Projects

A comprehensive technical log of research campaigns, plant design studies, and experimental mechanics across aerothermal, structural, and energy systems.

High fidelity CFD (URANS) OpenFOAM Conjugate Heat Transfer Turbulence modelling Gas dynamics Method of Characteristics WRF Atmospheric modelling Thermal structural FEA Anisotropic mechanics Progressive damage modelling Thin walled pressure vessel mechanics Design for Additive Manufacturing Neural network surrogates RANSAC outlier rejection Monte Carlo uncertainty propagation Signal processing (FFT) C++ OOP Python for Data Science Transient infrared thermography Hot wire wake analysis Structured light 3D scanning Experimental harmonic analysis Techno economic optimization
Domain: Aerothermal engineering, turbomachinery design, and energy systems integration
Signature work: Multi-year Rolls-Royce HPT deterioration research at the Oxford Thermofluids Institute
Methodology: Closing the loop between low-order physical models, experimental validation, and financial constraints

Flagship research

High pressure turbine deterioration

Oxford Thermofluids Institute , Rolls-Royce , 2021-Present

Experimental fluid dynamics Infrared thermography RANS Benchmarking

Technical challenge: Understanding how shower head erosion and leading edge holing impact the thermal margin of high pressure nozzle guide vanes (HPNGV). Standard aerothermal correlations often fail for engine-run parts, requiring a deeper investigation into how geometric damage alters film cooling effectiveness and component life.

Achievement: Managed the aerothermal characterization of multiple rainbow-sets of engine-run vanes at the ECAT facility. I executed parametric studies over a wide range of Coolant to Mainstream Pressure Ratios (CMPR) to decouple the aerodynamic and thermal effects of wall material loss from general surface degradation.

Insights: Proved that leading edge holing triggers a significant redistribution of the internal coolant flow. While the extra coolant discharge can lower mean surface temperatures in specific regions, it simultaneously creates localized hot spots at the hole perimeters by disrupting the protective film cooling layer. This research provided a mathematical framework to incorporate these localized hot spots into metal effectiveness invariants, supporting more accurate maintenance intervals for civil jet engines.

Facility: Engine Component AeroThermal (ECAT) facility
Methodology: Transient infrared thermography and CMPR parametric analysis
Physics: Coolant flow redistribution and shower-head erosion mechanics
Impact: Data-driven maintenance intervals based on localized hot-spot quantification

Aerodynamics & CFD

9 stage axial compressor aerodynamic synthesis

University of Cagliari

Free Vortex Law Lieblein Diffusion Factor Transonic Aerodynamics

Technical challenge: Designing a medium pressure compressor to achieve a total pressure ratio of 7 with a mass flow rate of 31 kg/s. Initial specific speed calculations (0.61) disqualified single stage architectures, while a preliminary 7 stage uniform-work setup resulted in excessive stage loading and diffusion factors that compromised aerodynamic stability in the first stage.

Achievement: Engineered a robust 9 stage configuration using the free vortex law to maintain radial equilibrium while keeping a constant mean aerodynamic diameter of 0.64 m. I implemented a non uniform enthalpy drop distribution, deliberately offloading the critical first stage and increasing work progressively through the machine. To ensure a smooth transition of flow angles, I formulated and numerically solved an 8th degree polynomial equation for the stator exit angles, identifying an optimal decay coefficient (k) of 0.843.

Insights: Through iterative solidity optimization, I constrained the Lieblein Diffusion Factor below the 0.45 safety threshold for every radial section. The analysis required careful management of transonic flow conditions at the first stage tip, where the Mach number reached 1.26. I balanced this by fine-tuning blade camber and momentum thickness ratios. The final design successfully synchronized 17 rotor and 25 stator blades for the initial stage, providing a high stall margin and a continuous, shock-free velocity triangle progression along the entire compressor axis.

Theory: Radial equilibrium via free vortex law and 1D/2D meanline parameterization
Modelling: Variable multi-stage enthalpy distribution and 8th degree polynomial numerical solver
Validation: Lieblein diffusion limits, Mach number mapping, and aerodynamic efficiency characterization

Minimal length supersonic nozzle design (MOC)

University of Cagliari

Method of Characteristics Prandtl Meyer Expansion Supersonic Gas Dynamics

Technical challenge: Synthesizing the divergent contour of a minimal length De Laval nozzle to achieve a perfectly uniform, shock free Mach 3 exhaust flow. This requires a precise mathematical cancellation of the Prandtl Meyer expansion waves originating from the throat corner to prevent internal reflections that degrade propulsive efficiency and flow quality.

