Browse > Article
http://dx.doi.org/10.14481/jkges.2022.23.1.25

Multi-layered Ground Back Analysis of Retaining Wall Using Differential Evolution Algorithm : Basic Research of Digital Twin  

Lee, Donggun (Department of Civil Engineering, Inha University)
Kang, Kyungnam (Department of Civil Engineering, Inha University)
Song, Kiil (Department of Civil Engineering, Inha University)
Publication Information
Journal of the Korean GEO-environmental Society / v.23, no.1, 2022 , pp. 25-30 More about this Journal
Abstract
It is very important to investigate the ground properties of a construction site for the stability during the construction of the retaining wall. In the retaining wall construction stage, ground properties are checked through ground investigation, but the actual ground properties may be different from the ground investigation result. In order to analyze the stability of the retaining wall in real time, it is important to reflect the properties of the actual ground. Also, when it is judged that the wall is unstable, an appropriate solution must be provided for the stability of the wall. This study aims to present a technique for predicting the actual ground properties through a differential evolution algorithm and judging the stability of the earth wall in real time through the digital twin of the retaining wall.
Keywords
Back analysis; Digital twin; Retaining wall; FLAC 3D;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Seong, J. H., Jeong, S. H. and Shin, J. Y. (2011), A study on safety management improvement plan for retaining excavation construction through accident case analysis, Journal of the Korea institute for structural maintenance and inspection., Vol. 15, No. 6, pp. 175~183.   DOI
2 Jeong, J. H., Hwang, S. Y., Yun, H. J. and Yu, U. S. (2020), [IV Focus Area] Smart construction digital platform construction and test bed operation, Construction Engineering and Management, Vol. 21, No. 4, pp. 25~30.
3 Schweiger, H. F. (2002), Benchmarking in geotechnics 1. Computational Geotechnics Group, CGG IR006.
4 Yin, Z. Y., Jin, Y. F., Shen, J. S. and Hicher, P. Y. (2018), Optimization techniques for identifying soil parameters in geotechnical engineering: comparative study and enhancement, International Journal for Numerical and Analytical Methods in Geomechanics, Vol. 42, No. 1, pp. 70~94.   DOI
5 Jeong, D. Y. (2021), A five-level model of the technical definition and detailed evolution of the digital twin, OSIA Standards & Technology Review, Vol. 34, No. 1, pp. 10~16.
6 Shim, C. S., Jeon, C. H., Kang, W. R., Dang, G. S. and Sso, K. Y. (2018), Definition of digital twin models for prediction of future performance of bridges, Journal of KBIM, Vol. 8, No. 4, pp. 13~22.
7 Vesterstrom, J. and Thomsen, R. (2004), A comparative study of differential evolution, particle swarm optimization, and evolutionary algorithms on numerical benchmark problems, In Proceedings of the 2004 congress on evolutionary computation (IEEE Cat. No. 04TH8753), Vol. 2, pp. 1980~1987.
8 Kang, K. N. (2019), Design and reinforcement plan of NATM tunnel wih optimization algorithm, Master's thesis, Inha University.
9 Han, M. S., Shin, S. B., Moon, T. W., Kim, D. W. and Lee, J. H. (2019), Digital twin model of a beam structure using strain measurement data, Journal of KBIM, Vol. 9, No. 3, pp. 1~7.
10 An, J. S. (2017), The development of differential evolution-based back analysis algorithm for the evaluation of operating tunnel stability, Ph.D's thesis, Inha University.