Detection of holes in an elastic body based on eigenvalues and traces of eigenmodes

We consider the numerical solution of an inverse problem of finding the shape and location of holes in an elastic body. The problem is solved by minimizing a functional depending on the eigenvalues and traces of corresponding eigenmodes. We use the adjoint method to calculate the shape derivative of this functional. The optimization is performed by BFGS, using a genetic algorithm as a preprocessor and the Method of Fundamental Solutions as a solver for the direct problem. We address several numerical simulations that illustrate the good performance of the method.info:eu-repo/semantics/publishedVersio

Researches on Non-standard Optics for Advanced Gravitational Waves Interferometers

This thesis presents a collection of different researches on non-standard optics in view of enhancing the performances of the Advanced Gravitational waves interferometric detectors, where the thermal noise of the test masses is expected to be a limiting factor for their sensitivity. We provide a quantitative analysis of the impact of non-Gaussian beams on different kinds of thermal noises. We developed the theory of mesa beam, in view of a future implementation in advanced GW interferometers of the mesa beam idea, focusing on the analytical derivation of the quantities (i.e. beam width, divergence, propagation factor), which are chosen as ISO standard reference parameters for the characterization of an optical beam. We also analytically proved a new duality relation between optical cavities with non-spherical mirrors. The interest of the GW community in this new beam technology led us to the construction and testing of a prototype mesa beam Fabry-Perot cavity with Mexican-hat mirror. Part of the work of this thesis was devoted to the development of new simulation programs of optical systems. These programs provided the theoretical expected behaviour of our experiment, in particular cavity modes structure and misalignments sensitivity to be confronted with the experimental results. We also explored another complementary way of reducing the mirror thermal noise, beside the beam shaping, that is the multi-layered coating thickness optimization. We show it to be effective in reducing the coating noise and explore the possible implications for GW interferometers in terms of sensitivity. During this analysis we developed an independent model for the coating effective elastic parameters, which is based on the well understood subject of homogenization theory.Comment: Ph.D. thesis, University of Pisa & LIGO-Caltech, 185 page

Geometric Expression Invariant 3D Face Recognition using Statistical Discriminant Models

Currently there is no complete face recognition system that is invariant to all facial expressions. Although humans find it easy to identify and recognise faces regardless of changes in illumination, pose and expression, producing a computer system with a similar capability has proved to be particularly di cult. Three dimensional face models are geometric in nature and therefore have the advantage of being invariant to head pose and lighting. However they are still susceptible to facial expressions. This can be seen in the decrease in the recognition results using principal component analysis when expressions are added to a data set. In order to achieve expression-invariant face recognition systems, we have employed a tensor algebra framework to represent 3D face data with facial expressions in a parsimonious space. Face variation factors are organised in particular subject and facial expression modes. We manipulate this using single value decomposition on sub-tensors representing one variation mode. This framework possesses the ability to deal with the shortcomings of PCA in less constrained environments and still preserves the integrity of the 3D data. The results show improved recognition rates for faces and facial expressions, even recognising high intensity expressions that are not in the training datasets. We have determined, experimentally, a set of anatomical landmarks that best describe facial expression e ectively. We found that the best placement of landmarks to distinguish di erent facial expressions are in areas around the prominent features, such as the cheeks and eyebrows. Recognition results using landmark-based face recognition could be improved with better placement. We looked into the possibility of achieving expression-invariant face recognition by reconstructing and manipulating realistic facial expressions. We proposed a tensor-based statistical discriminant analysis method to reconstruct facial expressions and in particular to neutralise facial expressions. The results of the synthesised facial expressions are visually more realistic than facial expressions generated using conventional active shape modelling (ASM). We then used reconstructed neutral faces in the sub-tensor framework for recognition purposes. The recognition results showed slight improvement. Besides biometric recognition, this novel tensor-based synthesis approach could be used in computer games and real-time animation applications

Surface Registration for Pharyngeal Radiation Treatment Planning

Endoscopy is an in-body examination procedure that enables direct visualization of tumor spread on tissue surfaces. In the context of radiation treatment planning for throat cancer, there have been attempts to fuse this endoscopic information into the planning CT space for better tumor localization. One way to achieve this CT/Endoscope fusion is to first reconstruct a full 3D surface model from the endoscopic video and then register that surface into the CT space. These two steps both require an algorithm that can accurately register two or more surfaces. In this dissertation, I present a surface registration method I have developed, called Thin Shell Demons (TSD), for achieving the two goals mentioned above. There are two key aspects in TSD: geometry and mechanics. First, I develop a novel surface geometric feature descriptor based on multi-scale curvatures that can accurately capture local shape information. I show that the descriptor can be effectively used in TSD and other surface registration frameworks, such as spectral graph matching. Second, I adopt a physical thin shell model in TSD to produce realistic surface deformation in the registration process. I also extend this physical model for orthotropic thin shells and propose a probabilistic framework to learn orthotropic stiffness parameters from a group of known deformations. The anisotropic stiffness learning opens up a new perspective to shape analysis and allows more accurate surface deformation and registration in the TSD framework. Finally, I show that TSD can also be extended into a novel groupwise registration framework. The advantages of Thin Shell Demons allow us to build a complete 3D model of the throat, called an endoscopogram, from a group of single-frame-based reconstructions. It also allows us to register an endoscopogram to a CT segmentation surface, thereby allowing information transfer for treatment planning.Doctor of Philosoph

Nonlinear effects in low-dimensional systems: graphene membrane and electron transport in semiconductor superlattices

