designed to seamlessly integrate these ML-predicted data directly into flowsheet optimization. Tailored for distillation, our approach is built on physically interpretable and continuous features derived from core vapor liquid equilibrium phenomena. This ensures compatibility with existing simulation tools and gradient-based optimization. We demonstrate the power and accuracy of this ML-fueled modelfluid by applying it to the problem of entrainer selection for an azeotropic separation. The results show that our framework successfully identifies optimal, thermodynamically consistent entrainers with high fidelity compared to conventional models. Ultimately, this work provides a practical pathway to incorporate large-scale property prediction into efficient process design and optimization, overcoming the limitations of both traditional thermodynamic models and complex molecular-based equations of state.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109486"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145620088","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 hybrid framework of intrinsic constraint handling and safe reinforcement learning for crude oil scheduling 原油调度的内在约束处理与安全强化学习混合框架

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-11-13 DOI: 10.1016/j.compchemeng.2025.109480

Zhineng Tao , Haoran Li , Tong Qiu

{"title":"A hybrid framework of intrinsic constraint handling and safe reinforcement learning for crude oil scheduling","authors":"Zhineng Tao , Haoran Li , Tong Qiu","doi":"10.1016/j.compchemeng.2025.109480","DOIUrl":"10.1016/j.compchemeng.2025.109480","url":null,"abstract":"<div><div>Crude oil scheduling is a critical but highly complex sequential decision-making problem in refinery operations. Traditional mathematical programming methods suffer from exponential computational complexity with increasing scale, while traditional reinforcement learning approaches struggle to guarantee the satisfaction of numerous process and product quality constraints. This highlights a critical issue in the current field of scheduling: the lack of an optimization methodology that can simultaneously achieve high computational efficiency and robust constraint satisfaction. To bridge this gap, we propose a novel hybrid framework based on constraint stratification. The framework embeds critical hard constraints, such as entity connectivity limit, directly into the scheduling environment for intrinsic satisfaction through action masking and shaping. Concurrently, it employs safe reinforcement learning algorithms to manage soft constraints, such as tank inventory levels and product quality specifications, by optimizing a primary objective while keeping constraint violations below a predefined threshold. Through comparative experiments on scheduling cases, the Constrained Policy Optimization algorithm was identified as the most effective safe reinforcement learning method. The results demonstrate that our proposed framework significantly outperforms traditional methods. It achieves the high computational efficiency and scalability of reinforcement learning while providing a much stronger safety guarantee than penalty-based approaches, offering a robust and practical solution for complex industrial scheduling problems.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109480"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576348","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-criteria decision-making and multi-objective optimization of a sustainable bio-based isopropanol supply chain 可持续生物基异丙醇供应链的多准则决策和多目标优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-11-17 DOI: 10.1016/j.compchemeng.2025.109487

Ching-Mei Wen, Marianthi Ierapetritou

{"title":"Multi-criteria decision-making and multi-objective optimization of a sustainable bio-based isopropanol supply chain","authors":"Ching-Mei Wen, Marianthi Ierapetritou","doi":"10.1016/j.compchemeng.2025.109487","DOIUrl":"10.1016/j.compchemeng.2025.109487","url":null,"abstract":"<div><div>This study focuses the multi-objective optimization and multi-criteria decision-making (MCDM) framework for designing a sustainable bio-based isopropanol (bio-IPA) supply chain under uncertainty, using sugar beet as the primary feedstock. By applying a two-stage stochastic programming model, the research optimizes the five-tier supply chain from sugar beet farms through storage, sugar plants, IPA production, and retail distribution across Minnesota. The study addresses economic, environmental, and supply chain performance objectives while accounting for uncertainties in biomass yield and market demand fluctuations. Results shows a cost-optimal supply chain configuration that can adapt to demand surges, achieving up to 94 % service levels when a $2.5/kg penalty for unsatisfied demand is applied. The analysis highlights the dominant influence of biomass cost, which accounts for approximately 65 % of total production costs, underscoring its critical role in supply chain economics. As environmental constraints tighten (e.g., greenhouse gas emission caps), the system experiences rising unsatisfied demand penalties and operational challenges. Furthermore, the study applies MCDM techniques, including the Weighted Product Method and data-driven weighting methods such as the coefficient of variation and interval entropy, to rank alternative configurations. Ternary plots, reflect the economic, environmental, and operational (performance-based) dimensions, are proposed as a tool to visualize trade-offs across economic, environmental, and operational dimensions, enhancing informed decision-making by exploring a diverse range of weight distributions that reflect varying stakeholder values.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109487"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576349","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

