ANALYSIS OF SLENDER PIEZOELECTRIC WING CONFIGURATIONS FOR ENERGY HARVESTING: AEROELASTIC MODELING AND EXPERIMENTAL COMPARISONS

The study of the aeroelastic behavior of slender piezoelectric wings gains its relevance within the design perimeter of High Altitude Long Endurance (HALE) aircraft, or more in general of energy independent systems. As a matter of fact, the exploitation of new energy sources, without implying any direct penalization of the flight performances nor of the original aircraft design concept, is particularly appealing for HALE unmanned air vehicles (UAVs). Long range missions entail several design requirements such as high aspect ratio wing and low zero fuel weight, both with the common objective of reducing the energy consumption. However, albeit the structural design challenges afforded during the last years to increase as much as possible the mission duration of HALE aircraft, satellite systems still remain the most effective solution for ground surveillance purposes. Therefore, having additional energy from alternative sources, such as from structural vibrations, has to be embraced as a mission evolution opportunity for HALE UAV. The research activity presented in this thesis aims at investigating the energy extraction, via the application of piezoelectric patches over the wings' surface, from the most commons aeroelastic phenomena: critical flutter, sub-critical and super-critical LCOs, and gust response. For the sake of the just mentioned study, a nonlinear analytical and numerical aeroelastic piezoelectric wing model, which includes geometrical nonlinearities up to the third order and a multi-modal approach, was developed. The importance of higher order nonlinear terms is furthermore investigated via a comparison with FEM and experimental results. The numerical results, in agreement with the experimental results, shown that when the wing undergoes to high static deformations a state of dynamical instabilities may settle at speed even 50% lower than the critical flutter speed, and, in particular, when the oscillation amplitude becomes high, the model has to include higher order nonlinear terms to correctly capture the real oscillation amplitude. The results in terms of energy harvesting from the gust induced vibrations shown that the Squared gust seemed to be more effective for energy harvesting purposes than the 1-Cosine, if compared on the base of the energy content subtended by each curve of the gust profiles. Furthermore, although the 1-Cosine appeared less effective in terms of the amount of power that it can provide to the wing for energy harvesting, it was identified an optimal value of gust penetration gradient at which the assumed piezoelectric wing was able to extract the maximum amount of energy. Finally, thanks to the modal shaker and wind tunnel tests campaign, the importance of the location of the piezoelectric patches over the wing with respect to its dynamical response was investigated. What was seen is that the amount of extractable energy, at LCO, from the second bending mode of the wing is higher than that extractable from the first bending mode and it increases if the piezo-patches are slightly moved towards the wing center. This results suggest the necessity to develop a piezoelectric wing with multiple piezoelectric patches properly located in order to extract energy from the higher number of modes, or simply to the most excited mode, according to the good knowledge of the operational wing dynamic behavior. The order of magnitude of the maximum instantaneous power extracted from the assumed model during LCOs is of 10 mW, a good result if compared to the power demand of modern electronic devices

Packages for Terahertz Electronics

In the last couple of decades, solid-state device technologies, particularly electronic semiconductor devices, have been greatly advanced and investigated for possible adoption in various terahertz (THz) applications, such as imaging, security, and wireless communications. In tandem with these investigations, researchers have been exploring ways to package those THz electronic devices and integrated circuits for practical use. Packages are fundamentally expected to provide a physical housing for devices and integrated circuits (ICs) and reliable signal interconnections from the inside to the outside or vice versa. However, as frequency increases, we face several challenges associated with signal loss, dimensions, and fabrication. This paper provides a broad overview of recent progress in interconnections and packaging technologies dealing with these issues for THz electronics. In particular, emerging concepts based on commercial ceramic technologies, micromachining, and 3-D printing technologies for compact and lightweight packaging in practical applications are highlighted, along with metallic split blocks with rectangular waveguides, which are still considered the most valid and reliable approach.119Ysciescopu

Etude des spécificités du frittage par micro-ondes de poudres d'alumine alpha et gamma

