At the first time,the finite element method was used to model and analyze the free vibration and transient response of non-uniform thickness bi-directional functionally graded sandwich porous(BFGSP)skew plates.The who...At the first time,the finite element method was used to model and analyze the free vibration and transient response of non-uniform thickness bi-directional functionally graded sandwich porous(BFGSP)skew plates.The whole BFGSP skew-plates is placed on a variable visco-elastic foundation(VEF)in the hygro-thermal environment and subjected to the blast load.The BFGSP skew-plate thickness is permitted to vary non-linearly over both the length and width of the skew-plate,thereby faithfully representing the real behavior of the structure itself.The analysis is based on a four-node planar quadrilateral element with eight degrees of freedom per node,which is approximated using Lagrange Q_(4)shape function and C^(1)level non-conforming Hermite shape function based on refined higher-order shear deformation plate theory.The forced vibration parameters of the non-uniform thickness BFGSP skew-plate are fully determined using Hamilton's principle and the Newmark-βdirect integration technique.Accuracy of the calculation program is validated by comparing its numerical results with those from reputable sources.Furthermore,a thorough assessment is conducted to determine the impact of various parameters on the free and forced vibration responses of the non-uniform thickness BFGSP skew-plate.The findings of the paper may be used in the development of civil and military structures in situations that are prone to exceptional forces,such as explosions and impacts load.展开更多
Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the ...Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.展开更多
Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the probl...Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.展开更多
The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression mo...Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.展开更多
In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump ...In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump intensity was introduced to the existing discrete microstructure model to denote large price fluctuations. The nonparametric method of LEE was used for detecting jumps. Further, the extended Kalman filter and the maximum likelihood method were applied to discrete microstructure modeling and the estimation of two market potential variables： market excess demand and liquidity. At last, based on the estimated variables, an assets allocation strategy using evolutionary algorithm was designed to control the weight of each asset dynamically. Case studies on IBM Stock show that jumps with variable intensity are detected successfully, and the assets allocation strategy may effectively keep the total assets growth or prevent assets loss at the stochastic financial market.展开更多
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
Aiming at the problem of deep surrounding rock instability induced by roadway excavation or mining disturbance,the true triaxial loading system was used to conduct graded cyclic maximum principal stress σ_(1) and int...Aiming at the problem of deep surrounding rock instability induced by roadway excavation or mining disturbance,the true triaxial loading system was used to conduct graded cyclic maximum principal stress σ_(1) and intermediate principal stress σ_(2) tests on sandstone to simulate the effect of mining stress in actual underground engineering.The influences of each principal stress cycle on the mechanical properties,acoustic emission(AE)characteristics,and fracture characteristics of sandstone were analyzed.The damage characteristics of sandstone under true triaxial cyclic loading were studied.Furthermore,the damage constitutive model of rock mass under true triaxial cyclic loading was established based on AE cumulative ringing count.The quantitative investigation was conducted on cumulative-damage changes in circulating sandstone,which elucidated the mechanism of damage deterioration in sandstone subjected to true triaxial cyclic loading.The results show that the influence of the graded cycleσ_(1) on limit maximum principal strain ɛ_(1max) and limit minimum principal strainɛ_(3max) was significantly greater than that of the limit intermediate principal strain ɛ_(2max).Graded cycleσ_(2) had a greater impact onɛ_(2max) and a smaller impact onɛ_(3max).The elasticity modulus of sandstone decreased exponentially with the increased cyclic load amplitude,while the Poisson ratio increased linearly.b of AE showed a trend of increasing,decreasing,slightly fluctuating,and finally decreasing during cyclingσ_(1).b showed a trend of slight fluctuation,large fluctuation,and finally increase during cyclingσ_(2).Sandstone specimens experienced mainly tensile failure,tensile-shear composite failure,and mainly shear failure with increased initialσ_(2) orσ_(3).This was determined by analyzing the rise angle-average frequency of the AE parameter,corresponding to the rock specimens from splitting failure to shear failure.Besides,the mechanical damage behavior of sandstone under true triaxial cyclic loading could be well described by the established constitutive model.At the same time,it was found that the sandstone damage variable decreased with increasedσ_(2) during cyclingσ_(1).The damage variable decreased first and then increased with increasedσ_(3) during cyclingσ_(2).展开更多
