Genetic programming for soil-fiber composite assessment
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Kurugodu:2018:AES,
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author = "H. V. Kurugodu and Sanandam Bordoloi and Yi Hong and
Ankit Garg and Akhil Garg and Sekharan Sreedeep and
A. H. Gandomi",
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title = "Genetic programming for soil-fiber composite
assessment",
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journal = "Advances in Engineering Software",
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year = "2018",
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volume = "122",
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pages = "50--61",
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month = aug,
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keywords = "genetic algorithms, genetic programming, Unconfined
compressive strength, Reinforced soil, Polypropylene
fiber, Strength improvement factor",
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ISSN = "0965-9978",
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URL = "http://www.sciencedirect.com/science/article/pii/S0965997817312000",
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DOI = "doi:10.1016/j.advengsoft.2018.04.004",
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abstract = "Unconfined compressive strength (UCS) of soil is one
of the basic index parameters for representing the
compressive bearing strength of soil. Fiber reinforced
soil is one of the most popular and practical ground
improvement approaches used in geotechnical
infrastructures. Analytical models for estimating UCS
of soil-fiber composites have been developed in the
literature. However, these models rarely incorporate
the combined effects of dynamic field parameters such
as fiber content, soil moisture, and density. These
effects can be studied by the development of a holistic
model based on a dimensionless strength improvement
factor (SIF), which is defined as the ratio of UCS of
reinforced soil to the unreinforced UCS. The current
model estimating SIF indicates the improvement expected
in UCS of soil-PP fiber composite based on the three
design conditions such as fiber content, soil density,
and moisture content. For this purpose, a series of 108
laboratory tests were first conducted to measure UCS of
both fiber-reinforced soil and unreinforced soil under
different fiber contents, soil density, and soil
moisture content. Clayey silt soil and commercially
used polypropylene (PP) fibres were selected in this
study as soil and fiber material respectively. Genetic
programming (GP) approach was then used to formulate
models based on the measured data. The hidden
non-linear relationships between SIF and the three
inputs were determined by sensitivity and parametric
analysis of the GP model. It was found that the
moisture content in the soil has the highest influence
on the strength factor that accounts for the change in
strength. Coupled effects of soil parameters (soil
moisture, soil density) and fiber content have been
studied using parametric analysis which includes
different possible field conditions (parameters). The
results have been discussed along with the
reinforcement mechanism of PP fiber for different soil
conditions. It is believed that the robust GP model
developed will be useful to determine optimum input
values for designing safe bearing foundation soils
which are reinforced with PP fibers.",
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notes = "Also known as \cite{KURUGODU201850}",
- }
Genetic Programming entries for
Kurugodu Harsha Vardhan
Sanandam Bordoloi
Yi Hong
Ankit Garg
Akhil Garg
Sekharan Sreedeep
A H Gandomi
Citations