Neural modelling of compactibility characteristics of cohesionless soil. (Received in the final form July 30, 2010)
Journal Title: Computer Assisted Methods in Engineering and Science - Year 2010, Vol 17, Issue 1
Abstract
Compaction is the method of in-situ soil modification to improve its engineering properties. Two key compactibility parameters are: the maximum dry density ρd max and the corresponding optimum water content wopt. They are basic parameters for designing, constructing and controlling the compaction quality of earth structures (e.g. earth dams, highway embankments). Soil compactibility can be determined from the laboratory compactibility curve basing on Proctor's test. However, this test is destructive, time-consuming and expensive. To facilitate the determination of the cohesionless soil compactibility parameters, correlations between ρd max and wopt and the basic parameters characterizing soil grain-size distribution (CU, D10, D20, D30, D40, D50, D60, D70, D80, and D90) were developed. Artificial neural networks are applied to determine models with good prediction quality. The neural models have higher accuracy than the classic statistical models.
Authors and Affiliations
Maria J. Sulewska
Keywords
Related Articles
- EP ID EP74057
- DOI -
- Views 133
- Downloads 0
Sequential stochastic identification of elastic constants using Lamb waves and particle filters
Sequential stochastic identification of elastic parameters of thin aluminum plates using Lamb waves is proposed. The identification process is formulated as a Bayesian state estimation problem in which the elastic consta...
CFD estimation of heat losses in thermal conductivity measurements
Knowledge of a material thermal conductivity is essential in several engineering applications. This material property serves also as a measure of the quality of manufactured materials. Nowadays, a lot of effort is direct...
Simulation of contact forces and contact characteristics during meshing of elastic beveloid gears.
Beveloid gears, also known as conical involute gears with very complex tooth shapes, gain more and more importance in industrial practice due to their ability to realize gear stages with crossed axes. This is why they ar...
Optimization of functionally gradient materials in valve design under cyclic thermal and mechanical loading
The robust and simple optimization method of functionally graded material (FGM) for combined cyclic thermal and mechanical loading with application to valve design is proposed. The optimization procedure starts from the...
A time-step insensitive recurrent approach to analyze non-stationary random responses. (Received in the final form October 28, 2008).
The recurrent approach constructed via the stochastic central difference (SCD) is a very fast method for analyzing non-stationary random responses. However, the computational results depend to a great extent upon the dis...