Achievement: Developed a numerical solver utilizing the Method of Characteristics to compute the flow field downstream of a 0.1 m radius throat. I built a framework to solve the compatibility equations for both positive and negative characteristics, iteratively determining the intersection points and local Mach numbers. The solver was designed to target an isentropic area ratio of 13.303, which corresponds to the theoretical expansion required for a Mach 3 exit condition in air with a specific heat ratio of 1.4.

Insights: Conducted a rigorous convergence study to optimize the discretization of the characteristic net. By comparing 10, 20, and 79 characteristic lines, I demonstrated that 79 lines represent the optimal threshold where the area error converges below 0.01 percent. The analysis confirmed that increasing the discretization density not only improves the fidelity of the exit radius (targeting 0.365 m) but also significantly reduces the total axial length of the divergent section, providing a more compact and efficient propulsion component.

Theory: Prandtl Meyer expansion and compatibility equations in supersonic flows
Algorithms: Custom MOC solver with iterative intersection point refinement
Validation: Area ratio convergence and Mach 3 exit profile uniformity checks

HPT blade aerodynamic design

University of Cambridge

Multi-fidelity design 3D RANS Flow solver JD75

Technical challenge: Executing the aerodynamic synthesis of a 4-stage axial turbine, balancing stage loading and reaction to maximize efficiency while strictly adhering to subsonic compressibility limits (Mach below 0.95).

Achievement: Implemented a hierarchical design process. I began with a 1D meanline approach to estimate hub and casing radii, followed by an axisymmetric throughflow calculation to resolve the radial equilibrium. I then utilized a quasi-orthogonal 3D (Q3D) iterative analysis to optimize individual blade profiles before performing a full 3D Navier-Stokes analysis on the final stacked blades using JD75.

Insights: By iterating on stage work fractions and inlet swirl angles, I successfully eliminated zones of negative reaction that were identified in the early throughflow stages. The final 3D validation demonstrated that while Q3D methods effectively capture profile losses, the high-fidelity 3D RANS was required to accurately quantify the secondary flow losses and endwall vortices that dictate the true efficiency of high-pressure turbine stages.

Methodology: Meanline, Axisymmetric Throughflow, and Q3D profile optimization
CFD: 3D RANS analysis of stacked blades using JD75 (Denton code)
Constraints: Positive stage reaction management and Mach number limit enforcement

Compressor redesign via Machine Learning

University of Cambridge

ML Surrogates MISES MULTALL

Technical challenge: Improving the aerodynamic performance of a transonic compressor stator without the computational expense of exhaustive 3D CFD sweeps across all operating points.

Achievement: Employed a multi-fidelity design process. Analysed boundary layers via a 2D viscid-inviscid solver (MISES) and performed 3D CFD (MULTALL) to optimise blade lean.

Insights: Trained a neural network surrogate model on the CFD database, allowing for rapid, low-cost prediction of the critical trade-off between loss coefficients and pressure rise.

CFD: 3D RANS (MULTALL), 2D coupled viscid-inviscid solver (MISES)
Machine Learning: Neural network surrogate modelling
Optimisation: Multi-objective trade-off analysis (loss vs. pressure rise)

Computational fluid dynamics solver development

University of Cambridge

Euler equations Runge-Kutta Local time-stepping

Technical challenge: Developing a robust 2D inviscid Euler solver from first principles capable of capturing transonic phenomena and shock waves without the numerical instabilities or spurious oscillations inherent in high-speed flow simulations.

Achievement: Engineered an explicit steady-state solver utilizing a cell-centered finite volume discretisation. I implemented a multi-stage Runge-Kutta time integration scheme for enhanced stability and a deferred correction method to achieve second-order spatial accuracy. To maximize computational efficiency, I integrated spatially variable time-stepping based on the local Courant-Friedrichs-Lewy (CFL) condition.

