Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 166-182 |
| Number of pages | 17 |
| Journal | Engineering Structures |
| Volume | 120 |
| Early online date | 3 May 2016 |
| DOIs | |
| Publication status | Published - 1 Aug 2016 |
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Keywords
- cable-stayed bridge
- deceptive problem
- global optimization algorithms
- inverse problem
- model updating
- multiple minima
- genetic algorithm
- sequential niche technique
- structural optimization
Cite this
Model updating using genetic algorithms with sequential niche technique. / Shabbir, Faisal; Omenzetter, Piotr.
In: Engineering Structures, Vol. 120, 01.08.2016, p. 166-182.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Model updating using genetic algorithms with sequential niche technique
AU - Shabbir, Faisal
AU - Omenzetter, Piotr
N1 - The authors would like to express their gratitude to organizations and people that supported this research. Piotr Omenzetter’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research. Ben Ryder of Aurecon and Graeme Cummings of HEB Construction assisted in obtaining access to the bridge and information for modelling. Luke Williams and Graham Bougen, undergraduate research students, assisted with testing.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - Structural model updating is an optimization problem where parameters that minimize the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimization 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.
AB - Structural model updating is an optimization problem where parameters that minimize the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimization 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.
KW - cable-stayed bridge
KW - deceptive problem
KW - global optimization algorithms
KW - inverse problem
KW - model updating
KW - multiple minima
KW - genetic algorithm
KW - sequential niche technique
KW - structural optimization
UR - http://authors.elsevier.com/a/1S~7WW4G4BhLE
U2 - 10.1016/j.engstruct.2016.04.028
DO - 10.1016/j.engstruct.2016.04.028
M3 - Article
VL - 120
SP - 166
EP - 182
JO - Engineering Structures
JF - Engineering Structures
SN - 0141-0296
ER -