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1 – 10 of 76Hamsavathi Kannan, Soorya Prakash K. and Kavimani V.
The aim of the work is to investigate structural behaviour of reinforced concrete (RF) beam retrofitted with basalt fibre (BF) fabric. The incorporation of BF showed enhancement…
Abstract
Purpose
The aim of the work is to investigate structural behaviour of reinforced concrete (RF) beam retrofitted with basalt fibre (BF) fabric. The incorporation of BF showed enhancement in bending strength, to increase confinement and to repair damages caused by cracking. In the early decades, using BF for composite materials shaped BF as an excellent physical substance with necessary mechanical properties, highlighting the significant procedures ability.
Design/methodology/approach
Specimens were casted with U-wrapped BF and then evaluated based on flexural tests. In the test carried over for flexural fortifying assessment, BF reinforcements demonstrated a definitive quality improvement in the case of the subjected control sample; ultimately, the end impacts depend upon the applied test parameters. From the outcomes introduced in this comparison, for the double-wrapped sample, the modifications improved by 12% than that of the single-wrapped beam, which is identified to subsist for a better strengthening of new-age retrofitting designs.
Findings
The current research deals with the retrofitting of RC beam by conducting a comparative experiment on wrapping of BF (single or double BF wrapping) in improving the mechanical behavior of concrete.
Originality/value
It can be shown from the experimental results that increasing the number of layers has significant effect on basalt strengthened beams.
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Youssef L. Nashed, Fouad Zahran, Mohamed Adel Youssef, Manal G. Mohamed and Azza M. Mazrouaa
The purpose of this study is to examine how well reinforced concrete structures can be shielded against concrete carbonation using anti-carbonation coatings based on synthetic…
Abstract
Purpose
The purpose of this study is to examine how well reinforced concrete structures can be shielded against concrete carbonation using anti-carbonation coatings based on synthetic polymer.
Design/methodology/approach
Applying free radical polymerization, an acrylate terpolymer emulsion that a surfactant had stabilized was created. A thermogravimetric analysis, minimum film-forming temperature, Fourier transform infrared spectroscopy and particle size distribution are used to characterize the prepared eco-friendly water base acrylate terpolymer emulsion. Using three different percentages of the acrylate terpolymer emulsion produced, 35%, 45% and 55%, the anti-carbonation coating was formed. Tensile strength, tensile strain, elongation, crack-bridging ability, carbon dioxide permeability, chloride ion diffusion, average pull-off adhesion strength, water vapor transmission, gloss, wet scrub resistance, QUV/weathering and storage stability are the characteristics of the anti-carbonation coating.
Findings
The formulated acrylate terpolymer emulsion enhances anti-carbonation coating performance in CO2 permeability, Cl-diffusion, crack bridging, pull-off adhesion strength and water vapor transmission. The formed coating based on the formulated acrylate terpolymer emulsion performed better than its commercial counterpart.
Practical implications
To protect the steel embedded in concrete from corrosion and increase the life span of concrete, the surface of cement is treated with an anti-carbonation coating based on synthetic acrylate terpolymer emulsion.
Social implications
In addition to saving lives from building collapse, it maintains the infrastructure for the long run.
Originality/value
The anti-carbonation coating, which is based on the synthetic acrylate terpolymer emulsion, is environmentally benign and stops the entry of carbon dioxide and chlorides, which are the main causes of steel corrosion in concrete.
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Rawan Ramadan, Hassan Ghanem, Jamal M. Khatib and Adel M. ElKordi
The purpose of this paper is to check the feasibility of using biomaterial such as of Phragmites-Australis (PA) in cement paste to achieve sustainable building materials.
Abstract
Purpose
The purpose of this paper is to check the feasibility of using biomaterial such as of Phragmites-Australis (PA) in cement paste to achieve sustainable building materials.
Design/methodology/approach
In this study, cement pastes were prepared by adding locally produced PA fibers in four different volumes: 0%, 0.5%, 1% and 2% for a duration of 180 days. Bottles and prisms were subjected to chemical shrinkage (CS), drying shrinkage (DS), autogenous shrinkage (AS) and expansion tests. Besides, prism specimens were tested for flexural strength and compressive strength. Furthermore, a mathematical model was proposed to determine the variation length change as function of time.
Findings
The experimental findings showed that the mechanical properties of cement paste were significantly improved by the addition of 1% PA fiber compared to other PA mixes. The effect of increasing the % of PA fibers reduces the CS, AS, DS and expansion of cement paste. For example, the addition of 2% PA fibers reduces the CS, expansion, AS and DS at 180 days by 36%, 20%, 13% and 10%, respectively compared to the control mix. The proposed nonlinear model fit to the experimental data is appropriate with R2 values above 0.92. There seems to be a strong positive linear correlation between CS and AS/DS with R2 above 0.95. However, there exists a negative linear correlation between CS and expansion.
Research limitations/implications
The PA used in this study was obtained from one specific location. This can exhibit a limitation as soil type may affect PA properties. Also, one method was used to treat the PA fibers.
Practical implications
The utilization of PA fibers in paste may well reduce the formation of cracks and limit its propagation, thus using a biomaterial such as PA in cementitious systems can be an environmentally friendly option as it will make good use of the waste generated and enhance local employment, thereby contributing toward sustainable development.
