Die heutige und zukünftige Entwicklung beim Entwurf von Axialverdichtern für die Anwendung in Flugzeugtriebwerken ist immer stärker davon geprägt, ein möglichst großes Druckverhältnis mit möglichst wenigen Stufen zu erzeugen. Ziel ist es, möglichst viel Leistung mit möglichst geringem Gewicht umzusetzen, um die Effizienz der Maschine weiter zu verbessern. Um dies zu erreichen, muss eine Erhöhung der Stufendruckverhältnisse und damit eine Erhöhung der Stufenbelastung in Kauf genommen werden. Die höhere Belastung hat jedoch einen Anstieg der Verluste aufgrund der stärker werdenden Sekundärströmungen zur Folge, und wirkt sich zunächst negativ auf die Stabilität und den Wirkungsgrad der Maschine aus. Diese negativen Effekte können nur durch eine Weiterentwicklung der Schaufelgeometrie kompensiert werden. Hierbei stoßen die derzeit benutzten Entwurfsmethoden jedoch an ihre Grenzen. Aus diesem Grund wurde ein neues Verfahren für den dreidimensionalen Entwurf von Rotoren in Axialverdichtern entwickelt. In dieser Arbeit wird dessen Entwicklung präsentiert. Das Verfahren umfasst die systematische Anwendung von Pfeilung und V-Stellung, sowie die dreidimensionale inverse Berechnung der radialen Skelettlinienverteilung. Um damit eine Verbesserung des Rotorwirkungsgrades zu erreichen, müssen vor allem die kritischen wand- bzw. spaltnahen Bereiche optimal an die Strömungsumgebung angepasst werden. Die vorliegende Arbeit beschreibt ausführlich die theoretischen Grundlagen der Rotorströmung und des Rotorentwurfs. Basierend darauf werden für die Umsetzung eines vollständigen dreidimensionalen Schaufelentwurfs zwei Panelverfahren zur Berechnung der dreidimensionalen jedoch reibungslosen Strömung, zur Lösung der Nachrechen- bzw. der Entwurfsaufgabe, entwickelt. Die Panelverfahren werden angewandt, um eine Methodik für den effektiven Einsatz von Pfeilung, V-Stellung und inverser Skelettlinienberechnung für den dreidimensionalen Rotorentwurf festzulegen. Die gewonnenen Erkenntnisse werden anschließend für den Entwurf eines hochbelasteten Rotors in einem einstufigen Niedergeschwindigkeitsverdichter nach dieser neuen Entwurfsmethodik genutzt. Anhand von Ergebnissen aus Rechnungen und Messungen für diesen Rotor wird die Wirksamkeit des Verfahrens demonstriert. / The recent and future design of axial compressors for aero engines is strongly affected by the aim to generate a high pressure ratio with less stages to increase power and reduce weight to achieve an improved efficiency. This can only be achieved when the stage pressure ratio is raised which leads to increased stage loading. But the higher stage loading results in higher losses caused by stronger secondary flows. This has a negative effect on compressor stability and efficiency. To counteract the negative effects enhanced blade geometries are necessary. With the recently used design methods this is hardly to achieve. For that reason a new method for the three-dimensional design of rotors and stators in axial compressors has been developed. This report summarizes that work. The method accounts for the systematic application of sweep and dihedral as well as the three-dimensional inverse calculation of the camber-line distributions along blade height. To achieve improved efficiency the regions close to the end-walls and the tip and hub gap have to be adapted to the flow environment. The recent report described in detail the theoretical background of the compressor blade flow and compressor blade design. Based on that, two inviscid panel methods for the fully three-dimensional design of compressor blades are described. The panel methods are applied to define a methodology for the effective application of sweep, dihedral and inverse camber-line calculation in a three-dimensional blade design process. Afterwards the findings are used to design a highly-loaded single-stage low-speed research compressor rotor. The validity of the presented design method is proven with CFD and test results.

No description available.

<div>The rapid development of topology optimization in photonics has greatly expanded the number of photonic structures with extraordinary performance. The optimization is usually solved by using a gradient-based optimization algorithm, where gradients are evaluated by the adjoint sensitivity analysis. While the adjoint sensitivity analysis has been demonstrated to provide reliable gradients for designs of dielectrics, there has not been too much success in plasmonics. The difficulty of obtaining accurate field solutions near sharp edges and corners in plasmonic structures, and the strong field enhancement jointly increase the numerical error of gradients, leading to failure of convergence for any gradient-based algorithm. </div><div> </div><div>We present a new method of calculating accurate sensitivity with the FDTD method by direct differentiation of the time-marching system in frequency domain. This new method supports general frequency-domain objective functions, does not relay on implementation details of the FDTD method, works with general isotropic materials and can be easily incorporated into both level-set-based and density-based topology optimizations. The method is demonstrated to have superior accuracy compared to the traditional continuous sensitivity. Next, we present a framework to carry out density-based topology optimization using our new sensitivity formula. We use the non-linear material interpolation to counter the rough landscape of plasmonics, adopt the filteringand-projection regularization to ensure manufacturability and perform the optimization with a continuation scheme to improve convergence. </div><div> </div><div>We give two examples involving reconstruction of near fields of plasmonic structures to illustrate the robustness of the sensitivity formula and the optimization framework. In the end, we apply our method to generate a rectangular temperature profile in the recording medium of the HAMR system. </div>