Aiming at the fact that the energy and mass exchange phenomena exist between barrel and gas-operated device of the automatic weapon, for describing its interior ballistics and dynamic characteristics of the gas-operat...Aiming at the fact that the energy and mass exchange phenomena exist between barrel and gas-operated device of the automatic weapon, for describing its interior ballistics and dynamic characteristics of the gas-operated device accurately, a new variable-mass thermodynamics model is built. It is used to calculate the automatic mechanism velocity of a certain automatic weapon, the calculation results coincide with the experimental results better, and thus the model is validated. The influences of structure parameters on gas-operated device's dynamic characteristics are discussed. It shows that the model is valuable for design and accurate performance prediction of gas-operated automatic weapon.展开更多
Analyzing the mass of behind-armor debris (BAD) generated by Rolled Homogeneous Armor (RHA) subjected to normal penetration of variable cross-section Explosively Formed Projectile (EFP) is the purpose of this paper. S...Analyzing the mass of behind-armor debris (BAD) generated by Rolled Homogeneous Armor (RHA) subjected to normal penetration of variable cross-section Explosively Formed Projectile (EFP) is the purpose of this paper. So theoretical analysis, numerical simulation and experimental data are combined to analyze the influence of variable cross-section characteristic on the time history of crater radius. Moreover the relationships between time history of crater radius (as well as mass of BAD) and the thickness of RHA (from 30mm to 70 mm) and the impact velocity of EFP (1650 m/s to 1860 m/s) are also investigated. The results indicate that: 1) being compared to the variable cross-section characteristic is ignored, the theoretical time history of crater radius is in better agreement with the simulation results when the variable cross-section characteristic is considered;2) being compared to the other three conditions of plug, the theoretical mass of BAD is in the best agreement with the simulation results when the shape of plug is frustum of a cone and the angle between generatrix and bottom is 45- and the axial length of mushroom is considered.展开更多
Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structur...Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.展开更多
Monitoring high-dimensional multistage processes becomes crucial to ensure the quality of the final product in modern industry environments. Few statistical process monitoring(SPC) approaches for monitoring and contro...Monitoring high-dimensional multistage processes becomes crucial to ensure the quality of the final product in modern industry environments. Few statistical process monitoring(SPC) approaches for monitoring and controlling quality in highdimensional multistage processes are studied. We propose a deviance residual-based multivariate exponentially weighted moving average(MEWMA) control chart with a variable selection procedure. We demonstrate that it outperforms the existing multivariate SPC charts in terms of out-of-control average run length(ARL) for the detection of process mean shift.展开更多
In order to increase the applying rate of liquid fertilizer and reduce environmental pollution, a slave computer control system for applying variable-rate liquid fertilizer was designed. The system used SMC as core pr...In order to increase the applying rate of liquid fertilizer and reduce environmental pollution, a slave computer control system for applying variable-rate liquid fertilizer was designed. The system used SMC as core processor and electrically controlled pressure regulator as execution component. The characteristic equation of the system was obtained by using classical control theory. Results indicated that the characteristic equation met the requirements of routh-criterion, which indicated the working process of the system was stable. Performance of the slave computer was verified via bench tests. Results demonstrated that there was no significant influence on the response from interclass error. The fertilization error was less than 0.9, and the fertilization accuracy was larger than 97%. The liquid fertilizer emitted by the fertilizing devices had no significant difference in uniformity, which met the demands of the slave computer control system for applying variable-rate liquid fertilizer.展开更多
土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获...土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。展开更多
文摘At the first time,the finite element method was used to model and analyze the free vibration and transient response of non-uniform thickness bi-directional functionally graded sandwich porous(BFGSP)skew plates.The whole BFGSP skew-plates is placed on a variable visco-elastic foundation(VEF)in the hygro-thermal environment and subjected to the blast load.The BFGSP skew-plate thickness is permitted to vary non-linearly over both the length and width of the skew-plate,thereby faithfully representing the real behavior of the structure itself.The analysis is based on a four-node planar quadrilateral element with eight degrees of freedom per node,which is approximated using Lagrange Q_(4)shape function and C^(1)level non-conforming Hermite shape function based on refined higher-order shear deformation plate theory.The forced vibration parameters of the non-uniform thickness BFGSP skew-plate are fully determined using Hamilton's principle and the Newmark-βdirect integration technique.Accuracy of the calculation program is validated by comparing its numerical results with those from reputable sources.Furthermore,a thorough assessment is conducted to determine the impact of various parameters on the free and forced vibration responses of the non-uniform thickness BFGSP skew-plate.The findings of the paper may be used in the development of civil and military structures in situations that are prone to exceptional forces,such as explosions and impacts load.
