Inversion of river-bottom sediment parameters using mechanically sampled specimens and subbottom profiling data

The study of river dynamics requires knowledge of physical parameters, such as porosity, permeability, and wave propagation velocity, of river-bottom sediments. To do so, sediment properties are determined on mechanically sampled specimens and from subbottom profiling. However, mechanical sampling introduces disturbances that affect test results, with the exception of grain-size distribution. In this study, we perform inversion of acoustic data using the grain-size distribution of mechanically sampled specimens and the relation between porosity and permeability from the Kozeny-Carman equation as prior information. The wave reflection coefficient of the water-silt interface is extracted from the raw subbottom profile. Based on the effective density fluid model, we combine the Kozeny-Carman equation and the wave reflection coefficient. We use experimental data from two Yellow River reservoirs to obtain the wave velocity and density of multiple sections and their spatial variations, and find that the inversion and testing results are in good agreement.

Distributed model predictive control based on adaptive sampling mechanism

In this work,an adaptive sampling control strategy for distributed predictive control is proposed.According to the proposed method,the sampling rate of each subsystem of the accused object is determined based on the periodic detection of its dynamic behavior and calculations made using a correlation function.Then,the optimal sampling interval within the period is obtained and sent to the corresponding sub-prediction controller,and the sampling interval of the controller is changed accordingly before the next sampling period begins.In the next control period,the adaptive sampling mechanism recalculates the sampling rate of each subsystem’s measurable output variable according to both the abovementioned method and the change in the dynamic behavior of the entire system,and this process is repeated.Such an adaptive sampling interval selection based on an autocorrelation function that measures dynamic behavior can dynamically optimize the selection of sampling rate according to the real-time change in the dynamic behavior of the controlled object.It can also accurately capture dynamic changes,meaning that each sub-prediction controller can more accurately calculate the optimal control quantity at the next moment,significantly improving the performance of distributed model predictive control(DMPC).A comparison demonstrates that the proposed adaptive sampling DMPC algorithm has better tracking performance than the traditional DMPC algorithm.

Optimum Anti-erosion Structures and Anti-erosion Mechanism for Rotatory Samples Inspired by Scorpion Armor of Parabuthus transvaalicus

Solid particle erosion on the material surfaces is a very common phenomenon in the industrial field,which greatly affects the efficiency,service life,and even poses a great threat to life safety.However,current research on erosion resistance is not only inefficient,but also limited to the improvement of hardness and toughness of materials.Inspired by typical scorpion(Parabuthus transvaalicus),biomimetic functional samples with exquisite anti-rosion structures were manufactured.Macroscopic morphology and structure of the biological prototype were analyzed and measured.According to above analysis,combined with response surface methodology,a set of biomimetic samples with different structural parameters were fabricated by using 3D printing technology.The anti-crosion performance of these biomimetic samples was investigated using a blasting jet machine.Based on the results of blasting jet test,as well as regression analysis and fiting,the optimal structural parameters were obtained.In addition to the static test conditions,the optimal biomimetic sample was also eroded in rotating condition and showed excellent erosion resistance property.The presence of bump and groove structures,on the one hand,reduced the croded area of biominetic sample surface.On the other hand,they made the airlow turbulent and consequently reduced the impact cnergy of solid particles,which significantly improved the erosion resistance of biomimetic materials.This study provides a new strategy to improvethe service life of components easily affected by erosion in the aviation,energy and military fields.