Chemical Engineering Science最新文献

Development of a machine learning-based symbolic regression model for mixing time in large petroleum storage tanks 基于机器学习的大型石油储罐混合时间符号回归模型的开发

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-29 DOI: 10.1016/j.ces.2025.121903

Reynaldo P. Fonseca, Diener V R Fontoura, Nicolas Spogis, William D P Fonseca, Dirceu Noriler, Guilherme J. Castilho, Jose R. Nunhez

{"title":"Development of a machine learning-based symbolic regression model for mixing time in large petroleum storage tanks","authors":"Reynaldo P. Fonseca, Diener V R Fontoura, Nicolas Spogis, William D P Fonseca, Dirceu Noriler, Guilherme J. Castilho, Jose R. Nunhez","doi":"10.1016/j.ces.2025.121903","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121903","url":null,"abstract":"This study investigates the use of Symbolic Regression, a machine learning technique, to develop a model for mixing time in large petroleum storage tanks stirred by side-entry impellers. Studies involving the mixing time for side-entry mixers are relatively scarce when compared to research on mixing time models for top-mounted impellers. This limited availability of predictive models for side-entry configurations highlights the relevance of this study and makes them an excellent case for applying Symbolic Regression in stirred tank modeling. Symbolic Regression was applied to mixing time data obtained for a large petroleum storage vessel. The study examines how key parameters, including oil viscosity, tank diameter, tank height, impeller inclination angle, and the number of impellers affect the mixing time in these large tanks. The data used for model development was generated via CFD simulations, with mixing time estimated through numerical analysis. To ensure reliable CFD results, a Grid Convergence Index (GCI) study was conducted, maintaining the GCI for the average fluid velocity within the tank below 5%. In addition, this work introduces advanced statistical tools for predictive modeling, which can be valuable not only for estimating mixing time but also for broader applications in fluid dynamics. The analysis includes Spearman rank correlation, analysis of variance (ANOVA), and Symbolic Regression. The proposed mixing time equation was developed using machine learning techniques trained on the CFD-generated data. The results indicate that the number of impellers, tank diameter, and tank height have the most significant impact. In contrast, within the investigated parameters range, oil viscosity and impeller inclination angle have a comparatively smaller statistical influence on the mixing time.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"36 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144165481","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 flexible multi-step prediction architecture for process variable monitoring in chemical intelligent manufacturing 化工智能制造过程变量监测的柔性多步预测体系结构

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-29 DOI: 10.1016/j.ces.2025.121943

Yue Li, Hongtao Cao, Zhongmei Li, Wenli Du, Weifeng Shen

{"title":"A flexible multi-step prediction architecture for process variable monitoring in chemical intelligent manufacturing","authors":"Yue Li, Hongtao Cao, Zhongmei Li, Wenli Du, Weifeng Shen","doi":"10.1016/j.ces.2025.121943","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121943","url":null,"abstract":"Multi-step prediction models can forecast variables ahead of time, which is valuable for process variable monitoring. Although deep learning (DL) is promising in multi-step prediction, its compatibility, interpretability and practicality, which are crucial for chemical applications, have received little attention. Thus, a DL architecture—Light Attention-Mixed Base Target Autoregression Unit (LAMB-TAU) is proposed. It utilizes special-designed networks to simulate process driving forces, and wraps these networks with a decoder, delivering an interpretable and high-accuracy multi-step prediction on process variables. Moreover, an adaptable sampling procedure is proposed to free the multi-step predictions on difficult-to-measure variables from high-cost experiments. The effectiveness of LAMB-TAU is verified by modeling studies on chemical processes including esterification and formaldehyde production. Besides, model practicalities including extended multi-step prediction, uncertainty and computational cost are explored. The proposed LAMB-TAU is instructive for DL multi-step prediction studies toward chemical process monitoring, which promotes the development of intelligent chemical industry.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"98 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144165476","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 modeling of photocatalytic contaminant degradation using nanomaterials synthesized with microalgal extracts 微藻提取物合成纳米材料光催化污染物降解的混合建模

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-28 DOI: 10.1016/j.ces.2025.121945

