Conception and deployment of innovative optimal control strategies for smart energy grids
District heating networks (DHNs) play a vital role in energy transition strategies due to their ability to integrate renewable and waste heat effectively. In France, the national low-carbon strategy emphasizes expanding and optimizing DHNs, including smaller networks with multiple heat sources like solar thermal and storage. Smart control systems, such as model-predictive control (MPC), aim to replace manual, expert-based practices to enhance efficiency. However, deploying advanced control systems on small DHNs remains challenging due to the cost and complexity of hardware and maintenance requirements.
Current industrial solutions for large DHNs leverage mixed-integer linear programming (MILP) for real-time optimization, while smaller networks often rely on rule-based systems. Research efforts focus on simplifying MPC models, utilizing offline pre-calculations, or incorporating machine learning to reduce complexity. Comparative studies assess various control strategies for adaptability, interpretability, and operational performance.
This postdoctoral project aims to advance DHN control strategies by developing, testing, and deploying innovative approaches on a real DHN experimental site. It involves creating and comparing control models, implementing them in a physical simulator, and deploying the most promising solutions. Objectives include optimizing operational costs, improving system robustness, and simplifying deployment while disseminating findings through conferences, publications, and potential patents. The researcher will have access to cutting-edge tools, computational resources, and experimental facilities.
Cascade of circulicity in compressible turbulence
In this post-doctorate, we propose to study the properties of the small scales of forced compressible homogeneous turbulence. More precisely, exact statistical relations similar to the Monin-Yaglom relation will be investigated. The idea, detailed in reference [1], is to understand how the transfer of circulicity is organized in the inertial range. Circulicity is a quantity associated with angular momentum and, by extension, with vortex motions. The analysis of its inertial properties allows to complete the description of the energy cascade already highlighted in previous works [2,3].
The objective of the post-doctorate is to carry out and exploit direct simulations of compressible homogeneous turbulence with forcing, in order to highlight the inertial properties of circulicity .
To this end, the post-doctoral student will be given access to the very large computing center (TGCC) as well as a code, Triclade, solving the compressible Navier-Stokes equations [4]. This code does not have a forcing mechanism and the first task will therefore be to add this functionality. Once this task has been accomplished, simulations will be carried out by varying the nature of the forcing and in particular the ratio between its solenoidal and dilatational components. These simulations will then be exploited by analyzing the transfer terms of circulicity.
[1] Soulard and Briard. Submitted to Phys. Rev. Fluids. Preprint at arXviv:2207.03761v1
[2] Aluie. Phys. Rev. Lett. 106(17):174502, 2011.
[3] Eyink and Drivas.Phys. Rev. X 8(1):011022, 2018.
[4] Thornber et al. Phys. Fluids 29:105107, 2017.
HPC simulations for PEM fuel cells
The goal is to improve TRUST-FC software -a joint development between LITEN and DES institutes at CEA- for detailed full 3D simulation of hydrogene PEM fuel cells and to run simulations on whole real bipolar plate geometries. Funded by AIDAS virtual lab (CEA/Forshungs Zentrum Juelich), a fully coupled electro-chemical, fluidic and thermal model has been built, based on CEA software TRUST. The model has been benchmarked against its FZJ counterpart (Open fuelcell, based on OpenFoam). The candidate will adapt the software and toolchain to larger and larger meshes up to billion cells meshes required to model a full bipolar plate. Besides, he will introduce two phase flow models in order to address the current technological challenges (local flooding or dryout). This ambitious project is actively supported by close collaboration with CEA/DES and FZJ.
ACCELERATING a DSN SWEEP KERNEL ALGORITHM FOR NEUTRONICS BY PORTING ON GPU.
In the framework of the Programmes Transversaux de Compétences (PTC or literally Cross-XXX Programme), the DES/ISAS/DM2S/SERMA/LLPR and the CEA-DIF are both working on the porting of deterministic neutron transport codes on GPU.
The DM2S within the Energies Direction (DES) is responsible for research and development activities on the numerical methods and codes for reactor physics, amongst which the APOLLO3® code. The neutronics laboratory of CEA-DIF is responsible for developing tools for deterministic methods in neutronics for the Simulation programme.
These two laboratories are actively preparing for the advent of new generation of supercomputers where GPU (Graphical Processing Units) will be predominant. Indeed, the underlying numerical problems to be solved along with the working methodology as well as the conclusions and experience which will be obtained from such studies may be rationalised between both laboratories. Thus, this work has given rise to this postdoctoral position which will be common to both teams. The postdoctoral researcher will be formally based at SERMA at CEA Saclay, with nevertheless regular meetings with the CEA-DIF scientists.
The postdoctoral research work is to study the acceleration of a toy model of a 3D discrete ordinates diamond-differencing sweep kernel (DSN) by porting the code on GPU. This work hinges on porting experiments which have previously been carried by both teams following two different approaches: a ‘’high-level’’ one based on the Kokkos framework for DES and a ‘’low-level’’ approach based on Cuda for CEA-DIF.