Massive reinforced concrete (RC) structure is widely used in long-term damp environments. To improve the concrete durability and reduce the reinforcing steel corrosion, crack width control is more rigorous in massive RC structure. In this paper, the short-term (30 days) temperatures of concrete are measured by the distributed temperature system (DTS) to inverse the thermal parameters using the genetic algorithm (GA), and the long-term (300 days) temperature is predicted by using the calculated thermal parameters. Moreover, thermal stress field considering the creep is calculated based on the eight-parameters-equation, and the parameters were modified by the results of temperature stress test machine (TSTM). Furthermore, a quantitative reinforcement configuration method is proposed on the basis of the predicted thermal stress field, and its feasibility and effectiveness are verified by a sluice pier structure. Finally, the optimal reinforcement scheme obtained was selected by the comparisons of the crack width, reinforcement stress and the total cross-sectional area of reinforcement. This article provides a new methodology to design reinforcement configuration for massive RC structure.

This paper proposed an adaptive vector nonsingular terminal sliding mode control (NTSMC) algorithm for the finite-time tracking control of a class of n-order nonlinear dynamical systems with uncertainty. The adaptive vector NTSMC incorporates a vector design idea and novel adaptive updating laws based on the commonly used NTSMC, which consider the common existence of the degree-of-freedom (DOF) directional differences and eliminate the chattering problem. The closed-loop stability of the n-order nonlinear dynamical systems under the adaptive vector NTSMC is demonstrated using Lyapunov direct method. Simulations performed on a two-degree-of-freedom (DOF) manipulator are provided to illustrate the effectiveness and advantages of the proposed adaptive vector NTSMC by comparing with the common NTSMC.