Insights: The primary optimization involved the calibration of the Jameson-Schmidt-Turkel (JST) artificial viscosity. By fine-tuning the smoothing factors, I successfully balanced shock-capturing capability with global entropy conservation. The solver was validated on a complex supersonic bend case, reaching a mean Mach number of 3.03 at the outlet with clean residual abatement and convergence achieved within the first 100 iterations.

Algorithms: 4-stage Runge-Kutta integration, cell-centered finite volume method
Stability: JST artificial viscosity and local CFL condition management
Performance: Spatially variable time-stepping and high-order deferred correction

Design & analysis

AM heat exchanger: design & validation

University of Oxford

DfAM Conjugate Heat Transfer Thermal FEA

Technical challenge: Protecting high-resolution infrared cameras within the 500 K environment of the ECAT+ turbine facility by designing a high-effectiveness, low-profile heat exchanger that fits within extreme spatial constraints without compromising facility flow quality.

Achievement: Developed a physics-based low-order aerothermal network model to optimize the internal cooling architecture. The solver utilized a Newton-Raphson iterative scheme to resolve the coupled pressure-temperature system, employing the McAdams correlation to model convective heat transfer within complex internal lattice geometries. The final design was manufactured in 316L stainless steel using Direct Metal Laser Sintering (DMLS).

Insights: Conducted multi-fidelity validation by benchmarking the low-order model against 3D Conjugate Heat Transfer (CHT) simulations in ANSYS Workbench. I performed a rigorous thermal-structural Finite Element Analysis (FEA) to verify that thermal expansion stresses remained safely below the 316L yield limit under a worst-case 200 degree Celsius thermal gradient, ensuring a safe lens operating temperature of 305 K during high-temperature facility campaigns.

Optimisation: Newton-Raphson based aerothermal network modelling and lattice geometry trade-offs
Manufacturing: Design for Additive Manufacturing (DfAM) and DMLS 316L characterisation
Simulation: ANSYS CHT and thermal-structural FEA with temperature-dependent properties

Holistic gas turbine design

University of Cambridge

Thermodynamics MATLAB Meanline design

Technical challenge: Executing the conceptual, end-to-end design of a 30 kN turbojet engine to strict performance specifications.

Achievement: Conducted 0D thermodynamic cycle analysis to select optimal pressure ratios and bypass ratios for the specific flight envelope.

Insights: Performed meticulous meanline sizing and component matching of the compressor, combustor, and turbine to meet thrust and specific fuel consumption targets.

Analysis: 0D thermodynamic cycle assessment
Design: Meanline component sizing and aerodynamic matching
System: Full propulsion system integration

Dyson product aeroacoustics

University of Cambridge

CFD CAD Aeroacoustics

Technical challenge: Reverse-engineering the fluid dynamics and noise generation mechanisms of the Dyson Supersonic hair dryer.

Achievement: Extracted accurate CAD geometry and utilized CFD to quantify the air multiplier effect and jet entrainment ratios.

Insights: Mapped how internal flow path geometry and the Coanda effect directly influence exit velocity profiles and the resulting acoustic signature.

Modelling: Reverse engineering and CAD geometry extraction
Fluid Mechanics: Jet entrainment physics, Coanda effect analysis
Acoustics: Acoustic signature correlation

Mesoscale wind modelling with WRF

University of Cagliari / TU Delft

WRF MATLAB HPC ERA-5

Technical challenge: Simulating atmospheric boundary layer flows and characterising wind resources over complex terrain.

Achievement: Set up and ran nested-domain simulations initialised with GFS and ERA-5 reanalysis data using the Weather Research and Forecasting (WRF) model.

Insights: Conducted sensitivity analysis of planetary boundary layer (PBL) schemes to accurately capture non-neutral atmospheric stability and successfully reproduce the diurnal cycle of a coastal low-level jet.

Simulation: WRF-ARW core, domain nesting, pre-processing
Physics: PBL parameterisation schemes, atmospheric stability limits
Analysis: MATLAB post-processing, vertical profile extraction

Utility-scale PV vs CSP plant design

University of Cagliari

Plant modelling ORC NPV Analysis

Technical challenge: Formulating an end-to-end comparative thermodynamic and economic analysis between a 5 MW Photovoltaic (PV) plant and a 5 MW Concentrated Solar Power (CSP) system to determine the most viable technology for a specific site.

