Canadian Journal of Chemical Engineering最新文献_第4页

Data collection framework for enhanced carbon intensity indicator (CII) in the oil tankers 加强油轮碳强度指标（CII）的数据收集框架

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-10 DOI: 10.1002/cjce.25384

Abdullah Sardar, Mohan Anantharaman, T. M. Rabiul Islam, Vikram Garaniya

{"title":"Data collection framework for enhanced carbon intensity indicator (CII) in the oil tankers","authors":"Abdullah Sardar, Mohan Anantharaman, T. M. Rabiul Islam, Vikram Garaniya","doi":"10.1002/cjce.25384","DOIUrl":"10.1002/cjce.25384","url":null,"abstract":"The International Maritime Organization (IMO) aims to reduce greenhouse gas (GHG) emissions by 40% by 2030 compared with 2008. The carbon intensity indicator (CII) calculates the annual reduction factor required to continuously improve a ship's operational carbon intensity at a specific rating level. Verification and documentation of the achieved annual operational CII against the prescribed target are necessary to establish the operational carbon intensity rating. This study focuses on the intricate process of data collection for CII within the oil shipping industry, targeting engineering departments and shipboard management teams. Against the backdrop of the industry's substantial carbon dioxide emissions, the IMO has mandated the calculation of CII values for ships exceeding 5000 gross tons to promote sustainability and reduce environmental impact. We have collected emission data of 20 oil tankers over a period of 2 years using our ship maintenance and operating system (SMOS) and analyzed the data to compare the CII ratings. Our results indicate that a staggering ~63% of the vessels had the lowest CII rating of category E. It is therefore crucial to properly collect, organize, and evaluate data for CII calculation and take necessary measures to improve rating. This paper provides a deeper insight into the evolving CII calculation methodology, emphasizing the incorporation of correction factors and exclusions, and delineates the essential data collection practices needed to facilitate accurate CII calculations.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 1","pages":"170-187"},"PeriodicalIF":1.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjce.25384","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Effect of ceria morphology on hydrogen production via methane steam reforming for membrane reformer 铈形态对膜式转化炉甲烷蒸汽转化制氢的影响

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-09 DOI: 10.1002/cjce.25396

Anjali Baudh, Meenakshi Garjola, Rahul Sharma, Sweta Sharma, Rajesh Kumar Upadhyay

{"title":"Effect of ceria morphology on hydrogen production via methane steam reforming for membrane reformer","authors":"Anjali Baudh, Meenakshi Garjola, Rahul Sharma, Sweta Sharma, Rajesh Kumar Upadhyay","doi":"10.1002/cjce.25396","DOIUrl":"10.1002/cjce.25396","url":null,"abstract":"Hydrogen is a potential energy carrier in comparison to conventional fuels due to its high energy content. Methane is an attractive source for ‘on-site’ production of hydrogen by using membrane reformer due to its low cost. However, such reformers are not well studied and high temperature operation of steam methane reforming (SMR) makes the integration with membrane separation difficult. Further, the main product of SMR is CO and H2 in which CO has an inhibition effect on the membrane separation process. Therefore, it is vital to synthesize a low temperature and low CO selective catalyst for a suitable integration with membrane reformer. Nickel-based catalyst is widely used for SMR due to its low cost and high catalytic activity. CeO2 is a favoured support as it mobilizes the lattice oxygen and reduces the coke formation and CO selectivity. Though several studies are reported on CeO2 based support, the effect of CeO2 surface morphology is not studied for SMR. In the current work, Ni/CeO2 of different shapes (nanocube and nanorod) are synthesized. The complete characterization of the support was performed. The effect of support shape, calcination temperature, and reduction temperature on SMR activity is found at different operating temperatures. For each condition conversion, CO, CO2 selectivity, and hydrogen yield are calculated. The results show the CeO2 morphology has a considerable effect on conversion, CO selectivity, and hydrogen yield. It is found that ceria nanocube calcined at 550°C provides better performance at high temperature.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"102 11","pages":"3803-3816"},"PeriodicalIF":1.6,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570095","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}

