| 1. |
- Helsing, Johan, et al.
(författare)
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Design of Perfectly Conducting Objects That Are Invisible to an Incident Plane Wave
- 2024
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Ingår i: IEEE Journal on Multiscale and Multiphysics Computational Techniques. - 2379-8793. ; 9, s. 104-112
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Tidskriftsartikel (refereegranskat)abstract
- This work concerns the design of perfectly conducting objects that are invisible to an incident transverse magnetic plane wave. The object in question is a finite planar waveguide with a finite periodic array of barriers. By optimizing this array, the amplitude of the scattered field is reduced to less than 10-9 times the amplitude of the incident plane wave everywhere outside the waveguide. To accurately evaluate such minute amplitudes, we employ a recently developed boundary integral equation technique, adapted for objects whose boundaries have endpoints, corners, and branch points.
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| 2. |
- Khan, Qazi Mashaal, 1992, et al.
(författare)
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Analysis of Q-factor for AM-SLM Cavity based Resonators using Surface Roughness Models
- 2024
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Ingår i: IEEE Journal on Multiscale and Multiphysics Computational Techniques. - 2379-8793. ; 9, s. 75-83
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Tidskriftsartikel (refereegranskat)abstract
- This research delves into losses of X-band cavity resonators manufactured using additive manufacturing-selective laser melting (AM-SLM) compared to the standard subtractive manufacturing milling technology. Measured losses are benchmarked in terms of resonator (quality) -factor. The measured data is further modelled using the Groiss and one-ball Huray models taking into account the implications of surface roughness and electrical conductivity. The unloaded -factor is derived from frequency-dependent scattering () parameters obtained from measurements and full-wave simulations. Surface roughness was found to impact the -factor significantly and the resonant frequency marginally. Cavities based on AM-SLM technology exhibit higher roughness compared to milling and lowers the -factor. A fusion of both manufacturing methods by milling AM-SLM cavity walls demonstrates an augmented -factor compared to a directly printed cavity. In the study it was also found that the Groiss model tends to overestimate the -factor owing to AM-SLM's rougher surface, while the one-ball Huray model furnishes precise projections by establishing a link between surface roughness and powder particles. Electrical conductivity's influence on -factor was also investigated, showing negligible impact with increased surface roughness. Further, side walls of the AM-SLM cavity were more susceptible to surface roughness, compared to the cavity front walls due to higher surface current density. This study underscores the significance of analyzing surface roughness and electrical conductivity in AM-SLM cavity resonators and highlights the suitability of the one-ball Huray model for accurate -factor prediction of microwave structures with rough surfaces
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| 3. |
- Litvinenko, A., et al.
(författare)
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Computation of electromagnetic fields scattered from objects with uncertain shapes using multilevel monte carlo method
- 2019
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Ingår i: IEEE Journal on Multiscale and Multiphysics Computational Techniques. - : Institute of Electrical and Electronics Engineers Inc.. - 2379-8793. ; 4, s. 51-64
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Tidskriftsartikel (refereegranskat)abstract
- Computational tools for characterizing electromagnetic scattering from objects with uncertain shapes are needed in various applications ranging from remote sensing at microwave frequencies to Raman spectroscopy at optical frequencies. Often, such computational tools use the Monte Carlo (MC) method to sample a parametric space describing geometric uncertainties. For each sample, which corresponds to a realization of the geometry, a deterministic electromagnetic solver computes the scattered fields. However, for an accurate statistical characterization, the number of MC samples has to be large. In this paper, to address this challenge, the continuation multilevel Monte Carlo (CMLMC) method is used together with a surface integral equation solver. The CMLMC method optimally balances statistical errors due to sampling of the parametric space, and numerical errors due to the discretization of the geometry using a hierarchy of discretizations, from coarse to fine. The number of realizations of finer discretizations can be kept low, with most samples computed on coarser discretizations to minimize computational cost. Consequently, the total execution time is significantly reduced, in comparison to the standard MC scheme.
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