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Article
Publication date: 29 March 2024

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.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 20 December 2022

Hamsavathi 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.

Details

World Journal of Engineering, vol. 21 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 27 June 2023

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.

Details

Journal of Financial Management of Property and Construction , vol. 29 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

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