Mención Internacional en el título de doctorThis PhD dissertation deals with two different topics: Mechanics of graphene from a statistical mechanics approach, where internal interactions and effects due to temperature are considered. And electron dynamics and chaos in semiconductor superlattices, where we aim at enhancing the chaotic behavior, with its applicability to random number generation in mind. It is not our purpose to bridge these two different topics. But we do believe that with the rise of nanotechnology and the ever-increasing interdisciplinary of science, studies where different topics are approached and discussed are highly desirable. Nanotechnology already rules our life. However, it is still surprising how much progress has been achieved without a fully understanding of the physics governing these structures. In particular, out-of-equilibrium behavior and non-linear responses are present in every nanostructure, but, sometimes, it is possible to avoid their effects at large time scales or small interactions. However, the increasing demand of better and/or new performances makes them sometimes unavoidable, or even, desirable. Micro-metric samples of graphene or semiconductor superlattices cannot be studied taking into account every microscopic interaction, which makes it necessary to use mesoscopic models with a certain range of validity. Throughout this work, we have tried to improve our understanding of the topics stated above, using mesoscopic physical models and techniques from statistical mechanics and dynamical systems. We hope that the obtained results will help the scientific community to gain insight into these fascinating topics and will motivate new research in this direction.Spanish Ministerio de Economía y Competitividad (MINECO) Grant No. MTM2014-56948-C2-2-P and FIS2011-28838-C02-01 and Comunidad de Madrid Grant No. P2009/ENE-1597(HYSYCOMB)Programa Oficial de Doctorado en Ciencia e Ingeniería de MaterialesPresidente: Francisco Guinea López.- Secretario: Jesús Salas Martínez.- Vocal: Beatriz Olmos Sánche

Investigations of surface plasmon resonances by energy-filtering transmission electron microscopy methods

This thesis concentrates on different plasmonic phenomena which are observed with a transmission electron microscope (TEM) in combination with electron energy loss spectroscopy (EELS) and energy-filtering transmission electron microscopy (EFTEM) techniques offering high energy and spatial resolution. Plasmonic coupling behaviour of nanoholes and nanoparticles having rectangular, circular, triangular etc. shapes were investigated using different techniques. The electromagnetic nature of the observed situations was unveiled with different simulation techniques based on discrete dipole approximation (DDA), finite element method (FEM), and three-dimensional finite-difference time-domain methods (3D-FDTD)

Homogenization of a model for the propagation of sound in the lungs

International audienceIn this paper, we are interested in the mathematical modeling of the propagation of sound waves in the lung parenchyma, which is a foam-like elastic material containing millions of air-filled alveoli. In this study, the parenchyma is governed by the linearized elasticity equations, and the air by the acoustic wave equations. The geometric arrangement of the alveoli is assumed to be periodic with a small period ε > 0. We consider the time-harmonic regime forced by vibrations induced by volumic forces. We use the two-scale convergence theory to study the asymptotic behavior as ε goes to zero and prove the convergence of the solutions of the coupled fluid-structure problem to the solution of a linear-elasticity boundary value problem

Athermal Phonon Sensors in Searches for Light Dark Matter

In recent years, theoretical and experimental interest in dark matter (DM) candidates have shifted focus from primarily Weakly-Interacting Massive Particles (WIMPs) to an entire suite of candidates with masses from the zeV-scale to the PeV-scale to 30 solar masses. One particular recent development has been searches for light dark matter (LDM), which is typically defined as candidates with masses in the range of keV to GeV. In searches for LDM, eV-scale and below detector thresholds are needed to detect the small amount of kinetic energy that is imparted to nuclei in a recoil. One such detector technology that can be applied to LDM searches is that of Transition-Edge Sensors (TESs). Operated at cryogenic temperatures, these sensors can achieve the required thresholds, depending on the optimization of the design. In this thesis, I will motivate the evidence for DM and the various DM candidates beyond the WIMP. I will then detail the basics of TES characterization, expand and apply the concepts to an athermal phonon sensor--based Cryogenic PhotoDetector (CPD), and use this detector to carry out a search for LDM at the surface. The resulting exclusion analysis provides the most stringent limits in DM-nucleon scattering cross section (comparing to contemporary searches) for a cryogenic detector for masses from 93 to 140 MeV, showing the promise of athermal phonon sensors in future LDM searches. Furthermore, unknown excess background signals are observed in this LDM search, for which I rule out various possible sources and motivate stress-related microfractures as an intriguing explanation. Finally, I will shortly discuss the outlook of future searches for LDM for various detection channels beyond nuclear recoils.Comment: 243 pages, Ph.D. Thesis in Physics at UC Berkele

12th International Conference on Vibrations in Rotating Machinery

Since 1976, the Vibrations in Rotating Machinery conferences have successfully brought industry and academia together to advance state-of-the-art research in dynamics of rotating machinery. 12th International Conference on Vibrations in Rotating Machinery contains contributions presented at the 12th edition of the conference, from industrial and academic experts from different countries. The book discusses the challenges in rotor-dynamics, rub, whirl, instability and more. The topics addressed include: - Active, smart vibration control - Rotor balancing, dynamics, and smart rotors - Bearings and seals - Noise vibration and harshness - Active and passive damping - Applications: wind turbines, steam turbines, gas turbines, compressors - Joints and couplings - Challenging performance boundaries of rotating machines - High power density machines - Electrical machines for aerospace - Management of extreme events - Active machines - Electric supercharging - Blades and bladed assemblies (forced response, flutter, mistuning) - Fault detection and condition monitoring - Rub, whirl and instability - Torsional vibration Providing the latest research and useful guidance, 12th International Conference on Vibrations in Rotating Machinery aims at those from industry or academia that are involved in transport, power, process, medical engineering, manufacturing or construction