文摘Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.
基金supported by the National Natural Science Foundation of China(51467013)
文摘Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
基金supported by the National Security Major Basic Research Project of China (973-61334).
文摘Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.
基金Projects(71271215,71221061) supported by the National Natural Science Foundation of ChinaProject(2011DFA10440) supported by the International Science&Technology Cooperation Program of ChinaProject(CX2012B067) supported by Hunan Provincial Innovation Foundation for Postgraduate,China
文摘In order to characterizc large fluctuations of the financial markets and optimize financial portfolio, a new dynamic asset control strategy was proposed in this work. Firstly, a random process item with variable jump intensity was introduced to the existing discrete microstructure model to denote large price fluctuations. The nonparametric method of LEE was used for detecting jumps. Further, the extended Kalman filter and the maximum likelihood method were applied to discrete microstructure modeling and the estimation of two market potential variables： market excess demand and liquidity. At last, based on the estimated variables, an assets allocation strategy using evolutionary algorithm was designed to control the weight of each asset dynamically. Case studies on IBM Stock show that jumps with variable intensity are detected successfully, and the assets allocation strategy may effectively keep the total assets growth or prevent assets loss at the stochastic financial market.
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
基金Project(2022m07020007)supported by the Key Research and Development Projects of Anhui Province,ChinaProjects(52174102,52074006,51404011,51874002,51974009)supported by the National Natural Science Foundation of China+1 种基金Project(2024cx1017)supported by the Graduate Innovation Fund of Anhui University of Science and Technology,ChinaProject(2024AH040067)supported by the Natural Science Research Project of Anhui Educational Committee,China。
文摘Aiming at the problem of deep surrounding rock instability induced by roadway excavation or mining disturbance,the true triaxial loading system was used to conduct graded cyclic maximum principal stress σ_(1) and intermediate principal stress σ_(2) tests on sandstone to simulate the effect of mining stress in actual underground engineering.The influences of each principal stress cycle on the mechanical properties,acoustic emission(AE)characteristics,and fracture characteristics of sandstone were analyzed.The damage characteristics of sandstone under true triaxial cyclic loading were studied.Furthermore,the damage constitutive model of rock mass under true triaxial cyclic loading was established based on AE cumulative ringing count.The quantitative investigation was conducted on cumulative-damage changes in circulating sandstone,which elucidated the mechanism of damage deterioration in sandstone subjected to true triaxial cyclic loading.The results show that the influence of the graded cycleσ_(1) on limit maximum principal strain ɛ_(1max) and limit minimum principal strainɛ_(3max) was significantly greater than that of the limit intermediate principal strain ɛ_(2max).Graded cycleσ_(2) had a greater impact onɛ_(2max) and a smaller impact onɛ_(3max).The elasticity modulus of sandstone decreased exponentially with the increased cyclic load amplitude,while the Poisson ratio increased linearly.b of AE showed a trend of increasing,decreasing,slightly fluctuating,and finally decreasing during cyclingσ_(1).b showed a trend of slight fluctuation,large fluctuation,and finally increase during cyclingσ_(2).Sandstone specimens experienced mainly tensile failure,tensile-shear composite failure,and mainly shear failure with increased initialσ_(2) orσ_(3).This was determined by analyzing the rise angle-average frequency of the AE parameter,corresponding to the rock specimens from splitting failure to shear failure.Besides,the mechanical damage behavior of sandstone under true triaxial cyclic loading could be well described by the established constitutive model.At the same time,it was found that the sandstone damage variable decreased with increasedσ_(2) during cyclingσ_(1).The damage variable decreased first and then increased with increasedσ_(3) during cyclingσ_(2).
