This research proposes a modified two-dimensional Peng-Robinson equation model to predict adsorption isotherm in adsorbate-adsorbent systems. The parameters of the proposed model are calculated by using the optimizati...This research proposes a modified two-dimensional Peng-Robinson equation model to predict adsorption isotherm in adsorbate-adsorbent systems. The parameters of the proposed model are calculated by using the optimization of experimental data for the different single gas adsorption systems at various temperatures. The experimental adsorption equilibrium data of adsorbate-adsorbent systems was compared with the calculated results in our proposed model and the two-dimensional Hill-deBoer equation model. The proposed model as indicated in the results shows a better prediction of the experimental results compared with two others.展开更多
This paper is to investigate a variable-coefficient modified Kortweg-de Vries （vc-mKdV） model, which describes some situations from fluid mechanics, ocean dynamics, and plasma mechanics. By the AblowRz-Kaup-NewellSe...This paper is to investigate a variable-coefficient modified Kortweg-de Vries （vc-mKdV） model, which describes some situations from fluid mechanics, ocean dynamics, and plasma mechanics. By the AblowRz-Kaup-NewellSegur procedure and symbolic computation, the Lax pair of the vc-MKdV model is derived. Then, based on the aforementioned Lax pair, the Darboux transformation is constructed and a new one-soliton-like solution is obtained as weft Features of the one-soliton-like solution are analyzed and graphically discussed to illustrate the influence of the variable coefficients in the solitonlike propagation.展开更多
In this paper, we extend the mapping transformation method through introducing variable coefficients.By means of the extended mapping transformation method, many explicit and exact general solutions with arbitrary fun...In this paper, we extend the mapping transformation method through introducing variable coefficients.By means of the extended mapping transformation method, many explicit and exact general solutions with arbitrary functions for some nonlinear partial differential equations, which contain solitary wave solutions, trigonometric function solutions, and rational solutions, are obtained.展开更多
Solubility of quinine in supercritical carbon dioxide(SCCO_2) was experimentally measured in the pressure range of 8 to 24 MPa, at three constant temperatures: 308.15 K, 318.15 K and 328.15 K. Measurement was carried ...Solubility of quinine in supercritical carbon dioxide(SCCO_2) was experimentally measured in the pressure range of 8 to 24 MPa, at three constant temperatures: 308.15 K, 318.15 K and 328.15 K. Measurement was carried out in a semi-dynamic system. Experimental data were correlated by iso-fugacity model(based on cubic equations of state, CEOS), Modified Mendez–Santiago–Teja(MST) and Modified Bartle semi-empirical models. Two cubic equations of state: Peng–Robinson(PR) and Dashtizadeh–Pazuki–Ghotbi–Taghikhani(DPTG) were adopted for calculation of equilibrium parameters in CEOS modeling. Interaction coefficients(k_(ij)& l_(ij)) of van der Waals(vdW) mixing rules were considered as the correlation parameters in CEOS-based modeling and their contribution to the accuracy of model was investigated. Average Absolute Relative Deviation(AARD) between correlated and experimental data was calculated and compared as the index of validity and accuracy for different modeling systems. In this basis it was realized that the semi-empirical equations especially Modified MST can accurately support the theoretical studies on phase equilibrium behavior of quinine–SCCO_2 media. Among the cubic equations of state DPGT within two-parametric vd W mixing rules provided the best data fitting and PR within one-parametric vd W mixing rules demonstrated the highest deviation respecting to the experimental data. Overall, in each individual modeling system the best fitting was observed on the data points attained at 318 K, which could be perhaps due to the moderate thermodynamic state of supercritical phase.展开更多
Two-level system model based probabilistic steady-state and dynamic security assessment model is introduced in this paper.Uncertainties of nodal power injection caused by wind power and load demand,steady-state and dy...Two-level system model based probabilistic steady-state and dynamic security assessment model is introduced in this paper.Uncertainties of nodal power injection caused by wind power and load demand,steady-state and dynamic security constraints and transitions between system configurations in terms of failure rate and repair rate are considered in the model.Time to insecurity is used as security index.The probability distribution of time to insecurity can be obtained by solving a linear vector differential equation.The coefficients of the differential equation are expressed in terms of configuration transition rates and security transition probabilities.The model is implemented in complex system successfully for the first time by using the following effective measures:firstly,calculating configuration transition rates effectively based on component state transition rate matrix and system configuration array;secondly,calculating the probability of random nodal power injection belonging to security region effectively according to practical parts of critical boundaries of security region represented by hyper-planes;thirdly,locating non-zero elements of coefficient matrix and then implementing sparse storage of coefficient matrix effectively;finally,calculating security region off-line for on-line use.Results of probabilistic security assessment can be used to conduct operators to analyze system security effectively and take preventive control.Test results on New England 10-generators and 39-buses power system verify the reasonableness and effectiveness of the method.展开更多
