The Experts below are selected from a list of 52692 Experts worldwide ranked by ideXlab platform
Fengrui Sun - One of the best experts on this subject based on the ideXlab platform.
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Entropy Generation Minimization for Reverse Water Gas Shift (RWGS) Reactors
MDPI AG, 2018Co-Authors: Lei Zhang, Shaojun Xia, Chao Wang, Lingen Chen, Fengrui SunAbstract:Thermal design and optimization for reverse water gas shift (RWGS) reactors is particularly important to fuel synthesis in naval or commercial scenarios. The RWGS reactor with irreversibilities of heat transfer, chemical reaction and viscous flow is studied based on finite time thermodynamics or entropy generation minimization theory in this paper. The total entropy generation rate (EGR) in the RWGS reactor with different boundary conditions is minimized subject to specific feed compositions and chemical conversion using optimal control theory, and the optimal configurations obtained are compared with three reference reactors with linear, constant Reservoir Temperature and constant heat flux operations, which are commonly used in engineering. The results show that a drastic EGR reduction of up to 23% can be achieved by optimizing the Reservoir Temperature profile, the inlet Temperature of feed gas and the reactor length simultaneously, compared to that of the reference reactor with the linear Reservoir Temperature. These optimization efforts are mainly achieved by reducing the irreversibility of heat transfer. Optimal paths have subsections of relatively constant thermal force, chemical force and local EGR. A conceptual optimal design of sandwich structure for the compact modular reactor is proposed, without elaborate control tools or excessive interstage equipment. The results can provide guidelines for designing industrial RWGS reactors in naval or commercial scenarios
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power density analysis and optimization of an irreversible closed intercooled regenerated brayton cycle
Mathematical and Computer Modelling, 2008Co-Authors: Junhua Wang, Fengrui SunAbstract:In this paper, power density, defined as the ratio of power output to the maximum specific volume in the cycle, is optimized for an irreversible closed intercooled regenerated Brayton cycle coupled to constant-Temperature heat Reservoirs in the viewpoint of the theory of thermodynamic optimization. The analytical formulae for dimensionless power density and efficiency, as functions of the total pressure ratio, the intercooling pressure ratio, the components (the regenerator, the intercooler, the hot- and cold-side heat exchangers) effectiveness, the compressor and turbine efficiencies, the heat Reservoir Temperature ratio, and the Temperature ratio of the cooling fluid in the intercooler and the cold-side heat Reservoir, are derived. The optimum dimensionless power density is obtained by optimizing the intercooling pressure ratio. The maximum dimensionless power density is obtained by searching the optimum heat conductance distributions between the hot- and cold-side heat exchangers for a fixed total heat exchanger inventory and fixed heat conductance distributions of the regenerator and the intercooler, and by searching the optimum intercooling pressure ratio. When the optimization is performed with respect to the total pressure ratio of the cycle, the maximum dimensionless power density can be maximized again, and a double-maximum power density and the corresponding optimum total pressure ratios are obtained. The effects of the heat Reservoir Temperature ratio, the Temperature ratio of the cooling fluid in the intercooler and the cold-side heat Reservoir, the efficiencies of the compressors and the turbine, and the total heat exchanger inventory on the optimum power density, the maximum power density, and the double-maximum power density and the corresponding optimal total pressure ratio are analyzed by numerical examples. In the analysis, the heat resistance losses in the four heat exchangers, and the irreversible compression and expansion losses in the compressors and the turbine are taken into account.
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power optimization of an endoreversible closed intercooled regenerated brayton cycle
International Journal of Thermal Sciences, 2005Co-Authors: Wenhua Wang, Fengrui SunAbstract:Abstract In this paper, power is optimized for an endoreversible closed intercooled regenerated Brayton cycle coupled to constant-Temperature heat Reservoirs in the viewpoint of finite-time thermodynamics (FTT) or entropy generation minimization (EGM). The effects of some design parameters, including the cycle heat Reservoir Temperature ratio and total heat exchanger inventory, on the maximum power and the corresponding efficiency are analyzed by numerical examples. The analysis shows that the cycle dimensionless power can be optimized by searching the optimum heat conductance distributions among the hot- and cold-side heat exchangers, the regenerator and the intercooler for fixed total heat exchanger inventory, and by searching the optimum intercooling pressure ratio. When the optimization is performed with respect to the total pressure ratio of the cycle, the maximum dimensionless power can be maximized again.