Federico Atzori, Bartolomeo Cosenza, Federico Zedda, Agnieszka Sidorowicz, Giacomo Fais, Giacomo Cao, Alessandro Concas

{"title":"Hybrid modeling of photocatalytic contaminant degradation using nanomaterials synthesized with microalgal extracts","authors":"Federico Atzori, Bartolomeo Cosenza, Federico Zedda, Agnieszka Sidorowicz, Giacomo Fais, Giacomo Cao, Alessandro Concas","doi":"10.1016/j.ces.2025.121945","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121945","url":null,"abstract":"Synthetic dyes released through industrial effluents pose significant environmental risks due to their persistence and toxicity. Photocatalytic degradation through metal nanoparticles offers a promising, eco-friendly remediation approach. This study presents a hybrid modeling framework for simulating the visible-light-driven degradation of Brilliant Blue R using silver nanoparticles (AgNPs) synthesized through extracts of Haematococcus pluvialis, Spirulina platensis, and Chlorella vulgaris. The biogenic AgNPs exhibited favorable physicochemical properties, including crystalline sizes of 13–16 nm and band gap energies between 2.17 and 2.33 eV.A simplified deterministic model was first developed, accounting for adsorption–desorption equilibrium and degradation kinetics, which enables analytical estimation of key kinetic parameters. These parameters were used to train artificial neural networks (ANNs) that map experimental conditions such as light intensity, dye concentration, nanoparticle dosage, and pH to degradation kinetics.To overcome the limited size of datasets obtained through experiments, a novel data augmentation strategy was implemented using Gaussian noise derived from measurement uncertainty and confidence intervals of the deterministic model’ parameters. This strategy enabled the significant augmentation of data enhancing the ANN performance. Indeed, the global mean squared error dropped from 5.6 × 10−4 to 1.3 × 10−5 for AgNPs from H. pluvialis, from 1.6 × 10−2 to 3.3 × 10−6 for C. vulgaris, and from 2.4 × 10−3 to 4.2 × 10−4 for S. platensis when using both input and output augmentation.The proposed hybrid framework couples mechanistic interpretability with data-driven prediction providing a reliable tool for optimizing photocatalytic degradation processes via sustainable nanomaterials of microalgal origin.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"98 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154269","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

Description of confined nanoflow transport considering the effects of capillary condensation and heat transfer by means of a two-phase lattice Boltzmann model 用两相晶格玻尔兹曼模型描述考虑毛细凝聚和传热影响的受限纳米流输运

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-28 DOI: 10.1016/j.ces.2025.121935

Javad Sodagar-Abardeh, Thomas Loimer

{"title":"Description of confined nanoflow transport considering the effects of capillary condensation and heat transfer by means of a two-phase lattice Boltzmann model","authors":"Javad Sodagar-Abardeh, Thomas Loimer","doi":"10.1016/j.ces.2025.121935","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121935","url":null,"abstract":"The pseudopotential two-phase Lattice Boltzmann method is used to study a flow with condensation and evaporation through slits ranging between 8 to 24 nm in width by applying a pressure gradient. The slits are about 700 nm long. The fluid described by the Carnahan-Starling equation of state is in the form of a vapor upstream of the pore. For the smaller applied pressure gradient, the vapor flows through the slit. However, for higher values of the pressure gradient, as the gas flows through the slit, the fluid condenses, and consequently, liquid flows through the slit. The liquid may leave the slit, or it evaporates. Here, the condition at the interface between the liquid and the gaseous flow region, where mass transfer by evaporation takes place, is investigated. The pressure difference across the curved meniscus is consistent with the Young-Laplace equation and nearly independent of the mass flow rate. However, the curvature of the interface depends on the strength of the fluid-wall interaction. The curvature of the meniscus and effects influencing the curvature play an important role in the process. Considering the temperature field in the transport process reveals that different boundary conditions for the domain influence the mass flow rate. Heating the slit from the downstream side decreases the mass flow rate.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"25 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154247","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

Evaluation of modifier type (mineral or organic) and modifier location (top layer or sublayer) on fouling mitigation in MMM and TFC membranes 改性剂类型（矿物或有机）和改性剂位置（顶层或下层）对缓解MMM和TFC膜污染的影响

