Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 318
| Issue Date | Title | Author(s) |
| 2025 | Investigation of the compactability of pervious concrete and its impact on porosity and compressive strength | Subramaniam, D.N. |
| 2025 | Investigation of Compaction on Compressive Strength and Porosity of Pervious Concrete | Sajeevan, M.; Subramaniam, D.N.; Rinduja, R.; Pratheeba, J. |
| 2025 | Investigation on the effectiveness of fourier shape analysis in classifying milled aggregates | Mithulavan, V.; Samarasinghe, T.; Valluvan, R.; Karnan, N.; Sathiparan, N.; Subramaniam, D.N. |
| 2025 | Investigation of impact of aggregate shape on pervious concrete using machine learning classification methods | Wijekoon, S.H.B.; Ahilash, N.; Pravinjan, V.; Virupashan, K.; Sathiparan, N.; Jeyananthan, P.; Subramaniam, D.N. |
| 2025 | Predicting compressive strength in cement mortar: The impact of fly ash composition through machine learning | Sathiparan, N. |
| 2025 | The impact of oxides of cementitious materials on mortar strength: A machine learning perspective | Sathiparan, N. |
| 2025 | A systematic review of corncob ash in construction: Current findings and future directions | Sathiparan, N. |
| 2024 | Soft computing to predict the porosity and permeability of pervious concrete based on mix design and ultrasonic pulse velocity | Sathiparan, N.; Wijekoon, S.H.; Jeyananthan, P.; Subramaniam, D.N. |
| 2025 | Response surface regression and machine learning models to predict the porosity and compressive strength of pervious concrete based on mix design parameters | Sathiparan, N.; Wijekoon, S.H.; Ravi, R.; Jeyananthan, P.; Subramaniam, D.N. |
| 2024 | Quantifying the impact of chemical composition on pervious concrete strength: a comparative analysis using full quadratic model and artificial neural network | Sathiparan, N.; Jeyananthan, P.; Subramaniam, D.N. |
| 2024 | Predicting compressive strength of quarry waste-based geopolymer mortar using machine learning algorithms incorporating mix design and ultrasonic pulse velocity | Sathiparan, N.; Jeyananthan, P. |
| 2024 | Optimisation of pervious concrete performance by varying aggregate shape, size, aggregate-tocement ratio, and compaction effort by using the Taguchi method | Wijekoon, S.H.B.; Sathiparan, N.; Subramaniam, D.N. |
| 2023 | Comparative study of fly ash and rice husk ash as cement replacement in pervious concrete: mechanical characteristics and sustainability analysis | Subramaniam, D.N.; Sathiparan, N. |
| 2024 | Characterisation of the shape of aggregates using image analysis | Subramaniam, D.N.; Dassanayake, D.H.H.P.; Ahilash, N.; Wijekoon, S.H.B.; Sathiparan, N. |
| 2024 | Silica fume as a supplementary cementitious material in pervious concrete: prediction of compressive strength through a machine learning approach | Sathiparan, N.; Jeyananthan, P.; Subramaniam, D.N. |
| 2023 | Statistical Assessment of Different Aggregate Shape Factors | Wijekoon, S.H.B.; Subramaniam, D.N.; Sathiparan, N. |
| 2025 | Statistical investigation of aggregate size and shape impact on porosity and compressive strength of pervious concrete | Sajeevan, M.; Ahilash, N.; Shobijan, J.; Pravinjan, V.; Virupashan, K.; Sathiparan, N.; Subramaniam, D.N. |
| 2024 | Prediction of moisture content of cementstabilized earth blocks using soil characteristics, cement content, and ultrasonic pulse velocity | Sathiparan, N.; Tharuka, R.A.N.S.; Jeyananthan, P. |
| 2023 | Soft computing techniques to predict the compressive strength of groundnut shell ash‑blended concrete | Sathiparan, N.; Jeyananthan, P. |
| 2025 | Comparative analysis of machine learning models and standard codes for predicting compressive strength in hollow block masonry | Sathiparan, N.; Jeyananthan, P. |
Collection's Items (Sorted by Submit Date in Descending order): 1 to 20 of 318