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closed intercooled regenerator brayton cycle with constant Temperature heat Reservoirs
Applied Energy, 2004Co-Authors: Wenhua Wang, Fengrui SunAbstract:The performance of an irreversible closed intercooled regenerator Brayton-cycle coupled to constant-Temperature heat Reservoirs is analyzed by using the theory of finite-time thermodynamics (FTT). Analytical formulae for dimensionless power and efficiency are derived. Especially, the intercooling pressure-ratio is optimized for the optimal power and the optimal efficiency, respectively. The effects of component (the intercooler, the regenerator, and the hot- and cold-side heat-exchangers) effectivenesses, the compressor and turbine efficiencies, the heat-Reservoir Temperature-ratio, and the Temperature ratio of the cooling fluid in the intercooler and the cold-side heat Reservoir on the optimal power and the corresponding efficiency and corresponding intercooling pressure ratio, as well as the optimal efficiency and the corresponding power and corresponding intercooling pressure-ratio are analyzed by detailed numerical examples.
Shahab Ayatollahi - One of the best experts on this subject based on the ideXlab platform.
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on the determination of co2 crude oil minimum miscibility pressure using genetic programming combined with constrained multivariable search methods
Fuel, 2016Co-Authors: Mohammad Fathinasab, Shahab AyatollahiAbstract:Abstract In addition to reducing carbon dioxide (CO2) emission, the high oil recovery efficiency achieved by CO2 injection processes makes CO2 injection a desirable enhance oil recovery (EOR) technique. Minimum miscibility pressure (MMP) is an important parameter in successful designation of any miscible gas injection process such as CO2 flooding; therefore, its accurate determination is of great importance. The current experimental techniques for determining MMP are expensive and time-consuming. In this study, multi-gene genetic programming has been combined with constrained multivariable search methods, and a simple empirical model has been developed which provides a reliable estimation of MMP in a wide range of Reservoirs, injection gases and crude oil systems. The experimental data for developing the proposed correlation consists of 270 data points from twenty-six authenticated literature sources. This model utilizes Reservoir Temperature, molecular weight of C5+, volatile (N2 and C1) to intermediate (H2S, CO2, C2, C3, C4) ratio and pseudo critical Temperature of the injection gas as input parameters. Both statistical and graphical error analyses have been employed to evaluate the accuracy and validity of the proposed model compared to the pre-existing correlations. The results showed that the new model provides an average absolute relative error of 11.76%. Moreover, the relevancy factor indicated that the Reservoir Temperature has the greatest impact on the minimum miscibility pressure.
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a rigorous approach to predict nitrogen crude oil minimum miscibility pressure of pure and nitrogen mixtures
Fluid Phase Equilibria, 2015Co-Authors: Mohammad Fathinasab, Shahab Ayatollahi, Abdolhossein HemmatisarapardehAbstract:Abstract Nitrogen has been appeared as a competitive gas injection alternative for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N 2 flooding, which is traditionally measured through time consuming, expensive and cumbersome experiments. In this communication, genetic programming (GP) and constrained multivariable search methods have been combined to create a simple correlation for accurate determination of the MMP of N 2 -crude oil, based on the explicit functionality of Reservoir Temperature as well as thermodynamic properties of crude oil and injection gas. The parameters of the developed correlation include Reservoir Temperature, average critical Temperature of injection gas, volatile and intermediate fractions of Reservoir oil and heptane plus-fraction molecular weight of crude oil. A set of experimental data pool from the literature was collected to evaluate and compare the results of the developed correlation with pre-existing correlations through statistical and graphical error analyses. The results of this study illustrate that the proposed correlation is more reliable and accurate than the pre-existing models in a wide range of thermodynamic and process conditions. The proposed correlation predicts the total data set (93 MMP data of pure and N 2 mixture streams as well as lean gases) with an average absolute relative error of 10.02%. Finally, by employing the relevancy factor, it was found that the intermediate components of crude oil have the most significant impact on the nitrogen MMP estimation.
Mohammad Fathinasab - One of the best experts on this subject based on the ideXlab platform.
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on the determination of co2 crude oil minimum miscibility pressure using genetic programming combined with constrained multivariable search methods
Fuel, 2016Co-Authors: Mohammad Fathinasab, Shahab AyatollahiAbstract:Abstract In addition to reducing carbon dioxide (CO2) emission, the high oil recovery efficiency achieved by CO2 injection processes makes CO2 injection a desirable enhance oil recovery (EOR) technique. Minimum miscibility pressure (MMP) is an important parameter in successful designation of any miscible gas injection process such as CO2 flooding; therefore, its accurate determination is of great importance. The current experimental techniques for determining MMP are expensive and time-consuming. In this study, multi-gene genetic programming has been combined with constrained multivariable search methods, and a simple empirical model has been developed which provides a reliable estimation of MMP in a wide range of Reservoirs, injection gases and crude oil systems. The experimental data for developing the proposed correlation consists of 270 data points from twenty-six authenticated literature sources. This model utilizes Reservoir Temperature, molecular weight of C5+, volatile (N2 and C1) to intermediate (H2S, CO2, C2, C3, C4) ratio and pseudo critical Temperature of the injection gas as input parameters. Both statistical and graphical error analyses have been employed to evaluate the accuracy and validity of the proposed model compared to the pre-existing correlations. The results showed that the new model provides an average absolute relative error of 11.76%. Moreover, the relevancy factor indicated that the Reservoir Temperature has the greatest impact on the minimum miscibility pressure.
