Journal of Science and Transport Technology
SCOPUS (2021-2024)
2734-9950
Cơ quản chủ quản: N/A
Phân tích ảnh hưởng
Các bài báo tiêu biểu
Prediction of California Bearing Ratio (CBR) of Stabilized Expansive Soils with Agricultural and Industrial Waste Using Light Gradient Boosting Machine
- 2021
Using agricultural and industrial waste such as bagasse ash, groundnut shell ash
and coal ash in stabilizing expansive soils are used as a subgrade material to
reduce harmful impaction of swelling/shrinkage of expansive soils, reduce
construction costs. It is also a solution for environmental protection.
California Bearing Ratio (CBR) is an important criterion to evaluate the
application technique...
#Stabilized exspansive soil #Machine learning #Light Gradient Boosting #California Bearing Ratio (CBR) #Agricultural/Industrial waste
Forecasting Construction Price Index using Artificial Intelligence Models: Support Vector Machines and Radial Basis Function Neural Network
- Trang 9-19 - 2022
Estimation of Construction Price Index (CPI) is important for a market economy
and it is a measure to manage construction investment costs. This is a tool to
help organizations and individuals to reduce the effort and management of
expenses for construction projects by reducing time of procedures for
calculating and adjusting the total investment for the estimation and evaluation
of contract price...
#Construction price index #Artificial Intelligence #SVM #RBFN
Forecast of surface chloride concentration of concrete utilizing ensemble decision tree boosted
- 2022
This study proposes the application of Ensemble Decision Tree Boosted (EDT
Boosted) model for forecasting the surface chloride concentration of marine
concrete A database of 386 experimental results was collected from 17 different
sources covering twelve variables was used to build and verify the predictive
power of the EDT model. The input factors considered the changes in eleven
variables, incl...
#Machine learning #Ensemble Descion Tree Boosted (EDT Boosted) #surface chloride concentration
Estimating the Compressive Strength of Self-compacting Concrete with fiber using an Extreme Gradient Boosting model
- 2023
Self-compacting concrete reinforced with fiber (SCCRF) is extensively utilized
in the construction and transportation industries due to its numerous
advantages, such as ease of building in challenging sites, noise reduction,
enhanced tensile strength, bending strength, and decreased structural cracking.
Traditional methods for assessing the compressive strength of SCCRF are
generally time-consumin...
#Compressive strength (CS) #Self-compacting concrete reinforced with fiber (SCCRF) #Extreme Gradient Boosting (XGB)
Nonlinear buckling and postbuckling of spiral stiffened FG-GPLRC cylindrical shells subjected to torsional loads
- 2021
The nonlinear buckling behavior of functionally graded graphene platelet
reinforced composite (FG-GPLRC) cylindrical shells reinforced by ring, stringer
and/or spiral FG-GPLRC stiffeners under torsional loads is studied by an
analytical approach. The governing equations are based on the Donnell shell
theory with geometrical nonlinearity of von Kármán-Donnell-type, combining the
improvability of Le...
#Functionally graded graphene platelet reinforced composite (FG-GPLRC) #Spiral stiffener #Nonlinear buckling #Torsional load #Cylindrical shell
Prediction of compressive strength of concrete at high heating conditions by using artificial neural network-based Bayesian regularization
Tập 2 Số 1 - Trang 9-21 - 2022
Cement concrete is the most commonly used material today for constructing
residential or commercial buildings, industrial parks, or particular components
such as tunnel slabs where there is a high risk of fire. This structure requires
concrete to be subjected to high temperatures generated by fires. However,
concrete under the influence of high temperature has very complex behavior
states with def...
#Machine learning #ANN #compressive strength #Bayesian regularization #K-fold cross-validation
Temperature effect on the characteristic quantities of microstructure and phase transition of the alloy Ag0.25Au0.75
- 2023
In this research, Molecular Dynamics (MD) simulations were conducted to explore
the temperature effect on the microstructure and phase transition of the
Ag0.25Au0.75 alloy. The findings reveal that as the temperature rises, the
material's phase transition switches from crystalline to liquid and vice versa.
Notably, during the phase transition, significant changes occur in the link
length (r), the ...
#Ag0.25Au0.75 alloy #microstructure #molecular dynamics #phase transition #temperature.
Temperature effect on the characteristic quantities of microstructure and phase transition of the alloy Ag0.25Au0.75
Tập 3 Số 1 - Trang 45-53 - 2023
In this research, Molecular Dynamics (MD) simulations were conducted to explore
the temperature effect on the microstructure and phase transition of the
Ag0.25Au0.75 alloy. The findings reveal that as the temperature rises, the
material's phase transition switches from crystalline to liquid and vice versa.
Notably, during the phase transition, significant changes occur in the link
length (r), the ...
#Ag0.25Au0.75 alloy #microstructure #molecular dynamics #phase transition #temperature.
Buckling behavior of spiral stiffened sandwich FGM cylindrical shells with porous core under axial compression using the FSDT
- Trang 1-9 - 2023
The linear buckling behavior of functionally graded cylindrical shells with
porous core stiffened by spiral stiffeners under axial compression using the
first-order shear deformation theory is presented in this paper. The improved
Lekhnitskii’s smeared stiffeners technique is applied for shear deformable
spiral FGM stiffeners. Approximate analytical solutions are assumed to satisfy
the simply supp...
#Functionally graded material #Porous core #Spiral stiffener #Linear buckling #Axial compression #Cylindrical shell #First-order shear deformation theory
Estimation of California Bearing Ratio of Soils Using Random Forest based Machine Learning
- 2021
California Bearing Ratio (CBR) is an essential parameter utilized to evaluate
the strength of the soil subgrades and base course materials of different types
of pavements. In this study, the Machine Learning (ML) approach has been adopted
using Random Forest (RF) model to estimate the CBR of the soil based on 10 input
parameters such as Plasticity Index (PI), Liquid Limit (LL), Silt Clay content
(...
#Machine Learning #California Bearing Ratio #Random Forest