To meet the new economic and environmental constraints that the industry faces today, fast sintering processes are developed for the fabrication of ceramics. Among them, a promising technique is microwave sintering, in which the electromagnetic field at the origin of heating could be used to obtain innovative microstructures, while reducing sintering temperature, cycle time and energy consumption. To explain the particular behavior of powders under microwaves, different hypotheses related with thermal or non-thermal effects have been proposed in the literature. These effects, however, has not really been demonstrated for the moment, especially because of the limits of experimental devices that do not allow for a meaningful comparison of microwave sintering with conventional sintering. In this context, the work performed during this thesis in the framework of FμRNACE ANR project has been dedicated to identifying and understanding the influence of the electromagnetic field on the mechanisms of densification and microstructure changes in ceramic powders. High attention has been paid to the technological development of the single-mode microwave cavity used in our research. The heating process has been fully automated and instrumented with various equipments allowing for temperature and sample shrinkage measurement. The aim was to ensure direct and reliable comparison of microwave sintering data with those resulting from conventional sintering. Numerical simulation has been conducted to improve our understanding of the propagation of the electromagnetic field and its interaction with the components introduced in the microwave cavity. Alumina has been chosen as a reference material and the influence of several features of the powders (specific surface area, doping elements, phase transformation) on densification kinetics and microstructure changes has been studied. The results have identified specific effects of microwaves on the mechanisms controlling densification and grain growth. These effects occur essentially during the initial and intermediate stages of sintering and during the phase transformation of transition powders. They have been attributed to the ponderomotive force as already proposed in the literature. However the use of microwaves as a heating mode does not permit obtaining alumina with better microstructures than those resulting from conventional sintering.Pour répondre aux nouvelles contraintes économiques et environnementales auxquelles l'industrie doit faire face aujourd'hui, des techniques de frittage rapide se développent pour la fabrication des céramiques. Parmi elles, une technique prometteuse est le frittage par micro-ondes dans laquelle le champ électromagnétique à l'origine du chauffage pourrait permettre d'obtenir des microstructures innovantes, tout en réduisant la température, le temps de cycle et la consommation énergétique. Pour expliquer le comportement particulier des poudres en présence des micro-ondes, différentes théories prévoyant des effets thermiques ou non-thermiques ont été proposées. L'existence même de ces effets n'a cependant toujours pas été démontrée de façon sûre, notamment à cause des limites des dispositifs expérimentaux qui ne permettent pas une comparaison pertinente du frittage micro-ondes avec le frittage conventionnel. Dans ce contexte, les travaux réalisés pendant cette thèse, dans le cadre du projet ANR Fµrnace, ont été consacrés à la mise en évidence et à la compréhension de l'influence du champ électromagnétique sur les mécanismes responsables de la densification et de l'évolution microstructurale de poudres céramiques. Une forte attention a été portée au développement technologique de la cavité de chauffage micro-ondes monomode utilisée dans nos recherches. Le procédé a été entièrement automatisé et équipé de divers systèmes de contrôle de la température et du retrait des échantillons pour que les résultats obtenus puissent être comparés de façon incontestable avec ceux issus d'essais de frittage conventionnel. Des simulations numériques ont été réalisées pour améliorer la compréhension de la propagation du champ électromagnétique et de son interaction avec les éléments introduits au sein de la cavité micro-ondes. Un matériau de référence, l'alumine, a été choisi et l'influence de certaines caractéristiques des poudres (surface spécifique, présence de dopants, transformation de phase) sur les cinétiques de densification et l'évolution microstructurale a été étudiée. Les résultats obtenus ont permis d'identifier des effets spécifiques des micro-ondes sur les mécanismes de diffusion responsables de la densification et de la croissance granulaire. Ces effets se produisent principalement pendant les stades initial et intermédiaire du frittage, ainsi que pendant la transformation de phase de poudres de transition et ont été attribués à une force de type pondéromotrice déjà proposée dans la littérature. L'utilisation de cette technique de frittage n'a cependant pas permis d'obtenir des alumines avec des microstructures plus performantes que celles issues du frittage conventionnel

Monitoring of Distillation Column Based on Indiscernibility Dynamic Kernel PCA

Aiming at complicated faults detection of distillation column industrial process, it has faced a grave challenge. In this paper, a new indiscernibility dynamic kernel principal component analysis (I-DKPCA) method is presented and applied to distillation column. Compared with traditional statistical techniques, I-DKPCA not only can capture nonlinear property and dynamic characteristic of processes but also can extract relevant variables from all the variables. Applying this new method to distillation column process (a hardware-in-the-loop simulation system), the results prove the proposed method has great advantages, that is, lower missing rate and higher detection rate for the faults, compared with KPCA and DPCA

