Research on a methodology for intelligent seismic performance evaluation and optimization design of buildings based on IFC and ontology

Abstract

• A set of theoretical framework of building seismic performance evaluation has been formed, and the automatic evaluation of actual seismic performance of buildings has been realized. • This framework meets the evaluation requirements of various performance indicators in the existing FEMA P-58, and can make rapid and accurate predictions, which greatly improves the evaluation efficiency and quality, and provides fundamental support for the rapid assessment and prediction of regional and city-level building groups. • A set of discrete size variable multi-objective optimization model is proposed. The multi-objective optimization model proposed in this paper establishes a one-to-one correspondence between the design scheme and the two major costs from the perspective of structural size variables, which realizes the micro-level optimization design and improves the optimization level. Seismic loss prediction and performance assessment for buildings have already been hot spots for resilience after earthquakes with the emergence of the concepts of digital twins. However, because a large amount of multisource heterogeneous data and a real-time accurate prediction model are required to implement the process, the popularization and implementation of these technologies are hampered. Based on performance-based seismic design (PBSD) theory, this study introduces BIM and ontology and other emerging technologies to carry out methodology research on intelligent earthquake damage prediction and seismic performance evaluation for individual buildings. First, based on FEMA P-58 (Seismic Performance Assessment of Buildings), this paper uses BIM technology to integrate and transmit component-level engineering information. Ontology method is used to express the assessment content and logic, and a multidimensional semantic ontology model based on IFC is proposed to form the linked data foundation to organize, store, associate and interact the multisource heterogeneous data required for assessment in a unified way to realize the semi-automated seismic performance assessment for individual RC frame building. On this basis, the seismic optimization design under the guidance of the “investment - benefit” criterion is regarded as the problem of seeking the balance between the initial construction cost and the expectation of seismic loss. The multi-objective genetic algorithm (NSGA-II) is used to realize the optimization iteration at the component level. According to the results of the case study, the new method in this paper significantly improves the quality of seismic performance assessment and seismic design optimization.