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In the era of big data, the efficient use of idle data in reinforced concrete structures has become a key issue in optimizing seismic performance evaluation methods for building structures. In this paper, based on the evaluation method of structural displacement seismic performance and based on the characteristics of high scalability and high fault tolerance of the cloud platform, the open source distributed and storage features of the Hadoop architecture cloud platform are introduced as a subproject of Apache Nutch project, Hadoop cloud platform. With features such as high scalability, high fault tolerance, and flexible deployment, the storage platform is secure, stable, and reliable. From the evaluation of the seismic performance of newly-built buildings and existing damaged buildings, according to the structural strength-ductility theory of the structure, the building structure resists earthquakes with its strength and ductility and buildings are divided into four categories. Due to the influence of time or seismic damage on the structure of reinforced concrete frame structures, their material properties are often deteriorating. Using the distributed computing design concept to efficiently process big data, a dynamic evaluation model for the seismic performance of reinforced concrete frame structures is established. A project of a 10-story reinforced concrete frame structure was selected for calculation and analysis; the engineering example was used to verify the accuracy and efficiency of the model, and the seismic performance of the floor was analyzed. It can be seen that the initial stiffness index of the structure is not sensitive to the damage location of the structure. The platform based on the concept of distributed computing big data processing can effectively improve the efficiency and accuracy of the evaluation of reinforced concrete frame structures.

Evaluation of Seismic Performance of Reinforced Concrete Frame Structures in the Context of Big Data