The recently proposed interface propagation-based method has shown its advantages in obtaining the thermal conductivity of phase change materials during solid-liquid transition over conventional techniques. However, i...The recently proposed interface propagation-based method has shown its advantages in obtaining the thermal conductivity of phase change materials during solid-liquid transition over conventional techniques. However, in previous investigation, the analysis on the measurement error was qualitative and only focused on the total effects on the measurement without decoupling the influencing factors. This paper discusses the effects of influencing factors on the measurement results for the interface propagation-based method. Numerical simulations were performed to explore the influencing factors, namely model simplification, subcooling and natural convection, along with their impact on the measurement process and corresponding measurement results. The numerical solutions were provided in terms of moving curves of the solid-liquid interface and the predicted values of thermal conductivity. Results indicated that the impact of simplified model was strongly dependent on Stefan number of the melting process. The degree of subcooling would lead to underestimated values for thermal conductivity prediction. The natural convection would intensify the heat transfer rate in the liquid region, thereby overestimating the obtained results of thermal conductivity. Correlations and experimental guidelines are provided. The relative errors are limited in ±1.5%,±3%and ±2% corresponding to the impact of simplified model, subcooling and natural convection, respectively.展开更多
A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural n...A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural network (GRNN) with incorporation of feature extraction method using principle component analysis. In the risk based security assessment formulation, the failure rate associated to weather condition of each line was used to compute the probability of line outage for a given weather condition and the extent of security violation was represented by a severity function. For low voltage and line overload, continuous severity function was considered due to its ability to zoom in into the effect of near violating contingency. New severity function for voltage collapse using the voltage collapse prediction index was proposed. To reduce the computational burden, a new contingency screening method was proposed using the risk factor so as to select the critical line outages. The risk based security assessment method using GRNN was implemented on a large scale 87-bus power system and the results show that the risk prediction results obtained using GRNN with the incorporation of principal component analysis give better performance in terms of accuracy.展开更多
Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nin...Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nine grades were selected as the alternatives of trip time, the variables affecting time choice and the method getting their values were determined, and a multinomial logit (MNL) model was developed. Another 1 200 trip data of rural population were selected to testify the model's validity. The result shows that the maximum absolute error of each period between calculated value and statistic is 3.6%, so MNL model has high calculation accuracy.展开更多
Support vector regression （SVR） method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study...Support vector regression （SVR） method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study presents four SVR models by selecting linear, radial basis, spline, and polynomial functions as kernels, respectively for the prediction of urban dust fall levels. The inputs of the models are identified as industrial coal consumption, population density, traffic flow coefficient, and shopping density coefficient. The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes. In addition, a number of scenario analyses reveal that the most suitable parameters （insensitive loss function e, the parameter to reduce the influence of error C, and discrete level or average distribution of parameters σ） are 0.001, 0.5, and 2 000, respectively.展开更多
An experimental model of maldistribution was established and grey correlation analysis method was employed to describe quantitatively the maldistribution phenomenon in the feeding device of copper flash smelting.Parti...An experimental model of maldistribution was established and grey correlation analysis method was employed to describe quantitatively the maldistribution phenomenon in the feeding device of copper flash smelting.Particle motion in the feeding device was separated into uniform flow in chute and restricted slanting parabolic motion in distributor channel.Factors affecting particle velocity at the chute outlet and particle moving distance in the distributor channel,which also cause the maldistribution,were analyzed based on the assumption of pseudo fluid.Experiments were conducted to study the maldistribution using river sand.The results indicate obvious mass maldistribution and an even higher degree with the increase of feeding mass rate;meanwhile,size maldistribution is negligible.Also,feeding intensity has a larger impact on circumferential maldistribution than on radial maldistribution.Based on the experimental results of the eight factors impacting the maldistribution,grey relation of each factor was calculated using grey correlation analysis.The importances of these factors were sequenced.The results show that a proper adjustment of the structure will ameliorate the maldistribution phenomenon in the feeding device of copper flash smelting.展开更多
