Predictive modeling of mechanical behavior in waste ceramic concrete using machine learning techniques Article Swipe

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Kamal Upreti , Adesh Kumar Pandey , Virendra Singh Kushwah , Pravin R. Kshirsagar , Kamal Kant Sharma , Jagendra Singh , Jyoti Parashar , Rituraj Jain ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.14419/ywwvvd04

This study identifies the critical demand for a certain approach that aims to predict and ascertain ‎the mechanical behavior of con-crete admixed with waste ceramic, a method to overcome and ‎mitigate the related environmental challenges as it pertains to the construction field. Concrete ‎modification with ceramic wastes has received significant attention due to its potential ‎improvement in sustainability. The developed predictive models on waste ceramic concrete ‎‎(WCC) involved the use of advanced machine learning techniques such as Artificial Neural ‎Network (ANN) and Light Gradient Boosting Machine (LightGBM). Experimental datasets ‎were formulated based on 5% and 20% variability of ceramic waste percentages as input ‎variables for training and testing data for validation of the proposed model. In each case, iterative ‎training improved model performance, with the ANN showing moderate predictability (R² = ‎‎0.70 and 0.67) and LightGBM demonstrating stronger accuracy. Predictive values ranged ‎between 1.02 MPa and 0.12 MPa for compressive and splitting tensile strengths and had R² ‎values of 0.70 and 0.67 for the ANN model, respectively. The established findings will lead to ‎a dependable framework for assessing and improving the performance of ceramic waste-modified concrete. In this regard, these findings have reinforced the potential of machine ‎learning in developing sustainable construction practices. This paper is of value to ‎engineers and decision-makers within the construction industry, providing an informed choice ‎towards environmental sustainability and better risk management‎.

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Ceramic Computer science Machine learning Materials science Composite material

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Type: article
Language: en
Landing Page: https://doi.org/10.14419/ywwvvd04
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DOI: https://doi.org/10.14419/ywwvvd04

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Title: Predictive modeling of mechanical behavior in waste ceramic concrete using machine learning techniques

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Publication year: 2025

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Publication date: 2025-04-30

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Authors: Kamal Upreti, Adesh Kumar Pandey, Virendra Singh Kushwah, Pravin R. Kshirsagar, Kamal Kant Sharma, Jagendra Singh, Jyoti Parashar, Rituraj Jain

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Landing page: https://doi.org/10.14419/ywwvvd04

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Concepts: Ceramic, Computer science, Machine learning, Materials science, Composite material

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