Achievement: Built an hour-by-hour operational model. Optimized the PV array layout and tilt to minimize shading using UNI 10349 standards. For the CSP variant, I sized the parabolic trough solar field and designed a 6-hour thermal energy storage tank (holding over 1.3 million kg of oil) to guarantee autonomy for the Organic Rankine Cycle (ORC) power block.

Insights: By accurately modeling Incident Angle Modifiers (IAM) through custom polynomials and setting a strict 40 MWh minimum activation threshold for the ORC, I proved that while the CSP plant offered dispatchability, it yielded a highly negative Net Present Value. The analysis demonstrated that the PV architecture offered a superior break-even trajectory due to significantly lower CapEx.

Modelling: Solar irradiance calculation, IAM polynomials, and shading analysis
Design: PV layout, parabolic trough sizing, 6-hour thermal storage integration
Economics: NPV calculation, 25-year incentive tracking, CapEx cost stacking

Centrifugal pump aerodynamic design

University of Cagliari

Turbomachinery Stepanoff theory MATLAB

Technical challenge: Designing the impeller and volute of a single-stage centrifugal pump from scratch to meet strict operational targets (160 cubic meters per hour at a 50m head) while maximizing hydraulic efficiency.

Achievement: Conducted a complete aerodynamic synthesis. I utilized Balje and Jaumotte statistical diagrams to select the optimal specific speed and dimensionless pressure and flow coefficients. The 11-blade impeller geometry was mathematically generated using the Kaplan error triangle method to transition from planar coordinates into cylindrical space.

Insights: Rather than assuming ideal Stepanoff conditions, I wrote a MATLAB script to plot the actual constant specific speed curve and find the true intersection with the operational line. This allowed me to correctly adjust the theoretical efficiency drop caused by the machine's smaller scale, ensuring the final volute and divergent diffuser sizing was grounded in realistic flow physics.

Theory: Stepanoff diagrams, Balje and Jaumotte specific speed matching
Design: Kaplan error triangle method for blade profiling, volute section sizing
Algorithms: MATLAB non-linear curve intersection to find operating points

Onshore wind farm feasibility study

University of Cagliari

Wind energy Data reduction Techno-economics

Technical challenge: Predicting true Annual Energy Production (AEP) and financial viability from raw anemometric data, while strictly adhering to environmental acoustic limits (sub-45 dB nighttime restrictions).

Achievement: Built a full-stack physical and financial model. Processed 8760 hourly data points to compute the specific wind shear exponent and extrapolate hub-height velocity. I corrected for site-specific air density (150m a.s.l.) and modeled turbine performance by interpolating manufacturer data via a custom 4th-degree polynomial.

Insights: The multi-variable analysis revealed a counter-intuitive financial strategy. By deliberately sizing the farm down to three 20 kW turbines (remaining under a 60 kW regulatory threshold), the project secured a much higher feed-in tariff, achieving a superior Internal Rate of Return and a 10-year payback period compared to larger multi-megawatt setups. I also mathematically verified that the array required a 2.25 km setback distance to satisfy spherical divergence noise limits.

Resource assessment: 8760-hour wind shear power-law extrapolation
Performance: 4th-degree polynomial power curve integration
Economics: NPV, IRR, and regulatory feed-in tariff optimization
Environmental: Acoustic propagation and noise constraint mapping

Reversible pump-storage hydro plant

University of Cagliari

Hydraulics Francis turbine Cavitation limits

Technical challenge: Evaluating the technical and economic feasibility of retrofitting an existing water pumping station (Su Stampu) into a reversible pump-storage hydroelectric plant to exploit energy arbitrage, while strictly adhering to environmental minimum flow constraints.

Achievement: Derived the h-Q flow rating curve and performed a complete hydraulic analysis. I calculated penstock diameters by optimising the trade-off between Darcy-Weisbach friction losses and capital pipe costs over a 120 m head. The study compared two different turbomachinery architectures: a high-head Pelton wheel and a reaction Francis turbine.

Insights: By calculating the Net Positive Suction Head (NPSH) to prevent cavitation and matching the specific speeds, the techno-economic analysis identified a 1.71 MW Francis turbine as the optimal solution. The integrated financial model proved this configuration maximized annual energy production, yielding a payback period of just 7 years with a profitability index of 1.24.

