Canadian Journal of Chemical Engineering最新文献

{"title":"An improved dynamic matrix control with output penalty for industrial processes","authors":"Sen Hong,&nbsp;Jianjun Bai,&nbsp;Hongbo Zou","doi":"10.1002/cjce.25672","DOIUrl":"https://doi.org/10.1002/cjce.25672","url":null,"abstract":"<p>For plants with complex dynamics, traditional dynamic matrix control (DMC), which includes output errors and control increments in the cost function, usually exhibits limited control performance. To obtain a better performance in system overshoot, we propose a novel DMC method with an output penalty term without increasing the computational complexity. First, we design a quadratic term for output increments and integrate it into the cost function. This term is used to penalize the system output, thereby reducing system overshoot. Considering that the cost function already contains three performance indexes, we propose a fast DMC algorithm to reduce the computational burden of the controller. The main idea of the proposed fast DMC is to move part of the control computation offline to reduce the cost of online computation. Finally, the proposed DMC strategy is applied to the oxygen content system of the coke furnace. The results show that the proposed DMC method is superior to the conventional DMC method in terms of reducing system overshoot. In addition, the proposed method achieves a significant improvement in computational efficiency.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"4952-4967"},"PeriodicalIF":1.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic characteristics of active stock in a circulating fluidized bed boiler based on unsteady state conditions","authors":"Xin Shen,&nbsp;Tianyi Chen,&nbsp;Xiaoqian Li,&nbsp;Yue Guo,&nbsp;Hairui Yang,&nbsp;Yan Jin","doi":"10.1002/cjce.25662","DOIUrl":"https://doi.org/10.1002/cjce.25662","url":null,"abstract":"<p>During rapid load increase and decrease in circulating fluidized bed (CFB) units, the presence of a large amount of bed material, including incompletely combusted carbon residue and incompletely reacted calcium-based desulphurizers, affects both the load change rate and pollutant emissions of the boiler. Therefore, the rational utilization of active stock within the boiler plays an important role in improving the heat release rate and increasing the load response rate. Using a 350 MW supercritical CFB boiler as the research object, numerical simulations were conducted on the load increase and decrease processes of the CFB boiler. Dynamic models of active carbon residue stock and active limestone were constructed to analyze the active stock during load increase and decrease processes. The results show that during the load increase from 175 to 350 MW, the coal feed rate is the main factor affecting the active carbon residue stock. The combustion rate of active carbon residue is lower than the coal feed rate, resulting in an increasing trend in active carbon residue stock, ranging from 6801.51 to 17,491.03 kg. During the load decrease from 350 to 300 MW, the active carbon residue stock decreases sharply, from 15,883.58 to 11,188.43 kg. During the load increase, there is a negative correlation between SO₂ concentration and active limestone stock. As the load increases from 208 to 280 MW, the SO₂ concentration rises from 1978.96 to 4951.94 mg/m³, while the active limestone stock decreases from 2223.65 to 1675.40 kg.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"5143-5158"},"PeriodicalIF":1.9,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault diagnosis method for chemical processes based on variable correlation-guided convolutional neural networks","authors":"Zhe Zhou,&nbsp;Hongwei Yu,&nbsp;Li Yang,&nbsp;Zuxin Li,&nbsp;Chenglin Wen","doi":"10.1002/cjce.25673","DOIUrl":"https://doi.org/10.1002/cjce.25673","url":null,"abstract":"<p>Convolutional neural networks (CNNs) have been widely applied in chemical process fault diagnosis due to their superior feature extraction capabilities. However, the inherent complexity and variability of chemical environments, involving multivariable interactions, noise interference, and other factors, pose challenges that hinder the direct application of CNNs. These limitations may compromise the accuracy of fault diagnosis by hindering the full exploitation of CNNs' feature extraction capabilities. To address these challenges, this paper proposes a novel fault diagnosis method for chemical processes based on a variable correlation-guided CNN. The proposed method uses the Pearson correlation coefficient to identify strongly correlated variable groups, integrating them into the original variables. This integration facilitates the convolution of these strongly correlated variables, thereby enhancing the extraction of more discriminative features and optimizing fault diagnosis methods. This approach enables CNNs to more accurately extract fault-relevant features, thereby improving diagnostic performance. The effectiveness of the proposed method is validated through comprehensive numerical simulations and the Tennessee Eastman (TE) process dataset. The results demonstrate substantial enhancements in both the accuracy and reliability of fault detection, validating the superiority of the proposed method.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"4874-4889"},"PeriodicalIF":1.