Strength characterization of concrete using industrial waste as cement replacing materials for rigid pavement

Chore, H.S.; Joshi, Mrunal P.

doi:10.1007/s41062-020-00328-5

Cited by 19 publications

(5 citation statements)

References 19 publications

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“…Damage to pavement in the form of fatigue cracking materializes due to recurrent vehicular loads generating stresses beneath the flexural tensile strength of concrete pavements [5]. The behavior of crack formation in reinforced concrete slabs is markedly influenced by repeated loading [6].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Effects of Reinforcement Ratio on Concrete Rigid Pavement Structure in Malang, Indonesia: Experimental Study and Analysis

Rasidi,

Aditya,

Mudjanarko

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Rigid pavement, known for its superior stiffness compared to flexible asphalt pavements, demands thorough scrutiny of deflection characteristics. Insufficient evaluations of concrete quality, slab thickness, and reinforcement levels can result in significant deflection issues, including slab cracks, pumping, and pavement faulting. This study seeks to evaluate deflection behavior in rigid pavement, considering various reinforcement ratios through experimental analysis using a monotonic static line load. A rectangular concrete slab is placed on soil with a specific California Bearing Ratio (CBR) value to provide support. Reinforcement ratios vary from the smallest to the largest values. Concrete quality is denoted by fc’ with a specified MPa value, and steel quality is indicated as fy with a predetermined MPa value. The findings indicate that deflection in rigid pavement is influenced by the reinforcement ratio, with higher ratios leading to reduced deflection for a given load. The most pronounced deflection is observed in rigid pavement with a particular reinforcement ratio, subjected to a specific load and stress, resulting in a specific deflection magnitude. The relationship between deflection and stress is characterized by sharp and gentle increments in deflection within different stress ranges, as described by proposed linear equations.

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Section: Introductionmentioning

confidence: 99%

Exploring the Effects of Reinforcement Ratio on Concrete Rigid Pavement Structure in Malang, Indonesia: Experimental Study and Analysis

Rasidi,

Aditya,

Mudjanarko

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…One of the best cost-effective approaches to enhance the qualities of RCA and obtain RAC that is similar to NAC is by adding supplementary cementitious materials [ 3 , 4 ]. Additional cementitious ingredients including metakaolin (MK), ground granulated blast-furnace slag (GGBS), silica fume (SF), and fly ash (FA) have been used in blended cement or Portland cement concretes for many years [ 5 , 6 , 7 ]. By providing a denser matrix, the use of GGBFS to replace ordinary Portland cement partially increases concrete strength and durability, extending the service life of concrete structures.…”

Section: Introductionmentioning

confidence: 99%

Development of Prediction Model to Predict the Compressive Strength of Eco-Friendly Concrete Using Multivariate Polynomial Regression Combined with Stepwise Method

et al. 2022

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Concrete is the most widely used building material, but it is also a recognized pollutant, causing significant issues for sustainability in terms of resource depletion, energy use, and greenhouse gas emissions. As a result, efforts should be concentrated on reducing concrete’s environmental consequences in order to increase its long-term viability. In order to design environmentally friendly concrete mixtures, this research intended to create a prediction model for the compressive strength of those mixtures. The concrete mixtures that were used in this study to build our proposed prediction model are concrete mixtures that contain both recycled aggregate concrete (RAC) and ground granulated blast-furnace slag (GGBFS). A white-box machine learning model known as multivariate polynomial regression (MPR) was developed to predict the compressive strength of eco-friendly concrete. The model was compared with the other two machine learning models, where one is also a white-box machine learning model, namely linear regression (LR), and the other is the black-box machine learning model, which is a support vector machine (SVM). The newly suggested model shows robust estimation capabilities and outperforms the other two models in terms of R2 (coefficient of determination) and RMSE (root mean absolute error) measurements.

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“…Based on the condition of the Simpang Pintu -Benakat road, Penungkal Abab Lematang Ilir (PALI), it is necessary to build a road that accommodates the load that traverses the section, using concrete/rigid pavement (Rigid Pavement) (Rasol et al, 2020). Concrete/rigid Pavement (Rigid Pavement) is a pavement construction with a binding material in the form of cement with a continuous and continuous type of concrete slab, as well as using or without reinforcement located on the subgrade or part of the foundation layer (Pillay et al, 2021;Chore & Joshi, 2020).…”

Section: Introductionmentioning

confidence: 99%

Planning of Rigid Pavement Thickness in The Construction of The Sp. Door - Sp. Benakat Penungkal Regency Abab Lematang Ilir

Nisumanti

Julian

Qubroh

2022

JAETS

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The access section to Benakat Village, Pali Regency is a special road made by the company, with the condition of the existing land being unpaved with a length of 1,375 meters and a width of 7 meters, and has severe damage triggered by vehicles with excess capacity or ODOL (Over Dimension Over Load)) that pass through that path. The purpose of this study was to determine the results of the calculation of rigid pavement thickness planning by comparing the 1993 AASHTO and 2017 MDPJ methods so that the road Sp. Doors – Sp. Benakat is able to accommodate ODOL vehicles. This study uses AASHTO 1993 and MDPJ 2017 as methods to produce rigid pavement thickness (Rigid Pavement) so that ODOL vehicles can pass. Based on the results of data analysis and calculations, the input indicators in each method are different for each method so that AASHTO 1993 produces a thickness of 35 cm, and in MDPJ it produces a thickness of 28.5 cm

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Strength characterization of concrete using industrial waste as cement replacing materials for rigid pavement

Cited by 19 publications

References 19 publications

Exploring the Effects of Reinforcement Ratio on Concrete Rigid Pavement Structure in Malang, Indonesia: Experimental Study and Analysis

Exploring the Effects of Reinforcement Ratio on Concrete Rigid Pavement Structure in Malang, Indonesia: Experimental Study and Analysis

Development of Prediction Model to Predict the Compressive Strength of Eco-Friendly Concrete Using Multivariate Polynomial Regression Combined with Stepwise Method

Planning of Rigid Pavement Thickness in The Construction of The Sp. Door - Sp. Benakat Penungkal Regency Abab Lematang Ilir

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