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Mohammed Elajadi

Mohammed Elajadi

Physics
Independent Researcher · Morocco
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About

Independent researcher with a background in physics and a strong interest in theoretical and computational research. My work and interests span fluid dynamics, turbulence, CFD, computational physics, numerical simulation, reduced-order modeling, and mathematical approaches to physical systems. I am particularly interested in exploring connections between theoretical models, numerical methods, and computational tools.

I am open to academic collaborations, research discussions, joint projects, and scientific partnerships with researchers and research groups working on related or interdisciplinary topics. I am also interested in contributing to collaborative research and exploring opportunities to develop and publish research together.

Research keywords

Geometric ModelingTurbulenceCFDComputational PhysicsFluid DynamicsNumerical SimulationNavier-StokesReduced-Order Modeling

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PhysicsResearch Collaboration in Computational Physics, Fluid Dynamics & Mathematical Modeling

I am an independent researcher from Morocco working in physics, computational physics, mathematical modeling, and scientific computing. My main interests include fluid dynamics, turbulence, CFD, numerical simulation, Navier–Stokes flows, and reduced-order modeling. I am looking to connect with researchers, research groups, and independent scientists interested in developing collaborative projects involving computational analysis, mathematical modeling, numerical experimentation, or related interdisciplinary problems. I am particularly interested in combining complementary expertise to investigate interesting physical questions and develop practical computational approaches. I welcome researchers with research ideas, theoretical frameworks, datasets, or computational challenges that could benefit from collaboration. Possible outcomes include joint research, computational studies, methodological development, and potentially co-authored scientific publications.

Publications

1

A Geometric Constraint Framework for Reduced-Order Turbulence Analysis and Prediction

Zenodo · 2026

This white paper proposes a research program toward a geometric framework for reduced-order turbulence analysis and prediction[span_1](start_span)[span_1](end_span). The central hypothesis is that, for a well-defined class of turbulent flows, macroscopic dynamics can be characterized by a finite set of geometric and invariant constraints, without explicitly resolving the complete multiscale energy cascade[span_2](start_span)[span_2](end_span). To investigate this hypothesis, the project introduces a new geometric object, the Gauge-Involutive Constraint Tensor, and outlines a mathematical program combining functional analysis, differential geometry, and computational verification[span_3](start_span)[span_3](end_span). The objective is to determine whether such a framework can provide a rigorous and computationally efficient representation of flow organization while remaining complementary to existing turbulence methodologies[span_4](start_span)[span_4](end_span).

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