The focus of this paper is to present the data analysis used to correlate the point load test index (Is50) with the uniaxial compressive strength (UCS), and to propose appropriate Is50 to UCS conversion factors for different coal measure rocks. Use of this design tool implies acceptance of the terms of use. From the open literature, a dataset was collected that included 176 different concrete compressive test sets. A., Hall, A., Pilon, L., Gupta, P. & Sant, G. Can the compressive strength of concrete be estimated from knowledge of the mixture proportions? ACI members have itthey are engaged, informed, and stay up to date by taking advantage of benefits that ACI membership provides them. Therefore, owing to the difficulty of CS prediction through linear or nonlinear regression analysis, data-driven models are put into practice for accurate CS prediction of SFRC. 12. Percentage of flexural strength to compressive strength To perform the parametric analysis to analyze the influence of one specific parameter (for example, W/C ratio) on the predicted CS of SFRC, the actual values of that parameter (W/C ratio) were considered, while the mean values for all the other input parameters values were introduced. It is a measure of the maximum stress on the tension face of an unreinforced concrete beam or slab at the point of. Tanyildizi, H. Prediction of the strength properties of carbon fiber-reinforced lightweight concrete exposed to the high temperature using artificial neural network and support vector machine. Compressive strengthis defined as resistance of material under compression prior to failure or fissure, it can be expressed in terms of load per unit area and measured in MPa. J. Zhejiang Univ. Beyond limits of material strength, this can lead to a permanent shape change or structural failure. Also, the characteristics of ISF (VISF, L/DISF) have a minor effect on the CS of SFRC. Download Solution PDF Share on Whatsapp Latest MP Vyapam Sub Engineer Updates Last updated on Feb 21, 2023 MP Vyapam Sub Engineer (Civil) Revised Result Out on 21st Feb 2023! Accordingly, 176 sets of data are collected from different journals and conference papers. In contrast, the splitting tensile strength was decreased by only 26%, as illustrated in Figure 3C. Standards for 7-day and 28-day strength test results The KNN method is a simple supervised ML technique that can be utilized in order to solve both classification and regression problems. Date:9/30/2022, Publication:Materials Journal 8, the SVR had the most outstanding performance and the least residual error fluctuation rate, followed by RF.