With the demand of computing power from electronic chips on a constant rise, innovative methods are needed for effective and efficient thermal management. Forced convection cooling through an array of micro pin-fins acts not only as a heat sink, but also allows for the electrical interconnection between stacked layers of integrated circuits. This work performs a multi-objective optimization of three shapes of pin-fins to maximize the efficiency of this cooling system. An inverse design approach that allows for the design of cooling configurations without prior knowledge of thermal mapping was proposed and validated. The optimization study showed that pin-fin configurations are capable of containing heat flux levels of next generation electronic chips. It was also shown that even under these high heat fluxes the structural integrity is not compromised. The inverse approach showed that configurations exist that are capable of cooling heat fluxes beyond those of next generation chips. Thin film heat spreaders made of diamond and graphene nano-platelets were also investigated and showed that further reduction in maximum temperature, increase in temperature uniformity and reduction in thermal stresses are possible.

Ce travail porte sur le développement de méthodes numériques innovantes pour la conception aéro-acoustique optimale de forme des configurations supersoniques. Ce manuscrit présente tout d'abord l'analyse et le développement des approches numériques pour la prévision du bang sonique . Le couplage du calcul CFD tridimensionnel en champ proche prenant en compte la décomposition multipolaire de Fourier et la propagation atmosphérique basée sur un algorithme de tracé de rayons est amélioré par l’intégration d'un processus automatique d' adaptation anisotrope de maillage. La deuxième partie de ce travail se concentre sur l’élaboration et l'application des techniques de conception pour l'optimisation d'une configuration aile-fuselage supersonique. Un module de conception inverse, AIDA , fournit à partir d'une signature acoustique cible au sol à faible bang sonique la géométrie de la configuration correspondante. Pour améliorer a la fois les performances acoustique et aérodynamique, des techniques d'optimisation directes de forme sont utilisées pour résoudre des problèmes d'optimisation mono et multi- disciplinaires et une analyse détaillée est réalisée. Des stratégies innovantes basées sur la coopération et les jeux compétitifs sont enfin appliquées au problème d'optimisation multidisciplinaire offrant une alternative aux algorithmes traditionnels MDO . L’hybridation de ces deux stratégies ouvre la voie a une nouvelle façon d'explorer le front de Pareto de manière efficace. Celle-ci est mise en application sur un cas pratique. / This work addresses the development of original numerical methods for the aero-acoustic optimal shape design of supersonic configurations. The first axis of the present research is the enhancement of numerical approaches for the prediction of sonic boom. The three dimensional CFD near-field prediction matched using a multipole decomposition approach coupled with atmospheric propagation using on a ray-tracing algorithm is improved by the integration of an automated anisotropic mesh adaptation process. The second part of this work focuses on the formulation and development of design techniques for the optimization of a supersonic wing-body configuration. An inverse design module, AIDA, is able to determine an equivalent configuration provided a target shaped signature at ground level corresponding to a low-boom profile. In order to improve both the aerodynamic and the acoustic performance, direct shape optimization techniques are used to solve single and multi-disciplinary optimization problems and a detailed analysis is carried out. At last, innovative strategies based on cooperation and competitive games are then applied to the multi-disciplinary optimization problem providing an alternative to traditional MDO algorithms. Hybridizing the two strategies opens a new efficient way to explore the Pareto front and this is shown on a practical case.