Based on the height of back-filled materials, thickness of ore body, height of boundary pillar and dipping angle of ore body and water pressure, the safety factors of all the pillars are calculated with the limit equi...Based on the height of back-filled materials, thickness of ore body, height of boundary pillar and dipping angle of ore body and water pressure, the safety factors of all the pillars are calculated with the limit equilibrium method. The calculation results present that the safety factors of pillars in Sections 19, 20, 24, 28 are less than 1.3, and those of unstable sections are identified preliminarily. Further, a numerical investigation in Sections 18, 20, 22, 24, 25 and 28 implemented with numerical code RFPA20 is employed to further validate the pillar performance and the stability of stopes. The numerical results show the pillars in Sections 18, 22 and 24 are stable and the designed pillar size is suitable. The width of the ore body near Section 28 averages 20 m, failure occurs in the left stope, but the boundary pillars near Section 28 maintain good performance. The pillars in Sections 20 and 25 are unstable which are mainly affected by the Faults F8 and F18. The existence of faults alters the stress distribution, failure mode and water inrush pathway. This work provides a meaningful standard for boundary pillar and stope design in a mine as it transitions from an open pit to underground.展开更多
Recently,the radial point interpolation meshfree method has gained popularity owing to its advantages in large deformation and discontinuity problems,however,the accuracy of this method depends on many factors and the...Recently,the radial point interpolation meshfree method has gained popularity owing to its advantages in large deformation and discontinuity problems,however,the accuracy of this method depends on many factors and their influences are not fully investigated yet.In this work,three main factors,i.e.,the shape parameters,the influence domain size,and the nodal distribution,on the accuracy of the radial point interpolation method(RPIM)are systematically studied and conclusive results are obtained.First,the effect of shape parameters(R,q)of the multi-quadric basis function on the accuracy of RPIM is examined via global search.A new interpolation error index,closely related to the accuracy of RPIM,is proposed.The distribution of various error indexes on the R q plane shows that shape parameters q[1.2,1.8]and R[0,1.5]can give good results for general 3-D analysis.This recommended range of shape parameters is examined by multiple benchmark examples in 3D solid mechanics.Second,through numerical experiments,an average of 30 40 nodes in the influence domain of a Gauss point is recommended for 3-D solid mechanics.Third,it is observed that the distribution of nodes has significant effect on the accuracy of RPIM although it has little effect on the accuracy of interpolation.Nodal distributions with better uniformity give better results.Furthermore,how the influence domain size and nodal distribution affect the selection of shape parameters and how the nodal distribution affects the choice of influence domain size are also discussed.展开更多
The soil masses of slopes were assumed to follow a nonlinear failure criterion and a nonassociated flow rule.The stability factors of slopes were calculated using vertical slice method based on limit analysis.The pote...The soil masses of slopes were assumed to follow a nonlinear failure criterion and a nonassociated flow rule.The stability factors of slopes were calculated using vertical slice method based on limit analysis.The potential sliding mass was divided into a series of vertical slices as well as the traditional slice technique.Equating the external work rate to the internal energy dissipation,the optimum solutions to stability factors were determined by the nonlinear programming algorithm.From the numerical results,it is found that the present solutions agree well with previous results when the nonlinear criterion reduces to the linear criterion,and the nonassociated flow rule reduces to the associated flow rule.The stability factors decrease by 39.7%with nonlinear parameter varying from 1.0 to 3.0.Dilation and nonlinearity have significant effects on the slope stability factors.展开更多
基金Project(51606224) supported by the National Natural Science Foundation of China
文摘The recently proposed interface propagation-based method has shown its advantages in obtaining the thermal conductivity of phase change materials during solid-liquid transition over conventional techniques. However, in previous investigation, the analysis on the measurement error was qualitative and only focused on the total effects on the measurement without decoupling the influencing factors. This paper discusses the effects of influencing factors on the measurement results for the interface propagation-based method. Numerical simulations were performed to explore the influencing factors, namely model simplification, subcooling and natural convection, along with their impact on the measurement process and corresponding measurement results. The numerical solutions were provided in terms of moving curves of the solid-liquid interface and the predicted values of thermal conductivity. Results indicated that the impact of simplified model was strongly dependent on Stefan number of the melting process. The degree of subcooling would lead to underestimated values for thermal conductivity prediction. The natural convection would intensify the heat transfer rate in the liquid region, thereby overestimating the obtained results of thermal conductivity. Correlations and experimental guidelines are provided. The relative errors are limited in ±1.5%,±3%and ±2% corresponding to the impact of simplified model, subcooling and natural convection, respectively.
