Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording con...Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing (q<sub>c</sub>), sleeve friction (f<sub>c</sub>) and dynamic pore pressure (u) with depth. The measured q<sub>c</sub>, f<sub>s</sub> and u values are utilized to estimate soil type and associated soil properties. A popular method to estimate soil type from CPT measurements is the Soil Behavior Type (SBT) chart. The SBT plots cone resistance vs friction ratio, R<sub>f</sub> [where: R<sub>f</sub> = (f<sub>s</sub>/q<sub>c</sub>)100%]. There are distortions in the CPT measurements which can result in erroneous SBT plots. Cone bearing measurements at a specific depth are blurred or averaged due to q<sub>c</sub> values being strongly influenced by soils within 10 to 30 cone diameters from the cone tip. The q<sub>c</sub>HMM algorithm was developed to address the q<sub>c</sub> blurring/averaging limitation. This paper describes the distortions which occur when obtaining sleeve friction measurements which can in association with q<sub>c</sub> blurring result in significant errors in the calculated R<sub>f</sub> values. This paper outlines a novel and highly effective algorithm for obtaining accurate sleeve friction and friction ratio estimates. The f<sub>c</sub> optimal filter estimation technique is referred to as the OSFE-IFM algorithm. The mathematical details of the OSFE-IFM algorithm are outlined in this paper along with the results from a challenging test bed simulation. The test bed simulation demonstrates that the OSFE-IFM algorithm derives accurate estimates of sleeve friction from measured values. Optimal estimates of cone bearing and sleeve friction result in accurate R<sub>f</sub> values and subsequent accurate estimates of soil behavior type.展开更多
When a solid cone with smooth side and base rotates about its long axis in a still fluid, theory says that the cone will advance along the direction of the axis, base first and apex last. Bernoulli’s law for closed s...When a solid cone with smooth side and base rotates about its long axis in a still fluid, theory says that the cone will advance along the direction of the axis, base first and apex last. Bernoulli’s law for closed streamline loops is combined with the cross-stream force balance between the centrifugal force and a pressure gradient in order to obtain the result, which is believed to be new. Confirmation of the prediction awaits observational evidence.展开更多
A numerical study is performed to examine the heat transfer characteristics of natural convection past a vertical cone under the combined effects of magnetic field and thermal radiation. The surface of the cone is sub...A numerical study is performed to examine the heat transfer characteristics of natural convection past a vertical cone under the combined effects of magnetic field and thermal radiation. The surface of the cone is subjected to a variable surface heat flux. The fluid considered is a gray, absorbing-emitting radiation but a non-scattering medium. With approximate transformations, the boundary layer equations governing the flow are reduced to non-dimensional equations valid in the free convection regime. The dimensionless governing equations are solved by an implicit finite difference method of Crank-Nicolson type which is fast convergent, accurate, and unconditionally stable. Numerical results are obtained and presented for velocity, temperature, local and average wall shear stress, and local and average Nusselt number in air and water. The present results axe compared with the previous published work and are found to be in excellent agreement.展开更多
The classical gradient flow optimization algorithm requires a valid initial point before starting the recursive algorithm,and the existing methods can’t guarantee that the initial values fully satisfy the friction co...The classical gradient flow optimization algorithm requires a valid initial point before starting the recursive algorithm,and the existing methods can’t guarantee that the initial values fully satisfy the friction cone constraints of contact point in the optimization process of gradient flow algorithm.In order to improve safety margin and prevent the finger from slipping at contact point,we present an iterative method of safe initial values with safety margin detection and develop a gradient flow optimization algorithm based on the safe initial values.Firstly,the safety margin is defined which more intuitively reflects the margin of the grasping forces at contact point.The resulting safe initial values can be achieved by the detection of desired safety margin at each iteration.Secondly,the safe initial values are usually not optimal,even with the valid initial values,and it can’t always ensure that the finger contact force always satisfies the friction cone constraints during the optimization.It is an effective way to eliminate the unreliable initial values in the optimization and obtain a safer initial values by increasing the safety margin.By transforming the safe initial values into an initial point of the gradient flow algorithm,the final optimized values of grasping forces can be generated efficiently by gradient flow iteration.Grasp examples of the soft multi-fingered hand indicate the effectiveness of the general solution of the force optimization algorithm based on safety margin detection.The method eliminates the shortcomings of the gradient flow optimization process caused by the initial value problem and provides a more accurate and reliable force optimization result for multi-fingered dexterous manipulation.展开更多
