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As a kind of space robot, the two-arm cascade combination system (TACCS) has been applied to perform auxiliary operations at different locations outside space cabins. The motion coupling relation of two arms and complex surrounding obstacles make the collision-free trajectory planning optimization of TACCS more difficult, which has become an urgent problem to be solved. For the above problem, this paper proposed collision-free and time–energy–minimum trajectory planning optimization algorithms, considering the motion coupling of two arms. In this method, the screw-based inverse kinematics (IK) model of TACCS is established to provide the basis for the motion planning in joint space by decoupling the whole IK problem into two IK sub-problems of two arms; the minimum distance calculation model is established based on the hybrid geometric enveloping way and basic distance functions, which can provide the efficient and accurate data basis for the obstacle-avoidance constraint condition of the trajectory optimization. Moreover, the single and bi-layer optimization algorithms are presented by taking motion time and energy consumption as objectives and considering obstacle-avoidance and kinematics constraints. Finally, through example cases, the results indicate that the bi-layer optimization has higher convergence efficiency under the premise of ensuring the optimization effect by separating variables and constraint terms. This work can provide theoretical and methodological support for the efficient and intelligent applications of TACCS in the space arena. [ABSTRACT FROM AUTHOR]

Machining time and energy consumption are common process planning evaluation metrics. However, it is difficult to obtain accurate machining time and energy consumption values in the process planning stage, which may result in non-optimal obtaining process routes. To solve these problems, this paper proposes a flexible process planning method based on processing time and energy consumption prediction models. The historical processing data is analyzed, and a prediction model of machining time and energy consumption based on a radial basis function neural network is proposed. Considering the flexibility of multiple processes, a mathematical model of the flexible process planning problem based on the machining time and energy consumption prediction model is established. A multi-objective algorithm using a multidimensional real number coding method is proposed for problem-solving with the completion time and energy consumption minimization as the optimization objective. Two algorithms with better multi-objective optimization performance, the strength Pareto evolution algorithm 2, and the dominance ranking genetic algorithm II are selected for comparative analysis to obtain a better effect of optimization. The better algorithm is selected with the best parameters. Finally, case studies are conducted to verify the validity of the prediction model and the flexible process planning model. [ABSTRACT FROM AUTHOR]

For enhanced energy utilization with improved flexibility and capability for object manipulation, a focused acoustic vortex (FAV) is devised by installing a spherical acoustic lens on a circular array of planar sector transducers. Based on the acoustic refraction of a concave spherical acoustic lens, numerical simulations show that an FAV with considerable pressure gain and strengthened acoustic gradient force (AGF) can be produced by the effective concentration of acoustic waves. The performance of rotational object trapping is shown by the axial and radial distributions of the AGF for FAVs of different orders. Elastic objects of nanometer, micrometer, millimeter, and even larger-than-wavelength size can be captured with the trapping radius determined by the topological charge. With the established 16-channel experimental system, FAVs of different orders are verified by their clear pressure circles and phase spirals. The trapping radius and rotation speed of object capture are demonstrated using polyethylene particles of various sizes and FAVs of different orders. The favorable results provide an experimentally applicable method of FAV generation using the simplified circular transducer array to accomplish more accurate, stable, and flexible object manipulations with strengthened AGFs. Also, FAVs could offer an efficient means of high-intensity focused ultrasound therapy to improve the therapeutic effect of tumor treatments by accumulating drug particles, thereby enabling more potential applications in clinical practice. [ABSTRACT FROM AUTHOR]

Abstract Currently, researchers have been studying ways to reduce the raw materials costs and energy consumption of ultra-high-performance concrete (UHPC) production. Therefore, the feasibility of using aeolian sand to partially or totally replace natural river sand in UHPC is studied. The workability and quasi-static and dynamic mechanical properties were comprehensively studied to investigate the effect of aeolian sand on UHPCs. It was found that: 1) The workability of UHPCs was significantly improved when river sand was partially or totally replaced by aeolian sand; 2) The compressive strength of UHPCs could be enhanced when river sand was partially or totally replaced by aeolian sand, and the differences in flexural strength among all the mixtures were not distinct; 3) Incorporation of aeolian sand as a fine aggregate slightly increased the toughness of UHPCs under uniaxial compression test; 4) The differences in the dynamic impact parameters among UHPCs containing aeolian or river sand, as well as those in the parameter evolution rules regarding impact times, were not obvious. The findings of this research promote the preparation of eco-friendly UHPC and provide a new way to use waste resources. [ABSTRACT FROM AUTHOR]