With the rapid development of artificial intelligence techniques such as neural networks,data-driven machine learning methods are popular in improving and constructing turbulence models.For high Reynolds number turbul...With the rapid development of artificial intelligence techniques such as neural networks,data-driven machine learning methods are popular in improving and constructing turbulence models.For high Reynolds number turbulence in aerodynamics,our previous work built a data-driven model applicable to subsonic airfoil flows with different free stream conditions.The results calculated by the proposed model are encouraging.In this work,we aim to model the turbulence of transonic wing flows with fully connected deep neural networks,where there is less research at present.The proposed model is driven by two flow cases of the ONERA(Office National d'Etudes et de Recherches Aerospatiales)wing and coupled with the Navier-Stokes equation solver.Four subcritical and transonic benchmark cases of different wings are used to evaluate the model performance.The iteration process is stable,and final convergence is achieved.The proposed model can be used to surrogate the traditional Reynolds averaged Navier-Stokes turbulence model.Compared with the data calculated by the Spallart-Allmaras model,the results show that the proposed model can be well generalized to the test cases.The mean relative error of the drag coefficient at different sections is below 4%for each case.This work demonstrates that modeling turbulence by data-driven methods is feasible and that our modeling pattern is effective.展开更多
The Cellular Automaton(CA) modeling and simulation of solid dynamics is a long-standing difficult problem.In this paper we present a new two-dimensional CA model for solid dynamics.In this model the solid body is repr...The Cellular Automaton(CA) modeling and simulation of solid dynamics is a long-standing difficult problem.In this paper we present a new two-dimensional CA model for solid dynamics.In this model the solid body is represented by a set of white and black particles alternatively positioned in the x-and y-directions.The force acting on each particle is represented by the linear summation of relative displacements of the nearest-neighboring particles.The key technique in this new model is the construction of eight coefficient matrices.Theoretical and numerical analyses show that the present model can be mathematically described by a conservative system.So,it works for elastic material.In the continuum limit the CA model recovers the well-known Navier equation.The coefficient matrices are related to the shear module and Poisson ratio of the material body.Compared with previous CA model for solid body,this model realizes the natural coupling of deformations in the x-and y-directions.Consequently,the wave phenomena related to the Poisson ratio effects are successfully recovered.This work advances significantly the CA modeling and simulation in the field of computational solid dynamics.展开更多
文摘This research proposes a modified two-dimensional Peng-Robinson equation model to predict adsorption isotherm in adsorbate-adsorbent systems. The parameters of the proposed model are calculated by using the optimization of experimental data for the different single gas adsorption systems at various temperatures. The experimental adsorption equilibrium data of adsorbate-adsorbent systems was compared with the calculated results in our proposed model and the two-dimensional Hill-deBoer equation model. The proposed model as indicated in the results shows a better prediction of the experimental results compared with two others.
基金Supported by the National Natural Science Foundation of China under Grant No. 60772023by the Open Fund of the State Key Laboratory of Software Development Environment under Grant No. BUAA-SKLSDE-09KF-04+1 种基金Beijing University of Aeronautics and Astronautics, by the National Basic Research Program of China (973 Program) under Grant No. 2005CB321901by the Specialized Research Fund for the Doctoral Program of Higher Education under Grant Nos. 20060006024 and 200800130006, Chinese Ministry of Education
文摘This paper is to investigate a variable-coefficient modified Kortweg-de Vries （vc-mKdV） model, which describes some situations from fluid mechanics, ocean dynamics, and plasma mechanics. By the AblowRz-Kaup-NewellSegur procedure and symbolic computation, the Lax pair of the vc-MKdV model is derived. Then, based on the aforementioned Lax pair, the Darboux transformation is constructed and a new one-soliton-like solution is obtained as weft Features of the one-soliton-like solution are analyzed and graphically discussed to illustrate the influence of the variable coefficients in the solitonlike propagation.
文摘In this paper, we extend the mapping transformation method through introducing variable coefficients.By means of the extended mapping transformation method, many explicit and exact general solutions with arbitrary functions for some nonlinear partial differential equations, which contain solitary wave solutions, trigonometric function solutions, and rational solutions, are obtained.
