Mouad Klai

Personal information

Full name : Klai Mouad

ORCID : https://orcid.org/0000-0003-3453-525X

LinkedIn : https://www.linkedin.com/in/mouad-klai/

Email : mouad.klai@ird.fr

TEL : +212 634 7282 65

Thesis

  • Thesis topic :

Modeling and simulation of biological dynamics using numerical schemes and machine learning : Application to microbial decomposition in porous media.

  • Overview :

This is a PhD studentship in Applied Mathematics and Computer Science, with a focus on utilizing PDEs, numerical methods, and machine learning to model and simulate complex systems.

This research is centered around the use of mathematical models and machine learning techniques to simulate microbial decomposition of organic matter in soil.

More specifically, This thesis is for devolopping numerical and theoritical tools for simulating transformation-diffusion processes in complex geometries, including porous media derived from 3D tomographic images of real soil samples.

The overall goal of this research project is to improve the understanding of these transformation-diffusion processes and their impact on microbial activity in soil.

  • Laboratories :

- North : Unit for Mathematical and Computer Modeling of Complex Systems (UMMISCO) — Sorbonne University

- South : Laboratory of mathematics and population dynamics (LMDP) — Cadi Ayyad University

  • Thesis Directors  :

- North : Professor Monga Olivier
- South : Professor Ezzinbi Khalil

Publications

1 - Olivier Monga, Frédéric Hecht, Moto Serge, Mouad Klai, Mbe Bruno, Jorge Dias, Patricia Garnier, Valérie Pot, Generic tool for numerical simulation of transformation-diffusion processes in complex volume geometric shapes : Application to microbial decomposition of organic matter, Computers & Geosciences, Volume 169, 2022, 105240, ISSN 0098-3004, https://doi.org/10.1016/j.cageo.202.... (https://www.sciencedirect.com/scien...) Abstract : This paper presents a generic framework for the numerical simulation of transformation-diffusion processes in complex volume geometric shapes. This work follows a previous one devoted to the simulation of microbial degradation of organic matter in porous system at microscopic scale using a graph based method. The pore space is represented by an optimal ball network. We generalized and improved the MOSAIC method significantly and thus yielded a much more generic and efficient numerical simulation scheme. We proposed to improve the numerical explicit scheme presented in a previous paper by updating the valuated graph in parallel instead of sequentially. From this parallel numerical explicit scheme, we derived an implicit numerical scheme that very significantly reduced the computational cost of the simulation of the diffusion process. We validated our method by comparing the results to the ones provided by classical Lattice Boltzmann Method (LBM) within the context of microbial decomposition simulation. For the same datasets, we obtained similar results in a significantly shorter computing time (i.e., 10–15 min) than the prior work (several hours). Besides the classical LBM method takes around 3 weeks computing time. This paper presents through details the algorithmic and mathematical schemes used in a previous paper. Keywords : computational Modeling ; Biological dynamics ; Pore space ; Computational geometry ; Explicit and implicit numerical scheme