주성분분석법과 그레인저 인과관계를 이용한 실시간 공정 모니터링 및 이상 전파 경로 계산

학위논문 (박사)-- 서울대학교 대학원 공과대학 화학생물공학부, 2017. 8. 한종훈.Modern industrial process is a complex device industry consisting of a combination of numerous unit processes. Numerous process parameters such as flow rate, temperature, pressure, concentration and composition have strong linear or nonlinear correlation. Since improvement of computing power and process control systems in industrial processes, several board operator and field operator can manage huge amounts of data and whole process information from industrial plant. However, the number of processes and devices to be handled by a single operator will increase, and operators meets a limitation of cognitive ability due to flood of information, causing problems such as process malfunction or instrumental failure. To solve this problem, we propose a PCA modeling procedures that aims to improve monitoring performance by variable selection, removing noise, operation mode classification and mode change detection. Fault diagnosis and causal analysis is also introduced. We calculated the causal relationship matrix between the process variables and find out the root cause of the unexpected process changes. The proposed approach was applied and validated to LNG plant located in Incheon and plasma condition monitoring in plasma etcher. Chapter 2 discusses the application methodologies of signal processing to eliminate noises from OES signal and multivariate statistical techniques to improve monitoring sensitivity. Among the plasma sensors, optical emission spectroscopy (OES) has been widely utilized and its high dimensionality has required multivariate analysis (MVA) techniques such as principal component analysis (PCA). PCA, however, might devaluate physical meaning of target process during its statistical calculation. In addition, inherent noise from charge coupled devices (CCD) array in OES might deteriorate PCA model performance. Therefore, it is desirable to pre-select physically important variables and to filter out noisy signals before modeling OES based plasma data. For these purposes, this chapter introduces a peak wavelength selection algorithm for selecting physically meaningful wavelength in plasma and discrete wavelet transform (DWT) for filtering out noisy signals from a CCD array. The effectiveness of the PCA model introduced in this paper is verified by comparing fault detection capabilities of conventional PCA model under the various source power or pressure faulty situations in a capacitively coupled plasma etcher. The PCA model introduced in this chapter successively detect even extremely small variation such as 0.67% of source power change even though the conventional PCA model fails to detect all of the faulty situations under the tests. Chapter 3 discusses the application methodology of operation mode identification and multimode PCA to improve the performance of LNG mixed refrigeration (MR) process and prevent process shutdown. LNG MR process is usually used for liquefying natural gas. The compressors for refrigerant compression are operated with the high-speed rotating parts to create a high-pressure. However, any malfunction in the compressors can lead to significant process downtime, catastrophic damage to equipment and potential safety consequences. The existing methodology assumes that the process has a single mode of operation, which makes it difficult to distinguish between a malfunction of the process and a change in mode of operation. Therefore, k-nearest neighbor algorithm (k-NN) is employed to classify the operation modes, which is integrated into multi-mode principal component analysis (MPCA) for process monitoring and fault detection. When the fault detection performance is evaluated with real LNG MR operation data, the proposed methodology shows more accurate and early detection capability than conventional PCA. Chapter 4 discusses PCA based fault amplification algorithm to detect both the root cause of fault and the fault propagation path in the system. The developed algorithm project the samples on the residual subspace (RS) to determine the disturbance propagation path. Usually, the RS of the fault data is superimposed with the normal process variations which should be minimized to amplify the fault magnitude. The RS containing amplified fault is then converted into the co-variance matrix followed by singular value decomposition (SVD) analysis which in turn generates the fault direction matrix corresponding to the largest eigenvalue. The fault variables are then re-arranged according to their magnitude of contribution towards a fault which in turn represents the fault propagation path using an absolute descending order functions. Moreover, the multivariate granger causality (MVGC) algorithm is used to analyze the causal relationship among the variables obtained from the developed algorithm. Both the methodologies are tested on the LNG fractionation process train and distillation column operation where some fault case scenarios are assumed to estimate the fault directions. It is observed that the hierarchy of variables obtained from fault propagation path algorithm are in good agreement with the MVGC algorithm. Therefore, fault amplification methodology can be used in industrial systems for identifying the root cause of fault as well as the fault propagation path. The application results show that the proposed multivariate statistical method can improve productivity and safety by providing useful information for process monitoring and fault diagnosis in various processes with distributed control system.CHAPTER 1 Introduction 1 1.1 Research motivation 1 1.2 Research objectives 4 1.3 Outline of the thesis 5 CHAPTER 2 : Multivariate monitoring, variable selection and OES signal filter design of plasma process 6 2.1 Introduction 6 2.2 Issues in PCA Modeling of OES based Plasma Data 8 2.3 Theoretical Background 11 2.3.1 Peak Wavelength Selection Algorithm 11 2.3.2 Discrete Wavelet Transform 14 2.4 Experimental Set-up 19 2.5 Results and Discussion 21 2.5.1 Pre-selected variables in OES data 21 2.5.2 Decomposition of OES signal by DWT 23 2.5.3 Comparison of Fault Detection Performance in OES based PCA Models 25 2.6 Conclusion 35 CHAPTER 3 : Multimode PCA and k-nearest neighbor algorithm for LNG mixed refrigeration process monitoring 36 3.1 Introduction 36 3.2 Target process and data description 38 3.3 Theoretical Background 45 3.3.1 Principal component analysis based fault detection 45 3.3.2 k-Nearest Neighbor classifier 48 3.4 Mode identification and fault detection 49 3.4.1 Operation mode identification and fault detection 49 3.5 Results and Conclusion 55 3.5.1 Consideration in LNG MR process monitoring 55 3.5.2 Global and local PCA modeling 59 3.5.3 Detection of operation mode 61 3.5.4 Comparison of fault detection performance 66 3.6 Conclusion 70 CHAPTER 4 : Estimation of disturbance propagation path using PCA and multivariate Granger Causality 71 4.1 Introduction 71 4.2 Theoretical Background 77 4.2.1 Fault propagation path detection 77 4.2.2 Causal analysis based on Granger Causality (GC) 82 4.3 Application to the Liquefied Natural Gas (LNG) Process 87 4.3.1 Process Description 87 4.3.2 Development of fault case scenarios 90 4.4 Conclusion 116 CHAPTER 5 Concluding Remarks 118 Nomenclature and Abbreviations 121 Literature cited 122 Abstract in Korean (요 약) 133Docto

