Soil compaction optimization with soft constrain

Article type: Research Article

Authors: Jelusic, Primoz^*

Affiliations: Faculty of Civil Engineering, University of Maribor, Maribor, Slovenia

Correspondence: [*] Correspondence to: Primoz Jelusic, Faculty of CivilEngineering, University of Maribor, Maribor, Slovenia, Tel.: +386 2 2294 331; Fax: +386 2 2524 179; primoz.jelusic@um.si

Abstract: The primary benefit of fuzzy systems theory is to approximate system behavior where analytic functions or numerical relations do not exist. In soil mechanics relationship between the causes and effects can be observed with laboratory tests but is difficult to develop analytical functions or numerical relations between input and output. In geotechnical optimization the most usual constraints represent state variables of structural response for each loading case. The aim of this paper is to define the soft constrain with adaptive network-based fuzzy inference system (ANFIS) in the soil mechanics. The developed soft constrain is than applied in non-linear programming (NLP) to obtain optimal solution. In the case of soil compaction the performance of the proposed optimization algorithm is evaluated. The main aim of soil compaction is to define optimal water content at which soil can be compacted to a densest state that improve their mechanical and physical properties.

Keywords: Soil compaction, fuzzy relation equations, adaptive network-based fuzzy inference system, non-linear programming

DOI: 10.3233/IFS-151624

Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 2, pp. 955-962, 2015