Techniques to reduce the computational burden in performance-based risk optimization problems

• Grant number: 23/02504-8
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: September 01, 2023
• End date: August 31, 2024
• Field of knowledge: Engineering - Civil Engineering - Structural Engineering
• Principal Investigator: André Teófilo Beck
• Grantee: Isabela Durci Rodrigues
• Supervisor: Seymour Milton John Spence
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: University of Michigan, United States
• Associated to the scholarship: 20/14072-7 - Performance-based optimization of RC structures subject to seismic actions, BP.DR

Abstract

This research project is associated with PhD project number 2020/14072-7 entitled "Performance-Based optimization of RC structures subjected to seismic actions". The project aims to investigate and implement techniques to reduce the computational effort necessary to solve Performance-Based Risk Optimization problems proposed in the associated research project, considering the Performance-Based Earthquake Engineering (PBEE) methodology. The techniques to be studied include Kriging, Machine Learning, Model Order Reduction, and combinations thereof. Performance-Based Engineering (PBE) for several hazards is a widely adopted methodology by researchers worldwide, since it gives risk scenarios and reveals potential losses for decision makers about the performance of a structure subjected to natural hazards. Along with knowledge about the structural performance, researchers also aim at reducing the vulnerability of structures subjected to hazards, naturally integrating optimization techniques. But the computational effort necessary for Performance-Based Risk Optimization may become prohibitive, since it is necessary to evaluate the structural performance in a probabilistic way inside an optimization loop. If the optimization problem becomes a multi-objective problem, which is common in the PBE field, this problem becomes even more time consuming. This project aims at complementing the knowledge of the research group in Brazil with Prof. Spence's research group expertise in Kriging and Model Order Reduction, as well as other advanced techniques for reducing the computional burden in solution of stochastic dynamics problems. Such techniques aim at approximating the response of a structure considering a seismic action and also to speed up the internal iterations of the optimization algorithm that will be transformed into a Multi-objective optimization problem. This research internship abroad will be fundamental to boost the candidates PhD thesis supported by FAPESP. (AU)