引用次数: 0

Identifying design criteria for implementing inherent safety in chemical process industries part 1: Design reasoning 确定化工工艺行业固有安全的设计标准，第 1 部分：设计推理

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-09 DOI: 10.1002/cjce.25405

Zafirah Zakaria, Kamarizan Kidam, Mimi H. Hassim

{"title":"Identifying design criteria for implementing inherent safety in chemical process industries part 1: Design reasoning","authors":"Zafirah Zakaria, Kamarizan Kidam, Mimi H. Hassim","doi":"10.1002/cjce.25405","DOIUrl":"10.1002/cjce.25405","url":null,"abstract":"Recurrence of similar accidents is evidenced by past accidents, which show that accidents are not decreasing globally. It is recommended to implement the concept of inherent safety design (ISD) in the chemical process industry as a component of accident prevention strategies. This study aims to identify potential indicators of ISD for each inherent safety (IS) keyword, which will be referred to later as design reasoning (DR), based on 529 selected cases that suggest design changes that enhance the safety of processes, materials, or equipment. The cases were collected from accident cases, IS handbooks, chemical engineering journals, new product brochures, and chemical engineering magazines. The cases have to demonstrate that the new design is safer than the previous design. The design changes were evaluated to extract the corrective action and determine the common strategy employed. This information was then interpreted as DR. The collected DR were subsequently categorized and measured in terms of frequency according to IS keywords. From the statistical analysis, the highest percentage of DR is improve mixing (18%) which accounted from 95 out of 529 cases. The second is loose proximity (15.5%) and the third is fewer equipment (14.9%). For the IS keyword ranking, it can be summarized that: moderation (40%) >minimization (27%) >simplification (21%) >substitution (12%). Results showed that moderation inherent safety is a popular strategy used to implement IS. The findings serve as a valuable reference for designers or engineer attempting to implement ISD in their design task.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"102 11","pages":"3692-3701"},"PeriodicalIF":1.6,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584712","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}

引用次数: 0

Issue Highlights 发行亮点

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-08 DOI: 10.1002/cjce.24995

引用次数: 0

Risk assessment of gas pipeline using an integrated Bayesian belief network and GIS: Using Bayesian neural networks for external pitting corrosion modelling 利用综合贝叶斯信念网络和地理信息系统对天然气管道进行风险评估：利用贝叶斯神经网络进行外部点蚀建模

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-07 DOI: 10.1002/cjce.25393

Haile Woldesellasse, Solomon Tesfamariam

{"title":"Risk assessment of gas pipeline using an integrated Bayesian belief network and GIS: Using Bayesian neural networks for external pitting corrosion modelling","authors":"Haile Woldesellasse, Solomon Tesfamariam","doi":"10.1002/cjce.25393","DOIUrl":"10.1002/cjce.25393","url":null,"abstract":"Corrosion poses a great risk to the integrity of oil and gas pipelines, leading to substantial investments in corrosion control and management. Several studies have been conducted on accurately estimating the maximum pitting depth in oil and gas pipelines using available field data. Some of the frequently employed machine learning techniques include artificial neural networks, random forests, fuzzy logic, Bayesian belief networks, and support vector machines. Despite the ability of machine learning methods to address a variety of problems, traditional machine learning methods have evident limitations, such as overfitting, which can diminish the model's generalization capabilities. Additionally, traditional machine learning models that provide point estimations are incapable of addressing uncertainties. In the current study, a Bayesian neural network is proposed to include uncertainty in estimating the corrosion defect of a pipeline exposed to external pitting corrosion. The results are then incorporated into a Bayesian belief network for evaluating the probability of failure and its corresponding consequences in terms of social impact, thus forming a comprehensive risk assessment framework. The results of the Bayesian neural network are validated using field data and achieved a testing accuracy of 90%. The framework of the study offers a powerful decision-making tool for the integrity management of pipelines against external corrosion.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 1","pages":"98-109"},"PeriodicalIF":1.6,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjce.25393","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Simultaneous state-estimator tuning and parameter estimation for systems with nonstationary disturbances, multi-rate data, and measurement delays 具有非稳态干扰、多速率数据和测量延迟的系统的同步状态估计器调整和参数估计

