Replacement of 10% WMP with cement improves the tensile behavior of concrete. The effect of partially replacing cement with WMP and finding suggests that tensile strength with WMP begins to deteriorate as the amount of waste marble powder increases. In comparison to the nominal mix, Soliman found that as the amount of WMP in the nominal concrete in place of cement increases, it deteriorates concrete strength. Marble sludge may be recycled and used as a major component of concrete mix, which can then be used as a construction material or in road pavements, among other things. The use of properly integrated industrial waste can help to minimize the amount of cement required in the concrete mix. Waste disposal is not cost-effective, and the environment is also a concern. Marble manufacturing results in a variety of chemical formations that are classified as hazardous waste. Marble is frequently used for ornamental purposes, increasing its market demand. If the waste created by the marble business is not correctly utilized, it may have an adverse effect on both the environment and the economy. From the beginning of the mining process until the end, waste is produced. India is the world’s third largest producer of marble trash. CaO, SiO 2, Al2O3, and Fe 2O 3 are significant constituents, whereas MgO, SO 3, K 2O, and Na 2O are minor constituents. WMP is a promising resource that may be used to partially replace cement and sand. As an alternative, WMP can be used instead of cement or fine aggregates. Apart from silica-fume and basalt fiber, some researchers use coconut fiber as a partial replacement for cement. Furthermore, silica fume can be used in place of cement in concentrations ranging from 0 to 10%, which improves the interface bond. The bond strength of the concrete matrix can be improved by using calcium carbonate whiskers and basalt fiber in the concrete matrix. In comparison to input factors for this data set, the number of curing days followed by the CA, C, FA, w, and MP is essential in predicting the flexural and compressive strength of a concrete mix for this data set. Results suggest that all applied techniques are reliable for predicting the compressive and flexural strength of concrete and are able to reduce the experimental work time. The Gaussian process and Support vector machines Stochastic predicts better outcomes for flexural and compressive strength because it has a higher coefficient of correlation (0.8235 and 0.9462), lower mean absolute and root mean squared error values as (2.2808 and 1.8104) and (2.8527 and 2.3430), respectively. Therefore, it can be inferred that the gaussian process and support vector machine methods can be used to predict the respective outputs, i.e., flexural and compressive strength. The effectiveness of models was also evaluated by using statistical criteria. In order to accomplish the goal, the models of Support vector machines, Support vector machines with bagging and Stochastic, Linear regression, and Gaussian processes were applied to the experimental data for predicting the compressive and flexural strength of concrete. The purpose of the research is to predict the compressive and flexural strengths of the concrete mix by using waste marble powder as a partial replacement of cement and sand, based on the experimental data that was acquired from the laboratory tests.
0 Comments
Leave a Reply. |