Build-X: Expert system for seismic analysis and assessment of 3D buildings using OpenSees

Nikolaos K. Psyrras, Anastasios G. Sextos*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
173 Downloads (Pure)


Despite the breadth of the available finite element codes for seismic analysis and assessment, the associated complexity in use and the generality in orientation are likely to increase the epistemic uncertainty involved in the models, particularly in nonlinear analysis procedures. Thus, it is of interest to develop tools for improving the reliable use of existing structural engineering software. This paper aims to present the capabilities of Build-X, a recently developed knowledge-based system tailored to the prediction of the seismic response of 3D buildings. This expert system features a simple visual user interface that supports the structural engineer throughout the structural configuration of a building, providing expert suggestions as to critical modeling decisions, and automations that increase the reliability of the analysis and accelerate the pre-processing stage. Build-X is linked with OpenSees, a widely used script-based freeware for seismic analysis of structures, which is utilized to perform the core finite element analysis. Post-processing tasks are easy to handle through the graphical engine of the system developed. A verification study demonstrates the efficiency of the system and reliability of the results generated, pointing to the way in which Build-X may serve as a useful tool for the seismic analysis of newly designed buildings and the assessment of existing ones at reduced computational cost and modeling uncertainty.

Original languageEnglish
Pages (from-to)23-35
Number of pages13
JournalAdvances in Engineering Software
Early online date6 Dec 2017
Publication statusPublished - 1 Feb 2018


  • Expert system
  • Buildings
  • Seismic assessment
  • Pushover analysis
  • Soil-structure interaction
  • OpenSees

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