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Andrew C. M. Austin
Researcher at University of Auckland
Publications - 39
Citations - 622
Andrew C. M. Austin is an academic researcher from University of Auckland. The author has contributed to research in topics: Finite-difference time-domain method & Polynomial chaos. The author has an hindex of 10, co-authored 34 publications receiving 457 citations. Previous affiliations of Andrew C. M. Austin include École Polytechnique Fédérale de Lausanne & Max Planck Society.
Papers
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Metamaterial beam with graded local resonators for broadband vibration suppression
TL;DR: In this paper, the authors investigated a technique for broadband vibration suppression using a graded metamaterial beam, where a series of local resonators with the same mass but different natural frequencies are attached to the beam, and a design strategy was proposed, and used to tune the frequency spacing to get a wide attenuation region.
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Efficient Analysis of Geometrical Uncertainty in the FDTD Method Using Polynomial Chaos With Application to Microwave Circuits
TL;DR: In this article, a finite-difference time-domain (FDTD)-based method is developed to analyze 3D microwave circuits with uncertain parameters, such as variability and tolerances in the physical dimensions and geometry introduced by manufacturing processes.
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Modeling Propagation in Multifloor Buildings Using the FDTD Method
TL;DR: In this paper, a three-dimensional parallel implementation of the FDTD method was used to identify and isolate the dominant propagation mechanisms in a multistorey building at 1.0 GHz.
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Application of Polynomial Chaos to Quantify Uncertainty in Deterministic Channel Models
TL;DR: In this article, a non-intrusive formulation of the polynomial chaos method is applied to quantify the uncertainties in deterministic models of the indoor radio channel and the analysis shows the expected variation in the sector-averaged path loss can be considerable for relatively small input parameter uncertainties.
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Modeling the Effects of Nearby Buildings on Inter-Floor Radio-Wave Propagation
TL;DR: In this paper, two buildings (A and B) were modeled and analyzed with a 2D TEz implementation of the FDTD algorithm in order to identify and characterize the mechanisms allowing signals to propagate between floors, specifically reflection and scattering from nearby buildings.