文摘Aiming at the fact that the energy and mass exchange phenomena exist between barrel and gas-operated device of the automatic weapon, for describing its interior ballistics and dynamic characteristics of the gas-operated device accurately, a new variable-mass thermodynamics model is built. It is used to calculate the automatic mechanism velocity of a certain automatic weapon, the calculation results coincide with the experimental results better, and thus the model is validated. The influences of structure parameters on gas-operated device's dynamic characteristics are discussed. It shows that the model is valuable for design and accurate performance prediction of gas-operated automatic weapon.
基金financially supported by the National Natural Science Foundation of China(Grant No.11372136)
文摘Analyzing the mass of behind-armor debris (BAD) generated by Rolled Homogeneous Armor (RHA) subjected to normal penetration of variable cross-section Explosively Formed Projectile (EFP) is the purpose of this paper. So theoretical analysis, numerical simulation and experimental data are combined to analyze the influence of variable cross-section characteristic on the time history of crater radius. Moreover the relationships between time history of crater radius (as well as mass of BAD) and the thickness of RHA (from 30mm to 70 mm) and the impact velocity of EFP (1650 m/s to 1860 m/s) are also investigated. The results indicate that: 1) being compared to the variable cross-section characteristic is ignored, the theoretical time history of crater radius is in better agreement with the simulation results when the variable cross-section characteristic is considered;2) being compared to the other three conditions of plug, the theoretical mass of BAD is in the best agreement with the simulation results when the shape of plug is frustum of a cone and the angle between generatrix and bottom is 45- and the axial length of mushroom is considered.
基金This work was supported by the Natural Science Foundation of Hebei Province(F2019203505).
文摘Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.
基金supported by the Qatar National Research Fund(NPRP5-364-2-142NPRP7-1040-2-293)
文摘Monitoring high-dimensional multistage processes becomes crucial to ensure the quality of the final product in modern industry environments. Few statistical process monitoring(SPC) approaches for monitoring and controlling quality in highdimensional multistage processes are studied. We propose a deviance residual-based multivariate exponentially weighted moving average(MEWMA) control chart with a variable selection procedure. We demonstrate that it outperforms the existing multivariate SPC charts in terms of out-of-control average run length(ARL) for the detection of process mean shift.
基金Supported by the Science and Technology Research Project of the 12th Five-year Plan(2011BAD20B03-01)
文摘In order to increase the applying rate of liquid fertilizer and reduce environmental pollution, a slave computer control system for applying variable-rate liquid fertilizer was designed. The system used SMC as core processor and electrically controlled pressure regulator as execution component. The characteristic equation of the system was obtained by using classical control theory. Results indicated that the characteristic equation met the requirements of routh-criterion, which indicated the working process of the system was stable. Performance of the slave computer was verified via bench tests. Results demonstrated that there was no significant influence on the response from interclass error. The fertilization error was less than 0.9, and the fertilization accuracy was larger than 97%. The liquid fertilizer emitted by the fertilizing devices had no significant difference in uniformity, which met the demands of the slave computer control system for applying variable-rate liquid fertilizer.
文摘土壤是具有高度异质性的复合体。早期的数字土壤制图研究主要关注水平方向的土壤空间变异和制图,对垂直方向空间变异和土壤三维制图考虑较少。近年来,三维地理信息技术和对地观测与探测技术的快速发展,极大地促进了土壤三维空间数据获取、三维空间推测、三维数据模型、三维模型构建和可视化方法等方面的研究。本文对三维空间土壤推测与土壤模型构建的已有方法进行梳理和评述,以期为三维数字土壤制图的应用和发展提供建议。以三维土壤制图、三维GIS、三维数据模型、三维地质建模、三维可视化、土壤空间变异、空间推测、克里格插值、土壤-景观分析、深度函数、机器学习、地统计学、随机模拟等为关键词检索Web of Science数据库,基于相关度、引用率和文献来源等因素进一步筛选出重点文献进行分析。归纳整理了土壤空间变异性、三维空间土壤推测、三维空间数据模型和三维模型构建等关键技术的现有研究体系,对各种三维推测和建模方法的优缺点和适用场景作出评价。针对目前研究中存在的垂直方向土壤数据稀少、土壤三维推测精度低、三维模型质量待提高等问题,提出一些可行的研究思路。
