Browsing by Author "Amarasinghe, N"

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Open Access
Correlation of tensile strength of blended cement concrete with specimen dimensions and aggregate size: A practical test review
(SLIIT, Faculty of Engineering, 2025-02) Amarasinghe, N; Somaratna, N
Test specimen dimensions affect most strength properties of concrete. The existing empirical relationships in this regard are predominantly based on concrete samples made by using Ordinary Portland cement (OPC). An important recent trend in Sri Lanka has been the increasing use of blended cements. This makes it necessary to examine whether the relationships hold for blended cements as well. In this study, split cylinder tensile strength tests were conducted to determine whether the specimen size and the tensile strength of concrete prepared using a blended cement (Portland Composite Cement (PCC)) display relationships similar to OPC. Tests were conducted on specimens using two cement types – OPC and PCC - and three concrete mix ratios and a range of specimen dimensions to study the effect of the specimen length (L), diameter (D), and aggregate size (a) on the split cylinder tensile strength (T). The data was examined using dimensional analysis based on Buckingham's π theorem. A slight increasing trend was observed in the ratio of split cylinder tensile strength to mean a compressive strength (T/fc,mean) with an increasing L/D ratio. As for the ratio of the aggregate size to the specimen diameter (a/D), the analysis showed an increasing trend in T/fc,mean values with an increasing a/D ratio, indicating a significant correlation between T/fc,mean and a/D. A nonlinear regression analysis was used in an attempt to determine a functional relationship among the non-dimensional parameters T/fc,mean, L/D, and a/D. But the differences in the derived relationships for different concrete mixes were too large for reaching a common relationship. Perhaps this was due to the small number of data points available. It was seen that relationships established for OPC may hold true for PCC too. However, the data used was limited in range and more comprehensive further tests should be conducted to confirm these findings.
Open Access
Queue Length Prediction at Un-Signalized Intersections with Heterogeneous Traffic Conditions
(SLIIT, 2022-02-11) Rathnayake, I; Amarasinghe, N; Wickramasinghe, V; Liyanage, K
Increasing queue lengths while reducing average vehicle speeds is a notable criterion in intersections with heterogeneous traffic conditions. Such queue lengths vary with different intersection controls. Thisstudy aimed to estimate the queue length at un-signalized intersections with heterogeneous traffic conditions. The study was done for un-signalized intersections in Peradeniya and Weliwita, Sri Lanka and the data were collected through video recordings. The queue lengths in an un-signalized intersection with mixed traffic conditions have an instantaneous aggressive variation due to the uncontrolled movements. Thus, a time series analysis with the aid of Vector Auto Regression (VAR) model was used in order to estimate the queue length. Variables considered in this study were arrival flow rate, discharge flow rate, number of conflicts for 15 seconds time intervals as independent variables and queue length at the end of each 15 seconds as the dependent variable. For the modelling, the procedure of “Box-Jenkins” method was followed. After the confirmation of the variables are stationary, Cointegration check and Granger causality tests were done to check the cointegration between variables and the granger causality between variables. Then, VAR models were developed using 80% data from the total data set for both locations. The remaining 20% of the data set was used to validate the model using the MAE, MAPE, and RMSE error values between the actual and predicted queues. Among both models, 0.94 of higher R2 value and Durbin Watson value as 2 was obtained for the developed model using raw variables for Weliwita junction. Furthermore, the observed MAE, MAPE, and RMSE values for Weliwita model were 3,5 and 6%, respectively. Thus, the results of this study can be used to reduce traffic congestion while enhancing the safety of the users at un-signalized intersections in Sri Lanka.