Originality/value
To the authors best knowledge, there is hardly any research on the effect of PA on the volume stability of cement paste. Therefore, the research outputs are considered to be original.
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Aminuddin Suhaimi, Izni Syahrizal Ibrahim and Mariyana Aida Ab Kadir
This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to…
Abstract
Purpose
This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.
Design/methodology/approach
This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.
Findings
The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.
Originality/value
The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.
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In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and…
Abstract
Purpose
In recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τu between the two materials in RC structures.
Design/methodology/approach
Three robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τu between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.
Findings
Among the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τu. According to SHAP value-based feature importance, compressive strength of concrete fc emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and fc can enhance τu between ribbed SS and concrete.
Originality/value
An online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τu. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.
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Muralidhar Vaman Kamath, Shrilaxmi Prashanth, Mithesh Kumar and Adithya Tantri
The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength…
Abstract
Purpose
The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.
Design/methodology/approach
In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.
Findings
The five statistical indicators like coefficient of determination (R2), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.
Originality/value
The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.
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Nirodha Fernando, Kasun Dilshan T.A. and Hexin (Johnson) Zhang
The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial…
Abstract
Purpose
The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.
Design/methodology/approach
The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.
Findings
An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.
Originality/value
The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.
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Khalil Idrissi Gartoumi, Mohamed Aboussaleh and Smail Zaki
This paper aims to explore a framework for implementing Lean Construction (LC) to provide corrective actions for quality defects, customer dissatisfaction and value creation…
Abstract
Purpose
This paper aims to explore a framework for implementing Lean Construction (LC) to provide corrective actions for quality defects, customer dissatisfaction and value creation during the construction of megaprojects.
Design/methodology/approach
This paper presents a case study involving the construction of the Mohamed VI Tower in Morocco. It is the tallest tower in Africa, with 55 floors and a total height of 250 m. This study of the quality of the work and the involvement of the LC was carried out using the Define–Measure–Analysis–Improve–Control approach from Lean six sigma. It describes the Critical to Quality and analyses the root causes of quality defects, customer dissatisfaction and variation in the quality process.
Findings
Firstly, the results of this study map the causal factors of lack of quality as established in the literature. Secondly, the LC tools have reduced non-value-added sources of quality waste and, consequently, improved critical quality indicators.
Research limitations/implications
This document focuses on one part of the tower’s construction and is limited to a project case in a country where LC is rarely used.
Originality/value
This study reinforces the literature reviews, surveys and the small number of case studies that have validated the potential of LC and further clarifies future directions for the practical emergence of this quality improvement approach, especially for large-scale projects.
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Ali Mohammed Ali, Manar Hamid Jasim and Bashar Dheyaa Hussein Al-Kasob
The purpose of this paper is to present an applied method to design the low-speed contact between a mass and surface of a beam using an analytical solution based on the…
Abstract
Purpose
The purpose of this paper is to present an applied method to design the low-speed contact between a mass and surface of a beam using an analytical solution based on the first-order shear deformation beam theory. Also, a simulation of impact process is carried out by ABAQUS finite element (FE) code.
Design/methodology/approach
In theoretical formulation, first strains and stresses are obtained, then kinetic and potential energies are written, and using a combination of Ritz and Lagrange methods, a set of system of motion equations in the form of mass, stiffness and force matrices is obtained. Finally, the motion equations are solved using Runge–Kutta fourth order method.
Findings
The von Mises stress contours at the impact point and contact force from the ABAQUS simulation are illustrated and it is revealed that the theoretical solution is in good agreement with the FE code. The effect of changes in projectile speed, projectile diameter and projectile mass on the results is carefully examined with particular attention to evaluate histories of the impact force and beam recess. One of the important results is that changes in projectile speed have a greater effect on the results than changes in projectile diameter, and also changes in projectile mass have the least effect.
Originality/value
This paper presents a combination of methods of energy, Ritz and Lagrange and also FE code to simulate the problem of sandwich beams under low velocity impact.
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Ying Ling Jin, Fatimah De’nan, Kok Keong Choong and Nor Salwani Hashim
Cold-formed steel has been used extensively as secondary elements such as purlins and girts in building frames. Purlin is critical to the structure of the roof because it supports…
Abstract
Purpose
Cold-formed steel has been used extensively as secondary elements such as purlins and girts in building frames. Purlin is critical to the structure of the roof because it supports the weight of the roof deck and aids to make the entire roof structure more rigid. Furthermore, cold-formed steel purlin is a replacement for wood purlin because steel purlins are light weight and more economical. Hence, the purpose of this study to investigate the effect of opening due to torsion behaviour.
Design/methodology/approach
This analysis used cold-formed steel hat purlin with and without openings (WOs) under different opening shape, location and spacing by using finite element LUSAS software.
Findings
The finite element results showed that purlin with openings had higher angle of rotation than section WO, with a percentage difference of not more than 6%. When the opening was located at mid-span, the angle of rotation reduced. Angle of rotation increased when the opening spacing increased. Number of openings also affected the torsional behaviour of the purlin. Five opening shapes, which were circle, diamond, C-hexagon, square and elongated circle, were studied. Among all the shapes, purlin with diamond opening was more resistance to torsion.
Originality/value
The use of cold-formed steel section with web openings (rectangular or circular) is a practical solution when it is required to pass service ducts through the structural member. However, the presence of opening gives minor effect on the structural behaviour of cold-formed steel hat purlin.
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