Determination of the shear speed of soil triaxial testing based on fuzzy logic

  • Chi Tran University of Warmia and Mazury in Olsztyn

Abstract

To design foundations, embankments and other soil structures, geotechnical engineers require methods of assessing engineering properties of soils. Some of the more complex phenomena that occur in soils have often been difficult to recreate in a laboratory: seismic activity, vibration, unsaturated condition, control of principal stresses etc. are areas which have proven difficult to replicate, despite their importance of being understood. This was partly due to the lack of test systems capable of reproducing these effects and the complexity of test systems that were developed to carry out such work. A number of advanced computer/ software controlled systems allow the geotechnical engineer to perform the most complex test regimes via a user-friendly software interface. However, it is difficult to determine firstly parameters needed, e.g. shear speed in soil triaxial testing. In this paper we represent a new approach to determine this shear speed by solving the inverse problem using testing results obtained by the forward procedure. Direct search method, i.e. Adaptive Neuro-Fuzzy Inference System (ANFIS), is developed and applied to soil triaxial shear tests. It allows us to use the advanced sensor and actuator technologies in order to change the traditional triaxial shear apparatus from a mechanical system to a mechatronics system in next work.

Keywords

soil triaxial testing, shear speed, fuzzy logic, neuro-fuzzy inference system,

References

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[5] Wykeham Farrance. Controls Group. Soil Mechanics Testing Systems. XIV Krajowa Konferencja Mechaniki Gruntów i Iniynierii Geotechnicznej, Białystok 2006.
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Published
Jul 22, 2022
How to Cite
TRAN, Chi. Determination of the shear speed of soil triaxial testing based on fuzzy logic. Computer Assisted Methods in Engineering and Science, [S.l.], v. 15, n. 2, p. 113-121, july 2022. ISSN 2956-5839. Available at: <https://cames.ippt.gov.pl/index.php/cames/article/view/751>. Date accessed: 23 nov. 2024.
Section
Articles