Machine learning prediction of the unconfined compressive strength of controlled low strength material using fly ash and pond ash

KL Dev, DR Kumar, W Wipulanusat - Scientific Reports, 2024 - nature.com
The sustainable use of industrial byproducts in civil engineering is a global priority,
especially in reducing the environmental impact of waste materials. Among these, coal ash …

Improved determination of the S-wave velocity of rocks in dry and saturated conditions: Application of machine-learning algorithms

M Rezaei, SR Ahmadi, H Nguyen… - Transportation …, 2024 - Elsevier
The determination of S-wave velocity (V s) is of significant importance in various engineering
disciplines, including mining, civil, and geotechnical engineering. It is beneficial to indirectly …

Stability of a rectangular trapdoor in three dimensions: A Gene expression programming method

R Domphoeun, J Shiau, S Keawsawasvong… - … and Underground Space …, 2025 - Elsevier
This paper focuses on the stability analysis of three-dimensional rectangular trapdoors
beneath cohesive-frictional soils via three-dimensional finite element limit analysis (3D …

Development of ANN-Based Metaheuristic Models for the Study of the Durability Characteristics of High-Volume Fly Ash Self-Compacting Concrete with Silica Fume

S Kumar, DR Kumar, W Wipulanusat… - Journal of Building …, 2024 - Elsevier
The construction of durable and sustainable infrastructure requires the use of industrial
byproducts such as fly ash (FA) and silica fume (SF) to enhance strength and durability. This …

[HTML][HTML] Optimization of ANN using metaheuristic algorithms for predicting failure envelope of ring foundations on anisotropic clay

DT Tran, J Shiau, DR Kumar, S Keawsawasvong - Applied Ocean …, 2025 - Elsevier
This paper is concerned with the assessment of VHM failure envelopes of ring foundations
subjected to general loadings on anisotropic clay using adaptive three-dimensional finite …

Regression Machine Learning Models for Probabilistic Stability Assessment of Buried Pipelines in Spatially Random Clays

B Chansavang, K Kounlavong, DR Kumar… - Arabian Journal for …, 2024 - Springer
The uplift capacity of pipelines buried in clay is a critical aspect of their structural integrity,
affecting their stability and performance under varying conditions. This study investigates the …

An application of coupling RAFELA and CatBoost model for tunnel stability prediction by considering the nonstationary random field of undrained shear strength

K Sang**da, S Keawsawasvong, TS Nguyen… - Modeling Earth Systems …, 2025 - Springer
This study presents a novel machine learning framework for predicting the probability of
failure (PoF) of tunnels constructed in spatially random clays considering a soil strength …

Compressive strength of bentonite concrete using state-of-the-art optimised XGBoost models

P Kumar, S Shekhar Kamal, A Kumar… - Nondestructive …, 2024 - Taylor & Francis
This study proposes an advanced soft-computing approach for predicting the compressive
strength (CS) of bentonite concrete using an optimised XGBoost model. Bentonite is valued …