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学者姓名：谷静连
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Abstract ：
Predicting the permeate flux is critical for evaluating and optimizing the performance of the forward osmosis (FO) process. However, the solution diffusion models have poor applicability in accessing the FO process. Recently, the data-driven eXtreme Gradient Boosting (XGBoost) algorithm has been proven to be effective in processing structure data in engineering problems and has not been utilized to assess the FO process. Herein, a combination of the XGBoost model with a genetic algorithm (GA) was first proposed to predict the permeate flux, highlighting its superiority in the FO process through comparison of the support vector regression (SVR) model, the artificial neural network (ANN), and the multiple linear regression (MLR). Moreover, the performance of these models was optimized by tuning hyperparameters with a genetic algorithm (GA) and compared via Taylor Diagram. Among these machine learning (ML) models, the GA-based XGBoost model is superior to the other three models in terms of mean square error (MSE, 2.7326) and coefficient of determination (R2, 0.9721) on the test data, and its prediction power was compared to that of the solution diffusion (SD) model in the literature. Finally, further insight into the feature importance that affects the permeate flux in the FO process was examined by utilizing the SHapley Additive exPlanations (SHAP) to estimate the contribution value of various variables. The results demonstrated that the XGBoost model could predict the permeate flux in the FO system with high accuracy and good generalization ability for the given data set and even on the unseen data. Furthermore, the findings of the SHAP method show that the osmotic pressure difference, the osmotic pressure difference of draw solution and FS solution, the crossflow velocity of the feed solution and draw solution, and the water permeability coefficient have a significant impact on water flux.
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| GB/T 7714 | Shi, Fengming , Lu, Shang , Gu, Jinglian et al. Modeling and Evaluation of the Permeate Flux in Forward Osmosis Process with Machine Learning [J]. | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 . |
| MLA | Shi, Fengming et al. "Modeling and Evaluation of the Permeate Flux in Forward Osmosis Process with Machine Learning" . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2022) . |
| APA | Shi, Fengming , Lu, Shang , Gu, Jinglian , Lin, Jiuyang , Zhao, Chengxi , You, Xinqiang et al. Modeling and Evaluation of the Permeate Flux in Forward Osmosis Process with Machine Learning . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 . |
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Abstract ：
A systematic procedure is proposed for the design of a pressure-swing distillation (PSD) process for a ternary mixture. This procedure involves thermodynamic insight, global optimization, and heat integration. The aim of thermodynamic insight is to analyze the process feasibility and find all of the possible separation sequences via residue curve maps and the distillation boundaries. The global optimization for a total of 16 variables in three columns is conducted by multiobjective genetic algorithm (MOGA) with economy and environmental impact as objectives. In heat integration, a four-step heat integration MOGA method was first proposed to optimize the heat-integrated PSD process and the optimally integrated heat duty was achieved. The separation of a methanol/tetrahydrofuran/water ternary mixture is employed to elucidate the effectiveness of the proposed procedure. An energy-saving heat-integrated PSD process is obtained, and the total annual cost and CO2 emissions are reduced by 22.5 and 30.4% compared with the conventional PSD process.
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| GB/T 7714 | Gu, Jinglian , Lu, Shang , Shi, Fengming et al. Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization [J]. | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 , 61 (25) : 9004-9014 . |
| MLA | Gu, Jinglian et al. "Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization" . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 61 . 25 (2022) : 9004-9014 . |
| APA | Gu, Jinglian , Lu, Shang , Shi, Fengming , Wang, Xiujuan , You, Xinqiang . Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 , 61 (25) , 9004-9014 . |
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Abstract ：
A systematic procedure is proposed for the design of a pressure-swing distillation (PSD) process for a ternary mixture. This procedure involves thermodynamic insight, global optimization, and heat integration. The aim of thermodynamic insight is to analyze the process feasibility and find all of the possible separation sequences via residue curve maps and the distillation boundaries. The global optimization for a total of 16 variables in three columns is conducted by multiobjective genetic algorithm (MOGA) with economy and environmental impact as objectives. In heat integration, a four-step heat integration MOGA method was first proposed to optimize the heat-integrated PSD process and the optimally integrated heat duty was achieved. The separation of a methanol/tetrahydrofuran/water ternary mixture is employed to elucidate the effectiveness of the proposed procedure. An energy-saving heat-integrated PSD process is obtained, and the total annual cost and CO2 emissions are reduced by 22.5 and 30.4% compared with the conventional PSD process.
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Gu, Jinglian , Lu, Shang , Shi, Fengming et al. Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization [J]. | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 , 61 (25) : 9004-9014 . |
| MLA | Gu, Jinglian et al. "Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization" . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 61 . 25 (2022) : 9004-9014 . |
| APA | Gu, Jinglian , Lu, Shang , Shi, Fengming , Wang, Xiujuan , You, Xinqiang . Economic and Environmental Evaluation of Heat-Integrated Pressure-Swing Distillation by Multiobjective Optimization . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2022 , 61 (25) , 9004-9014 . |
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An improved model for calculating physical properties and phase behavior of confined fluids (oil and gas resources in shale reservoirs) by considering adsorption film theory was developed based on the square-well chain-like fluid with variable well-width range (SWCF-VR) equation of state. The accuracy of the improved model is greatly increased via comparing the experimental data of argon in cylindrical pores at 87.3 K. The physical properties of pure component hydrocarbons, mixture hydrocarbons, and real Bakken oils in nanopores were predicted and analyzed. The results show that the properties of confined fluids are very different from those of bulk-phase fluids, where confinement decreases the gas-liquid phase equilibrium constant (K-value), bubble point pressure, and interfacial tension of the fluid. The presence of the adsorption film further decreases the K-value and bubble point and increases the capillary pressure, and these properties change more significantly in pore radius with only a few nanometers. The results demonstrate the importance of improving the accuracy in calculating the properties and phase behaviors of confined fluids and also draw the necessity of considering the adsorption film theory.
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| GB/T 7714 | Fang, Fei , Gu, Jinglian , You, Xinqiang . Improved Model for Calculating Physical Properties of Confined Fluid by Considering Adsorption Film Theory Based on the SWCF-VR Equation of State [J]. | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2021 , 60 (35) : 13094-13106 . |
| MLA | Fang, Fei et al. "Improved Model for Calculating Physical Properties of Confined Fluid by Considering Adsorption Film Theory Based on the SWCF-VR Equation of State" . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 60 . 35 (2021) : 13094-13106 . |
| APA | Fang, Fei , Gu, Jinglian , You, Xinqiang . Improved Model for Calculating Physical Properties of Confined Fluid by Considering Adsorption Film Theory Based on the SWCF-VR Equation of State . | INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH , 2021 , 60 (35) , 13094-13106 . |
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