Models built for the physical world.
From nanofluid transport to battery thermal management—high-fidelity mathematics translated into practical prediction.
Research Interests
These can be shown as cards or icons on the About or Research page.
- AI-Driven Mathematical Modeling
- Computational Fluid Dynamics & Nanofluids
- Sustainable Energy Systems (Solar, Wind, Thermal Systems)
- Machine Learning for Engineering Applications
- Nanofluid Modeling for Electric Vehicles
- Nanofluid Modeling for Solar Energy
- Wind Turbine Energy
Research Areas (Detailed)
Four connected themes shape the research programme: nanofluid heat transfer, computational fluid dynamics, AI-driven modelling, and sustainable energy systems.
Nanofluid & Hybrid-Nanofluid Heat Transfer
Nanofluids - base fluids carrying engineered nanoparticles - can dramatically improve heat transfer compared with conventional coolants. My work models how these fluids behave in porous media, cavities, and thermal systems, using both classical CFD and modern mathematical frameworks such as the Tiwari-Das and Buongiorno models, to predict and optimise thermal performance for real engineering applications.
Computational Fluid Dynamics (CFD)
I build and solve numerical models of fluid flow and heat transfer across different geometries, using finite-volume methods and simulation tools including ANSYS and COMSOL. This underpins applications from enhanced oil recovery to solar thermal collectors and battery cooling.
AI-Driven & Surrogate Modeling
High-fidelity simulations are accurate but slow. I pair CFD with machine-learning surrogate models - including physics-informed neural networks - so that expensive simulations become fast, usable predictions that engineers can run in seconds, bridging the gap between a research model and a design tool.
Sustainable & Thermal Energy Systems
A unifying theme of my research is clean energy: predicting the performance of solar collectors, improving battery thermal management for electric vehicles, and studying wind-solar hybrid systems and cleaner combustion through nanoparticle-enhanced fuels. The goal is measurable contributions to affordable clean energy and low-carbon transport.
Research Projects & Grants
Nanofluids in Battery Thermal Management Systems (BTMS)
Role: Principal Investigator (Main PI)
Funder: Ministry of Higher Education (MOHE), Malaysia - Exploratory and Transformative Research Grant (GET)
Amount: RM 145,432.00
Duration: Oct 2026 - Sep 2028 (2 years)
Abstract (draft)
Electric-vehicle batteries generate significant heat during fast charging and high-rate discharge, and poor thermal management shortens battery life while raising safety risks. This project investigates nanofluids - coolants with enhanced thermal conductivity - as the working fluid in battery thermal management systems. Combining numerical simulation with experimental validation, it evaluates how nanofluid type, concentration, and flow configuration affect heat dissipation, temperature uniformity, and overall system efficiency, with the aim of enabling safer, longer-lasting batteries for cleaner transport.
Objectives (draft)
- Develop and validate numerical models of nanofluid-cooled battery thermal management systems
- Experimentally measure cooling performance across nanofluid types and concentrations
- Optimise flow and design parameters for temperature uniformity and thermal safety
- Assess feasibility and scalability for electric-vehicle adoption
Novel Mathematical Models to Predict Solar Energy Performance Using Newtonian and Non-Newtonian Nanofluids
Role: Principal Investigator (Main PI)
Funder: Asia Pacific University (APU), Malaysia
Amount: RM 20,000
Duration: Jul 2025 - Jul 2027 (2 years)
Abstract (draft)
The efficiency of solar thermal collectors depends strongly on the heat-transfer properties of the working fluid. This project develops new mathematical models to predict solar collector performance when Newtonian and non-Newtonian nanofluids are used as absorber fluids. By capturing the distinct rheological behaviour of each fluid class, the models aim to identify formulations and operating conditions that maximise the capture and conversion of solar heat, supporting more efficient renewable-energy systems.
Objectives (draft)
- Formulate mathematical models for Newtonian and non-Newtonian nanofluids in solar collectors
- Predict thermal efficiency across nanofluid types, concentrations and flow regimes
- Identify optimal operating conditions for maximum solar-thermal performance
- Validate model predictions against benchmark and experimental data
Mechanistic Investigation of Pickering Emulsified Polymeric Gel for Water Shut-Off Conformance Control
Role: Graduate Research Assistant
Funder: Yayasan Universiti Teknologi PETRONAS (YUTP)
Duration: Feb 2023 - Dec 2024 (10 months active)
Contribution
- Analysed fluid transport and gel behaviour in porous reservoirs for conformance control
- Supported experimental and computational modeling for improved oil-recovery efficiency
- Assisted in research design, simulation, and dissemination of findings
Viscous and Thermal Transport Effects of Novel Oil-Based Nanofluid on Natural Convection in Porous Cavities for Enhanced Oil Recovery
Role: Graduate Research Assistant
Funder: Yayasan Universiti Teknologi PETRONAS (YUTP)
Duration: Feb 2021 - Feb 2023 (14 months active)
Contribution
- Conducted numerical and computational analysis of nanofluid flow in porous media
- Investigated heat and mass-transfer mechanisms to optimise enhanced oil recovery
- Contributed to model development, ANSYS/CFD simulation, and research Publications