Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives

NF Alkayem, L Shen, A Mayya, PG Asteris, R Fu… - Journal of Building …, 2024 - Elsevier
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …

A comprehensive study on controlled low strength material

SK Parhi, S Dwibedy, S Panda, SK Panigrahi - Journal of Building …, 2023 - Elsevier
Abstract Controlled Low Strength Material (CLSM) is a unique and versatile material that has
gained significant attention in various engineering applications. This study presents a …

Alkali–silica reaction expansion prediction in concrete using hybrid metaheuristic optimized machine learning algorithms

SK Parhi, SK Panigrahi - Asian Journal of Civil Engineering, 2024 - Springer
Alkali–silica reaction (ASR) expansion prediction in concrete is crucial for assessing the
long-term durability and structural performance of concrete infrastructure. This study …

Efficient machine learning algorithm with enhanced cat swarm optimization for prediction of compressive strength of GGBS-based geopolymer concrete at elevated …

PK Dash, SK Parhi, SK Patro, R Panigrahi - Construction and Building …, 2023 - Elsevier
In order to assess building damage and develop fire safety applications, it is crucial to
examine the mechanical behavior of concrete after exposure to high temperatures …

A soft-computing-based modeling approach for predicting acid resistance of waste-derived cementitious composites

Q Cao, X Yuan, MN Amin, W Ahmad, F Althoey… - … and Building Materials, 2023 - Elsevier
This research aimed to build estimation models for the compressive strength (CS) of cement
mortar containing eggshell and glass powder after the acid attack using machine learning …

Influence of chemical constituents of binder and activator in predicting compressive strength of fly ash-based geopolymer concrete using firefly-optimized hybrid …

PK Dash, SK Parhi, SK Patro, R Panigrahi - Materials Today …, 2023 - Elsevier
This study focuses on investigating the impact of chemical constituents in binders and
activators on the prediction of strength, particularly proposing a novel hybrid ensemble …

Application of R-curve, ANCOVA, and RSM techniques on fracture toughness enhancement in PET fiber-reinforced concrete

SK Parhi, SK Patro - Construction and Building Materials, 2024 - Elsevier
The present study focuses on evaluating the optimal mix-design parameters of waste PET-
fiber reinforced concrete (PFRC), aiming to enhance its fracture toughness. This study is …

Factors affecting the structural performance of geopolymer concrete beam composites

S Dwibedy, SK Panigrahi - Construction and Building Materials, 2023 - Elsevier
Geopolymer concrete (GPC) is a potentially sustainable building material having acceptable
fresh, mechanical, and durable characteristics still, it has not attained global acceptance due …

AI-driven critical parameter optimization of sustainable self-compacting geopolymer concrete

SK Parhi, S Dwibedy, SK Panigrahi - Journal of Building Engineering, 2024 - Elsevier
This study aims to optimize the critical parameters of self-compacting geopolymer concrete
(SCGC) with a primary focus on enhancing compressive strength. Optimization of SCGC …

Novel ensemble learning algorithm for early detection of lower back pain using spinal anomalies

M Haider, MSA Hashmi, A Raza, M Ibrahim… - Mathematics, 2024 - mdpi.com
Lower back pain (LBP) is a musculoskeletal condition that affects millions of people
worldwide and significantly limits their mobility and daily activities. Appropriate ergonomics …