2007/05/17 by Tshilidzi Marwala, Marwala, Tshilidzi, Lungile Mdlazi +3
Decision Sciences · Engineering · Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #Infrastructure Maintenance and Monitoring #Probabilistic and Robust Engineering Design #Structural Health Monitoring Techniques #stat.AP
paper · pdf · doi:10.48550/arxiv.0705.2515
7 pages, IMAC2004
arxiv created 2007/05/17 · openalex publication_date 2007/05/17 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper compares the Maximum-likelihood method and Bayesian method for finite element model updating. The Maximum-likelihood method was implemented using genetic algorithm while the Bayesian method was implemented using the Markov Chain Monte Carlo. These methods were tested on a simple beam and an unsymmetrical H-shaped structure. The results show that the Bayesian method gave updated finite element models that predicted more accurate modal properties than the updated finite element models obtained through the use of the Maximum-likelihood method. Furthermore, both these methods were found to require the same levels of computational loads.