In 2015, Manchester Royal Infirmary commissioned the project "Predicting regions prone to atherosclerosis in animal models using CFD" to address a defined challenge in the healthcare sector. The assignment combined computational fluid dynamics (CFD) with a decision-focused engineering study. Its purpose was to explain the governing physical behaviour, identify the variables controlling performance, and convert the findings into practical recommendations for design, operation and future development.

We used computational fluid dynamics to examine arterial haemodynamics in pre‑clinical models and identify regions susceptible to atherosclerotic plaque formation. Anatomically realistic vascular geometries and pulsatile boundary conditions resolved wall shear stress, oscillatory shear index and exposure to low shear, reported over multiple cardiac cycles to improve stability. Sensitivity checks on viscosity models and inflow profiles tested the robustness of relative patterns. Outputs included maps and statistics highlighting persistently low or oscillatory shear regions and their spatial extent, enabling direct comparison with imaging or histology. The results provide a physics‑based rationale for selecting sites for further investigation and for evaluating the influence of anatomical variations or interventions, and the workflow is reproducible and extendable to additional models or imaging datasets to support Manchester Royal Infirmary’s translational research goals.

The methodology centred on an anatomically realistic, pulsatile cardiovascular CFD model derived from the available imaging or pre-clinical geometry. The representation retained the arterial branches and wall regions where curvature, branching and pulsatility create complex shear patterns. Boundary and operating conditions covered representative cardiac waveforms, alternative viscosity assumptions and relevant anatomical or physiological variations, with material, fluid and equipment properties assigned from the available design information. Resolution was concentrated in regions where steep velocity, thermal, concentration or phase gradients were expected, while the overall model remained efficient enough to compare several credible configurations. This balance allowed system-level performance to be linked to the local mechanisms responsible for it.

The assessment compared comparative haemodynamic scenarios intended to identify robust spatial trends rather than a single nominal result. Performance was judged using velocity, pressure, wall shear stress, oscillatory shear index, residence or exposure to low shear, and the size and persistence of potentially vulnerable regions. Results were reviewed through quantitative summaries and engineering visualisations, such as contours, vectors, streamlines, sections and time histories, selected to suit the physics. Important assumptions and operating uncertainties were considered so that the recommendations relied on repeatable comparative trends rather than a single nominal case.

For Manchester Royal Infirmary, the principal value was a physics-based basis for selecting sites for further imaging, histology or translational investigation. The final evidence linked each recommendation to the relevant model or process output, making it suitable for internal design reviews, supplier or contractor discussions and, where applicable, planning, safety or regulatory dialogue. The work also created a reusable baseline that can be updated as geometry, operating data or test results become available, reducing the cost and risk of later design iterations.

A disciplined quality-control workflow supported the analysis. Geometry, units, mass and energy balances, boundary-condition consistency and solver convergence were checked before options were ranked. Mesh or parameter sensitivities were used where they were most likely to affect the engineering conclusion, and limitations were documented explicitly. This ensured that the study remained traceable and reproducible rather than relying on isolated simulation images.