文摘Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing (q<sub>c</sub>), sleeve friction (f<sub>c</sub>) and dynamic pore pressure (u) with depth. The measured q<sub>c</sub>, f<sub>s</sub> and u values are utilized to estimate soil type and associated soil properties. A popular method to estimate soil type from CPT measurements is the Soil Behavior Type (SBT) chart. The SBT plots cone resistance vs friction ratio, R<sub>f</sub> [where: R<sub>f</sub> = (f<sub>s</sub>/q<sub>c</sub>)100%]. There are distortions in the CPT measurements which can result in erroneous SBT plots. Cone bearing measurements at a specific depth are blurred or averaged due to q<sub>c</sub> values being strongly influenced by soils within 10 to 30 cone diameters from the cone tip. The q<sub>c</sub>HMM algorithm was developed to address the q<sub>c</sub> blurring/averaging limitation. This paper describes the distortions which occur when obtaining sleeve friction measurements which can in association with q<sub>c</sub> blurring result in significant errors in the calculated R<sub>f</sub> values. This paper outlines a novel and highly effective algorithm for obtaining accurate sleeve friction and friction ratio estimates. The f<sub>c</sub> optimal filter estimation technique is referred to as the OSFE-IFM algorithm. The mathematical details of the OSFE-IFM algorithm are outlined in this paper along with the results from a challenging test bed simulation. The test bed simulation demonstrates that the OSFE-IFM algorithm derives accurate estimates of sleeve friction from measured values. Optimal estimates of cone bearing and sleeve friction result in accurate R<sub>f</sub> values and subsequent accurate estimates of soil behavior type.
文摘When a solid cone with smooth side and base rotates about its long axis in a still fluid, theory says that the cone will advance along the direction of the axis, base first and apex last. Bernoulli’s law for closed streamline loops is combined with the cross-stream force balance between the centrifugal force and a pressure gradient in order to obtain the result, which is believed to be new. Confirmation of the prediction awaits observational evidence.
文摘A numerical study is performed to examine the heat transfer characteristics of natural convection past a vertical cone under the combined effects of magnetic field and thermal radiation. The surface of the cone is subjected to a variable surface heat flux. The fluid considered is a gray, absorbing-emitting radiation but a non-scattering medium. With approximate transformations, the boundary layer equations governing the flow are reduced to non-dimensional equations valid in the free convection regime. The dimensionless governing equations are solved by an implicit finite difference method of Crank-Nicolson type which is fast convergent, accurate, and unconditionally stable. Numerical results are obtained and presented for velocity, temperature, local and average wall shear stress, and local and average Nusselt number in air and water. The present results axe compared with the previous published work and are found to be in excellent agreement.
基金National Natural Science Foundation of China(51305180)International Science&Technology Cooperation Program of China(2014DFR10620)Shandong Provincial Natural Science Foundation(ZR2013FM026,ZR2014YL009)
文摘The classical gradient flow optimization algorithm requires a valid initial point before starting the recursive algorithm,and the existing methods can’t guarantee that the initial values fully satisfy the friction cone constraints of contact point in the optimization process of gradient flow algorithm.In order to improve safety margin and prevent the finger from slipping at contact point,we present an iterative method of safe initial values with safety margin detection and develop a gradient flow optimization algorithm based on the safe initial values.Firstly,the safety margin is defined which more intuitively reflects the margin of the grasping forces at contact point.The resulting safe initial values can be achieved by the detection of desired safety margin at each iteration.Secondly,the safe initial values are usually not optimal,even with the valid initial values,and it can’t always ensure that the finger contact force always satisfies the friction cone constraints during the optimization.It is an effective way to eliminate the unreliable initial values in the optimization and obtain a safer initial values by increasing the safety margin.By transforming the safe initial values into an initial point of the gradient flow algorithm,the final optimized values of grasping forces can be generated efficiently by gradient flow iteration.Grasp examples of the soft multi-fingered hand indicate the effectiveness of the general solution of the force optimization algorithm based on safety margin detection.The method eliminates the shortcomings of the gradient flow optimization process caused by the initial value problem and provides a more accurate and reliable force optimization result for multi-fingered dexterous manipulation.
