In order to accurately predict the productivity of herringbone multilateral well,a new productivity prediction model was founded.And based on this model,orthogonal test and multiple factor variance analysis were appli...In order to accurately predict the productivity of herringbone multilateral well,a new productivity prediction model was founded.And based on this model,orthogonal test and multiple factor variance analysis were applied to study optimization design of herringbone multilateral well.According to the characteristics of herringbone multilateral well,by using pressure superposition and mirror image reflection theory,the coupled model of herringbone multilateral well was developed on the basis of a three-dimensional pseudo-pressure distribution model for horizontal wells.The model was formulated in consideration of friction loss,acceleration loss of the wellbore and mixed loss at the confluence of main wellbore and branched one.After mathematical simulation on productivity of the herringbone multilateral well with the coupled model,the effects of well configuration on productivity were analyzed.The results show that lateral number is the most important factor,length of main wellbore and length of branched wellbore are the secondary ones,angle between main and branched one has the least influence.展开更多
This paper presents a new theoretical model to determine the optimal axial preload of a spindle system, for challenging the traditional method which relies heavily on experience of engineers. The axial preloading stif...This paper presents a new theoretical model to determine the optimal axial preload of a spindle system, for challenging the traditional method which relies heavily on experience of engineers. The axial preloading stiffness was treated as the sum of the spindle modal stiffness and the framework elastic stiffness, based on a novel concept that magnitude of preloads can be controlled by measuring the resonant frequency of a spindle system. By employing an example of a certain type of aircraft simulating rotary table, the modal stiffness was measured on the Agilent 35670A Dynamic Signal Analyzer by experimental modal analysis. The equivalent elastic stiffness was simulated by both finite element analysis in ANSYS? and a curve fitting in MATLAB?. Results showed that the static preloading stiffness of the spindle was 7.2125×107 N/m, and that the optimal preloading force was 120.0848 N. Practical application proved the feasibility of our method.展开更多
A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a n...A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.展开更多
Constitutive models aimed at predicting the mechanical response of lead-core bearing devices for passive seismic isolation are discussed in this paper. The study is focused on single-degree-of-freedom models which pro...Constitutive models aimed at predicting the mechanical response of lead-core bearing devices for passive seismic isolation are discussed in this paper. The study is focused on single-degree-of-freedom models which provide a relation between the shear displacement （shear strain） and the shear force （shear stress） in elastomeric and lad-core rubber bearings. Classical Bouc-Wen model along with a numerical procedure for identification of the model constants is described. Alternatively, a constitutive relation introducing a damage variable aimed at assessing the material degradation is also considered.展开更多
The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual...The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual＇s Willingness To Pay according to geographical location. Within this framework, an estimator （of type Nadaraya-Watson） is proposed for the regression of the variable related to geolocation. The specific characteristics of the location variable lead us to a more general regression model than the traditional models. Results are established for convergence of our estimator.展开更多
Precise temperature control to decrease movements in positions due to thermal expansion of work pieces is required in the manufacturing processes to achieve nanometer-order accuracy. We analytically examined the effec...Precise temperature control to decrease movements in positions due to thermal expansion of work pieces is required in the manufacturing processes to achieve nanometer-order accuracy. We analytically examined the effect of a method of minimizing movements in positions on a plate with varying generation of noise-heat. Control by monitoring temperature changes caused larger movements in positions than that without control because maximum change in temperature occurred at non-monitoring positions. The best method of minimizing movements in positions due to thermal expansion of a plate with varying generation of noise-heat was model predictive control by the monitoring movements and distributed temperature changes in the control heater according to the effects of the generation of noise-heat. The maximum movement in positions was 6 nm, which was 1/4 times of that without control.展开更多
In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individua...In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.展开更多
When voyaging,ships are subject to inevitable hull deformations caused by the changes in the environmental temperature and external stress.These are a crucial source of errors when measuring data using a spacecraft tr...When voyaging,ships are subject to inevitable hull deformations caused by the changes in the environmental temperature and external stress.These are a crucial source of errors when measuring data using a spacecraft tracking,telemetry,and control(TT&C) ship.A prototype system based on photogrammetry was developed for the real-time measurement of a spacecraft TT&C ship's hull deformation.This system has high accuracy,a simple structure,and convenient maintenance,and requires few changes to the ship's structures.To improve its performance,an estimation approach is proposed for hull deformation angles.With the proposed approach,the central positions of cross spots in successive frames can be predicted based on the prediction of the camera's attitude,and their extract locations can be found by defining a series of small windows around each predictive location.Then,the optimal estimate of the camera's attitude is updated by the designed extended Kalman filter using the extracted cross spots and their corresponding local coordinates,with which the hull deformation angles can be found.To verify the proposed measurement approach,its performance was tested during the normal sailing,floating,and rocking on the sea of a spacecraft TT&C ship.The experimental testing results demonstrated that the proposed approach performs well in terms of accuracy and robustness.It can satisfy the hull deformation measurement requirement for a spacecraft TT&C ship in real time.展开更多
Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical f...Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed(constant, acceleration, or deceleration), yaw(left, right, or straight), and pitch(climb, descent, or cruise) using a hidden Markov model(HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models(GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.展开更多
基金Project(12521044) supported by Scientific and Technological Research Program of Heilongjiang Provincial Education Department,China
文摘In order to accurately predict the productivity of herringbone multilateral well,a new productivity prediction model was founded.And based on this model,orthogonal test and multiple factor variance analysis were applied to study optimization design of herringbone multilateral well.According to the characteristics of herringbone multilateral well,by using pressure superposition and mirror image reflection theory,the coupled model of herringbone multilateral well was developed on the basis of a three-dimensional pseudo-pressure distribution model for horizontal wells.The model was formulated in consideration of friction loss,acceleration loss of the wellbore and mixed loss at the confluence of main wellbore and branched one.After mathematical simulation on productivity of the herringbone multilateral well with the coupled model,the effects of well configuration on productivity were analyzed.The results show that lateral number is the most important factor,length of main wellbore and length of branched wellbore are the secondary ones,angle between main and branched one has the least influence.