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-03 DOI: 10.1002/cjce.25386

Qiujun A. Liu, Kimberley B. McAuley

{"title":"Simultaneous state-estimator tuning and parameter estimation for systems with nonstationary disturbances, multi-rate data, and measurement delays","authors":"Qiujun A. Liu, Kimberley B. McAuley","doi":"10.1002/cjce.25386","DOIUrl":"10.1002/cjce.25386","url":null,"abstract":"Model-based monitoring and control of chemical and biochemical processes rely on state estimators such as extended Kalman filters (EKFs) to ensure accurate online model predictions. Accurate predictions depend on appropriate model parameters and suitable state-estimator tuning factors. Extensions to our previously developed simultaneous parameter estimation and tuning (SPET) method are proposed so that SPET can be used for systems with nonstationary disturbances, time-varying parameters, multi-rate data, and measurement delays. A continuous stirred tank reactor (CSTR) case study with simulated data is used to illustrate and test the proposed method. Superior online model predictions and state-estimator performance are achieved using SPET compared to a traditional approach for parameter estimation and EKF tuning, with improvements in the average sum-of-squared prediction errors ranging from 3% to 52% for the scenarios tested. The SPET approach will also be useful for more-advanced state estimators that require the same tuning information as EKFs.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 1","pages":"323-338"},"PeriodicalIF":1.6,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjce.25386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Large-scale synthesis of nano-ZIF-90 from zinc chloride application orientation heat storage materials 从氯化锌大规模合成纳米 ZIF-90 应用于定向蓄热材料

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-02 DOI: 10.1002/cjce.25382

Ta Ngoc Don, Le Van Duong, Nguyen Thi Hong Phuong, Nguyen Thi Thu Huyen, Ta Ngoc Thien Huy, Danh Mo, Bui Thi Thanh Ha, Vy Anh Tran

{"title":"Large-scale synthesis of nano-ZIF-90 from zinc chloride application orientation heat storage materials","authors":"Ta Ngoc Don, Le Van Duong, Nguyen Thi Hong Phuong, Nguyen Thi Thu Huyen, Ta Ngoc Thien Huy, Danh Mo, Bui Thi Thanh Ha, Vy Anh Tran","doi":"10.1002/cjce.25382","DOIUrl":"10.1002/cjce.25382","url":null,"abstract":"The paper presents the results of the first research on the synthesis of nano-ZIF-90 from zinc chloride. More specifically, the paper also introduces the results of large-scale pure nano-ZIF-90 synthesis with a high specific surface, uniform cubic crystals, and good thermal strength. ZIF-90 is synthesized from zinc chloride-containing medium capillaries, which have both a weak acid center and a strong base center. The post-synthetic ZIF-90 was also evaluated for heat storage based on its ability to adsorb water, methanol, and ethanol. XRD, FTIR, SEM, TEM, N2 adsorption and desorption methods, TG mass thermal analysis, and NH3-TPD/CO2-TPD were used to study the ZIF-90 crystallization process with modifications of precursors, solvents, additives, and reaction conditions. From this, a large-scale synthesis of nano-ZIF-90 from high-efficiency zinc chloride has been derived. DSC measurements are used to evaluate the enthalpy adsorption of water, methanol, and ethanol on ZIF-90.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"103 1","pages":"311-322"},"PeriodicalIF":1.6,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548585","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}

引用次数: 0

Development of new correlation for the prediction of power number for closed clearance impellers using machine learning methods trained on literature data 使用根据文献数据训练的机器学习方法，开发用于预测闭式间隙叶轮功率数的新相关性

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-02 DOI: 10.1002/cjce.25385

Sumit S. Joshi, Vishwanath H. Dalvi, Vivek S. Vitankar, Jyeshtharaj B. Joshi, Aniruddha J. Joshi

