Open Access Open Access  Restricted Access Subscription or Fee Access

Genetic Algorithm for the Analysis of the Stability of Retaining Walls


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irece.v15i1.23457

Abstract


The design of a retaining structure requires mastery of the laws of application of the forces and constraints acting on the structure and the calculation of the resulting constraints to ensure balance. This balance is partially guaranteed by adequate sizing to verify progressively the stability in the face of three types of instability (sliding, overturning and rupture of the ground under the foundation). If this is not the case, the check is recalculated. Given the complexity of the laws and the multitude of equations used, a mediocrity of the numerical software used in this field has been noted. Thus, this work aims to create a help tool to assist users (such as students and office engineers) in obtaining as quickly as possible an appropriate sizing proposal that ensures stability against sliding and overturning and prevents the foundation from warping and rupturing, depending on the properties of the soil and the relief of the slope. The validation of the model, designed with an expert system generator and using the C++ programming language, is based on a comparison with the analytical method. A good correlation has been obtained with a minimal difference range proportional to each parameter processed. The results have been made drawing curves of the three safety factors and their intersection possible to delimit the safety zone. As a result, the tool allows users to focus on the safety margin of the retaining wall and choose the best element dimensions.
Copyright © 2024 Praise Worthy Prize - All rights reserved.

Keywords


Wall Retaining; Algorithm; Stability; Reversal; Reversal; Slip

Full Text:

PDF


References


N. Bolloju, et al. A knowledge-based system for improving theconsistency between object models and use case narratives, ExpertSystems with Applications, vol. 39, pp. 9398-9410, 2012.
https://doi.org/10.1016/j.eswa.2012.02.126

K. Tripathi, A Review on Knowledge-based Expert System:Concept and Architecture, Artificial Intelligence Technique 2011.

E. Dogantekin, et al. An intelligent diagnosis system for diabeteson linear discriminant analysis and adaptive network based fuzzyinference system: LDA-ANFIS, Digital Signal Processing, vol. 20,pp. 1248-1255, 2010.
https://doi.org/10.1016/j.dsp.2009.10.021

W. Shiue, et al. A frame knowledge system for managing financialdecision knowledge, Expert Systems with Applications, vol. 35,pp. 1068-1079, 2008.
https://doi.org/10.1016/j.eswa.2007.08.035

M. G. Omran, et al. Self-adaptive differential evolution, in Computational intelligence and security, ed: Springer, 2005, pp.192-199.
https://doi.org/10.1007/11596448_28

W. Shen, et al. Systems integration and collaboration inarchitecture, engineering, construction, and facilities management : A review, Advanced Engineering Informatics, vol. 24, pp. 196-207, 2010.
https://doi.org/10.1016/j.aei.2009.09.001

B. N. Prasad, et al. An expert system for diagnosis and therapy inlung transplantation, Computers in biology and medicine, vol. 26,pp. 477-488, 1996.
https://doi.org/10.1016/S0010-4825(96)00030-3

S. L. Kendal and M. Creen, An introduction to knowledge engineering, Springer, 2007.

Abdur Rashid Khan, Zia Ur Rehman, Hafeez Ullah Amin (2011). Knowledge-Based System's Modeling for Software Process Model Selection. International Journal of Advanced Computer Science & Applications, 2(2), 20-25.
https://doi.org/10.14569/IJACSA.2011.020205

Richard J. Fateman, A Review of Macsyma, Computer Science Division Electrical Engineering and Computer Sciences Dept.University of CaliforniaBerkeley, California1982-1984, revised lightly 10/2001.