Hydraulics: Penstock sizing, Darcy-Weisbach head loss, cavitation analysis
Machinery: Turbomachinery selection (Pelton vs Francis), specific speed matching
Economics: Net present value, internal rate of return, 7-year payback projection

Fluid machinery design & gas dynamics

University of Cagliari

Compressors Method of characteristics Gas dynamics

Technical challenge: Designing both a multi-stage axial compressor and the divergent section of a De Laval supersonic nozzle using fundamental theories.

Achievement: Engineered a 9-stage compressor configuration by solving an 8th-degree equation for deviation angle decay. Built a numerical solver for the nozzle using the Method of Characteristics.

Insights: Mapped the Prandtl-Meyer expansion waves for the nozzle and proved that computing exactly 79 characteristic lines provided the strict mathematical threshold to minimize area error for a uniform Mach 3 exit flow.

Compressor: Meanline analysis, velocity triangles, diffusion factor validation
Gas dynamics: Supersonic expansion, shock-free design
Algorithms: Method of characteristics iteration

Composites & structural analysis

Composite hydrofoil structural analysis

University of Cagliari

FEA CLT Carbon/Epoxy

Technical challenge: Guaranteeing the structural integrity of thin-profile NACA hydrofoils under extreme, asymmetrical hydrodynamic loads.

Achievement: Conducted theoretical characterization using Classical Lamination Theory (CLT). Validated the stiffness matrices for layups like [0, 30, -30]s against experimental data.

Insights: Quantified the coupling between extension and bending in non-symmetric laminates. Observed experimental stiffness values (~21 GPa) matching orthotropic predictions, defining optimal layup sequences to prevent delamination.

Theory: Composite mechanics, off-axis stress analysis
Modelling: Finite element analysis of NACA profiles
Application: Structural resilience against peak hydrodynamic bending moments

Composites: manufacturing and characterisation

University of Cagliari

Autoclave curing ASTM D638 Orthotropic elasticity

Technical challenge: Moving beyond theoretical mechanics to physically manufacture low-void pre-preg laminates and experimentally isolate their orthotropic stiffness matrices, while avoiding testing artifacts like grip-induced stress concentrations or shear-dominated bending.

Achievement: Executed a complete aerospace-grade manufacturing cycle using hand lay-up, vacuum bagging, and autoclave consolidation. I then conducted destructive tensile and flexural testing campaigns on an Instron 5585 universal testing machine, utilizing precision MTS extensometers to capture multi-axial strain data.

Insights: By testing specific stacking sequences (such as using a [+45/-45]2s laminate to isolate the in-plane shear modulus), I successfully extracted the fundamental stiffness parameters. During the flexural testing phase, I performed variable-span 3-point bending tests (from 160 mm down to 30 mm) to explicitly quantify the scale at which transverse shear deformation begins to artificially reduce the apparent flexural stiffness, proving the necessity of high span-to-thickness ratios for accurate modulus characterisation.

Manufacturing: Autoclave temperature and pressure cure cycles, vacuum bagging
Testing: ASTM standard tensile and flexural destructive characterisation
Analysis: Orthotropic elasticity extraction, transverse shear influence mapping

15-layer carbon fiber shaft design

University of Cagliari

CFRP manufacturing Tsai-Wu criteria Progressive damage

Technical challenge: Designing and fabricating a composite drive shaft that simultaneously resists extreme torsional buckling and maintains a high flexural critical speed, without exceeding strict weight and geometric constraints.

Achievement: Engineered and computationally optimized a 15-layer asymmetric carbon-epoxy laminate stack to precisely balance longitudinal stiffness with shear strength. I executed the physical manufacturing using pre-preg tube rolling around a Teflon mandrel, applying 2.52 bar of radial consolidation pressure via thermodynamic contraction using Hi-Shrink Tape at 120 degrees Celsius.

Insights: Developed a 7-step progressive damage model in MATLAB to simulate ply-by-ply matrix degradation under increasing torque. By recalculating the reduced stiffness matrices after each localized failure, the model successfully predicted the exact sequence of ply failures and the non-linear angular deformation trajectory prior to ultimate catastrophic breakage.

