The COVID-19 pandemic highlighted the urgent necessity of understanding and managing air quality within enclosed spaces. In confined public areas like hospitals, buses, and train coaches, Heating, Ventilation, and Air Conditioning (HVAC) systems are crucial in the airborne spread of pathogens. Computational Fluid Dynamics (CFD) has emerged as an essential tool for analysing fluid flow dynamics and aerosol movement in these environments. This study involved CFD simulations to explore how HVAC configurations—particularly the quantity and layout of supply air inlets—impact airflow distribution in a railway coach, excluding a Discrete Phase Model (DPM) for particle transport. The results indicate that changes in inlet air velocity have little effect on overall flow patterns; however, the quantity and positioning of supply inlets greatly influence air distribution. Streamline analyses consistently pinpointed areas of decreased airflow circulation, especially at the front and in specific zones throughout the coach. This effect likely arises from the train's relative motion, which tends to move high-momentum air toward the rear, creating stagnation zones in the front regions.This thesis investigates the relationship between thermal comfort and power consumption in railway carriages. It assesses thermal comfort using Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) indices, as well as temperature and velocity non-uniformity coefficients, across three carriage configurations and two different passenger loadings, 50 and 100 passengers. A new thermal comfort index (Yc) based on the PMV has been developed to employ an empirical linear mapping of PMV and to help quantify and optimise the relationship between power consumption and thermal comfort in the railway carriage. This index effectively measures both energy consumption and thermal comfort, guiding the design of more efficient and comfortable railway carriages. Simulations were validated against experimental data obtained from a railway simulator at the University of Huddersfield, which showed a strong correlation (91% to 99%), confirming the reliability of the CFD models. The research further indicates that increasing the number of supply air inlets to enhance airflow and temperature uniformity is not directly proportional to increased thermal comfort, emphasising the importance of well-structured ventilation systems in public transportation. This is validated through the relationship between thermal comfort (Yc) and power consumption (Pc), indicating that the railway carriages with 6 supply air inlets occupied by both 50 and 100 passenger loadings, achieve an optimal balance between thermal comfort and power consumption (Thermal comfort (Yc) level close to 90% for 50 passenger occupancy level and around 73% for 100 passenger occupancy level, and power consumed between 16.58kW for 50 passenger occupancy level and 23.93kW for 100 passenger occupancy level), while, the railway carriage with 36 supply air inlets occupied by both 50 and 100 passenger loadings consumed significantly more energy (Thermal comfort (Yc) level at around 89% for 50 passenger occupancy level and around 72% for 100 passenger occupancy level, and higher power consumption between 100.10kW for 50 passenger occupancy and 144.38kW for 100 passenger occupancy level. without a proportionate increase in thermal comfort. A thorough comprehension of airflow dynamics is crucial for effectively modelling the spread of airborne diseases in these environments. This research lays the groundwork for evaluating the risk of airborne infection transmission in train coaches and guides strategies for HVAC system design and enhancement. This thesis offers an extensive examination of aerosol droplet dispersion within the ventilated railway carriage configurations, concentrating on creating and validating semi-empirical models to describe the behaviour of respiratory droplets under different flow and occupancy scenarios. By utilising high-fidelity Computational Fluid Dynamics (CFD) simulations as our benchmark, we explored the spatiotemporal changes in three key droplet parameters: mean droplet velocity, mean droplet diameter, and non-dimensional droplet flux—across various normalised distances (D') from the emission source. We analysed carriage configurations with 6, 12, and 36 supply air inlets, considering passenger loads of 50 and 100 occupants, and set initial droplet velocities at 5 m/s, 10 m/s, and 15 m/s to simulate breathing, speaking, and coughing events, respectively. A series of novel semi-empirical correlations was developed to articulate the decay patterns in velocity and diameter through exponential and damped-oscillation models. Meanwhile, droplet flux was modelled as a function of airflow momentum, droplet size, and thermophysical properties using a generalised power-law approach. Calibration of the model indicated a strong correlation with CFD data, achieving log-transformed R^2 values as high as 0.986, especially under conditions of high inlet and velocity. The model exhibited considerable adaptability in accurately representing both inertial and diffusive droplet transport regimes, influenced by ventilation layout and occupant density. Significantly, setups with more supply air inlets consistently produced uniform dispersion and reduced flux accumulation in occupied areas. zones. These findings enhance the analytical basis for modelling droplet-laden flows and provide useful predictive instruments for designing ventilation systems and mitigating risks in public transport environments. The suggested framework connects comprehensive CFD modelling with rapid engineering estimation, enabling real-time assessments of exposure risks and dynamic ventilation control methods.
| Date of Award | 16 Oct 2025 |
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| Original language | English |
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| Supervisor | Rakesh Mishra (Main Supervisor) & Naeem Mian (Co-Supervisor) |
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