文摘This paper presents a new theoretical model to determine the optimal axial preload of a spindle system, for challenging the traditional method which relies heavily on experience of engineers. The axial preloading stiffness was treated as the sum of the spindle modal stiffness and the framework elastic stiffness, based on a novel concept that magnitude of preloads can be controlled by measuring the resonant frequency of a spindle system. By employing an example of a certain type of aircraft simulating rotary table, the modal stiffness was measured on the Agilent 35670A Dynamic Signal Analyzer by experimental modal analysis. The equivalent elastic stiffness was simulated by both finite element analysis in ANSYS? and a curve fitting in MATLAB?. Results showed that the static preloading stiffness of the spindle was 7.2125×107 N/m, and that the optimal preloading force was 120.0848 N. Practical application proved the feasibility of our method.
基金Project(9140A18010210KG01) supported by the Departmental Pre-Research Fund of China
文摘A novel configuration performance prediction approach with combination of principal component analysis(PCA) and support vector machine(SVM) was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers' individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.
文摘Constitutive models aimed at predicting the mechanical response of lead-core bearing devices for passive seismic isolation are discussed in this paper. The study is focused on single-degree-of-freedom models which provide a relation between the shear displacement （shear strain） and the shear force （shear stress） in elastomeric and lad-core rubber bearings. Classical Bouc-Wen model along with a numerical procedure for identification of the model constants is described. Alternatively, a constitutive relation introducing a damage variable aimed at assessing the material degradation is also considered.
文摘The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual＇s Willingness To Pay according to geographical location. Within this framework, an estimator （of type Nadaraya-Watson） is proposed for the regression of the variable related to geolocation. The specific characteristics of the location variable lead us to a more general regression model than the traditional models. Results are established for convergence of our estimator.
文摘Precise temperature control to decrease movements in positions due to thermal expansion of work pieces is required in the manufacturing processes to achieve nanometer-order accuracy. We analytically examined the effect of a method of minimizing movements in positions on a plate with varying generation of noise-heat. Control by monitoring temperature changes caused larger movements in positions than that without control because maximum change in temperature occurred at non-monitoring positions. The best method of minimizing movements in positions due to thermal expansion of a plate with varying generation of noise-heat was model predictive control by the monitoring movements and distributed temperature changes in the control heater according to the effects of the generation of noise-heat. The maximum movement in positions was 6 nm, which was 1/4 times of that without control.
文摘In this study, we examine the impacts that EVs （electric vehicles） have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs＇ parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G （vehicle-to-grid）. According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to ＋8%, depending on its characteristics.
基金supported by the National Natural Science Foundation of China(Grant No.11272347)
文摘When voyaging,ships are subject to inevitable hull deformations caused by the changes in the environmental temperature and external stress.These are a crucial source of errors when measuring data using a spacecraft tracking,telemetry,and control(TT&C) ship.A prototype system based on photogrammetry was developed for the real-time measurement of a spacecraft TT&C ship's hull deformation.This system has high accuracy,a simple structure,and convenient maintenance,and requires few changes to the ship's structures.To improve its performance,an estimation approach is proposed for hull deformation angles.With the proposed approach,the central positions of cross spots in successive frames can be predicted based on the prediction of the camera's attitude,and their extract locations can be found by defining a series of small windows around each predictive location.Then,the optimal estimate of the camera's attitude is updated by the designed extended Kalman filter using the extracted cross spots and their corresponding local coordinates,with which the hull deformation angles can be found.To verify the proposed measurement approach,its performance was tested during the normal sailing,floating,and rocking on the sea of a spacecraft TT&C ship.The experimental testing results demonstrated that the proposed approach performs well in terms of accuracy and robustness.It can satisfy the hull deformation measurement requirement for a spacecraft TT&C ship in real time.
基金Project supported by the National Natural Science Foundation of China(No.71573184)the National Key Scientific Instrument and Equipment Development Project(No.2013YQ490879)the Special Program of Office of China Air Traffic Control Commission(No.GKG201403004)
文摘Traditional methods for plan path prediction have low accuracy and stability. In this paper, we propose a novel approach for plan path prediction based on relative motion between positions(RMBP) by mining historical flight trajectories. A probability statistical model is introduced to model the stochastic factors during the whole flight process. The model object is the sequence of velocity vectors in the three-dimensional Earth space. First, we model the moving trend of aircraft including the speed(constant, acceleration, or deceleration), yaw(left, right, or straight), and pitch(climb, descent, or cruise) using a hidden Markov model(HMM) under the restrictions of aircraft performance parameters. Then, several Gaussian mixture models(GMMs) are used to describe the conditional distribution of each moving trend. Once the models are built, machine learning algorithms are applied to obtain the optimal parameters of the model from the historical training data. After completing the learning process, the velocity vector sequence of the flight is predicted by the proposed model under the Bayesian framework, so that we can use kinematic equations, depending on the moving patterns, to calculate the flight position at every radar acquisition cycle. To obtain higher prediction accuracy, a uniform interpolation method is used to correct the predicted position each second. Finally, a plan trajectory is concatenated by the predicted discrete points. Results of simulations with collected data demonstrate that this approach not only fulfils the goals of traditional methods, such as the prediction of fly-over time and altitude of waypoints along the planned route, but also can be used to plan a complete path for an aircraft with high accuracy. Experiments are conducted to demonstrate the superiority of this approach to some existing methods.
