Based on the field destructive test of six rock-socketed piles with shallow overburden,three prediction models are used to quantitatively analyze and predict the intact load−displacement curve.The predicted values of ...Based on the field destructive test of six rock-socketed piles with shallow overburden,three prediction models are used to quantitatively analyze and predict the intact load−displacement curve.The predicted values of ultimate uplift capacity were further determined by four methods(displacement controlling method(DCM),reduction coefficient method(RCM),maximum curvature method(MCM),and critical stiffness method(CSM))and compared with the measured value.Through the analysis of the relationship between the change rate of pullout stiffness and displacement,a method used to determine the ultimate uplift capacity via non-intact load−displacement curve was proposed.The results show that the predicted value determined by DCM is more conservative,while the predicted value determined by MCM is larger than the measured value.This suggests that RCM and CSM in engineering applications can be preferentially applied.Moreover,the development law of the change rate of pullout stiffness with displacement agrees well with the attenuation form of power function.The theoretical predicted results of ultimate uplift capacity based on the change rate of pullout stiffness will not be affected by the integrity of the curve.The method is simple and applicable for the piles that are not loaded to failure state,and thus provides new insights into ultimate uplift capacity determination of test piles.展开更多
Reduction of drag torque in disengaged wet clutch is one of important potentials for vehicle transmission improvement. The flow of the oil film in clutch clearance is investigated. A three-dimension Navier-Stokes(N-S)...Reduction of drag torque in disengaged wet clutch is one of important potentials for vehicle transmission improvement. The flow of the oil film in clutch clearance is investigated. A three-dimension Navier-Stokes(N-S) equation based on laminar flow is presented to model the drag torque. Pressure and speed distribution in radial and circumferential directions are deduced. The theoretical analysis reveals that oil flow acceleration in radial direction caused by centrifugal force is the key reason for the shrinking of oil film as constant feeding flow rate. The peak drag torque occurs at the beginning of oil film shrinking. A variable is introduced to describe effective oil film area and drag torque after oil film shrinking is well evaluated with the variable. Under the working condition, tests were made to obtain drag torque curves at different clutch speed and oil viscosity. The tests confirm that simulation results agree with test data. The model performs well in the prediction of drag torque and lays a theoretical foundation to reduce it.展开更多
This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,...This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.展开更多
Soil moisture characteristic curve （SMC） is a fundamental soil property and its direct measurement is tedious and time consuming. Therefore, various indirect methods have been developed to predict SMC from particle-...Soil moisture characteristic curve （SMC） is a fundamental soil property and its direct measurement is tedious and time consuming. Therefore, various indirect methods have been developed to predict SMC from particle-size distribution （PSD）. However, the majority of these methods often yield intermittent SMC data because they involve estimating individual SMC points. The objectives of this study were 1） to develop a procedure to predict continuous SMC from a limited number of experimental PSD data points and 2） to evaluate model predictions through comparisons with measured values. In this study, an approach that allowed predicting SMC from the knowledge of PSD, parameterized by means of the closed-form van Genuchten model （VG）, was used. Through using Mohammadi and Vanclooster （MV） model, the parameters obtained from fitting of VG to PSD data were applied to predict SMC curves. Since the residual water content （Or） could not be obtained through fitting of VG-MV integrated model to PSD data, we also examined and compared four different methods estimating 0r. Results showed that the proposed equation （MV-VG integrated model） provided an excellent fit to all the PSD data and the model could adequately predict SMC as measured in forty-two soils sampled from different regions of Iran. For all soils, the method in which Or Was obtained through parameter optimization procedure provided the best overall predictions of SMC. The two methods estimating Or with Campbell and Shiozawa （CS） model resulted in less accuracy than the optimization procedure. Furthermore, the proposed model underestimated the moisture content in the dry range of SMC when the value of 0r was assumed to equal zero. 0r could be attributed to the incomplete desorption of water coated on soil particles and the accurate estimation of 0r was critical in prediction of SMC, especially for fine-textured soils at high suction heads. It could be concluded that the advantages of our approach were the continuity, robustness, and independency of model performance on soil type, allowing to improve predictions of SMC from PSD at the field and watershed scales.展开更多
