180 research outputs found

    FDTD Simulation Techniques for Simulation of Very Large 2D and 3D Domains Applied to Radar Propagation over the Ocean

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    abstract: A domain decomposition method for analyzing very large FDTD domains, hundreds of thousands of wavelengths long, is demonstrated by application to the problem of radar scattering in the maritime environment. Success depends on the elimination of artificial scattering from the “sky” boundary and is ensured by an ultra-high-performance absorbing termination which eliminates this reflection at angles of incidence as shallow as 0.03 degrees off grazing. The two-dimensional (2D) problem is used to detail the features of the method. The results are cross-validated by comparison to a parabolic equation (PE) method and surface integral equation method on a 1.7km sea surface problem, and to a PE method on propagation through an inhomogeneous atmosphere in a 4km-long space, both at X-band. Additional comparisons are made against boundary integral equation and PE methods from the literature in a 3.6km space containing an inhomogeneous atmosphere above a flat sea at S-band. The applicability of the method to the three-dimensional (3D) problem is shown via comparison of a 2D solution to the 3D solution of a corridor of sea. As a technical proof of the scalability of the problem with computational power, a 5m-wide, 2m-tall, 1050m-long 3D corridor containing 321.8 billion FDTD cells has been simulated at X-band. A plane wave spectrum analysis of the (X-band) scattered fields produced by a 5m-wide, 225m-long realistic 3D sea surface, and the 2D analog surface obtained by extruding a 2D sea along the width of the corridor, reveals the existence of out-of-plane 3D phenomena missed by the traditional 2D analysis. The realistic sea introduces random strong flashes and nulls in addition to a significant amount of cross-polarized field. Spatial integration using a dispersion-corrected Green function is used to reconstruct the scattered fields outside of the computational FDTD space which would impinge on a 3D target at the end of the corridor. The proposed final approach is a hybrid method where 2D FDTD carries the signal for the first tens of kilometers and the last kilometer is analyzed in 3D.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

    Modeling and Simulation of Optical Properties of Noble Metals Triangular Nanoprisms

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    Gold and silver has gained huge attention across the scientific community for its applications arising from its plasmonic properties. The optical properties achieved by these materials via excitation of plasmons is very unique to these materials and used as diagnostic and therapeutic agents in the field of medicine, and as sensors in a gamut of disciplines such as energy and environmental protection to name a few. Surface plasmon resonance (SPR) properties of the gold and silver are size and shape dependent. Of the various shapes reported in literature, triangular nanoprisms has tunable optical properties in the visible and near IR region by manipulating the structural features such as thickness, edge length, and morphology of tip. To understand the effect of these parameters on dipole surface plasmon resonance we have constructed triangular silver nanoprism and sandwich of gold and triangular nanoprism using Optiwave FDTD. Silver triangular nanoprism has exhibited blue shift on introduction of truncation and the blue shift continued further with depth of truncation. Similar observations were made for increase in thickness of nanoprism. In contrast, increase in edge length of the nanoprism has introduced a blue shift in dipole surface plasmon resonance. Coupling of gold and silver as sandwich with a dielectric material has introduced two plasmon resonance peaks in the visible and near IR region. In contrast to individual silver triangular nanoprism, increasing the edge length and thickness of gold and silver has introduced a red shift. Interestingly, thickness of the dielectric layer controls the wavelength of the dipole plasmon resonance of metals in the sandwich and its strength

    Topology Optimization of Nanophotonic Devices

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    Advanced ultrawideband imaging algorithms for breast cancer detection