Mechanics: Torsional buckling, flexural critical speed, Tsai-Wu interaction criteria
Simulation: 7-step progressive damage modelling, localized matrix cracking degradation
Manufacturing: Pre-preg tube rolling, thermal shrink-tape consolidation

Composites: laminate analysis and failure theory

University of Cagliari

MATLAB CLT Tsai-Hill Failure criteria

Technical challenge: Predicting the stiffness and failure loads of complex, multi-directional composite laminate stacks mathematically, reducing the reliance on costly empirical testing for every design iteration.

Achievement: Developed a MATLAB codebase to automate Classical Lamination Theory (CLT). The program calculated the extensional, coupling, and bending stiffness matrices (the [A], [B], and [D] matrices) from constituent fiber and matrix properties across various stacking sequences. I then benchmarked these theoretical predictions against experimental data from tensile and bending tests.

Insights: The study explicitly quantified the coupling effects inherent in non-symmetric laminates, such as extension-bending and bending-twisting interactions. By integrating the Tsai-Hill and maximum stress failure criteria, the model successfully predicted the first-ply failure loads of coupled laminates with a deviation of less than 10% from the experimental rupture data.

Theory: Classical Lamination Theory, stiffness matrix derivation
Failure criteria: Tsai-Hill envelope, maximum stress criterion
Mechanics: Anisotropy, extension-bending coupling quantification

Experimental mechanics

Strain-gauge pressure measurement

University of Cagliari

Wheatstone bridge Thin-walled vessels Uncertainty analysis

Technical challenge: Measuring the internal pressure of a thin-walled cylindrical vessel through indirect circumferential deformation, requiring the decoupling of sensor noise from micro-strain signals.

Achievement: Instrumented a cylindrical aluminum vessel with foil strain gauges in a quarter-bridge Wheatstone configuration. I utilized micrometric tools to characterize the vessel's geometric tolerances and executed a controlled depressurization cycle to measure the resulting elastic recovery strain.

Insights: I developed an uncertainty model using Student's t-distribution to account for gauge factors and geometric variance. By applying Mariotte's formula to the measured circumferential strain, I calculated an internal pressure of 0.665 bar. The high precision of the result validated the measurement chain and provided a baseline for the design of industrial safety monitoring systems for pressure vessels.

Instrumentation: Foil strain gauges and Vishay signal conditioning
Theory: Mariotte's formula for thin-walled pressure vessel mechanics
Statistics: Uncertainty propagation via Student's t-distribution

Tensile testing and elastic characterization

University of Cagliari

MTS Testing ASTM D638 Chi squared linearity

Technical challenge: Experimentally determining the Young Modulus of metallic specimens by reconciling the procedural differences between ISO 527 and ASTM D638 standards, particularly regarding pre load requirements and the precision of the initial elastic slope.

Achievement: Conducted monoaxial tensile tests on standard and holed specimens using an MTS testing suite equipped with 647 hydraulic wedge grips and a 634 1IF extensometer. I performed a rigorous statistical characterization of specimen geometry through ten discrete measurements per dimension, applying a Student t distribution at a 68.27 percent confidence level to propagate geometric uncertainties into the final calculations.

Insights: To ensure high fidelity results, I implemented a linearity assessment using a normalized Chi squared algorithm in MATLAB. This allowed me to select the optimal 800 point interpolation interval within the elastic regime, successfully converging on a Young Modulus of 70216.95 MPa. The study proved that even with high precision MTS instrumentation, geometric tolerance variance remains the dominant source of experimental uncertainty.

Testing: ASTM D638 tensile characterisation via MTS hydraulic systems
Statistics: Uncertainty propagation via Student t distribution and Chi squared checks
Metrology: High precision extensometry and specimen geometric tolerance mapping

Flexural mechanics and Poisson ratio analysis

University of Cagliari

Strain Gauges RANSAC Outlier Rejection Poisson Ratio

Technical challenge: Determining the Poisson ratio and Young Modulus of an aluminum specimen under bending while isolating the signal from non linearities and discontinuities caused by instrument sensitivity limits at low load increments.