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a rigorous approach to predict nitrogen crude oil minimum miscibility pressure of pure and nitrogen mixtures
Fluid Phase Equilibria, 2015Co-Authors: Mohammad Fathinasab, Shahab Ayatollahi, Abdolhossein HemmatisarapardehAbstract:Abstract Nitrogen has been appeared as a competitive gas injection alternative for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N 2 flooding, which is traditionally measured through time consuming, expensive and cumbersome experiments. In this communication, genetic programming (GP) and constrained multivariable search methods have been combined to create a simple correlation for accurate determination of the MMP of N 2 -crude oil, based on the explicit functionality of Reservoir Temperature as well as thermodynamic properties of crude oil and injection gas. The parameters of the developed correlation include Reservoir Temperature, average critical Temperature of injection gas, volatile and intermediate fractions of Reservoir oil and heptane plus-fraction molecular weight of crude oil. A set of experimental data pool from the literature was collected to evaluate and compare the results of the developed correlation with pre-existing correlations through statistical and graphical error analyses. The results of this study illustrate that the proposed correlation is more reliable and accurate than the pre-existing models in a wide range of thermodynamic and process conditions. The proposed correlation predicts the total data set (93 MMP data of pure and N 2 mixture streams as well as lean gases) with an average absolute relative error of 10.02%. Finally, by employing the relevancy factor, it was found that the intermediate components of crude oil have the most significant impact on the nitrogen MMP estimation.
Wenhua Wang - One of the best experts on this subject based on the ideXlab platform.
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power optimization of an endoreversible closed intercooled regenerated brayton cycle
International Journal of Thermal Sciences, 2005Co-Authors: Wenhua Wang, Fengrui SunAbstract:Abstract In this paper, power is optimized for an endoreversible closed intercooled regenerated Brayton cycle coupled to constant-Temperature heat Reservoirs in the viewpoint of finite-time thermodynamics (FTT) or entropy generation minimization (EGM). The effects of some design parameters, including the cycle heat Reservoir Temperature ratio and total heat exchanger inventory, on the maximum power and the corresponding efficiency are analyzed by numerical examples. The analysis shows that the cycle dimensionless power can be optimized by searching the optimum heat conductance distributions among the hot- and cold-side heat exchangers, the regenerator and the intercooler for fixed total heat exchanger inventory, and by searching the optimum intercooling pressure ratio. When the optimization is performed with respect to the total pressure ratio of the cycle, the maximum dimensionless power can be maximized again.
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closed intercooled regenerator brayton cycle with constant Temperature heat Reservoirs
Applied Energy, 2004Co-Authors: Wenhua Wang, Fengrui SunAbstract:The performance of an irreversible closed intercooled regenerator Brayton-cycle coupled to constant-Temperature heat Reservoirs is analyzed by using the theory of finite-time thermodynamics (FTT). Analytical formulae for dimensionless power and efficiency are derived. Especially, the intercooling pressure-ratio is optimized for the optimal power and the optimal efficiency, respectively. The effects of component (the intercooler, the regenerator, and the hot- and cold-side heat-exchangers) effectivenesses, the compressor and turbine efficiencies, the heat-Reservoir Temperature-ratio, and the Temperature ratio of the cooling fluid in the intercooler and the cold-side heat Reservoir on the optimal power and the corresponding efficiency and corresponding intercooling pressure ratio, as well as the optimal efficiency and the corresponding power and corresponding intercooling pressure-ratio are analyzed by detailed numerical examples.
Fanhua Zeng - One of the best experts on this subject based on the ideXlab platform.
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simulation of co2 oil minimum miscibility pressure mmp for co2 enhanced oil recovery eor using neural networks
Energy Procedia, 2013Co-Authors: Guangying Chen, Xiangzeng Wang, Zhiwu Liang, Ruimin Gao, Teerawat Sema, Peng Luo, Fanhua ZengAbstract:Abstract CO2-oil minimum miscibility pressure (MMP) is a key parameter in CO2 enhanced oil recovery (CO2-EOR) process. This work developed a fast and vigorous mathematical method using artificial neural network (ANN) model based on genetic algorithm to predict the CO2-oil MMP which was affected by several factors (i.e. Reservoir Temperature, the composition of Reservoir oil, and the composition of injected gas). The study evaluated the performance of the newly developed ANN-based model by the errors between the predicted values and the target values. It was found that the developed ANN model provided a reliable theoretical basis for CO2 flooding, as well as offered a guidance to the successful implementation of CO2-EOR process.