Aeronautical engineering: A continuing bibliography with indexes (supplement 223)

This bibliography lists 423 reports, articles, and other documents introduced into the NASA scientific and technical information system in January, 1988

Capteur à fibre optique basé sur le principe de Résonance de Plasmons de Surface : optimisation pour la détection d'espèces chimiques

Surface plasmon resonance (SPR) has been effectively used in the last years for creating highly sensitive sensors required in various fields such as health, security, and environment. The aim of this work is to investigate sensors based on SPR. They are very attractive due to their advantages such as high accuracy and real time monitoring. The novelty of this work is the use of optical fibers to build SPR sensors and than adding new features such as device miniaturizing and remote control of the measurements.The manuscript starts with a review of the theoretical treatment of surface plasmons. It continues with the presentation of the experimental set-up and details the process used for sensors manufacturing. It follows the experimental characterization of the SPR response for the obtained sensors. In particular, we have analyzed the effect of the ultra-thin metal film, of the fiber properties and the monolayer of thiols on the sensor sensitivity. The last section is dedicated to the numerical modelling of the sensor's response for both absorbing and non-absorbing media. This numerical study evaluates the effects of several other parameters on the sensor reponse, such as the effect of the thiol monolayer's refractive index on the SPR or kinetic studies of the absorbed organic materials (mass detection). From these numerical simulations, we demonstrate that the SPR theoretical curves agree well with experiments. The direct comparison between numerical and experimental results is used to optimize the physical parameters for the metal film and optical fiber characteristics.Ce travail de thèse s'inscrit dans la recherche et le développement de capteurs chimiques. Il est motivé par un besoin toujours croissant d'outils de détection dans des domaines aussi variés que la santé, la sécurité et l'environnement. Nous présentons l'étude de capteurs basés sur le principe de résonance plasmons de surface - SPR. L'intérêt de ce type de capteurs est principalement lié à leur grande sensibilité, leur réponse rapide en temps réel et leur grande précision sans l'utilisation de marqueurs. L'originalité de notre approche est l'utilisation de fibres optiques. Celles-ci offrent de nouveaux attraits tels la simplification de l'instrumentation et sa miniaturisation. Dans une première partie, nous présentons une revue théorique sur les plasmons de surface à l'interface métal – diélectrique. Nous présentons ensuite une étude expérimentale en deux parties : la première décrit la réalisation et la caractérisation des capteurs SPR à fibre optique, la seconde présente l'analyse de la réponse SPR des transducteurs ainsi réalisés. En particulier nous avons caractérisé par des études systématiques l'influence de paramètres physiques importants liés au métal, à la fibre optique et au traitement de surface de la partie sensible par le greffage d'une couche de thiols.Enfin, nous proposons une étude numérique simulant la réponse du capteur en fonction de différents stimuli. Ce modèle, basée sur le calcul de la réflectance de la lumière à l'interface d'un ensemble multicouches nous a permis de valider l'étude expérimentale et d'étendre les recherches en prenant en compte différent type de molécules cibles. En particulier, nous présentons des résultats sur des molécules absorbants ou non absorbants, greffées ou non à la surface du transducteur. Une comparaison entre résultats expérimentaux et simulations numériques valide l'ensemble du travail et nous permet finalement de proposer une configuration optimisée du capteur, en fonction de la nature de la couche métallique et de la fibre optique, ainsi que des molécules cibles à détecter