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Utilizing panel data pertaining to green building across 333 prefecture-level administrative units in China (excluding Hong Kong, Macao, and Taiwan) during the period spanning 2008–2020, an exhaustive examination of the evolution of China's spatial pattern in green building is conducted employing the nearest neighbor index method, spatial autocorrelation analysis method, and kernel density analysis method. Furthermore, geographic probes are employed to scrutinize the determinants influencing China's spatial configuration of green buildings. The findings reveal that: (1) An alteration in the density distribution from a "unipolar nucleus and double sub-nuclei" configuration to a "triple polar nuclei and multiple sub-nuclei" manifestation has been discerned in the spatial agglomeration of green buildings in China, exhibiting annual growth. Additionally, the center of green building development has shifted from the northwest to the southwest. (2) Pronounced agglomerations are predominantly situated in the eastern, central, and western regions of the country. High-high agglomerations have gradually dissipated over time in the central provincial capitals of China, the Yangtze River Delta, the Pearl River Delta, and the city clusters of Beijing-Tianjin-Hebei along the eastern seaboard. The western regions manifest a concentration of low-low and low-high aggregates, with high-low agglomeration primarily observed in the provincial capitals of the western regions. (3) The spatial differentiation of green buildings in China is attributable to a multitude of variables encompassing the environment, economy, society, and policies. Among these factors, economic, social, and innovative elements exert the most significant influence on the explicable degree of spatial differentiation. [ABSTRACT FROM AUTHOR]

The asymmetric reforcement technique of composite laminates with small holes has been studied a lot, but the lamiates with big holes are paid less attention.The tensile and shear experiments are conducted for the laminates reinforced by bolt connection technique and intercalation technique.The finite element method is used to perform the numerical simulation for the reinforced composite laminate, and the simulation results are in accord with experiment results.The position where maximum strain happens are gotten from experiment study and numeral simulation, and the reinforcement schemes are compared.The results show that the intercalation reinforcement scheme is better than bolt reinforcement scheme.

To give full play to the coefficient of utilization of composite materials and reduce the structure weight, it is very important to optimize the design of thick composite structure. However, the complex design space, the inter-laminar stresses problem, and the discrete design variables make the optimization of thick composite structures very difficult. Aiming at the optimum design of thick composite structure which is formed by repeating sub-laminates, a multi-step optimization method is proposed in this paper. This method is composed of two steps. The first-step optimization design is conducted using the approximate model which is based on radial basis function neural network. The design variables include the number of plies in the sub-laminate and ply volume proportion. The second-step optimization is divided into two levels. The design variables of the system level are the number of sub-laminates, and the objective is to minimize the structural mass. The sub-system level is the optimization of laminate stacking sequence using genetic algorithm, and the objective is to minimize the inter-laminar stress factor. Matlab is adopted to program the genetic algorithm, and then integrated with Isight to carry out the whole optimization process. The case study shows that the multi-step optimization design method proposed in this paper is effective, and can achieve the optimization of thick composite laminate structure consisting of a repeating sub-laminate.