Efficacies of suggested strength-based prediction models for estimation of compressive and tensile properties of normal concrete
DOI: https://doi.org/10.20528/cjcrl.2023.02.003
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One of the most crucial challenges faced by today’s construction industry for a speedy delivery is undeniably the ‘time-factor’ accompanied by promised quality within the framework of distinct budget. Strength based - Prediction models helps in estimating the early strengths as well as later-stage strength or strength at any age of concrete. Such models assist the structural and execution engineers in arriving at a fair judgement of compressive strength of concrete. A normal practice usually followed by the material testing laboratories and quality assurance cell at site is to assess the cube compressive strength of concrete which is an intrinsic engineering property governing the design and performance phase of structures. It is found from the literature that most of the prediction models that are formulated to estimate the compressive strength of concrete at any age are actually based on cylinder compressive strength of concrete. Therefore, this paper attempts to use some of the suggested prediction models with two sets of data, that is, one by considering experimental results of cube compressive strength found at the age of 7, 14 and 28-days and two by utilizing a conversion value, suitable cylinder compressive strength is obtained. These datasets are thoroughly used in the prediction models to accurately estimate the compressive strength of concrete. Similarly, appropriate prediction models are sought to determine the split tensile strength of normal concretes based on cubic compressive strength and cylinder compressive strength. Particularly, results of the present study showcase that although the prediction models are developed based on cylinder compressive strength, they can agreeably be used on cube strength data as the ratio of (Pi/Ai) obtained is the higher range of 0.85-1.00 and with only an early cube strength result, it is possible to predict an accurate value of split tensile strength of concrete at an age of 28-days. The effectiveness of suggested prediction models through statistical parameters are determined and their efficiencies are found to be in the higher range of 94% to 98%.
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Açıkgenç M, Alyamaç KE, Ulucan ZÇ (2015). Relation between splitting tensile and flexural strengths of steel fiber-reinforced concrete. The International Conference on the Regeneration and Conservation of Concrete Structures, Nagasaki, Japan.
Ahsanul K, Monjurul H, Md. Khasro M (2012). Predicting 28 days compressive strength of concrete from 7 days test result. Proceedings of International Conference on Advances in Design and Construction of Structures, 18-22.
Ashwini K, Srinivasa Rao P (2021). Evaluation of correlation between compressive and splitting tensile strength of concrete using alccofine and nano silica. ICIRMCT 2021, IOP Conf. Series: Materials Science and Engineering, 1-8.
Chopra P, Rajendra KS, Maneek K (2014). Predicting compressive strength of concrete for varying workability using regression models. International Journal of Engineering & Applied Sciences, 6(4), 10-22.
Chopra P, Rajendra KS, Maneek K (2015). Prediction of compressive strength of concrete using artificial neural network and genetic programming. Advances in Materials Science and Engineering, 2016, 7648467.
David JE, Gongkang FU (1995). Compression testing of concrete: cylinders vs. cubes. Special Report 119, Transportation Research and Development Bureau, New York, USA.
Jinping Z, Jianxing C, Xuefeng C, Hao Q (2019). Experiment research of concrete splitting tensile strength based on age and curing temperature. IOP Conference Series: Earth and Environmental Science, 267, 1-6.
João NP, de Brito j, Carlos C, Luís E (2019). Probabilistic conversion of the compressive strength of cubes to cylinders of natural and recycled aggregate concrete specimens. Materials, 12(2), 280.
Mane KM, Kulkarni DK, Prakash KB (2019). Prediction of tensile strength of concrete produced by using pozzolanic materials and partly replacing natural sand by manufactured sand. Challenge Journal of Concrete Research Letters, 10(3), 50-55.
Masood MR, Murtaza MN (2015). Models for prediction of 28-days concrete compressive strength. Journal of Testing and Evaluation, ASTM International, 44(3), 1-13.
Mehrdad AM, Ramezan AI (2021). Prediction of the tensile strength of normal and steel fiber reinforced concrete exposed to high temperatures. International Journal of Concrete Structures and Materials, 15(47), 1-16.
Metwally AAAA (2014). Compressive strength prediction of Portland cement concrete with age using a new model. Housing and Building National Research Center Journal, 10(2), 145-155.
Monjurul Hasan M, Kabir A (2011). Prediction of compressive strength of concrete from early age test result. 4th Annual Paper Meet and 1st Civil Engineering Congress, Dhaka, Bangladesh, 1-7.
Ramadoss P (2014). Combined effect of silica fume and steel fiber on the splitting tensile strength of high-strength concrete. International Journal of Civil Engineering, Transactions: A, 12(1), 96-103.
Reinhardt HW (2013). Understanding the tensile properties of concrete. In: Jaap Weerheijm, editor. Factors Affecting the Tensile Properties of Concrete. Woodhead Publishing Series in Civil and Structural Engineering, 19-49.
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