CFD engineer focused on turbomachinery and aerodynamics.
I use numerical simulation and flow analysis to investigate
aerodynamic performance, understand loss mechanisms,
and support engineering design.
Fluid mechanics engineer focused on turbomachinery and
aerodynamics, with experience in CFD workflows for
compressible and incompressible flows, from geometry
preparation and mesh generation to solver setup
and post-processing.
My education at École Centrale Casablanca and Centrale
Méditerranée, combined with training at Flowthermolab,
brings together aerodynamics, mesh generation,
RANS turbulence modelling, and scientific computing.
Available for permanent roles
CFD · Turbomachinery · Aerodynamics
01
Computational fluid dynamics
Numerical simulation of turbulent internal and external
flows, covering compressible and incompressible conditions.
ANSYS Fluent
ANSYS CFX
OpenFOAM
02
Meshing & pre-processing
Geometry preparation and mesh generation for CFD,
with a focus on turbomachinery flow passages.
SpaceClaim
ANSYS Meshing
TurboGrid
03
Turbomachinery
Preliminary compressor design, rotor–stator modelling,
and aerodynamic performance assessment.
Objective:
assess a transonic compressor’s performance.
My work:
simulated the rotor flow and analysed Mach distributions,
shock waves, blade-tip flow and aerodynamic losses.
88.58%
Total-to-total efficiency
1.889
Total pressure ratio
19.64 kg/s
Mass flow rate
Against NASA reference values: −2.74% in mass flow and
−10.32% in pressure ratio. These differences remain
part of the analysis.
Method & technical findings
Compressible-flow simulation through an axial
compressor rotor.
Post-processing of pressure, velocity and relative
Mach number distributions.
Investigation of shock waves, tip-clearance flow
and aerodynamic loss mechanisms.
Performance comparison with NASA reference data:
the calculated pressure ratio is lower than
the reference.
Objective:
investigate separation, wake development and drag.
My work:
prepared the domain and locally refined mesh,
ran a steady RANS calculation and analysed the flow field.
0.322
Calculated drag coefficient
0.289
Literature comparison value
+11.4%
Difference from literature
Preliminary comparison with Tian et al. (2017).
Geometry, coefficient definitions and mesh sensitivity
require further investigation.
Method & interpretation
Geometry and domain preparation with local
mesh refinement.
Steady RANS simulation using the SST k–ω
turbulence model.
Post-processing of velocity contours, separation
and the downstream wake.
The drag discrepancy is reported explicitly;
mesh independence has not been established.
Compressor design / Internal flow
Centrifugal compressor
ANSYS Vista CCD · CFX · 2026
Preliminary designGeometry & meshFlow analysis
Objective:
connect impeller geometry to aerodynamic performance.
My work:
preliminary impeller design, mesh generation and CFD
analysis of pressure ratio, efficiency and losses.
Design parameters & analysis
Hub and shroud contours, blade geometry,
backsweep and tip clearance.
Mesh generation and simulation of the compressor flow.
Assessment of pressure rise and aerodynamic losses.
Simulation output · Mach number distribution
Compressible flow / External aerodynamics
Spiked Blunt Body
ANSYS Fluent · RANS · SST k–ω · 2026
Objective:
explore compressible flow around a spiked blunt body
and understand how the spike modifies the shock system.
My work:
simulated the flow using the SST k–ω turbulence model
and interpreted Mach number, velocity and static
pressure contours.
Mach
Flow regime visualization
Velocity
Near-body flow deceleration
Pressure
Compression patterns
Educational CFD study with a qualitative discussion
based on Roveda (2009). Quantitative agreement and
mesh independence have not been established.
Method & interpretation
RANS modelling with the SST k–ω turbulence model.
Post-processing of Mach number, velocity magnitude
and static pressure fields.
The displayed fields show a fast outer flow,
near-body deceleration and localized pressure changes.
Drag and aerodynamic heating are discussed as
physical concepts; no performance improvement
or thermal-load prediction is claimed.
The analysis focuses on understanding compressible-flow
phenomena rather than vehicle design or optimization.
03 · Experience
Research & applied engineering.
Research and engineering internships involving experimental
fluid mechanics, scientific data analysis and energy systems.
IRPHE · Institut de Recherche sur les Phénomènes Hors
Équilibre · Marseille, France
Research Intern — Variable-Density Turbulent Jets
Research objective:
investigate how density differences affect turbulent jet
behaviour and assess the applicability of
constant-density models.
My contribution:
processed PIV/PLIF data from air and helium jets using
Python, analysed turbulence anisotropy and compared
observations with similarity models. Also adapted a
MATLAB optical model to study laser-sheet characteristics.
Variable-density turbulent jets · IRPHE research internship
Air & helium
Variable-density jet datasets
16,400 / 7,000
Reynolds numbers studied
PIV / PLIF
Experimental diagnostics
Research outputs:
processed datasets, turbulence visualisations,
comparisons with reference models and a technical
internship report.
Fluid mechanics
Turbulence
Python
MATLAB
PIV / PLIF
Scientific data analysis
Explore the research methods & technical findings
01 — Experimental data analysis
Processed and visualised PIV/PLIF datasets from air
and helium jets at Reynolds numbers of 16,400 and
7,000. Used Python to analyse the measurements and
compare jet behaviour with similarity models.
02 — Turbulence anisotropy
Analysed Reynolds stresses and turbulence anisotropy
using invariants and the Lumley diagram. Investigated
the directional structure of turbulent fluctuations
in the measured jet flows.
03 — Assessment of reference models
Compared experimental observations with reference
descriptions and assessed the applicability of a
constant-density model to variable-density jets.
Interpreted discrepancies in relation to the
assumptions of the model.
04 — Laser-sheet modelling in MATLAB
Adapted an optical model to investigate laser-sheet
thickness and depth at a wavelength of 532 nm.
Explored lens spacing numerically for a target
sheet thickness of 1 mm.
The optical work concerns numerical modelling.
Experimental validation of the optical adjustments
and a reduction in measurement noise are not claimed.
A–CID · Conseil, Ingénierie et Développement ·
Salé, Morocco
AI Engineering Intern — Photovoltaic Power Plants
Investigation of AI-based approaches to photovoltaic
plant performance optimisation. Analysis of solar
tracker orientation and the effects of dust and UV
radiation on energy performance.
Artificial intelligence
Python
Solar energy
04 · Education
Education & technical training.
Flowthermolab
Aerospace CFD Program
Specialised training in CFD for aerospace and
turbomachinery applications, covering compressible flows,
mesh generation, numerical modelling, and aerodynamic
performance analysis.
ANSYS CFX
ANSYS Fluent
Turbomachinery
Centrale Méditerranée · Marseille, France
Master’s Programme, Year 2 (M2) — Aeronautics & Transport
Advanced study in aerodynamics and fluid mechanics,
with applications to aerospace and transport systems.
Aeronautics
Transport
CFD
École Centrale Casablanca · Casablanca, Morocco
Engineering Degree — Fluids & Energy
Multidisciplinary engineering education with a
specialisation in fluid mechanics, energy systems,
and numerical simulation.
Fluid mechanics
Energy systems
Engineering
Morocco
Preparatory Classes for Engineering Schools — PCSI / PSI
Intensive two-year preparatory programme in mathematics,
physics, and engineering sciences for competitive
entrance examinations to engineering schools.