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical modelling of the permeability of filter media exhibiting a bimodal fibre diameter distribution—Beyond empirical models","authors":"Félicie Theron,&nbsp;Walid Mrad,&nbsp;Aurélie Joubert,&nbsp;Fatma Haouas,&nbsp;Sonia Woudberg,&nbsp;John Puentes,&nbsp;Laurence Le Coq","doi":"10.1002/cjce.25664","DOIUrl":"https://doi.org/10.1002/cjce.25664","url":null,"abstract":"<p>The prediction of the permeability of bimodal fibrous media dedicated to air filtration, that is, highly porous media, is addressed. Two types of models, using similar input parameters (mean porosity and mean fibre diameter), are compared: several analytical models and the empirical models still commonly used by the air filtration community. It is demonstrated than even if every model under-predicts the media permeability, the isotropic versions of the analytical representative unit cell (RUC) model and Tomadakis and Robertson model yield significantly better predictions than the empirical models. The additional improvement in the analytical model predictions, by including the bimodal fibre diameter distribution as a unimodal equivalent diameter, is furthermore outlined. This model comparison is made possible due to new accurate experimental data, obtained from the characterization of the structural properties of a commercial bimodal fibrous medium. The fibre diameter distribution and mean medium porosity are determined from SEM analyses and mercury porosimetry, respectively. The anisotropic/isotropic and homogeneous/heterogeneous nature of the medium is evaluated based on X-ray micro-tomography data. Finally, to go further than the prediction of one permeability value based on mean media properties, permeability mappings are generated based on the porosity mappings and the adapted RUC permeability model.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"5065-5080"},"PeriodicalIF":1.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generalizable global kinetic model for catalyst synthesis–structure–activity relationships: Application to C3H6-SCR of NOx","authors":"Shivaraj Kumar Kummari,&nbsp;Parasuraman Selvam,&nbsp;Niket S. Kaisare,&nbsp;Preeti Aghalayam","doi":"10.1002/cjce.25656","DOIUrl":"https://doi.org/10.1002/cjce.25656","url":null,"abstract":"<p>The detrimental impacts of nitrogen oxides (NO_<i>x</i>) on health and the environment necessitates their selective catalytic reduction. Among many catalysts, Ag/γ-Al₂O₃ shows promise for effective NO_<i>x</i> reduction. However, its formulation varies in terms of preparation protocols, which influence the structural, morphological, and textural properties of Ag/γ-Al₂O₃ catalyst and ultimately impact the catalytic performance. In this work, an inclusive crucial parameter that represents the loading of Ag atoms per given area (nm²) of the catalyst surface—silver surface density (<i>σ</i>_Ag) is introduced and incorporated into a kinetic model in order to account for these catalyst properties influential factors. By mathematically formulating the sensitive rate constants based on <i>σ</i>_Ag, a simplified global kinetic model is developed that successfully validates NO_<i>x</i> conversions for large datasets of literature. The proposed model captures experiments covering diverse catalyst preparation methods for Ag/γ-Al₂O₃ (impregnation and sol–gel) and Ag loadings (2–6 wt.%). It applies well to various reactor operating conditions, including various inlet feed concentrations, flow rates, space velocities, and catalyst amounts. The developed kinetic model is identified the optimal <i>σ</i>_Ag value to 1.0, which is an important parameter for the catalyst design. The model prediction of NO_<i>x</i> conversions reached 99%, and more than 70% NO_<i>x</i> conversion is observed over a broader activity temperature window ranging from 350 to 600°C, under the estimated optimal reaction conditions. Therefore, this model, along with its versatile applicability, provides deep insights into catalyst synthesis–structure–activity relationships and delivers practical understandings for improved NO_<i>x</i> reduction in exhaust gases in automotive applications.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"5039-5055"},"PeriodicalIF":1.9,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Highlights","authors":"","doi":"10.1002/cjce.25325","DOIUrl":"https://doi.org/10.1002/cjce.25325","url":null,"abstract":"","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 4","pages":"1463"},"PeriodicalIF":1.6,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maximizing the production of total reducing sugars from sugarcane bagasse using ultrasound-assisted acid hydrolysis based on response surface methodology approach","authors":"Madhuri M. Kininge,&nbsp;Parag R. Gogate","doi":"10.1002/cjce.25653","DOIUrl":"https://doi.org/10.1002/cjce.25653","url":null,"abstract":"<p>The depletion of fossil fuels and the associated environmental impact necessitate the development of sustainable energy sources as well as feedstocks for value added chemicals. Lignocellulosic biomass, particularly sugarcane bagasse (SCB), is a promising feedstock for various industrial processes and products with the total reducing sugars (TRS) as one of the valuable intermediates. The current study focuses on maximizing TRS production from sugarcane bagasse using ultrasound-assisted acid hydrolysis. The Box–Behnken design of response surface methodology was employed to determine the best conditions for maximizing TRS concentration, with the study involving five independent variables as time, ultrasonic power, duty cycle, temperature, and acid loading. The statistical analysis predicted the best operating parameters as time of 82.77 min, ultrasonic power of 124.03 W, 60.95% duty cycle, temperature of 61°C, and acid concentration of 3.44%, resulting in the highest TRS concentration of 3.49 mg/mL. Experimental data and statistical analysis validated the quadratic model's predictive capability, demonstrating its practical applicability in enhancing TRS production efficiency. Overall, the work has demonstrated an effective method of using delignified biomass for maximizing the yield of reducing sugars based on detailed study of the effect of operating parameters.