基金Project(2016YFC0802203)supported by the National Key R&D Program of ChinaProject(2013G001-A-2)supported by the Science and Technology Research and Development Program of China Railway CorporationProject(SKLGDUEK2011)supported by the State Key Laboratory for GeoMechanics and Deep Underground Engineering,China University of Mining&Technology。
文摘Based on the field destructive test of six rock-socketed piles with shallow overburden,three prediction models are used to quantitatively analyze and predict the intact load−displacement curve.The predicted values of ultimate uplift capacity were further determined by four methods(displacement controlling method(DCM),reduction coefficient method(RCM),maximum curvature method(MCM),and critical stiffness method(CSM))and compared with the measured value.Through the analysis of the relationship between the change rate of pullout stiffness and displacement,a method used to determine the ultimate uplift capacity via non-intact load−displacement curve was proposed.The results show that the predicted value determined by DCM is more conservative,while the predicted value determined by MCM is larger than the measured value.This suggests that RCM and CSM in engineering applications can be preferentially applied.Moreover,the development law of the change rate of pullout stiffness with displacement agrees well with the attenuation form of power function.The theoretical predicted results of ultimate uplift capacity based on the change rate of pullout stiffness will not be affected by the integrity of the curve.The method is simple and applicable for the piles that are not loaded to failure state,and thus provides new insights into ultimate uplift capacity determination of test piles.
基金supported by National Defense Arming Pre-researching Project(Grant No. 40402060102)
文摘Reduction of drag torque in disengaged wet clutch is one of important potentials for vehicle transmission improvement. The flow of the oil film in clutch clearance is investigated. A three-dimension Navier-Stokes(N-S) equation based on laminar flow is presented to model the drag torque. Pressure and speed distribution in radial and circumferential directions are deduced. The theoretical analysis reveals that oil flow acceleration in radial direction caused by centrifugal force is the key reason for the shrinking of oil film as constant feeding flow rate. The peak drag torque occurs at the beginning of oil film shrinking. A variable is introduced to describe effective oil film area and drag torque after oil film shrinking is well evaluated with the variable. Under the working condition, tests were made to obtain drag torque curves at different clutch speed and oil viscosity. The tests confirm that simulation results agree with test data. The model performs well in the prediction of drag torque and lays a theoretical foundation to reduce it.
基金“National Science and Technology Council”(NSTC 111-2221-E-027-088)。
文摘This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.
文摘Soil moisture characteristic curve （SMC） is a fundamental soil property and its direct measurement is tedious and time consuming. Therefore, various indirect methods have been developed to predict SMC from particle-size distribution （PSD）. However, the majority of these methods often yield intermittent SMC data because they involve estimating individual SMC points. The objectives of this study were 1） to develop a procedure to predict continuous SMC from a limited number of experimental PSD data points and 2） to evaluate model predictions through comparisons with measured values. In this study, an approach that allowed predicting SMC from the knowledge of PSD, parameterized by means of the closed-form van Genuchten model （VG）, was used. Through using Mohammadi and Vanclooster （MV） model, the parameters obtained from fitting of VG to PSD data were applied to predict SMC curves. Since the residual water content （Or） could not be obtained through fitting of VG-MV integrated model to PSD data, we also examined and compared four different methods estimating 0r. Results showed that the proposed equation （MV-VG integrated model） provided an excellent fit to all the PSD data and the model could adequately predict SMC as measured in forty-two soils sampled from different regions of Iran. For all soils, the method in which Or Was obtained through parameter optimization procedure provided the best overall predictions of SMC. The two methods estimating Or with Campbell and Shiozawa （CS） model resulted in less accuracy than the optimization procedure. Furthermore, the proposed model underestimated the moisture content in the dry range of SMC when the value of 0r was assumed to equal zero. 0r could be attributed to the incomplete desorption of water coated on soil particles and the accurate estimation of 0r was critical in prediction of SMC, especially for fine-textured soils at high suction heads. It could be concluded that the advantages of our approach were the continuity, robustness, and independency of model performance on soil type, allowing to improve predictions of SMC from PSD at the field and watershed scales.
