Study on the effect of ground motion direction on the response of engineering structure

Due to the randomness of earthquake wave magnitude and direction, and the uncertain direction of strong axis and weak axis in the construction of engineering structures, the effect of the direction of ground motion on a structure are studied herein. Ground motion records usually contain three vertical ground motion data, which are obtained by sensors arranged in accordance with the EW （East -West） direction, NS （South- North） direction and perpendicular to the surface （z） direction, referring to the construction standard of seismic stations. The seismic records in the EW and NS directions are converted to Cartesian coordinates in accordance with the rotation of θ = 0°-180°, and consequently, a countless group of new ground motion time histories are obtained. Then, the characteristics of the ground motion time history and response spectrum of each group were studied, resulting in the following observations： （1） the peak and phase of ground motion are changed with the rotation of direction θ, so that the direction θ of the maximum peak ground motion can be determined; （2） response spectrum values of each group of ground motions change along with the direction θ, and their peak, predominant period and declining curve are also different as the changes occur; then, the angle θ in the direction of the maximum peak value or the widest predominant period can be determined; and （3） the seismic response of structures with different directions of ground motion inputs has been analyzed under the same earthquake record, and the results show the difference. For some ground motion records, such as the Taft seismic wave, these differences are significant. Next, the Lushan middle school gymnasium structure was analyzed and the calculation was checked using the proposed method, where the internal force of the upper space truss varied from 25% to 28%. The research results presented herein can be used for reference in choosing the ground motion when checking the actual damage to structures following earthquakes and explaining the seismic damage. Meanwhile, it also provides a reference value for research into the most severe ground motion.

Optimal control of stretching process of flexible solar arrays on spacecraft based on a hybrid optimization strategy

The optimal control of multibody spacecraft during the stretching process of solar arrays is investigated,and a hybrid optimization strategy based on Gauss pseudospectral method（GPM） and direct shooting method（DSM） is presented. First, the elastic deformation of flexible solar arrays was described approximately by the assumed mode method, and a dynamic model was established by the second Lagrangian equation. Then, the nonholonomic motion planning problem is transformed into a nonlinear programming problem by using GPM. By giving fewer LG points, initial values of the state variables and control variables were obtained. A serial optimization framework was adopted to obtain the approximate optimal solution from a feasible solution. Finally, the control variables were discretized at LG points, and the precise optimal control inputs were obtained by DSM. The optimal trajectory of the system can be obtained through numerical integration. Through numerical simulation, the stretching process of solar arrays is stable with no detours, and the control inputs match the various constraints of actual conditions.The results indicate that the method is effective with good robustness.

Motion direction prediction through spike timing based on micro Capsnet networks

Neural activity extraction and neural decoding from neural signals are an important part of critical components of brain-computer interface systems.With the development of brain-computer interface technology,the demand for precise external control and nervous activities in macaque monkey during unilateral hand grasp has increased the complexity of control and neural decoding,which puts forward higher requirements for the accuracy and stability of feature extraction and neural decoding.In this study,a micro Capsnet network architecture that consists of a few network layers,a vector feature structure,and optimization network parameters,is proposed to decrease the computing time and complexity,decrease artificial debugging,and improve the decoding accuracy.Compared with KNN,SVM,XGBOOST,CNN,Simple RNN,and LSTM,the algorithm in this study improves the decoding accuracy by 98.03%,and achieves state-of-the-art accuracy and stronger robustness.Furthermore,the proposed algorithm can further enhance the control accuracy in the brain-computer interface.

A fluctuating lattice-Boltzmann model for direct numerical simulation of particle Brownian motion

A single-relaxation-time fluctuating lattice-Boltzmann （LB） model for direct numerical simulation （DNS） of particle Brownian motion is established by adding a fluctuating component to the lattice-Boltzmann equations （LBEs）. The fluctuating term is proved to be the random stress tensor in fluctuating hydrodynamics by recovering Navier-Stokes equations from LBEs through a Chapman-Enskog expansion. A three-dimensional implementation of the model is also presented, along with simulations of a single spherical particle and 125 spherical particles at short times. Numerical results including the meansquare displacement, velocity autocorrelation function and self-diffusion coefficient of particles compare favorably with theoretical results and previous numerical results.

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.