Hart, P. E., Duda, R. O., & Einaudi, M. T. (1978). PROSPECTOR-a computer-based consultation system for mineral exploration. Journal of the International Association for Mathematical Geology, 10(5), 589-610.
https://doi.org/10.1007/BF02461988

Straub J. (2022). Impact of techniques to reduce error in high error rule-based expert system gradient descent networks. Journal of Intelligent Information Systems. 58:3. (481-512). Online publication date: 1-Jun-2022.
https://doi.org/10.1007/s10844-021-00672-7

Hutchinson, Michael A. Rosenman, John S. Gero, RETWALL: An expert system for the selection and preliminary design of earth retaining structures, Knowledge-Based Systems, Volume 1, Issue 1, 1987, Pages 11-23, ISSN 0950-7051.
https://doi.org/10.1016/0950-7051(87)90003-7

Adams, T M, Hendrickson, C, Christiano, P, Expert System Architecture For Retaining Wall Design 1988, p. 9-20, Expert Systems in Transportation, Issue Number: 1187, Transportation Research Board, ISSN: 0361-1981.

Yuwen Yang, Jian-Hua Yin, Jian-Xin Yuan, Jeff N Schulyer, An expert system for selection of retaining walls and groundwater controls in deep excavation, Computers and Geotechnics, Volume 30, Issue 8, 2003, Pages 707-719, ISSN 0266-352X.
https://doi.org/10.1016/j.compgeo.2003.09.002

Esra Uray , Vahdettin Demir , Aslı Ülke Keskin , Özcan Tan, use of artificial neural networks in stability control of cantilever retaining walls, International civil engineering and architecture ICEARC'19, 2019 Trabzon, Turkey.

Mustafa, R.; Samui, P.; Kumari, S. Reliability Analysis of Gravity Retaining Wall Using Hybrid ANFIS. Infrastructures 2022, 7, 121.
https://doi.org/10.3390/infrastructures7090121

Dhamdhere, V. R. Rathi, P. K. Kolase , Design And Analysis Of Retaining Wall, International Journal of Management, Technology And Engineering Volume 8, Issue IX, september/2018 ISSN NO : 2249- 7455.

Muhammad Akram, Ismail Abdul Rahman1, Irfana Memon, A Review on Expert System and its Applications in Civil Engineering, International Journal of Civil Engineering and Built EnvironmentVol.1, No.1, 2014; ISSN 2289-6317Published by YSI Publisher.

Peter Aitken & L. Jones Bradley, The C Language, Simon & Schuster Macmillan edition, 1995.

Mustafa, R.; Samui, P.; Kumari, S. Reliability Analysis of Gravity Retaining Wall Using Hybrid ANFIS. Infrastructures 2022, 7, 121.
https://doi.org/10.3390/infrastructures7090121

Schlosser.F, Retaining walls, Engineering Techniques, Traité Construction Volume C 244, Paris 1991.

Dagdeviren, U., Kaymak, B. A regression-based approach for estimating preliminary dimensioning of reinforced concrete cantilever retaining walls. Struct Multidisc Optim 61, 1657-1675 (2020).
https://doi.org/10.1007/s00158-019-02470-w

Tintu Mary C, N. Sankar, Knowledge Based Expert System for the Selection of Retaining Walls, International Journal of Scientific & Engineering Research, Volume 7, Issue 4, April-2016 34 ISSN 2229-5518 Padfield, C.

Vautier Alph, Calculation of retaining walls Bulletin of the Vaudoise Society of Engineers and Architects, 188, Segmental Concrete Gravity Retaining Walls - Design and Construction Guide, Concrete Masonry Association of Australia, MA53, March 2005.

M. Mommessin, Analysis of the stability of retaining walls by calculation at failure, Scientific and Medical University of Grenoble French Review Of Geotechnique.

