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This paper proposes a hybrid coupled partially encased composite (PEC) wall system, obtained through the connection of two PEC walls by means of the shear critical steel coupling beams with an innovative welded connection. This structural solution is designed to take advantage of both the stiffness of the PEC walls (required to limit building damage under frequent earthquakes) and the ductility of the steel coupling beams (necessary to dissipate energy under medium-intensity and high-intensity earthquakes). The connection performance of an innovative rigid joint with different configurations in this system is studied through pseudostatic analysis, and the seismic performance of the proposed hybrid coupled PEC wall system is evaluated through multirecord nonlinear dynamic analysis of a set of case studies. Adopted finite element models are developed and validated against the available experimental results. A summary of the results is presented and discussed to highlight the potential of the proposed hybrid coupled PEC wall systems. The key feature of this system is development of a reasonable two-level yielding mechanism (the first level is the yielding of the coupling beams, and the second level is the yielding of the PEC wall) without damage to the welded joints.

In order to maintain and enhance the operational reliability of a robotic manipulator deployed in space, an operational reliability system control method is presented in this paper. First, a method to divide factors affecting the operational reliability is proposed, which divides the operational reliability factors into task-related factors and cost-related factors. Then the models describing the relationships between the two kinds of factors and control variables are established. Based on this, a multivariable and multiconstraint optimization model is constructed. Second, a hierarchical system control model which incorporates the operational reliability factors is constructed. The control process of the space manipulator is divided into three layers: task planning, path planning, and motion control. Operational reliability related performance parameters are measured and used as the system’s feedback. Taking the factors affecting the operational reliability into consideration, the system can autonomously decide which control layer of the system should be optimized and how to optimize it using a control level adjustment decision module. The operational reliability factors affect these three control levels in the form of control variable constraints. Simulation results demonstrate that the proposed method can achieve a greater probability of meeting the task accuracy requirements, while extending the expected lifetime of the space manipulator.