An optimization framework for renewable liquefied gas supply chain: A case study on glycerol-based production 可再生液化气供应链的优化框架：以甘油为基础的生产为例

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-11-13 DOI: 10.1016/j.compchemeng.2025.109481

Larissa Thaís Bruschi, Luiz Kulay, Moisés Teles dos Santos

{"title":"An optimization framework for renewable liquefied gas supply chain: A case study on glycerol-based production","authors":"Larissa Thaís Bruschi, Luiz Kulay, Moisés Teles dos Santos","doi":"10.1016/j.compchemeng.2025.109481","DOIUrl":"10.1016/j.compchemeng.2025.109481","url":null,"abstract":"<div><div>Renewable Liquefied Gas (RLG) is emerging as a viable alternative to Liquefied Petroleum Gas (LPG), providing environmental benefits and strengthening energy security. However, the implementation of biofuels faces challenges such as long-term feedstock availability, technology scalability, facility site selection, and tax policies. This study proposes a Mixed Integer Linear Programming optimization model to support strategic and tactical RLG supply chain decisions in Brazil. The model determines the optimal feedstock purchasing, facility locations, processing capacities, material flows, and product distribution to maximize the Net Present Value (NPV), in a case study that explores the production of RLG from glycerol. For the economic feasibility of the supply chain the RLG selling price must be 80 % higher than that of LPG. The optimal network favors a centralized system, where transportation costs minimally impact NPV, while economies of scale lower investment and production costs. A decentralized approach is evaluated by limiting the installed production capacity. Although a decentralized network requires an RLG selling price 220 % higher than LPG, it allows smaller stakeholders to enter the market and achieves the same payback period as the centralized system. Sensitivity analysis on conversion yield shows that a 5 % efficiency increase shortens the payback period by four years and triples the NPV. The study highlights the importance of supply chain integration, cost reduction strategies, and policy incentives in enhancing RLG competitiveness, thereby contributing to its deployment despite facing economic and logistical challenges.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109481"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145526245","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

C2 and C+ compound production from carbon dioxide: supply chain design and optimization 从二氧化碳中生产C2和C+化合物：供应链设计和优化

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-15 Epub Date: 2025-10-31 DOI: 10.1016/j.compchemeng.2025.109476

Grazia Leonzio , Nilay Shah

{"title":"C2 and C+ compound production from carbon dioxide: supply chain design and optimization","authors":"Grazia Leonzio , Nilay Shah","doi":"10.1016/j.compchemeng.2025.109476","DOIUrl":"10.1016/j.compchemeng.2025.109476","url":null,"abstract":"<div><div>The use of carbon dioxide to produce chemical products can in principle decrease both fossil resource exploitation and greenhouse gas emissions. Potential compounds that can be obtained are ethylene and polyurethane, characterized by large markets underpinning many industries. The importance of such platform chemicals means that different routes have been investigated in the literature for their alternative synthesis. However, there is lack of a direct comparison of these products and processes in a carbon capture utilization and storage supply chain in the existing literature: a gap which we wish to address here.</div><div>A mixed integer linear optimization model for a carbon capture utilization and storage supply chain is developed here: carbon dioxide can be extracted from flue gas to be stored and/or utilized for ethylene (via the tandem or methanol to olefin processes), polyethylene or polyurethane production and these can be either sold immediately or stored. The framework is exemplified by a case study localised within the UK Teesside petrolchemical cluster and the best topology is suggested to minimize total costs. Moreover, a dynamic analysis of the system over the years is considered here to suggest the best way to implement carbon dioxide capture and utilisation through to 2050. Results show that the optimal cost is achieved by capturing carbon dioxide and converting it into ethylene via the methanol-to-olefin process; the whole system levelized cost is 7.3 $/kg<sub>Ethylene</sub>. Moreover, ensuring an homogeneous way of capturing carbon dioxide over time maximises the profitability of the overall system.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109476"},"PeriodicalIF":3.9,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145576225","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 modelling of chemical processes: a unified framework based on deductive, inductive, and abductive inference 化学过程的混合建模：基于演绎、归纳和溯因推理的统一框架