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-28 DOI: 10.1016/j.ces.2025.121942

Zohre Hajhashemi, Maryam Homayoonfal

{"title":"Evaluation of modifier type (mineral or organic) and modifier location (top layer or sublayer) on fouling mitigation in MMM and TFC membranes","authors":"Zohre Hajhashemi, Maryam Homayoonfal","doi":"10.1016/j.ces.2025.121942","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121942","url":null,"abstract":"Membrane fouling, a major challenge in filtration which lowers performance and membrane lifespan, is the focus of this research. The study introduces a key novelty by examining the combined effects of modifier type (mineral nanoparticles vs. organic substances) and their specific loading site (sublayer vs. top layer) on fouling mitigation, an aspect that has not been comprehensively addressed in prior studies. Hydrophilic mineral nanoparticles (CdSe, ZnSe, ZnTe) and dopamine hydrophilic organic substance were loaded in the sublayers of mixed matrix membranes (MMM) and the top layer of thin-film composite (TFC). Mineral modifiers outperformed organic counterparts. ZnSe nanoparticles was the most effective modifier; its strong hydrophilicity enhanced hydration layer formation, delayed phase inversion, and resulted in smaller pores and lower tortuosity in MMM (0,ZnSe), with the lowest pore fouling. Highlighting the significance of research, MMM membranes containing mineral modifiers (especially ZnSe) are suggested for lower pore fouling (4.62% vs 67.31%). In contrast, for lower cake fouling and higher rejection (98.00% vs 75.09%), TFC membranes containing both organic (dopamine) and mineral (especially ZnSe) modifiers are recommended.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"80 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154248","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

Size-induced axial segregation of binary mixtures in rotating drum of different lengths 不同长度转鼓中二元混合物的尺寸诱导轴向偏析

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-28 DOI: 10.1016/j.ces.2025.121941

Jielong He, Yuelei Wang, Liuyimei Yang, Jin Xu, Qijun Zheng, Sida Liu, Zongyan Zhou

引用次数: 0

Calculation of evaporation of chemicals into air 计算化学物质在空气中的蒸发量

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-27 DOI: 10.1016/j.ces.2025.121937

Mirza M. Shah

{"title":"Calculation of evaporation of chemicals into air","authors":"Mirza M. Shah","doi":"10.1016/j.ces.2025.121937","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121937","url":null,"abstract":"Calculation of the rate of evaporation of volatile chemicals exposed to air is needed in many situations to determine environmental impact and need for mitigating actions such as providing ventilation. Such situations include emission sources in industrial manufacturing operations such as open surface tanks, container filling, indoor spills, spills occurring in transportation and from bulk storage facilities. There have been a number of experimental studies to measure rate of evaporation of chemicals from horizontal surfaces. A number of theoretical and empirical prediction methods have been proposed. However, there has been no evaluation of various prediction methods with a database consisting of data from many sources covering a wide range of properties and conditions so that the best methods could be identified. This research was done to fulfil this need. Data for 21 chemicals with very diverse properties exposed to air at a wide range of velocities and temperatures were compared to available general correlations. These included empirical and semi-theoretical correlations as well as the analogy between heat and mass transfer. Data were from tests done under natural convection as well as with forced convection. Air velocity ranged from 0 to 5.1 m/s, air temperature from 5 to 61 °C, evaporating liquid temperature −1 to 64 °C, and liquid saturation pressure 0.01 to 61 kPa. A simplified formula was derived for natural convection evaporation using the analogy between heat transfer which shows excellent agreement with data. The results of this research are presented and recommendations are made regarding the most suitable correlations under various conditions.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"25 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145515","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

Investigation of unsteady flow in liquid-liquid hydrocyclone using Eulerian-Lagrangian approach 用欧拉-拉格朗日方法研究液-液旋流器的非定常流动

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-27 DOI: 10.1016/j.ces.2025.121936

