Block Krylov Recycling Algorithms for FETI-2LM Applied to 3-D Electromagnetic Wave Scattering and Radiation

Improvement of DDM Preprocessing for the Simulation of the GRAVES Radar Densified Sparse Array for Space Surveillance and Tracking

“…This method has also demonstrated its effectiveness for simulating linearly independent multi-source (TEM mode feeds) problems with the implementation of Block Krylov Recycling Strategy (BKRS) and improves significantly the previous works of [4], [5] and [6]. The efficiency of the method for linearly independent feeds (in our application the 200 surrounded antenna near fields are significantly different) as already been demonstrated in [9] for array antennas where gains in computation time of around 11 have been observed. Each sub-domain of our decomposition belonging to a limited set of unit-cell meshes (antenna, air and groud plane subdomains), is locally meshed with an automatic procedure of the GID preprocessor [12] based on GID batch files and T cl scripts [13].…”

“…Recently [1], to overcome the calculation difficulties indicated above, the simulation of the large size GRAVES sparse array has been performed with the Finite Element Tearing and Interconnecting using two Lagrange multipliers (FETI-2LM) technique [3], [9], [10] implemented in ONERA's FACTOPO code. The originality is that the complete mesh is not built upstream of the resolution of the electromagnetic problem avoiding the use of specific mesh splitter tools such as METIS [11] to decompose the large scale initial mesh.…”

Simulation of Active Reflection Coefficient Phenomena of Large Antenna Array Using FEM Domain Decomposition Methods

“…Step by step description 1) Field expansion on the n th TEM ports of the array: On each antenna port, the electric and magnetic fields (E n and H n ) are expanding using incoming (e n , h n ) and outgoing (e n , −h n ) TEM electromagnetic modal waves [17] of amplitudes a n and b n . 2) Solving the FEM problem: The Generalized Admittance Matrix (GAM) of the array is first FEM-computed with the FETI-2LM domain decomposition method [14] and converted to a Generalized Scattering Matrix (GSM) 'S' as proposed in [6].…”

“…However, the methodology to extract the scattering matrix of the array is based on a mix of periodic approximations (for the center elements) and partial local embedded zones for the border elements of the array. In this work, so as to efficiently calculate the embedded radiation patterns of all the radiating elements (internal and boundary radiating elements) as well as the complete Scattering Matrix [6] of the array, we discuss the interest of the implementation of the FETI-2LM domain decomposition methods taking into account the finitude o f t he a rray on massively parallel computers initially developed in [14] and optimized in [15] and [16] for large size sparse arrays. The main goal is to implement a method allowing in a first step to calculate the radiating elements radiation patterns and the GSM of the array, and in a second post processing step to calculate the gain patterns of the antenna array for azimuth and elevation scanning directions while taking into account the active reflection c oefficient.…”

Evolutionary optimization for pattern synthesis and reduction of mutual coupling of linear antenna arrays

“…These side lobes can be suppressed by controlling the control parameters of the antenna arrays. [4][5][6][7][8][9] Different optimization techniques like particle swarm optimization (PSO), [10][11][12][13][14][15][16][17][18][19] genetic algorithm (GA), 20 block Krylov recycling algorithms, 21 hybrid technique, 22 Chichen swarm optimization, 23 using integral operator, 24 PSO, 25 bat algorithm, 26 differential evolution (DE) 21 are being used in the field of the antenna and electromagnetic as well as other fields of engineering and real-life application.…”