Achievement: Conducted a cantilever bending test on a rectangular specimen instrumented with a six element strain gauge rosette. I utilized a P 3500 Strain Indicator to acquire multi axial data across half bridge and full bridge configurations. To ensure consistency, I applied a geometric correction factor to align the longitudinal and transverse strain measurements at the same effective distance from the load point.

Insights: I implemented a RANSAC (RANdom Sample And Consensus) algorithm in MATLAB to clean the experimental dataset. The algorithm successfully identified and rejected outliers in the strain curves caused by small mass differences, such as the 1.20g and 3.66g increments, that fell below the effective resolution of the sensor. This statistical refinement converged on a precise Poisson ratio of 0.2902, validating the measurement chain against theoretical expectations for aluminum.

Instrumentation: P 3500 Strain Indicator and multi axial resistance strain gauges
Algorithms: RANSAC iterative fitting and outlier rejection for noise reduction
Analysis: Navier bending formula application and uncertainty propagation

Indirect metrology in thin walled vessels

University of Cagliari

Mariotte Mechanics Strain Gauge Analysis Uncertainty Propagation

Technical challenge: Quantifying the internal pressure of Al 3004 H19 thin walled vessels via indirect measurement of elastic recovery strain, while isolating the target signal from thermal interference and geometric constraints.

Achievement: Engineered a measurement chain utilizing foil resistance strain gauges in a quarter bridge Wheatstone configuration linked to a P 3500 Strain Indicator. The protocol required critical surface preparation including thermal conditioning to prevent condensation, controlled abrasion, and precise axial alignment to ensure the capture of pure circumferential strain data.

Insights: By applying Mariotte's formula for inverse stress calculation, I translated a measured micro strain of 252 into a final internal pressure of 0.665 bar. The analysis was supported by a rigorous statistical treatment using a Student t distribution for specimen characterization, achieving a final uncertainty of 1.6 percent and validating the reliability of strain based monitoring for non invasive structural assessment.

Sensing: Foil sensor installation with lead soldering and bridge balancing
Physics: Pressure vessel mechanics and membrane stress derivation
Statistics: Micrometric tolerance analysis and measurement error propagation

Damping & dynamic elasticity

University of Cagliari

Harmonic Analysis Damping Coefficient Dynamic Modulus

Technical challenge: Characterising the dissipative and elastic properties of an aluminum specimen by analysing its out of plane damped oscillatory motion, specifically isolating the material dynamic response from the energy dissipation introduced by experimental boundary conditions.

Achievement: Conducted a series of dynamic tests across three different clamping configurations, including high rigidity setups with additional metal plates, to measure natural frequency and logarithmic decrement. I utilized a longitudinal strain gauge in a quarter bridge configuration connected to a P 3500 Strain Indicator. To ensure data fidelity, I implemented a custom zero offset algorithm in MATLAB to correct for signal drift and isolate the true peak to peak amplitude of the harmonic decay.

Insights: By solving the characteristic equation of damped motion and applying the natural frequency formula for inflected beams, I determined a dynamic Young Modulus of approximately 74 GPa. The study revealed that while the elastic modulus remains consistent, the damping coefficient n is highly sensitive to the clamping stiffness, proving that increased constraint rigidity directly correlates with higher observable damping in the experimental signal.

Testing: Damped free vibration analysis with high frequency strain acquisition
Modelling: Second order differential equation for damped harmonic oscillators
Analysis: Sensitivity study on clamping rigidity and boundary condition effects

Structured-light 3D scanning

University of Cagliari

Optical metrology Phase unwrapping Triangulation

Technical challenge: Generating a high-density 3D reconstruction of non-planar surfaces using non-contact optical methods, while managing the phase-ambiguity inherent in periodic fringe patterns.

Achievement: Engineered a robust 3D metrology pipeline utilizing digital projection and high-speed imaging. I implemented and compared two encoding algorithms in MATLAB: Binary Sequential Coding (Gray Code) for absolute phase identification and Continuous Varying Color Code (RGB phase shifting) for superior spatial resolution.

Insights: Developed custom triangulation algorithms to transform pixel-space phase maps into a global coordinate point cloud. The investigation revealed that while the RGB phase shifting method increased data density by an order of magnitude, it required advanced chromatic aberration calibration to maintain sub-millimeter geometric accuracy across complex surface gradients.

