Browsing by Author Daniel Niruban, S.
Showing results 1 to 13 of 13
| Issue Date | Title | Author(s) |
| 2023 | Characterization of the shape of aggregates using image analysis and machine learning classification tools | Daniel Niruban, S.; Mohan, S.; Pratheeba, J.; Sathushka, Heshan Bandara Wijekoon; Sathiparan, N. |
| 2023 | Characterization of the shape of aggregates using image analysis and machine learning classification tools | Daniel Niruban, S.; Sajeevan, M.; Pratheeba, J.; Sathushka Heshan, B.W.; Sathiparan, N. |
| 2023 | Comparative study of fly ash and rice husk ash as cement replacement in pervious concrete: mechanical characteristics and sustainability analysis | Daniel Niruban, S.; Sathiparan, N. |
| 2023 | Effect of aggregate size, aggregate to cement ratio and compaction energy on ultrasonic pulse velocity of pervious concrete: prediction by an analytical model and machine learning techniques | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
| 2022 | Influence of aggregate gradation and compaction on compressive strength and porosity characteristics of pervious concrete | Anburuvel, A.; Daniel Niruban, S. |
| 2023 | Investigation of boundary layer impact on pervious concrete | Sajeevan, M.; Daniel Niruban, S. |
| 2023 | Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete | Sajeevan, M.; Daniel Niruban, S.; Rinduja, R.; Pratheeba, J. |
| 2018 | Landfill site selection using ARCGIS and techniques | Yogananth, Y.; Nilani, S.; Vivek, N.; Thanojithan, S.; Nirojan, A.; Daniel Niruban, S.; Sampath, D.S. |
| 2023 | Mathematical Model to Predict the Compressive Strength of Pervious Concrete | Sathushka Heshan, W.; Janotha, P.; Shajeefpiranath, T.; Daniel Niruban, S.; Sathiparan, N. |
| 2023 | A mathematical model to predict the porosity and compressive strength of pervious concrete based on the aggregate size, aggregate‑to‑cement ratio and compaction effort | Sathushka Heshan, W.; Thirugnasivam, S.; Daniel Niruban, S.; Sathiparan, N. |
| 2023 | Prediction of compressive strength of fly ash blended pervious concrete: a machine learning approach | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
| 2023 | Soft computing techniques to predict the electrical resistivity of pervious concrete | Daniel Niruban, S.; Pratheeba, J.; Sathiparan, N. |
| 2023 | Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity | Sathiparan, N.; Pratheeba, J.; Daniel Niruban, S. |