文摘A comprehensive risk based security assessment which includes low voltage, line overload and voltage collapse was presented using a relatively new neural network technique called as the generalized regression neural network (GRNN) with incorporation of feature extraction method using principle component analysis. In the risk based security assessment formulation, the failure rate associated to weather condition of each line was used to compute the probability of line outage for a given weather condition and the extent of security violation was represented by a severity function. For low voltage and line overload, continuous severity function was considered due to its ability to zoom in into the effect of near violating contingency. New severity function for voltage collapse using the voltage collapse prediction index was proposed. To reduce the computational burden, a new contingency screening method was proposed using the risk factor so as to select the critical line outages. The risk based security assessment method using GRNN was implemented on a large scale 87-bus power system and the results show that the risk prediction results obtained using GRNN with the incorporation of principal component analysis give better performance in terms of accuracy.
基金Project(51178158) supported by the National Natural Science Foundation of ChinaProjects(2010HGZY0010, 2011HGBZ0936) supported by the Fundamental Research Funds for the Central Universities of China
文摘Referring to the 1 248 survey data of rural population in 14 provinces of China, the influencing factors of trip time choice were analyzed. Based on the basic theory of disaggregate model and its modelling method, nine grades were selected as the alternatives of trip time, the variables affecting time choice and the method getting their values were determined, and a multinomial logit (MNL) model was developed. Another 1 200 trip data of rural population were selected to testify the model's validity. The result shows that the maximum absolute error of each period between calculated value and statistic is 3.6%, so MNL model has high calculation accuracy.
基金Projects(2007JT3018, 2008JT1013, 2009FJ4056) supported by the Key Project in Hunan Science and Technology Program, ChinaProject(20090161120014) supported by the New Teachers Sustentation Fund in Doctoral Program, Ministry of Education, China
文摘Support vector regression （SVR） method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study presents four SVR models by selecting linear, radial basis, spline, and polynomial functions as kernels, respectively for the prediction of urban dust fall levels. The inputs of the models are identified as industrial coal consumption, population density, traffic flow coefficient, and shopping density coefficient. The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes. In addition, a number of scenario analyses reveal that the most suitable parameters （insensitive loss function e, the parameter to reduce the influence of error C, and discrete level or average distribution of parameters σ） are 0.001, 0.5, and 2 000, respectively.
基金Project(2010AA065201) supported by the National High Technology Research and Development Program of China
文摘An experimental model of maldistribution was established and grey correlation analysis method was employed to describe quantitatively the maldistribution phenomenon in the feeding device of copper flash smelting.Particle motion in the feeding device was separated into uniform flow in chute and restricted slanting parabolic motion in distributor channel.Factors affecting particle velocity at the chute outlet and particle moving distance in the distributor channel,which also cause the maldistribution,were analyzed based on the assumption of pseudo fluid.Experiments were conducted to study the maldistribution using river sand.The results indicate obvious mass maldistribution and an even higher degree with the increase of feeding mass rate;meanwhile,size maldistribution is negligible.Also,feeding intensity has a larger impact on circumferential maldistribution than on radial maldistribution.Based on the experimental results of the eight factors impacting the maldistribution,grey relation of each factor was calculated using grey correlation analysis.The importances of these factors were sequenced.The results show that a proper adjustment of the structure will ameliorate the maldistribution phenomenon in the feeding device of copper flash smelting.