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 9","pages":"4079-4093"},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable approaches to water management and water quality in hydraulic fracturing for unconventional oil and gas development in the United States: A critical review and compilation","authors":"Ali Akbari","doi":"10.1002/cjce.25646","DOIUrl":"https://doi.org/10.1002/cjce.25646","url":null,"abstract":"<p>This study critically reviews the impact of hydraulic fracturing on water management and quality, emphasizing environmental, economic, and sustainability challenges. Hydraulic fracturing, essential for extracting hydrocarbons from unconventional reservoirs, requires significant water volumes, often competing with local water demands. The study explores the use of produced water as an alternative to freshwater, examining its potential to alleviate water scarcity while mitigating environmental risks. It identifies key challenges such as contamination from hydraulic fracturing fluids, harmful substances in produced water, and groundwater migration. Additionally, the review highlights advanced water treatment technologies, including reverse osmosis and thermal methods, for addressing the high salinity and toxicity of wastewater. Strategies for recycling and reusing produced water are analyzed to reduce freshwater dependency and improve operational efficiency. The paper also discusses innovative approaches like alternative fracturing fluids and non-aqueous additives to further enhance sustainability. Findings underscore the critical need for comprehensive water management strategies that balance resource extraction with environmental protection. Recommendations include stricter regulations, technological advancements, and adopting best practices to minimize ecological and public health risks. By addressing these challenges, the study aims to contribute to sustainable hydraulic fracturing operations that ensure the long-term viability of unconventional oil and gas development.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 9","pages":"4220-4249"},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel ensemble network based on CNN-AM-BiLSTM learner for temperature prediction of distillation columns","authors":"Jianji Ren,&nbsp;Linpeng Fu,&nbsp;Yanan Li,&nbsp;Yongliang Yuan,&nbsp;Haiqing Liu,&nbsp;Zhenxi Wang,&nbsp;Yunfeng Chen,&nbsp;Guojun Deng","doi":"10.1002/cjce.25661","DOIUrl":"https://doi.org/10.1002/cjce.25661","url":null,"abstract":"<p>In recent years, complexity has significantly increased in chemical processes where a distillation column serves as a crucial unit. It is worthwhile to develop an accurate and reliable predictive model to maintain the steady operation condition of distillation column. Although data-driven models that do not rely on any prior knowledge present a promising approach, they encounter challenges associated with nonlinearity and dynamic behaviour within process data. To tackle these challenges, a deep learning-based combined distilled spatiotemporal attention ensemble network (CDSAEN) is proposed. The CDSAEN is constructed by sequentially integrating multiple base learners, which are iteratively distilled and generated with decreasing attention span lengths through the boosting method implemented by a specially designed attention extraction evaluation function. In a base learner, convolutional neural network (CNN), attention mechanism (AM), and bidirectional long short-term memory (BiLSTM) are utilized to adaptively capture deep and intricate spatiotemporal features and establish a robust mapping relationship from inputs to output. Real-world process data from a distillation system in a chemical plant is reconstructed as a time series dataset and is subsequently fed into CDSAEN for training to forecast the temperature of the distillation column apparatus in advance. The results exhibited effectiveness and reliability. Additionally, in comparison to six other data-driven predictive approaches, the proposed method attained superior performance with mean absolute error (MAE) = 0.084, root mean squared error (RMSE) = 0.108, and <i>R</i>² = 0.974. This study can provide support for maintaining the stable operation of distillation columns in chemical processes.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 10","pages":"4859-4873"},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145037581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust optimal iterative learning control for constrained batch processes with nonuniform batch lengths","authors":"Jian Ding,&nbsp;Kaihua Gao,&nbsp;Husnain Ali,&nbsp;Furong Gao","doi":"10.1002/cjce.25666","DOIUrl":"https://doi.org/10.1002/cjce.25666","url":null,"abstract":"<p>In practical applications, the durations of operations in uncertain batch processes may fluctuate due to security considerations, physical constraints, and environmental changes. Regarding this issue, this paper addresses iterative learning control (ILC) for a class of uncertain single-input single-output (SISO) batch processes with nonuniform batch lengths. The aim is to develop an optimization-based ILC scheme that guarantees robustness while meeting input constraints requirements. Two robust optimal ILC algorithms resting upon the modified error update model are proposed for the nonuniform batch length problem, where the linear matrix inequality (LMI) optimization techniques are employed to deal with polytopic and ellipsoidal model uncertainties. Hence, the ILC design requirements are reduced to a convex optimization method involving LMIs, which results in iterative input update signals at the end of each batch. Also, the theoretical analyses of the proposed algorithms are presented. Finally, two numerical cases for batch processes are simulated to testify the feasibility and performance of the proposed methods.</p>","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 9","pages":"4343-4359"},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}