Selected Projects delivered to our Clients

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This project leverages ANSYS Fluent and Mechanical to simulate the vibration characteristics of high-pressure water injection pipelines under dynamic fluid flow conditions. It evaluates key parameters such as vibration frequency and amplitude, and models the sources and propagation paths of vibration throughout the system. The insights gained are used to optimise pipeline support and fixation strategies—minimising vibration-induced stress and enhancing overall operational stability.

This project employs Computational Fluid Dynamics (CFD) simulation to investigate the leakage behavior of supercritical carbon dioxide pipelines in both atmospheric and subsurface environments. It examines the spatial distribution of concentration and temperature around the leakage zone, enabling prediction of potential hazards based on flow field characteristics. These insights inform the optimal design of pipeline leakage monitoring systems, supporting more efficient design.

This project applies the Discrete Phase Model (DPM) within CFD simulations to predict wax deposition patterns in wax-bearing natural gas as it flows through a throttle valve. It evaluates the spatial distribution and quantity of wax accumulation, analysing the impact of key operating parameters on deposition behavior. Based on these insights, the study provides targeted operational recommendations to mitigate wax buildup and reduce associated risks to pipeline integrity and flow assurance.

This project utilises CFD to simulate the flow behavior of particle-laden crude oil within pipeline systems. By analysing velocity, temperature, pressure, and related flow variables, it assesses erosion and wear effects on the pipeline’s inner wall and critical components. The simulation identifies corrosion distribution patterns and predicts high-risk zones most susceptible to degradation which formed the basis for anti-corrosion strategies

This project simulates the multiphase flow of oil and water within a separator to evaluate separation efficiency. By analysing the internal flow field distribution, the study identifies optimisation opportunities for key components—including baffles, coalescing plates, and swirlers. These insights support enhanced separator design, ultimately improving phase separation performance and operational reliability.

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This project utilises Computational Fluid Dynamics (CFD) to simulate internal fluid flow within machinery such as centrifugal pumps and compressors. By analysing flow field characteristics—including velocity, pressure, and turbulence profiles—the study supports optimisation of key components such as impellers and flow passages. These insights enhance the efficiency, reliability, and operational performance of fluid machinery across industrial applications.

This project applies the Multiple Reference Frame (MRF) method within CFD simulations to model the operation of a dual-blade stirrer in a mixing tank. By analysing the internal flow dynamics, the study evaluates stirrer performance, mixing efficiency, and identifies key areas for design optimisation. These insights support enhanced mixing effectivenes.

This study focused on analysing air velocity distribution within a dump hopper to support passive dust control strategies. By understanding airflow behaviour, the research aims to minimise particulate dispersion and enhance containment efficiency without relying on active suppression systems.

This study employs Computational Fluid Dynamics (CFD) to simulate airflow distribution, wind velocity fields, pressure profiles, and related parameters around wind turbine blades. By analysing turbine performance under varying operating conditions, the research identifies optimisation opportunities for key design parameters. These insights support improvements in efficiency, stability, and long-term reliability of wind turbine systems.

This study applies advanced CFD-DEM modelling to simulate particle flow trajectories, energy distribution, and interaction forces within industrial mixers and fluidized beds. The research explores bubble formation, energy exchange, and operational dynamics under varying conditions, leading to optimized design parameters that enhance mixing efficiency, fluidization quality, and overall operational stability.