Techniques: Gray Code and RGB phase-shifting codification strategies
Algorithms: Optical triangulation and mathematical phase unwrapping
Analysis: Chromatic aberration correction and point-cloud density optimization

Other

Gnome rotary engine training

University of Cagliari

Hands-on mechanics Propulsion architecture

Stripped down and reassembled a vintage Gnome rotary engine as part of a hands-on mechanical training module. This practical teardown built direct familiarity with radial engine architecture, master-and-articulated rod crankshaft dynamics, and precision mechanical assembly tolerances.

Mechanical assembly and strip-down
Rotary engine architecture
Propulsion system history

Multi-facility 5-hole probe cross-calibration

Oxford · Cambridge · RUB

MATLAB DAQ Monte Carlo

Technical challenge: Quantifying the end-to-end measurement uncertainty of five-hole pneumatic probes by decoupling manufacturing errors from facility-induced aerodynamic biases.

Achievement: Coordinated the testing of sixteen AM probes across four European transonic wind tunnels. Engineered a high-precision modular probe holder to eliminate mounting variance.

Insights: Developed a MATLAB data reduction suite to derive calibration coefficients and propagate error rigorously via Monte Carlo analysis.

Design: Modular probe holders, anti-rotation interface features
Analysis: Monte Carlo uncertainty propagation
Coordination: International multi-facility rig testing

Fan performance mapping

University of Cagliari

Fluid machinery Experimental rig Similarity theory

Technical challenge: Translating raw pressure differentials from an experimental test rig into accurate performance maps, while identifying the physical limits of aerodynamic scaling laws at low flow regimes.

Achievement: Mapped the full operational envelope of a Solar & Palau TD-500/160 elicocentrifugal fan at 1850 and 2500 RPM. I managed the instrumentation suite, including Pitot-static probes and Betz micro-manometers, and utilized a calibrated nozzle to determine precise volumetric flow rates through the circuit.

Insights: By computing the dimensionless flow and pressure coefficients, I proved that Similarity Theory holds strictly only at high flow rates where Reynolds number effects are negligible. To model multi-fan systems, I developed an iterative solver in MATLAB to resolve a 5th-degree polynomial characteristic equation, allowing for the precise prediction of flow distribution in complex parallel configurations.

Testing: Performance characterisation via Betz micro-manometers and DPI 610 sensors
Analysis: Dimensionless similarity mapping and Reynolds effect quantification
Modelling: 5th-degree polynomial iteration for parallel system impedance matching

Flat plate aerodynamics & wake analysis

University of Cambridge

Wind tunnel Hot-wire anemometry Unsteady analysis Signal processing

Technical challenge: Executing a multi-stage experimental characterisation of flow around a flat plate at zero angle of attack, transitioning from steady surface pressure mapping to high-frequency unsteady wake analysis[cite: 399, 400, 5].

Achievement: Conducted a comprehensive wind tunnel campaign utilizing a 3-hole pneumatic yaw probe for mean velocity traversing and a constant-temperature hot-wire anemometer (HWA) for unsteady data acquisition[cite: 402, 14, 5]. I instrumented the plate leading edge with trip wires to induce early laminar-to-turbulent transition and utilized 104 pressure tappings to identify adverse gradients responsible for flow separation[cite: 6, 449, 404].

Insights: By performing Fast Fourier Transforms (FFT) on 50 kHz sampled signals, I isolated the primary vortex shedding frequency (St = 0.2) from electrical and random noise[cite: 39, 47, 51]. The study proved that while vortex shedding frequency increases with Reynolds number (2.09e4 to 3.27e4), the Strouhal number remains Re-independent[cite: 382]. I successfully re-phased out-of-phase periodic waves using a bandwidth filter (f_max +/- 1 percent) and stored phase shifts to perform ensemble averaging on unfiltered wake data[cite: 57, 58].

Instrumentation: HWA calibration via King's Law and 3-hole probe characterisation [cite: 18, 455]
Metrology: RMS analysis for sample size optimization and precision error reduction [cite: 444, 446]
Analysis: Stagnation pressure loss integration and boundary layer thickness mapping [cite: 473, 107]

Open to R&D roles, consulting, research partnerships, and academic mentoring.

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