Fathol Bari, Julita Andrini Repadi, Andriani, Febrin Anas Ismail, and Abdul Hakam, Optimal Cost Of Slope Stabilization With Retaining Wall International Journal of GEOMATE, May, 2022, Vol.22, Issue 93, pp.83-90ISSN: 2186-2982 (P), 2186-2990 (O), Japan.
https://doi.org/10.21660/2022.93.3129

Bouacha, Nadjet and Belachia, Mouloud. Elaboration of an Expert System for Sizing, Designing and Verifying Flexible. Pavements Civil and Environmental Engineering Reports, vol.30, no.3, 2020, pp.94-121.
https://doi.org/10.2478/ceer-2020-0035

T. M. Adams, C. Hendrickson, P. Christiano, Expert System Architecture for Retaining Wall Design, Transportation Research Record 1187 9.

Padfield, C J and Robert J. Mair. Design Of Retaining Walls Embedded In Stiff Clay, (1984).

E A Aslamova, L. V. Arshinskiy, V. S. Aslamova, M V Krivov, Expert system for aggregate industrial safety assessment at enterprises based on knowledge technologies, IOP Conference Series Materials Science and Engineering 760(1):012007.
https://doi.org/10.1088/1757-899X/760/1/012007

Ezzedine E.mvila, Program for calculating structures in seismic zones, Analysis and implementation, Office of University Publications, 2003 edition.

Annane Abdallah, master's thesis, Retaining Wall In Seismic Zone, Hadj Lakhdar University - Batna, Algeria 2013.

Li KS, Lim J, Discussion on factor of safety and reliability in geotechnical engineering, Journal of Geotechnical and Geo environmental Engineering ASCE: 714-715, 2021.

Duncan JM, Factors of safety and reliability in geotechnical engineering. J Geotech Geo environ Eng 126(4):307-316 2000.
https://doi.org/10.1061/(ASCE)1090-0241(2000)126:4(307)

Uray, Esra & Demir, Vahdettin & Ulke, Asli & Tan, Özcan, Use of Artificial Neural Networks in Stability Control of Cantilever Retaining Walls, 2019.

Sarı, A., Çiçek, K., Effects of Parameters on Non-Linear Seismic Analysis of Fixed Offshore Platform, (2022) International Review of Civil Engineering (IRECE), 13 (5), pp. 347-356.
https://doi.org/10.15866/irece.v13i5.21186

Dhamdhere, V. R. Rathi, P. K. Kolase, Design And Analysis Of Retaining Wall, International Journal of Management, Technology And Engineering Volume 8, Issue IX, SEPTEMBER/2018 ISSN NO : 2249- 7455.

N. Bolloju, et al. A knowledge-based system for improving theconsistency between object models and use case narratives, ExpertSystems with Applications, vol. 39, pp. 9398-9410, 2012.
https://doi.org/10.1016/j.eswa.2012.02.126

K. Tripathi, A Review on Knowledge-based Expert System:Concept and Architecture, Artificial Intelligence Technique 2011.

E. Dogantekin, et al. An intelligent diagnosis system for diabeteson linear discriminant analysis and adaptive network based fuzzyinference system: LDA-ANFIS, Digital Signal Processing, vol. 20,pp. 1248-1255, 2010.
https://doi.org/10.1016/j.dsp.2009.10.021

W. Shiue, et al. A frame knowledge system for managing financialdecision knowledge, Expert Systems with Applications, vol. 35,pp. 1068-1079, 2008.
https://doi.org/10.1016/j.eswa.2007.08.035

M. G. Omran, et al. Self-adaptive differential evolution, in Computational intelligence and security, ed: Springer, 2005, pp.192-199.
https://doi.org/10.1007/11596448_28

W. Shen, et al. Systems integration and collaboration inarchitecture, engineering, construction, and facilities management:A review, Advanced Engineering Informatics, vol. 24, pp. 196-207, 2010.
https://doi.org/10.1016/j.aei.2009.09.001

B. N. Prasad, et al., An expert system for diagnosis and therapy inlung transplantation, Computers in biology and medicine, vol. 26,pp. 477-488, 1996.
https://doi.org/10.1016/S0010-4825(96)00030-3

S. L. Kendal and M. Creen, An introduction to knowledge engineering, Springer, 2007.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize