Sathvik S, Kumar Rakesh, Ulloa Nestor, Shakor Pshtiwan, Ujwal M S, Onyelowe Kennedy, Kumar G Shiva, Christo Mary Subaja
Department of Civil Engineering, Dayananda Sagar College of Engineering, Bengaluru, Karnataka, 560111, India.
Department of Civil Engineering, National Institute of Technology, Patna, India.
Sci Rep. 2024 May 21;14(1):11552. doi: 10.1038/s41598-024-62412-5.
India's cement industry is the second largest in the world, generating 6.9% of the global cement output. Polycarbonate waste ash is a major problem in India and around the globe. Approximately 370,000 tons of scientific waste are generated annually from fitness care facilities in India. Polycarbonate waste helps reduce the environmental burden associated with disposal and decreases the need for new raw materials. The primary variable in this study is the quantity of polycarbonate waste ash (5, 10, 15, 20 and 25% of the weight of cement), partial replacement of cement, water-cement ratio and aggregates. The mechanical properties, such as compressive strength, split tensile strength and flexural test results, of the mixtures with the polycarbonate waste ash were superior at 7, 14 and 28 days compared to those of the control mix. The water absorption rate is less than that of standard concrete. Compared with those of conventional concrete, polycarbonate waste concrete mixtures undergo minimal weight loss under acid curing conditions. Polycarbonate waste is utilized in the construction industry to reduce pollution and improve the economy. This study further simulated the strength characteristics of concrete made with waste polycarbonate ash using least absolute shrinkage and selection operator regression and decision trees. Cement, polycarbonate waste, slump, water absorption, and the ratio of water to cement were the main components that were considered input variables. The suggested decision tree model was successful with unparalleled predictive accuracy across important metrics. Its outstanding predictive ability for split tensile strength (R = 0.879403), flexural strength (R = 0.91197), and compressive strength (R = 0.853683) confirmed that this method was the preferred choice for these strength predictions.
印度的水泥行业是世界第二大水泥行业，占全球水泥产量的6.9%。聚碳酸酯废灰是印度乃至全球的一个主要问题。印度的健身护理设施每年产生约37万吨科学废物。聚碳酸酯废料有助于减轻与处置相关的环境负担，并减少对新原材料的需求。本研究的主要变量是聚碳酸酯废灰的用量（占水泥重量的5%、10%、15%、20%和25%）、水泥的部分替代量、水灰比和集料。与对照混合料相比，含有聚碳酸酯废灰的混合料在7天、14天和28天时的力学性能，如抗压强度、劈裂抗拉强度和弯曲试验结果更好。吸水率低于标准混凝土。与传统混凝土相比，聚碳酸酯废混凝土混合料在酸养护条件下的重量损失最小。聚碳酸酯废料被用于建筑行业以减少污染并提高经济效益。本研究进一步使用最小绝对收缩和选择算子回归以及决策树模拟了用废聚碳酸酯灰制成的混凝土的强度特性。水泥、聚碳酸酯废料、坍落度、吸水率和水灰比是被视为输入变量的主要成分。所建议的决策树模型在重要指标上具有无与伦比的预测准确性，取得了成功。其对劈裂抗拉强度（R = 0.879403）、抗弯强度（R = 0.91197）和抗压强度（R = 0.853683）的出色预测能力证实了该方法是这些强度预测的首选。
