Utilization of EPS Beats and Polypropylene Fiber in Controlled Low Strength Material

Controlled low-strength material (CLSM) is a self-levelling cementitious material. It is not concrete nor soil-cement, however, it possesses properties similar to both. CLSM is widely used as a replacement for soil-cement material in many geotechnical applications such as structural backfill, pipeline beddings, void fill, pavement bases and bridge approaches. This paper study potential possibility of polypropylene fiber in CLSM. Harden and fresh properties compressive strength , flowability and density for the proposed CLSM were investigated. This CLSM mix design with different percentage of polypropylene fiber and pond ash, cement and water. EPS beats and polypropylene add 0 %, 0.5%, 1.0% and 1.5% of total weight is added in CLSM MIx. Results show that the CLSM incorporating EPS beats and polypropylene satisfies compressive strength requirement as per the requirements of ACI committee 229. polypropylene decreases the flowability of CLSM mix and at the same tine by adding EPS beats the density of CLSM mix are reduce which become lightweight CLSM mix. from this it can conclude that polypropylene fibers is less effective in CLSM mix and EPS beats make CLSM mix lightweight which create lightweight CLSM mix applicable for filling application.

Predicting CBR value of stabilized pond ash with lime and lime sludge using multivariate adaptive regression splines

In this study, multivariate adaptive regression splines (MARS) model with order two and three were developed for predicting the California bearing capacity (CBR) value of pond ash stabilized with lime and lime sludge. To this aim, the model had five variables named maximum dry density, optimum moisture content, lime percentage, lime sludge percentage, and curing period as inputs, and CBR as output variable. MARS-O3 has the best results, which its R2 stood at 0.9565 and 0.9312, and PI 0.0709 and 0.1061 for the training and testing phases, respectively. In both developed models, the estimated CBR values in training and testing stages specify acceptable agreement with experimental results, representing the workability of proposed equations for predicting the CBR values with high accuracy. Comparison of two developed equations supplied that MARS-O3 has a better result than MARS-O2. Based on error curves, the MARS-O3 model results in the lowest error percentage in the CBR predicting process, providing roughly accurate prediction than those of the rest developed methods specified. Therefore, MARS-O3 could be recognized as the proposed model.