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-09-17 DOI: 10.1016/j.compchemeng.2025.109395

Raymoon Hwang, Jae Hyun Cho, Il Moon, Min Oh

{"title":"Hybrid modelling of chemical processes: a unified framework based on deductive, inductive, and abductive inference","authors":"Raymoon Hwang, Jae Hyun Cho, Il Moon, Min Oh","doi":"10.1016/j.compchemeng.2025.109395","DOIUrl":"10.1016/j.compchemeng.2025.109395","url":null,"abstract":"<div><div>Hybrid modelling offers a powerful means of combining mechanistic principles with data-driven learning for complex chemical processes. However, most existing approaches rely on structural coupling without a principled basis for integrating distinct modes of reasoning or enabling modular reuse. This work introduces a unified layered hybrid modelling architecture grounded in three epistemic layers: deductive, inductive, and abductive. Roles of each layer are: enforcing physical laws, learning unknown dynamics, and inferring latent states. The formulation is expressed in operator-theoretic terms. Results demonstrate improved accuracy, interpretability, and adaptability, highlighting the framework’s potential as a transparent and generalizable strategy for hybrid modelling under uncertainty in chemical process systems, while also supporting compositional reasoning and layer-wise retraining.</div><div>The first case study considers a single-unit non-isothermal batch polymerization reactor with unknown reaction kinetics and partial temperature observability. The deductive layer encodes mass and energy balances, the inductive layer learns kinetics via a neural network, and the abductive layer reconstructs latent temperature states. The second case study examines a multi-unit fed-batch bioreactor flowsheet, representative of typical chemical process configurations. Here, the deductive layer models feed-flow dynamics (unit #1), the inductive layer predicts biomass growth (unit #2), and the abductive layer estimates latent physiological states such as oxygen uptake rate and pH (unit #3). These examples demonstrate that the framework can integrate multiple inference modes within a single unit or distribute them across a flowsheet, enabling application to a wide range of hybrid modelling scenarios. The approach is general and suited for scalable, transparent modelling under uncertainty.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109395"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145322890","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

Applications of machine learning for decision support in biomass supply chains: A systematic review 机器学习在生物质供应链决策支持中的应用：系统综述

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-12 DOI: 10.1016/j.compchemeng.2025.109451

Shayan Razmi, Hossein Mirzaee, Gaurav Kumar, Taraneh Sowlati

{"title":"Applications of machine learning for decision support in biomass supply chains: A systematic review","authors":"Shayan Razmi, Hossein Mirzaee, Gaurav Kumar, Taraneh Sowlati","doi":"10.1016/j.compchemeng.2025.109451","DOIUrl":"10.1016/j.compchemeng.2025.109451","url":null,"abstract":"<div><div>Effective planning of biomass supply chains (BSC), which involve collection, transportation, pre-processing, storage, conversion, and delivery of bioproducts, is essential to ensure efficiency and sustainability. Recently, machine learning (ML) has been adopted to address the supply chain’s complexities for effective planning. ML provides dynamic and data-driven solutions that enhance decision-making. It has been applied for predicting biomass yields, forecasting supply and demand, optimizing logistics and facility location, and improving the efficiency of conversion processes. This review paper highlights the role of ML in BSC planning. This study considers biomass sources such as food processing residues, animal waste (e.g., manure), in addition to forest-based and agricultural-based biomass, examining processes across all stages of a supply chain from upstream to downstream. We examine ML models in previous studies based on their learning paradigms: supervised, unsupervised, and reinforcement learning, and the type of performed analytics: predictive, and both predictive and prescriptive analytics. Challenges related to data availability, computational requirements, and model generalization limit ML applications in BSCs. Future research could focus on scalable and adaptable models for preprocessing, transportation, and harvesting activities by addressing the uncertainty. Integrating advanced ML could significantly enhance the resiliency, sustainability, and efficiency of BSCs, supporting bioeconomy advancement and the achievement of sustainability goals.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109451"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145322887","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

