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A platform for research: civil engineering, architecture and urbanism
Model updating using genetic algorithms with sequential niche technique
https://orcid.org/0000-0001-9363-4878
Highlights A novel method for finite element model updating using sequential niche technique. Higher confidence in finding global minimum enabled by sequential niche technique. Application to lab structure and in-situ bridge and careful assessment of results.
Abstract Structural model updating is an optimisation problem where parameters that minimise the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimisation algorithms are efficient optimisation tools but are not fully immune to missing the global minimum. To increase the chance of finding the global minimum, a combination of genetic algorithm with sequential niche technique is proposed. The method performs systematic search to find multiple minima and facilitates detecting the minimum that best describes the system. The technique is applied to experimental data from a simple laboratory structure and a full-scale pedestrian cable-stayed bridge, and also tested on a deceptive problem using the numerical model of a space frame.
Model updating using genetic algorithms with sequential niche technique
https://orcid.org/0000-0001-9363-4878
Highlights A novel method for finite element model updating using sequential niche technique. Higher confidence in finding global minimum enabled by sequential niche technique. Application to lab structure and in-situ bridge and careful assessment of results.
Abstract Structural model updating is an optimisation problem where parameters that minimise the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimisation algorithms are efficient optimisation tools but are not fully immune to missing the global minimum. To increase the chance of finding the global minimum, a combination of genetic algorithm with sequential niche technique is proposed. The method performs systematic search to find multiple minima and facilitates detecting the minimum that best describes the system. The technique is applied to experimental data from a simple laboratory structure and a full-scale pedestrian cable-stayed bridge, and also tested on a deceptive problem using the numerical model of a space frame.
Model updating using genetic algorithms with sequential niche technique
https://orcid.org/0000-0001-9363-4878
Highlights A novel method for finite element model updating using sequential niche technique. Higher confidence in finding global minimum enabled by sequential niche technique. Application to lab structure and in-situ bridge and careful assessment of results.
Abstract Structural model updating is an optimisation problem where parameters that minimise the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimisation algorithms are efficient optimisation tools but are not fully immune to missing the global minimum. To increase the chance of finding the global minimum, a combination of genetic algorithm with sequential niche technique is proposed. The method performs systematic search to find multiple minima and facilitates detecting the minimum that best describes the system. The technique is applied to experimental data from a simple laboratory structure and a full-scale pedestrian cable-stayed bridge, and also tested on a deceptive problem using the numerical model of a space frame.
Model updating using genetic algorithms with sequential niche technique
Shabbir, Faisal (author) / Omenzetter, Piotr (author)
Engineering Structures ; 120 ; 166-182
2016-04-11
17 pages
Article (Journal)
Electronic Resource
English
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