Research Projects – Dr. Suvash C. Saha

Dr. Suvash C. Saha

Senior Lecturer of Mechanical Engineering
School of Mechanical and Mechatronic Engineering
University of Technology Sydney (UTS), Sydney, Australia

Phone:+61 2 9514 3183 (Office)

Email: cfd@suvash.com.au (Preferred); s_c_saha@yahoo.com; suvash.saha@uts.edu.au

Biography

Dr. Suvash C. Saha is a Senior Lecturer in Mechanical Engineering at the University of Technology Sydney (UTS), Australia. His research expertise spans a range of interdisciplinary areas, with current interests in computational biomechanical engineering, solar thermal energy technologies, natural convection heat transfer in buildings and confined geometries, and scale analysis of transient fluid flows. He earned his PhD in Computational Fluid Dynamics from the School of Engineering and Physical Sciences at James Cook University, Australia, in 2009. Prior to that, he completed his BSc (Honours) in Mathematics and MSc in Applied Mathematics (with thesis) from the Department of Mathematics, University of Dhaka, Bangladesh. Following his postgraduate studies, Dr. Saha began his academic career at IBAIS University, Bangladesh, where he served as a Lecturer in Mathematics and was subsequently promoted to Assistant Professor. His strong foundation in both mathematics and fluid mechanics underpins his contributions to advanced modelling in mechanical and biomedical engineering domains.

Research Interests

- - - Computational biomechanical engineering
    - Particle flow through lung airways
    - Solar thermal energy technology
    - Natural convection heat transfer in buildings and other confined geometries
    - Scale analysis for the transient flow
    - Computational fluid dynamics, porous media, boundary layer theory
    - Magnetic convection with and without gravity
    - Natural convection-induced transport in natural water bodies

Expertise

My expertise in CFD particularly includes Direct Numerical Simulation (DNS), Large Eddy Simulation (LES) and laminar natural convection-based numerical modelling. My expertise broadly covers the area of energy research as well as biomedical engineering. Details of the specific application areas have been highlighted in the Section above. I am a member of the Australasian Fluid Mechanics Society (AFMS) and a life member of the Bangladesh Mathematical Society.

Recent Collaborators

- - - Prof. Suman Chakroborty, Professor and Director, IIT Kharagpur, India
    - Prof. Chengwang Lei, Associate Professor, Fluid Engineering and Fluid Mechanics, School of Civil Engineering. The University of Sydney, Australia
    - Prof. Feng Xu, Beijing Jiaotong University, Beijing 100044, China
    - Prof. Rama S. R. Gorla, Cleveland State University, USA
    - Dr. Mamun Molla, University of Manitoba, North South University, Bangladesh
    - Prof. Masud K. Khan, CQ University, Australia
    - Prof. Richard J. Brown, Queensland University of Technology. Australia

Current Projects

Lung Modelling

Respiratory Deposition of Inhaled Microplastics: A Murine Model Study

Microplastics (MPs) are widespread environmental pollutants that pose serious risks to respiratory health, contributing to asthma, COPD, fibrosis, and lung cancer. MPs such as polystyrene and nylon fibres interact with lung epithelial cells, inducing oxidative stress, inflammation, and mitochondrial dysfunction. This leads to cell damage, impaired repair, and altered pathways like autophagy and ferroptosis, which drive lung injury and epithelial-mesenchymal transition (EMT). MPs also weaken immune defences, disrupt lung surfactant, and may carry other toxins, compounding their effects. This review explores the molecular mechanisms of MP-induced lung damage and highlights the need for further research on long-term impacts, exposure risks, and mitigation strategies.

This scientific illustration shows the experimental process of studying microplastic exposure in laboratory mice. The image depicts nano- and microplastic particles being administered intranasally using a syringe, mimicking inhalation exposure. The particles travel through the nasal passage into the respiratory tract, where they eventually deposit in the lung tissues. A magnified view of the lungs highlights the distribution of microplastics within the pulmonary branches, emphasising how inhaled particles can settle deep into the airways. The aim is to investigate the respiratory effects of microplastics and their potential health impacts.

Red Blood Cell Modelling

Deformation of RBC flowing through the capillary

The modelling of red blood cell (RBC) deformation as it flows through capillaries is crucial for understanding microcirculatory blood flow and its implications for oxygen delivery and vascular health. Due to the narrow diameter of capillaries—often comparable to or smaller than the RBC diameter—cells must undergo significant deformation to pass through. Computational models, often based on fluid–structure interaction (FSI) frameworks, capture the complex interplay between the viscoelastic membrane of the RBC and the surrounding plasma, typically modelled as a Newtonian or slightly non-Newtonian fluid. These models incorporate the cytoskeletal mechanics of the RBC, its biconcave shape, and the nonlinear elastic properties of the membrane, often using methods such as the immersed boundary method or boundary integral techniques. Such simulations help quantify shear stress distributions, transit velocities, and potential damage or pathological alterations in RBCs, offering insights into diseases like sickle cell anemia, malaria, or diabetes, where altered deformability can impair capillary perfusion.

Heat and Mass Transfer

Natural convection, heat transfer and phase change materials

Natural convection, heat transfer, and phase change materials (PCMs) collectively play a vital role in enhancing thermal management in various energy systems. Natural convection occurs due to buoyancy-driven flow when temperature gradients exist in a fluid, resulting in heat transfer without external forcing. This mechanism becomes particularly effective when integrated with PCMs, which absorb or release latent heat during phase transitions—typically from solid to liquid or vice versa—maintaining a nearly constant temperature. When PCMs are placed in enclosures or cavities, the melting or solidification process interacts with the surrounding fluid, initiating or enhancing convective currents. This synergy facilitates efficient thermal regulation, enabling applications in building energy storage, electronic cooling, solar thermal systems, and thermal protection in aerospace. The coupling of natural convection and PCM behaviour presents complex heat transfer dynamics that often require advanced numerical modelling to predict accurately and optimise performance.

Physics-Informed Neural Networks (PINNs) Project

NeuroPhysNet is a novel framework that integrates the biophysically-inspired FitzHugh-Nagumo neuronal model into a physics-informed neural network (PINN) for analysing EEG signals and classifying motor imagery tasks. By embedding differential equations that govern neural excitation and recovery directly into the learning architecture, NeuroPhysNet ensures that its predictions remain consistent with known neurophysiological behaviour. The model processes raw EEG signals, learns latent dynamics through the PINN, and simultaneously satisfies the FitzHugh-Nagumo constraints, enhancing interpretability and robustness. This approach not only improves the accuracy of classifying motor intentions (e.g., left-hand vs. right-hand movements) but also advances the field by tightly coupling data-driven AI with neuroscience theory—offering a more meaningful, generalizable solution for brain-computer interface (BCI) applications

Hydrogen Supply chain and disruption mitigation

The hydrogen supply chain, encompassing production, storage, transportation, and distribution, plays a critical role in the global transition to clean energy. However, it is highly vulnerable to disruptions due to its dependence on specialised infrastructure, high-pressure storage requirements, and limited pipeline and transport networks. Mitigating these disruptions requires a multi-faceted strategy that includes diversifying hydrogen production methods (e.g., electrolysis, SMR with CCS, biomass), developing decentralised and modular production hubs, enhancing storage technologies, and establishing robust logistics and monitoring systems. Integrating digital tools such as AI-driven predictive maintenance, blockchain for traceability, and scenario-based risk modelling can improve resilience and adaptability across the supply chain. Additionally, policy coordination, international collaboration, and strategic investments in infrastructure are essential to building a secure and flexible hydrogen economy that can withstand geopolitical, environmental, and technological uncertainties.