Industrial & Engineering Chemistry Research最新文献

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Energy Consumption of Nanofiltration Diafiltration Process: Identifying the Optimal Conditions of Continuous and Intermittent Feed Diafiltration 纳滤滤过程的能量消耗:确定连续和间歇进料滤滤的最佳条件
Industrial & Engineering Chemistry Research Pub Date : 2022-02-28 DOI: 10.1021/acs.iecr.1c04868
Qian Wang, Shi‐Peng Sun, Qigang Wu, Taoli Huhe, Zhengzhong Zhou
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引用次数: 4
State of Charge Estimation of Lithium-Ion Based on VFFRLS-Noise Adaptive CKF Algorithm 基于vffrls -噪声自适应CKF算法的锂离子电荷状态估计
Industrial & Engineering Chemistry Research Pub Date : 2022-02-24 DOI: 10.1021/acs.iecr.1c03999
Limei Wang, Ji-yong Han, Chang Liu, Guochun Li
{"title":"State of Charge Estimation of Lithium-Ion Based on VFFRLS-Noise Adaptive CKF Algorithm","authors":"Limei Wang, Ji-yong Han, Chang Liu, Guochun Li","doi":"10.1021/acs.iecr.1c03999","DOIUrl":"https://doi.org/10.1021/acs.iecr.1c03999","url":null,"abstract":"","PeriodicalId":13650,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86026360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Physics-based neural networks for simulation and synthesis of cyclic adsorption processes 基于物理的神经网络模拟和合成循环吸附过程
Industrial & Engineering Chemistry Research Pub Date : 2021-12-01 DOI: 10.26434/chemrxiv-2021-lm2sl
Sai Gokul Subraveti, Zukui Li, V. Prasad, A. Rajendran
{"title":"Physics-based neural networks for simulation and synthesis of cyclic adsorption processes","authors":"Sai Gokul Subraveti, Zukui Li, V. Prasad, A. Rajendran","doi":"10.26434/chemrxiv-2021-lm2sl","DOIUrl":"https://doi.org/10.26434/chemrxiv-2021-lm2sl","url":null,"abstract":"A computationally faster and reliable modelling approach called a physics-based artificial neural network framework for adsorption and chromatography emulation (PANACHE) is developed. PANACHE uses deep neural networks for cycle synthesis and simulation of cyclic adsorption processes. The proposed approach focuses on learning the underlying governing partial differential equations in the form of a physics-constrained loss function to simulate adsorption processes accurately. The methodology developed herein does not require any system-specific inputs such as isotherm parameters. Accordingly, unique neural network models were built to fully predict the column dynamics of different constituent steps based on unique boundary conditions that are typically encountered in adsorption processes. The trained neural network model for each constituent step aims to predict the entire spatiotemporal solutions of different state variables by obeying the underlying physical laws. The proposed approach is tested by constructing and simulating four different vacuum swing adsorption cycles for post-combustion CO2 capture without retraining the neural network models. For each cycle, 50 simulations, each corresponding to a unique set of operating conditions, are carried out until the cyclic-steady state. The results demonstrated that the purity and recovery calculated from the neural network-based simulations are within 2.5% of the detailed model's predictions. PANACHE reduced computational times by 100 times while maintaining similar accuracy of the detailed model simulations.","PeriodicalId":13650,"journal":{"name":"Industrial & Engineering Chemistry Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84204478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
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