Hossein Ramezani, Sajad Khodadadi, Reza Maddahian

{"title":"Investigation of unsteady flow in liquid-liquid hydrocyclone using Eulerian-Lagrangian approach","authors":"Hossein Ramezani, Sajad Khodadadi, Reza Maddahian","doi":"10.1016/j.ces.2025.121936","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121936","url":null,"abstract":"The considerable influence of inflow variations within hydrocyclones on separation efficiency and the time required to achieve steady-state flow made the examination of the transient behavior of two-phase flow crucial. This study investigated the overall progression of two-phase flow, starting from the injection of oil droplets until reaching a steady state in a de-oiling hydrocyclone simulated using the open-source software OpenFOAM v5. Furthermore, the impact of sinusoidal variations in the inlet flow was examined, as vibrations on oil platforms significantly affected the inlet flow of hydrocyclones, thereby influencing their efficiency. To assess the improvement in efficiency over time, the analysis focused on the variations in efficiency from the initial introduction of oil droplets into the hydrocyclone until maximum efficiency was achieved. This examination revealed three key time spans (Start-Up, Semi-Stable, and Fully Stable) where the efficiency trend underwent noticeable changes. Notably, the initial time span (Start-Up) was the most critical, showing an 80% increase in efficiency within the first two seconds. Additionally, the study examined the breakup and coalescence of droplets during transient oil injection at three different time intervals. Sinusoidal variations of 10% in the inlet flow led to a decrease in efficiency from 91% to 82%. This decrease in efficiency was caused by extreme variations in the inlet flow rate, which disrupted the vortices in the core of the flow responsible for carrying droplets to the overflow. During the first and second cone time spans of each cycle, the disruption resulted in a decrease in efficiency that was recovered by the return flow in the second half of the cycle.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"25 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145423","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

Biomimetic microfluidic chip fabrication for studying fluid transport in micro- and nanoscale carbonate rock fracture 用于研究微纳米碳酸盐岩缝中流体运移的仿生微流控芯片的制作

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-27 DOI: 10.1016/j.ces.2025.121939

Yujie Jin, Xiongqi Pang, Fan Xu, Junqing Chen, Yao Hu, Zhi Xu, Caijun Li, Kanyuan Shi, Lei Wang, Junjie Chu

{"title":"Biomimetic microfluidic chip fabrication for studying fluid transport in micro- and nanoscale carbonate rock fracture","authors":"Yujie Jin, Xiongqi Pang, Fan Xu, Junqing Chen, Yao Hu, Zhi Xu, Caijun Li, Kanyuan Shi, Lei Wang, Junjie Chu","doi":"10.1016/j.ces.2025.121939","DOIUrl":"https://doi.org/10.1016/j.ces.2025.121939","url":null,"abstract":"The flow of fluids between minerals involves complex physicochemical coupling effects, and using real rock cores as reactors for characterization presents significant challenges. This is due to the lack of fluid visualization capabilities in rock cores, as well as their highly heterogeneous structure. This study introduces a biomimetic microfluidic chip fabrication method that enables the direct observation of fluid-mineral interactions at the micro- and nanoscale, with the added benefit of scalability for mass production. The fabrication process starting with machine learning algorithms are employed to extract fracture structures from natural rock samples; second, soft lithography is utilized to replicate these fractures at a 1:1 scale; and finally, the fracture surfaces are modified through in situ growth of calcium carbonate minerals, thereby creating high-fidelity models of carbonate rock fractures for fluid transport. Notably, this method offers tunable parameters for key variables, such as porous structures, mineral types, and the physicochemical properties of mineral surfaces. This makes it an ideal platform for in-depth studies of fluid transport mechanisms under complex conditions, such as the sealing effects of chemical agents on fractures or the migration of oil and gas in reservoirs.","PeriodicalId":271,"journal":{"name":"Chemical Engineering Science","volume":"57 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144154249","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

Field-effect control of ion transport of power-law fluids in a pH-regulated nanochannel ph调节纳米通道中幂律流体离子输运的场效应控制

IF 4.7 2区工程技术

Chemical Engineering Science Pub Date : 2025-05-27 DOI: 10.1016/j.ces.2025.121938

Yu Hao, Li Peng, Runxin Liu, Zhengyang Zhao, Teng Zhou, Jie Li

引用次数: 0