A5010650089- Masonry and Concrete Structural Analysis
- Innovative concrete reinforcement materials
- Concrete and Cement Materials Research
- Urban Stormwater Management Solutions
- Hygrothermal properties of building materials
- Infrastructure Maintenance and Monitoring
- Seismic Performance and Analysis
- Building materials and conservation
- Smart Materials for Construction
- Structural Behavior of Reinforced Concrete
- Recycled Aggregate Concrete Performance
- Recycling and utilization of industrial and municipal waste in materials production
- Geotechnical Engineering and Soil Stabilization
- Structural Analysis of Composite Materials
- Innovations in Concrete and Construction Materials
- Geotechnical and construction materials studies
- Natural Fiber Reinforced Composites
- Structural Health Monitoring Techniques
- Structural Analysis and Optimization
- Water Quality Monitoring Technologies
- Magnesium Oxide Properties and Applications
- Asphalt Pavement Performance Evaluation
- BIM and Construction Integration
- Acoustic Wave Phenomena Research
- Materials Engineering and Processing
University of Jaffna
2017-2025
The University of Tokyo
2005-2015
University of Ruhuna
2013-2015
Tokyo University of Science
2012
Advanced Institute of Industrial Technology
2005-2009
Meguro Parasitological Museum
2008
Pervious concrete is a special type of consisting cement, coarse aggregate and water. Cement widely used raw material for construction including pervious had led to the release huge amounts CO2 environment. Therefore, there lot research interest in finding supplementary cementitious materials. The present study examined compared feasibility using industrial waste fly ash (FA) agricultural rice husk (RHA) sustainable production. An experimental program was performed with substitution FA RHA...
The current study aimed to investigate the possibility of predicting compressive strength geopolymer mortar by mix design parameters, ultrasonic pulse velocity (UPV) and machine learning techniques. Here is produced from eggshell ash rice husk as precursors, NaOH solution activator quarry waste fine aggregate. Twenty-seven combinations a total 189 cubes were cast tested for UPV strength. Seven different techniques used predict assessment tools: linear regression, artificial neural networks,...
Abstract The prediction of compressive strength is crucial, as it influenced by various mix parameters such aggregate size, aggregate-to-cement ratio, and compaction. Accurate forecasting ensures optimized designs, enhancing both performance material efficiency in construction projects. novelty this study lies integrating machine learning techniques to predict the pervious concrete, incorporating these key improve predictive accuracy facilitate more precise sustainable design choices. For...
The study investigated the improvements in post-peak resistance induced by introduction of coconut fiber earth cement blocks. Earth blocks reinforced various weight fractions were tested under axial compression and flexural loading to examine response material terms peak load-carrying capacity, residual strength toughness. It was observed that reinforcement greatly improved strength, ductility energy absorption For durability, against alkaline attack acid reduced addition mortar. Similar...
ABSTRACTThe quality monitoring technique for Cement stabilised earth blocks (CSEBs) is so challenging that it often neglected. This study has investigated the possibility of using machine learning to predict compressive strength CSEBs based on cement content, electrical resistivity and Ultrasonic pulse velocity (UPV) as a potential way enhance control. The considered three types soil different content in preparation with 10 cement-soil mixtures. Various models were proposed CSEBs. evaluated...
ABSTRACTThis study presents a prediction model for estimating the compressive strength of pervious concrete through utilisation machine learning techniques. The models were trained and tested using 437 datasets sourced from published literature. This work employed collection six algorithms as statistical evaluation tools to determine optimal dependable forecasting concrete. Out all considered, eXtreme Gradient Boosting had greater performance in predicting strength. coefficient determination...