Probabilistic assessment and automatic detection of oscillations in industrial control loops 工业控制回路振荡的概率评估与自动检测

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-10-05 DOI: 10.1016/j.compchemeng.2025.109437

An-qi Guan , Fang-na Xiang , Ling-feng Hang , Zhi-yan Li , Zhen-hao Lin , Zhi-jiang Jin , Jin-yuan Qian

{"title":"Probabilistic assessment and automatic detection of oscillations in industrial control loops","authors":"An-qi Guan , Fang-na Xiang , Ling-feng Hang , Zhi-yan Li , Zhen-hao Lin , Zhi-jiang Jin , Jin-yuan Qian","doi":"10.1016/j.compchemeng.2025.109437","DOIUrl":"10.1016/j.compchemeng.2025.109437","url":null,"abstract":"<div><div>Loop oscillation is a prevalent issue in industrial control loops. Affected by changes in production tasks, loop load, and external environment, industrial control systems typically have more complex oscillation patterns. Industrial signals often exhibit multimodal superposition, noise interference, and non-stationarity. Binary judgment of oscillation is prone to false alarms or missed detections in industrial control loops. More fundamentally, the binary classification framework fails to quantify oscillation risks. Therefore, complex oscillations in industrial control loops still need a more flexible assessment framework. In this paper, a probabilistic assessment framework for oscillations is proposed from the perspective of the statistical characteristics of zero-crossings. To enhance the reliability of signal preprocessing, adaptive VMD and significant IMFs identification are combined. By incorporating the statistical characteristics for coefficient of variation into regularity test of oscillation, the conventional binary classification is transformed into the probabilistic assessment. In simulation studies, the effectiveness of adaptive VMD, significant IMFs identification, and probabilistic assessment in complex signals and negative feedback loops is verified through three examples. In industrial scenario studies, the performance of the proposed method is analyzed in 93 benchmark industrial loops. The proposed method is compared with 12 distinct methods. The detection results of benchmark industrial loops show that the performance of this method is superior to most detection methods. The proposed method can not only ensure high accuracy, sensitivity and specificity, but also evaluate and grade the oscillation probability without historical data and model training. This detection method provides reference value for risk classification and decision optimization of process monitoring.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109437"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145324018","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

3D modeling of isothermal adsorption in structured contactors 结构接触器等温吸附的三维建模

IF 3.9 2区工程技术

Computers & Chemical Engineering Pub Date : 2026-02-01 Epub Date: 2025-09-24 DOI: 10.1016/j.compchemeng.2025.109404

Nicolas Antunes Morgado, Marco Mazzotti

{"title":"3D modeling of isothermal adsorption in structured contactors","authors":"Nicolas Antunes Morgado, Marco Mazzotti","doi":"10.1016/j.compchemeng.2025.109404","DOIUrl":"10.1016/j.compchemeng.2025.109404","url":null,"abstract":"<div><div>Structured contactors, such as honeycomb monoliths and laminates, have gained increased interest as sorbent supports in adsorption separations due to their ability to enable process intensification without the trade-offs of traditional packed beds. While 1D models are commonly used in cycle design, they often lump key 3D features of the adsorption process. An accurate description of these features within the contactor, such as spatial variations in sorbent saturation, can be leveraged during the design stage to enhance contactor performance. This work presents a general 3D model for structured contactors under isothermal conditions, capable of capturing flow phenomena like variable cross-flow within unit cells that lead to unconventional sorbent loading dynamics. To illustrate this capability, a case study comparing flow-through (FTM) and wall-flow (WFM) monoliths as air contactors in a direct air CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> capture (DAC) cycle was carried out, examining the impact of air flow rate and wall permeability. The analysis highlights differences in fluid dynamics, mass transfer mechanisms, and the evolution of the concentration and loading level of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> on the sorbent for the two configurations, highlighting the 3D effects not captured by 1D models. Finally, a performance comparison based on sorbent requirements and exergy per unit CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> captured was carried out, showing under which conditions WFMs may become competitive with FTMs.</div></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"205 ","pages":"Article 109404"},"PeriodicalIF":3.9,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145360236","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