NUMELEC2026, The 11th European Conference on Numerical Methods in Electromagnetism (NUMELEC 2026) will take place from November 18 to 20 in Grenoble at GreEn-Er.
The aim of NUMELEC is to offer the two communities working in the fields of low and high frequencies the opportunity to meet and exchange views on the latest advances in their research. The three-day conference will feature joint oral and poster sessions, discussions on common topics, and the development of useful guidelines for both communities. The areas covered will include methodological aspects such as formulations of electromagnetic problems in static, quasi-static or variable regimes, resolution and optimization methods, as well as applicative aspects linked to the modeling of materials and devices.
- Topic 1: Mathematical modeling and formulations
Static (electrostatics, magnetostatics) and quasi-static (induced currents) problems, radiation, propagation and diffraction, boundary conditions, absorbing boundaries, time-dependent domains.
- Topic 2: Discretization methods
Finite elements, finite difference and mimetic approaches, finite volumes, spectral methods, integral methods, discontinuous Galerkin methods, polytopal approximations, temporal schemes, asymptotic methods, multiscale problems, meshless methods, mixed methods, mesh generation, error estimators.
- Topic 3: Methods for solving large systems
Direct methods, iterative methods, multipole and compression methods, preconditioners, linear/non-linear eigenvalue problems, high-performance computing, domain decomposition methods, model reduction.
- Topic 4: Materials modeling
Magnetic and dielectric materials, superconducting materials, composite materials, metamaterials, plasmonics, active materials, plasma, ferroelectricity, photonic bandgap structures, absorbers, homogenization.
- Topic 5: Coupled problems
Multi-physics problems: electromagnetics/thermics/mechanics of solids and fluids, plasma, field/circuit coupling.
- Topic 6: Design and optimization
Parametric, shape and topological optimization, sensitivity analysis, multi-objective and multi-level optimization, robust design, design methods.
- Machine learning and data-driven methods
Data-driven methods, inverse problems, digital twins, supervised and unsupervised learning, deep learning, expert systems, neural networks
Electric motors and other electromechanical actuators, transformers and electric power transmission, field-transducers, induction and microwave heating, wave interactions with inert and living matter, EMC, telecommunications, waveguides and optical fibers, non-destructive testing, antennas, radar and RCS, optics and photonics, terahertz imaging, nano-optics, nano-magnetism.
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