Sediment-laden flow measurement with Particle Tracking Velocimetry （PTV） introduces a series of finite-sized sampling bins along the vertical of the flow. Instantaneous velocities are collected at each bin and a sig...Sediment-laden flow measurement with Particle Tracking Velocimetry （PTV） introduces a series of finite-sized sampling bins along the vertical of the flow. Instantaneous velocities are collected at each bin and a significantly large sample is established to evaluate mean and root mean square （rms） velocities of the flow. Due to the presence of concentration gradient, the established sample for the solid phase involves more data from the lower part of the sampling bin than from the upper part. The concentration effect causes bias errors in the measured mean and rms velocities when velocity varies across the bin. These bias errors are analyti- cally quantified in this study based on simplified linear velocity and concentration distributions. Typical bulk flow characteristics from sediment-laden flow measurements are used to demonstrate rough estimation of the error magnitude. Results indicate that the mean velocity is underestimated while the rms velocity is overestimated in the ensemble-averaged measurement. The extent of devia- tion is commensurate with the bin size and the rate of concentration gradient. Procedures are proposed to assist determining an appro- priate sampling bin size in certain error limits.展开更多
In an experimental realization of the sheared cylindrical slab, the level of plasma turbulence is strongly reduced by application of a sufficient bias potential difference in the radial direction. Density fluctuation ...In an experimental realization of the sheared cylindrical slab, the level of plasma turbulence is strongly reduced by application of a sufficient bias potential difference in the radial direction. Density fluctuation levels △nrms/n decrease by more than a factor of five. The ion flow velocity profile is measured spectroscopically from the Doppler shift of an argon ion line. Comparison of the shearing rates with the turbulent amplitudes as a function of bias show no relation between the shearing rate and turbulence reduction, contrary to expectations.展开更多
To improve the tracking accuracy of hypersonic sliding target in near space,the influence of target hypersonic movement on radar detection and tracking is analyzed,and an IMM tracking algorithm is proposed based on ra...To improve the tracking accuracy of hypersonic sliding target in near space,the influence of target hypersonic movement on radar detection and tracking is analyzed,and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed(ECEF) coordinate.Based on the analysis of effect of target hypersonic movement,a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch.The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space.The high dynamic biases are further eliminated by the cancellation processing of different radars,in which the track association problem can be solved when the dynamic biases are low.An IMM algorithm based on constant acceleration(CA),constant turning(CT) and Singer models is used to achieve the hypersonic sliding target tracking in near space.Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.展开更多
Sound velocity profile(SVP)data is indispensable in the multi-beam data processing.The sampling density is of great importance for SVP to represent the vertical variation of sound velocity accurately and guarantee the...Sound velocity profile(SVP)data is indispensable in the multi-beam data processing.The sampling density is of great importance for SVP to represent the vertical variation of sound velocity accurately and guarantee the accuracy of sound ray tracing(SRT).However,the SVP also affects the SRT efficiency significantly,especially in deep-sea multi-beam sounding data processing.To improve SRT efficiency and ensure SRT accuracy,an adaptive SVP simplification method based on area difference is proposed in this article.Firstly,the relationship between the area difference of the raw SVP and the simplified one and SRT bias is studied,and the relationship model of them is built.Then,by considering the constraint of SRT accuracy,the SVP simplification method and the simplifying SVP procedure SVP are given.Finally,a deep water experiment is conducted to verify the proposed method.Compared to the existing method,the proposed method improves the robustness,feasibility of SVP simplification as well as the accuracy and efficiency of SRT.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.50779023)
文摘Sediment-laden flow measurement with Particle Tracking Velocimetry （PTV） introduces a series of finite-sized sampling bins along the vertical of the flow. Instantaneous velocities are collected at each bin and a significantly large sample is established to evaluate mean and root mean square （rms） velocities of the flow. Due to the presence of concentration gradient, the established sample for the solid phase involves more data from the lower part of the sampling bin than from the upper part. The concentration effect causes bias errors in the measured mean and rms velocities when velocity varies across the bin. These bias errors are analyti- cally quantified in this study based on simplified linear velocity and concentration distributions. Typical bulk flow characteristics from sediment-laden flow measurements are used to demonstrate rough estimation of the error magnitude. Results indicate that the mean velocity is underestimated while the rms velocity is overestimated in the ensemble-averaged measurement. The extent of devia- tion is commensurate with the bin size and the rate of concentration gradient. Procedures are proposed to assist determining an appro- priate sampling bin size in certain error limits.
基金supported by the Department of Energy Office of Fusion Energy Sciences DE-FG02-04ER54766
文摘In an experimental realization of the sheared cylindrical slab, the level of plasma turbulence is strongly reduced by application of a sufficient bias potential difference in the radial direction. Density fluctuation levels △nrms/n decrease by more than a factor of five. The ion flow velocity profile is measured spectroscopically from the Doppler shift of an argon ion line. Comparison of the shearing rates with the turbulent amplitudes as a function of bias show no relation between the shearing rate and turbulence reduction, contrary to expectations.
文摘To improve the tracking accuracy of hypersonic sliding target in near space,the influence of target hypersonic movement on radar detection and tracking is analyzed,and an IMM tracking algorithm is proposed based on radial velocity compensating and cancellation processing of high dynamic biases under the earth centered earth fixed(ECEF) coordinate.Based on the analysis of effect of target hypersonic movement,a measurement model is constructed to reduce the filter divergence which is caused by the model mismatch.The high dynamic biases due to the target hypersonic movement are approximately compensated through radial velocity estimation to achieve the hypersonic target tracking at low systematic biases in near space.The high dynamic biases are further eliminated by the cancellation processing of different radars,in which the track association problem can be solved when the dynamic biases are low.An IMM algorithm based on constant acceleration(CA),constant turning(CT) and Singer models is used to achieve the hypersonic sliding target tracking in near space.Simulation results show that the target tracking in near space can be achieved more effectively by using the proposed algorithm.
文摘Sound velocity profile(SVP)data is indispensable in the multi-beam data processing.The sampling density is of great importance for SVP to represent the vertical variation of sound velocity accurately and guarantee the accuracy of sound ray tracing(SRT).However,the SVP also affects the SRT efficiency significantly,especially in deep-sea multi-beam sounding data processing.To improve SRT efficiency and ensure SRT accuracy,an adaptive SVP simplification method based on area difference is proposed in this article.Firstly,the relationship between the area difference of the raw SVP and the simplified one and SRT bias is studied,and the relationship model of them is built.Then,by considering the constraint of SRT accuracy,the SVP simplification method and the simplifying SVP procedure SVP are given.Finally,a deep water experiment is conducted to verify the proposed method.Compared to the existing method,the proposed method improves the robustness,feasibility of SVP simplification as well as the accuracy and efficiency of SRT.
