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  • Open Access

    ARTICLE

    An Innovative Technique to Measure Lateral Pressure of Self-Compacting Concrete Using Fiber Bragg Grating Sensor

    Pshtiwan Shakor1,2,*, Nadarajah Gowripalan3, Paul Rocker4

    Structural Durability & Health Monitoring, Vol.18, No.4, pp. 395-408, 2024, DOI:10.32604/sdhm.2024.049366 - 05 June 2024

    Abstract Self-compacting concrete (SCC) is the most flowable concrete type that exerts high pressure on formwork. SCC is the most commonly used concrete globally for construction applications due to its cost-effectiveness. However, to make a formwork resist the exerted lateral pressure of SCC, it is required to have a suitable design for formwork. This paper presents a novel approach on how could create and prepare the Fiber Bragg Grating (FBG) optics using as a sensor to measure lateral pressure and temperature of SCC. To ensure the FBG sensor works properly a validated methodology is conducted. In More > Graphic Abstract

    An Innovative Technique to Measure Lateral Pressure of Self-Compacting Concrete Using Fiber Bragg Grating Sensor

  • Open Access

    ARTICLE

    Workability and Strength of Ceramsite Self-Compacting Concrete with Steel Slag Sand

    Suiwei Pan1, Anqi Ren1, Yongli Peng1, Min Wu2, Wanguo Dong3, Chunlin Liu2, Depeng Chen2,*

    Journal of Renewable Materials, Vol.11, No.2, pp. 881-904, 2023, DOI:10.32604/jrm.2022.023000 - 22 September 2022

    Abstract This study focuses on the workability and compressive strength of ceramsite self-compacting concrete with fine aggregate partially substituted by steel slag sand (CSLSCC) to prevent the pollution of steel slag in the environment. The SF, J-ring, visual stability index, and sieve analysis tests are primarily employed in this research to investigate the workability of freshly mixed self-compacting concrete containing steel slag at various steel slag sand replacement rates. The experiment results indicate that CSLSCC with the 20% volume percentage of steel slag (VPS) performs better workability, higher strength, and higher specific strength. The 7-day compressive More > Graphic Abstract

    Workability and Strength of Ceramsite Self-Compacting Concrete with Steel Slag Sand

  • Open Access

    ARTICLE

    Study on Acoustic Emission Characteristics of Self-Compacting Concrete under Uniaxial Compression Test

    Yongshuai Sun1,*, Guihe Wang2, Yixuan li2

    Journal of Renewable Materials, Vol.10, No.8, pp. 2287-2302, 2022, DOI:10.32604/jrm.2022.019660 - 25 April 2022

    Abstract To study the relationship between acoustic emission characteristic parameters of self-compacting concrete(SCC) and its destruction evolution, under uniaxial compression, acoustic emission(AE) tests are performed on C30 selfcompacting concrete test blocks that are preserved for 7 days and 28 days, the corresponding relationship among energy, amplitude, ring count and different failure stages of the specimens are analyzed by AE experiment, and the spatial distribution of AE in each stage is described by introducing location map. The test shows that there are two rules for the failure of SCC specimens cured for 7 days and 28 days:… More >

  • Open Access

    ARTICLE

    Mechanical Properties and Microcosmic Properties of Self-Compacting Concrete Modified by Compound Admixtures

    Song Yang1, Bing Qi1, Zubin Ai1, Zhensheng Cao1, Shiqin He2,*, Lijun Li3

    Journal of Renewable Materials, Vol.10, No.4, pp. 897-908, 2022, DOI:10.32604/jrm.2022.016653 - 02 November 2021

    Abstract It has become a research hotspot to explore raw material substitutes of concrete. It is important to research the mechanical properties of self-compacting concrete (SCC) with slag powder (SP) and rubber particle (RP) replacing cement and coarse aggregate, respectively. 12 kinds of composite modified self-compacting concrete (CMSCC) specimens were prepared by using 10%, 20% and 30% SP and 30%, 40%, 50% and 60% RP. The rheological properties, mechanical properties and microstructure of the CMSCC were investigated. Results indicate that the workability, compressive strength, splitting tensile strength and flexural strength of CMSCC prepared by 20% SP… More >

  • Open Access

    ARTICLE

    Experimental Study of Waste Tire Rubber, Wood-Plastic Particles and Shale Ceramsite on the Performance of Self-Compacting Concrete

    Lei Tian, Liuchao Qiu*, Jingjun Li, Yongsen Yang

    Journal of Renewable Materials, Vol.8, No.2, pp. 154-170, 2020, DOI:10.32604/jrm.2020.08701 - 01 February 2020

    Abstract In recent decades, the utilization of waste tires, plastic and artificial shale ceramsite as alternative fine aggregate to make self-compacting concrete (SCC) has been recognized as an eco-friendly and sustainable method to manufacture renewable construction materials. In this study, three kinds of recycled aggregates: recycled tire rubber particles, wood-plastic particles, artificial shale ceramsite were used to replace the sand by different volume (5%, 10%, 20% and 30%), and their effects on the fresh and hardened properties of SCC were investigated. The slump flow and V-funnel tests were conducted to evaluate the fresh properties of modified-SCC… More >

  • Open Access

    ARTICLE

    Prediction of Compressive Strength of Various SCC Mixes Using Relevance Vector Machine

    G. Jayaprakash1, M. P. Muthuraj2,*

    CMC-Computers, Materials & Continua, Vol.54, No.1, pp. 83-102, 2018, DOI:10.3970/cmc.2018.054.083

    Abstract This paper discusses the applicability of relevance vector machine (RVM) based regression to predict the compressive strength of various self compacting concrete (SCC) mixes. Compressive strength data various SCC mixes has been consolidated by considering the effect of water cement ratio, water binder ratio and steel fibres. Relevance vector machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification and regression. RVM is based on a Bayesian formulation of a More >

  • Open Access

    ARTICLE

    Prediction of Compressive Strength of Self-Compacting Concrete Using Intelligent Computational Modeling

    Susom Dutta1, A. Ramach,ra Murthy2, Dookie Kim3, Pijush Samui4

    CMC-Computers, Materials & Continua, Vol.53, No.2, pp. 157-174, 2017, DOI:10.3970/cmc.2017.053.167

    Abstract In the present scenario, computational modeling has gained much importance for the prediction of the properties of concrete. This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete (SCC). Three models, namely, Extreme Learning Machine (ELM), Adaptive Neuro Fuzzy Inference System (ANFIS) and Multi Adaptive Regression Spline (MARS) have been employed in the present study for the prediction of compressive strength of self compacting concrete. The contents of cement (c), sand (s), coarse aggregate (a), fly ash (f), water/powder (w/p) ratio and superplasticizer (sp) dosage More >

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