基金Supported by the National Natural Science Foundation of China(20976103)
文摘Solubility of quinine in supercritical carbon dioxide(SCCO_2) was experimentally measured in the pressure range of 8 to 24 MPa, at three constant temperatures: 308.15 K, 318.15 K and 328.15 K. Measurement was carried out in a semi-dynamic system. Experimental data were correlated by iso-fugacity model(based on cubic equations of state, CEOS), Modified Mendez–Santiago–Teja(MST) and Modified Bartle semi-empirical models. Two cubic equations of state: Peng–Robinson(PR) and Dashtizadeh–Pazuki–Ghotbi–Taghikhani(DPTG) were adopted for calculation of equilibrium parameters in CEOS modeling. Interaction coefficients(k_(ij)& l_(ij)) of van der Waals(vdW) mixing rules were considered as the correlation parameters in CEOS-based modeling and their contribution to the accuracy of model was investigated. Average Absolute Relative Deviation(AARD) between correlated and experimental data was calculated and compared as the index of validity and accuracy for different modeling systems. In this basis it was realized that the semi-empirical equations especially Modified MST can accurately support the theoretical studies on phase equilibrium behavior of quinine–SCCO_2 media. Among the cubic equations of state DPGT within two-parametric vd W mixing rules provided the best data fitting and PR within one-parametric vd W mixing rules demonstrated the highest deviation respecting to the experimental data. Overall, in each individual modeling system the best fitting was observed on the data points attained at 318 K, which could be perhaps due to the moderate thermodynamic state of supercritical phase.
文摘Two-level system model based probabilistic steady-state and dynamic security assessment model is introduced in this paper.Uncertainties of nodal power injection caused by wind power and load demand,steady-state and dynamic security constraints and transitions between system configurations in terms of failure rate and repair rate are considered in the model.Time to insecurity is used as security index.The probability distribution of time to insecurity can be obtained by solving a linear vector differential equation.The coefficients of the differential equation are expressed in terms of configuration transition rates and security transition probabilities.The model is implemented in complex system successfully for the first time by using the following effective measures:firstly,calculating configuration transition rates effectively based on component state transition rate matrix and system configuration array;secondly,calculating the probability of random nodal power injection belonging to security region effectively according to practical parts of critical boundaries of security region represented by hyper-planes;thirdly,locating non-zero elements of coefficient matrix and then implementing sparse storage of coefficient matrix effectively;finally,calculating security region off-line for on-line use.Results of probabilistic security assessment can be used to conduct operators to analyze system security effectively and take preventive control.Test results on New England 10-generators and 39-buses power system verify the reasonableness and effectiveness of the method.
基金supported by the National Natural Science Foundation of China(Grant Nos.92152301,and 91852115)the National Numerical Wind tunnel Project(Grand No.NNW2018-ZT1B01).
文摘With the rapid development of artificial intelligence techniques such as neural networks,data-driven machine learning methods are popular in improving and constructing turbulence models.For high Reynolds number turbulence in aerodynamics,our previous work built a data-driven model applicable to subsonic airfoil flows with different free stream conditions.The results calculated by the proposed model are encouraging.In this work,we aim to model the turbulence of transonic wing flows with fully connected deep neural networks,where there is less research at present.The proposed model is driven by two flow cases of the ONERA(Office National d'Etudes et de Recherches Aerospatiales)wing and coupled with the Navier-Stokes equation solver.Four subcritical and transonic benchmark cases of different wings are used to evaluate the model performance.The iteration process is stable,and final convergence is achieved.The proposed model can be used to surrogate the traditional Reynolds averaged Navier-Stokes turbulence model.Compared with the data calculated by the Spallart-Allmaras model,the results show that the proposed model can be well generalized to the test cases.The mean relative error of the drag coefficient at different sections is below 4%for each case.This work demonstrates that modeling turbulence by data-driven methods is feasible and that our modeling pattern is effective.
基金Supported by the Science Foundations of China Academy of Engineering Physics under Grant Nos. 2012B0101014 and 2011A0201002National Natural Science Foundation of China under Grant Nos. 11075021,91130020,and 11202003Foundation of State Key Laboratory of Explosion Science and Technology
文摘The Cellular Automaton(CA) modeling and simulation of solid dynamics is a long-standing difficult problem.In this paper we present a new two-dimensional CA model for solid dynamics.In this model the solid body is represented by a set of white and black particles alternatively positioned in the x-and y-directions.The force acting on each particle is represented by the linear summation of relative displacements of the nearest-neighboring particles.The key technique in this new model is the construction of eight coefficient matrices.Theoretical and numerical analyses show that the present model can be mathematically described by a conservative system.So,it works for elastic material.In the continuum limit the CA model recovers the well-known Navier equation.The coefficient matrices are related to the shear module and Poisson ratio of the material body.Compared with previous CA model for solid body,this model realizes the natural coupling of deformations in the x-and y-directions.Consequently,the wave phenomena related to the Poisson ratio effects are successfully recovered.This work advances significantly the CA modeling and simulation in the field of computational solid dynamics.
