Python-based computational platform to automate seismic design, nonlinear structural model construction and analysis of steel moment resisting frames. (1st December 2020)

• Record Type: Journal Article
• Authors: Guan, Xingquan; Burton, Henry; Sabol, Thomas
• Is Part Of: Engineering structures. Volume 224(2020)
• Publication Date: 2020-12-01
• Subjects: Computational platform -- Seismic design automation -- Nonlinear structural model construction -- Nonlinear structural analysis -- Steel moment frames; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2020.111199
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Developed a platform to automate seismic design and nonlinear structural analysis. The algorithms and programing structures of the platform were presented. The reliability and efficiency of the platform were rigorously evaluated. Possible extensions and limitations of the platform were discussed. Abstract: An end-to-end computational platform is presented, which automates seismic design, nonlinear structural model construction, and response simulation (static and dynamic) of steel moment resisting frames. A modular framework is adopted along with the object-oriented programming paradigm to ensure the adaptability of the platform. The seismic design module iteratively generates code-conforming section sizes and detailing for beams, columns, and beam-column connections based on the relevant input design variables including the building configuration (e.g., the number of stories, the number of lateral-force resisting systems, and the building dimensions), loads (e.g., dead and live loads on each floor), and site conditions (mapped spectral acceleration parameters). The nonlinear model construction and analysis module takes the design results as input and produces structural models that capture flexural strength and stiffness deterioration in the frame beam-column elements, and performs pushover and response history analyses. Illustrative examples are presented to demonstrate the reliability, accuracy, and efficiency of the platform, which significantly reduces the time and effort involved in producing iterative structural designs and conducting nonlinear analyses, both of which are necessary for performance-based seismic design. Additionally, the platform can be used to create an extensive database of archetype steel moment frame buildings towards the development of analytics-driven design methods.