基金Projects(1004025,51174044,50934006)supported by the National Natural Science FoundationProject(2011AA060400)supported by the National High Technique Research and Development Program of ChinaProject(Sklgduek1113)supported by Funds of the State Key Laboratory for Geomechanics&Deep Underground Engineering,Chinese University of Mining and Technology,China
文摘Based on the height of back-filled materials, thickness of ore body, height of boundary pillar and dipping angle of ore body and water pressure, the safety factors of all the pillars are calculated with the limit equilibrium method. The calculation results present that the safety factors of pillars in Sections 19, 20, 24, 28 are less than 1.3, and those of unstable sections are identified preliminarily. Further, a numerical investigation in Sections 18, 20, 22, 24, 25 and 28 implemented with numerical code RFPA20 is employed to further validate the pillar performance and the stability of stopes. The numerical results show the pillars in Sections 18, 22 and 24 are stable and the designed pillar size is suitable. The width of the ore body near Section 28 averages 20 m, failure occurs in the left stope, but the boundary pillars near Section 28 maintain good performance. The pillars in Sections 20 and 25 are unstable which are mainly affected by the Faults F8 and F18. The existence of faults alters the stress distribution, failure mode and water inrush pathway. This work provides a meaningful standard for boundary pillar and stope design in a mine as it transitions from an open pit to underground.
基金Project(2010CB732103)supported by the National Basic Research Program of ChinaProject(51179092)supported by the National Natural Science Foundation of ChinaProject(2012-KY-02)supported by the State Key Laboratory of Hydroscience and Engineering,China
文摘Recently,the radial point interpolation meshfree method has gained popularity owing to its advantages in large deformation and discontinuity problems,however,the accuracy of this method depends on many factors and their influences are not fully investigated yet.In this work,three main factors,i.e.,the shape parameters,the influence domain size,and the nodal distribution,on the accuracy of the radial point interpolation method(RPIM)are systematically studied and conclusive results are obtained.First,the effect of shape parameters(R,q)of the multi-quadric basis function on the accuracy of RPIM is examined via global search.A new interpolation error index,closely related to the accuracy of RPIM,is proposed.The distribution of various error indexes on the R q plane shows that shape parameters q[1.2,1.8]and R[0,1.5]can give good results for general 3-D analysis.This recommended range of shape parameters is examined by multiple benchmark examples in 3D solid mechanics.Second,through numerical experiments,an average of 30 40 nodes in the influence domain of a Gauss point is recommended for 3-D solid mechanics.Third,it is observed that the distribution of nodes has significant effect on the accuracy of RPIM although it has little effect on the accuracy of interpolation.Nodal distributions with better uniformity give better results.Furthermore,how the influence domain size and nodal distribution affect the selection of shape parameters and how the nodal distribution affects the choice of influence domain size are also discussed.
基金Project(200550)supported by the Foundation for the Author of National Excellent Doctoral Dissertation of ChinaProject(200631878557)supported by West Traffic of Science and Technology of China
文摘The soil masses of slopes were assumed to follow a nonlinear failure criterion and a nonassociated flow rule.The stability factors of slopes were calculated using vertical slice method based on limit analysis.The potential sliding mass was divided into a series of vertical slices as well as the traditional slice technique.Equating the external work rate to the internal energy dissipation,the optimum solutions to stability factors were determined by the nonlinear programming algorithm.From the numerical results,it is found that the present solutions agree well with previous results when the nonlinear criterion reduces to the linear criterion,and the nonassociated flow rule reduces to the associated flow rule.The stability factors decrease by 39.7%with nonlinear parameter varying from 1.0 to 3.0.Dilation and nonlinearity have significant effects on the slope stability factors.