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    Ultrawideband (UWB) technology has received considerable attention in recent years as it is regarded to be able to revolutionise a wide range of applications. UWB imaging for breast cancer detection is particularly promising due to its appealing capabilities and advantages over existing techniques, which can serve as an early-stage screening tool, thereby saving millions of lives. Although a lot of progress has been made, several challenges still need to be overcome before it can be applied in practice. These challenges include accurate signal propagation modelling and breast phantom construction, artefact resistant imaging algorithms in realistic breast models, and low-complexity implementations. Under this context, novel solutions are proposed in this thesis to address these key bottlenecks. The thesis first proposes a versatile electromagnetic computational engine (VECE) for simulating the interaction between UWB signals and breast tissues. VECE provides the first implementation of its kind combining auxiliary differential equations (ADE) and convolutional perfectly matched layer (CPML) for describing Debye dispersive medium, and truncating computational domain, respectively. High accuracy and improved computational and memory storage efficiency are offered by VECE, which are validated via extensive analysis and simulations. VECE integrates the state-of-the-art realistic breast phantoms, enabling the modelling of signal propagation and evaluation of imaging algorithms. To mitigate the severe interference of artefacts in UWB breast cancer imaging, a robust and artefact resistant (RAR) algorithm based on neighbourhood pairwise correlation is proposed. RAR is fully investigated and evaluated in a variety of scenarios, and compared with four well-known algorithms. It has been shown to achieve improved tumour detection and robust artefact resistance over its counterparts in most cases, while maintaining high computational efficiency. Simulated tumours in both homogeneous and heterogeneous breast phantoms with mild to moderate densities, combined with an entropy-based artefact removal algorithm, are successfully identified and localised. To further improve the performance of algorithms, diverse and dynamic correlation weighting factors are investigated. Two new algorithms, local coherence exploration (LCE) and dynamic neighbourhood pairwise correlation (DNPC), are presented, which offer improved clutter suppression and image resolution. Moreover, a multiple spatial diversity (MSD) algorithm, which explores and exploits the richness of signals among different transmitter and receiver pairs, is proposed. It is shown to achieve enhanced tumour detection even in severely dense breasts. Finally, two accelerated image reconstruction mechanisms referred to as redundancy elimination (RE) and annulus predication (AP) are proposed. RE removes a huge number of repetitive operations, whereas AP employs a novel annulus prediction to calculate millions of time delays in a highly efficient batch mode. Their efficacy is demonstrated by extensive analysis and simulations. Compared with the non-accelerated method, RE increases the computation speed by two-fold without any performance loss, whereas AP can be 45 times faster with negligible performance degradation

    Back-Propagation Optimization and Multi-Valued Artificial Neural Networks for Highly Vivid Structural Color Filter Metasurfaces

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    We introduce a novel technique for designing color filter metasurfaces using a data-driven approach based on deep learning. Our innovative approach employs inverse design principles to identify highly efficient designs that outperform all the configurations in the dataset, which consists of 585 distinct geometries solely. By combining Multi-Valued Artificial Neural Networks and back-propagation optimization, we overcome the limitations of previous approaches, such as poor performance due to extrapolation and undesired local minima. Consequently, we successfully create reliable and highly efficient configurations for metasurface color filters capable of producing exceptionally vivid colors that go beyond the sRGB gamut. Furthermore, our deep learning technique can be extended to design various pixellated metasurface configurations with different functionalities.Comment: To be published. 25 Pages, 17 Figure

    Engineering optical nonlinearities in metal nanoparticle arrays

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    Thesis (Ph.D.)--Boston UniversityMetal nanostructures supporting localized surface plasmon (LSP) resonances are an emerging technology for sensing, optical switching, radiative engineering, and solar energy harvesting, among other applications. The unique property of LSP resonances that enable these technologies is their ability to localize and enhance the optical field near the surface of metal nanoparticles. However, many questions still remain regarding the effects of nanoparticle coupling on the linear and nonlinear optical properties of these structures. In this thesis, I investigate the role of long-range photonic and near-field plasmonic coupling on the linear and nonlinear optical properties of metal nanoparticles in periodic and deterministic aperiodic arrays within a combined experimental and theoretical framework. In particular, I have developed optical characterization techniques to study various properties of planar metal nano-cylinder arrays fabricated by electron beam lithography (EBL). These include the effect of Fano-type coupling between structural grating modes and LSP resonances on linear diffraction and second harmonic generation (SHG), the influence of near-field coupling on the efficiency of plasmon enhanced metal photoluminescence (PL), the dependence of two-photon PL (TPPL) on nanoparticle size, and the multi-polar nature of SHG from planar plasmonic arrays. Experimental results are fully supported by linear scattering theory of the near and far-field properties of particle arrays based on a range of analytical, semi-analytical, and fully numerical techniques. The breadth of computational methods used allows the investigation of a wide range of structures including large aperiodic arrays with hundreds of discrete particles and periodic arrays with realistic particle shapes, substrates, and excitation conditions. The technological potential of engineered plasmonic structures is demonstrated by enhanced vibrational sum frequency generation (VSFG) spectroscopy, a novel nonlinear sensing technique. These studies have revealed design principles for engineering the interplay of photonic and plasmonic coupling for future linear and nonlinear plasmonic devices for sensing, switching, and modulation. The optical characterization techniques developed in this thesis may additionally be used across a wide range of devices in photonics and nano-optics

    Tools for urban sound quality assessment

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