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Mathematical Model for Prediction of Compressive Strength of Normal, Standard and High Strength SCC with RCA

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Advances in Structural Engineering

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 74))

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Abstract

Sustainable development aims at improving the standard of life without compromising the environmental qualities and for future needs. These objectives can be achieved through recycling of construction/demolished waste. In the past, landfilling of construction and demolished waste materials was the general solution. As raw construction material charges have risen dramatically and also natural resources are exhausting, alternative solutions and methods are to be thought of, such as recycling of demolished waste. In the present study, recycled concrete aggregate (RCA) was used as partial and full replacements of natural aggregates (NA) to produce self-compacting concrete (SCC). Different SCC mixes were produced with RCA, substituting 0, 25, 50, 75 and 100% NA by weight. The present study aims at developing an empirical model to predict the compressive strength of SCC of different grades with different proportions of RCA. The empirical model developed resulted in predicting the compressive strength of SCC with recycled aggregate self-compacting concrete (RASCC) mixes with a maximum error of 10.9% which is within acceptable limit considering the heterogeneity of concrete mixtures. Further, the present study has also established a close correlation between theoretical (predicted) and experimental values of compressive strength having correlation coefficient value of 0.98.

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Correspondence to Srinivas Vasam .

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Vasam, S., Jaganadha Rao, K., Seshagiri Rao, M.V. (2020). Mathematical Model for Prediction of Compressive Strength of Normal, Standard and High Strength SCC with RCA. In: Subramaniam, K., Khan, M. (eds) Advances in Structural Engineering. Lecture Notes in Civil Engineering, vol 74. Springer, Singapore. https://doi.org/10.1007/978-981-15-4079-0_13

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  • DOI: https://doi.org/10.1007/978-981-15-4079-0_13

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4078-3

  • Online ISBN: 978-981-15-4079-0

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