{"title":"Development of new correlation for the prediction of power number for closed clearance impellers using machine learning methods trained on literature data","authors":"Sumit S. Joshi, Vishwanath H. Dalvi, Vivek S. Vitankar, Jyeshtharaj B. Joshi, Aniruddha J. Joshi","doi":"10.1002/cjce.25385","DOIUrl":"10.1002/cjce.25385","url":null,"abstract":"The accurate estimation of the power number for closed clearance impellers holds significant importance in industries such as chemical, biochemical, paper and pulp, as well as paints, pigments, and polymers. Existing state-of-the-art correlations for predicting power numbers, however, are inaccurate for impeller Reynolds number <math>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mi>R</mi>\u0000 <msub>\u0000 <mi>e</mi>\u0000 <mi>I</mi>\u0000 </msub>\u0000 </mrow>\u0000 </mfenced>\u0000 <mo>></mo>\u0000 <mn>100</mn>\u0000 </mrow></math>. In this study, we compiled a dataset of 1470 data points from 15 research articles in the open literature, covering five types of impellers: (i) anchor; (ii) gate; (iii) single helical ribbon; (iv) double helical ribbon; and (v) helical ribbon with screw. Six machine learning models, namely artificial neural networks (ANN), CatBoost regressor, extra tree regressor, support vector regressor, random forest, and XGBoost regressor, were developed and compared. The results revealed that ANN emerged as the most efficient model, demonstrating the highest testing R2 value of 0.99 and the lowest testing MAPE of 7.3%. Further, we used the ANN model to develop a novel set of process correlations to estimate impeller power numbers for the industrially important anchor and double helical ribbon impellers: which significantly outperform the existing state-of-the-art correlations available in literature.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"102 11","pages":"3832-3851"},"PeriodicalIF":1.6,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141552754","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}

引用次数: 0

Data-driven battery capacity estimation using support vector regression and model bagging under fast-charging conditions 在快速充电条件下使用支持向量回归和模型袋法进行数据驱动的电池容量估算

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-02 DOI: 10.1002/cjce.25394

Yixiu Wang, Qiyue Luo, Liang Cao, Arpan Seth, Jianfeng Liu, Bhushan Gopaluni, Yankai Cao

{"title":"Data-driven battery capacity estimation using support vector regression and model bagging under fast-charging conditions","authors":"Yixiu Wang, Qiyue Luo, Liang Cao, Arpan Seth, Jianfeng Liu, Bhushan Gopaluni, Yankai Cao","doi":"10.1002/cjce.25394","DOIUrl":"10.1002/cjce.25394","url":null,"abstract":"Lithium-ion batteries offer significant advantages in terms of their high energy and power density and efficiency, but capacity degradation remains a major issue during their usage. Accurately estimating the remaining capacity is crucial for ensuring safe operations, leading to the development of precise capacity estimation models. Data-driven models have emerged as a promising approach for capacity estimation. However, existing models predominantly focus on constant current charging conditions, limiting their applicability in real-world scenarios where fast-charging conditions are commonly employed. The primary objective of this work is to develop a more versatile machine learning model (i.e., support vector regression [SVR]) capable of estimating battery capacity under fast-charging conditions, with broader applicability across various work conditions. Genetic algorithm and cross-validation techniques are employed to simultaneously optimize feature extraction hyperparameters and SVR hyperparameters. A model bagging method is further implemented to address prediction challenges under unknown fast-charging conditions. The effectiveness of the developed model is validated on a cycling dataset of lithium-ion batteries under different two-stage fast-charging conditions.","PeriodicalId":9400,"journal":{"name":"Canadian Journal of Chemical Engineering","volume":"102 10","pages":"3322-3332"},"PeriodicalIF":1.6,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cjce.25394","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Effect of anti-Agglomerants on carbon dioxide hydrate formation in oil–water systems 抗凝聚剂对油水体系中二氧化碳水合物形成的影响

IF 1.6 4区工程技术

Canadian Journal of Chemical Engineering Pub Date : 2024-07-02 DOI: 10.1002/cjce.25383

Shaochang Huang, Xiao Wang, Guiyang Ma, Chunyang Zang

引用次数: 0