<p>The demand for the faster information transport and better computational abilities is ever increasing. In the last few decades, the electronic industry has met this requirement by increasing the number of transistors per square inch. This lead to the scaling of devices to tens of nm. However, the speed of the electronics is limited to few GHz. Using light, the operating speed of photonic devices can be much larger than GHz. But the photonic devices are diffraction limited and hence the size of photonic device is much larger than the electronic components. Plasmonics is an emerging field with light-induced surface excitations, and can manipulate the light at nanoscale. It can bridge the gap between electronics and photonics. </p> <p>With the present scaling of devices to few nm, the scientific community is looking for alternatives for continued progress. This has opened up several promising routes recently, including two-dimensional materials, quantum computing, topological computing, spintronics and valleytronics. The discovery of graphene has led to the immense interest in the field of two-dimensional materials. Two dimensional-materials have extraordinary properties compared to its bulk. This work discusses the applications of plasmonics in this emerging field of two-dimensional materials and for heat assisted magnetic recording.</p> <p>Black phosphorus is an emerging low-direct bandgap two-dimensional semiconductor, with anisotropic optical and electronic properties. It has high mobility and is promising for photo detection at infrared wavelengths due to its low band gap. We demonstrate two different plasmonic designs to enhance the photo responsivity of black phosphours by localized surface plasmons. We use bowtie antenna and bowtie apertures to increase the absorption and polarization selectivity respectively. Plasmonic structures are designed by numerical electromagnetic simulations, and are fabricated to experimentally demonstrate the enhanced photo responsivity of black phosphorus. </p> <p>Next, we look at another emerging two-dimensional material, bismuth telluride selenide (Bi₂Te₂Se). It is a topological insulator with an insulating bulk but conducting electronic surface states. These surface states are Dirac like, similar to graphene and can lead to exotic plasmonic phenomena. We investigated the optical properties of Bi₂Te₂Se and found that the bulk is plasmonic below 650 nm wavelength. We study the distinct surface plasmons arising from the bulk and surface state of the topological insulator, Bi₂Te₂Se. The propagating surface plasmons at a nanoscale slit in Bi₂Te₂Se are imaged using near-field scanning optical microscopy. The surface state plasmons are studied with a below band gap excitation of 10.6 µm wavelength and the surface plasmons of the bulk are studied with a visible wavelength of 633 nm. The surface state plasmon wavelength is 100 times shorter than the incident wavelength in sharp contrast to the plasmon wavelength of the bulk. </p> <p>Next, we look at the application of plasmonics in heat assisted magnetic recording (HAMR). HAMR is one of the next generation data storage technology that can increase the areal density to beyond 1 Tb/in². Near-field transducer (NFT) is a key component of the HAMR system that locally heats the recording medium by concentrating light below the diffraction limit using surface plasmons. In this work, we use density-based topology optimization for inverse design of NFT for a desired temperature profile in the recording medium. We first perform an inverse thermal calculation to obtain the required volumetric heat generation (electric field) for a desired temperature profile. Then an inverse electromagnetic design of NFT is performed for achieving the desired electric field. NFT designs for both generating a small heated spot size and a heated spot with desired aspect ratio in recording medium are demonstrated. The effect of waveguide, write pole and moving recording medium on the heated spot size is also investigated. </p>

Die heutige und zukünftige Entwicklung beim Entwurf von Axialverdichtern für die Anwendung in Flugzeugtriebwerken ist immer stärker davon geprägt, ein möglichst großes Druckverhältnis mit möglichst wenigen Stufen zu erzeugen. Ziel ist es, möglichst viel Leistung mit möglichst geringem Gewicht umzusetzen, um die Effizienz der Maschine weiter zu verbessern. Um dies zu erreichen, muss eine Erhöhung der Stufendruckverhältnisse und damit eine Erhöhung der Stufenbelastung in Kauf genommen werden. Die höhere Belastung hat jedoch einen Anstieg der Verluste aufgrund der stärker werdenden Sekundärströmungen zur Folge, und wirkt sich zunächst negativ auf die Stabilität und den Wirkungsgrad der Maschine aus. Diese negativen Effekte können nur durch eine Weiterentwicklung der Schaufelgeometrie kompensiert werden. Hierbei stoßen die derzeit benutzten Entwurfsmethoden jedoch an ihre Grenzen. Aus diesem Grund wurde ein neues Verfahren für den dreidimensionalen Entwurf von Rotoren in Axialverdichtern entwickelt. In dieser Arbeit wird dessen Entwicklung präsentiert. Das Verfahren umfasst die systematische Anwendung von Pfeilung und V-Stellung, sowie die dreidimensionale inverse Berechnung der radialen Skelettlinienverteilung. Um damit eine Verbesserung des Rotorwirkungsgrades zu erreichen, müssen vor allem die kritischen wand- bzw. spaltnahen Bereiche optimal an die Strömungsumgebung angepasst werden. Die vorliegende Arbeit beschreibt ausführlich die theoretischen Grundlagen der Rotorströmung und des Rotorentwurfs. Basierend darauf werden für die Umsetzung eines vollständigen dreidimensionalen Schaufelentwurfs zwei Panelverfahren zur Berechnung der dreidimensionalen jedoch reibungslosen Strömung, zur Lösung der Nachrechen- bzw. der Entwurfsaufgabe, entwickelt. Die Panelverfahren werden angewandt, um eine Methodik für den effektiven Einsatz von Pfeilung, V-Stellung und inverser Skelettlinienberechnung für den dreidimensionalen Rotorentwurf festzulegen. Die gewonnenen Erkenntnisse werden anschließend für den Entwurf eines hochbelasteten Rotors in einem einstufigen Niedergeschwindigkeitsverdichter nach dieser neuen Entwurfsmethodik genutzt. Anhand von Ergebnissen aus Rechnungen und Messungen für diesen Rotor wird die Wirksamkeit des Verfahrens demonstriert. / The recent and future design of axial compressors for aero engines is strongly affected by the aim to generate a high pressure ratio with less stages to increase power and reduce weight to achieve an improved efficiency. This can only be achieved when the stage pressure ratio is raised which leads to increased stage loading. But the higher stage loading results in higher losses caused by stronger secondary flows. This has a negative effect on compressor stability and efficiency. To counteract the negative effects enhanced blade geometries are necessary. With the recently used design methods this is hardly to achieve. For that reason a new method for the three-dimensional design of rotors and stators in axial compressors has been developed. This report summarizes that work. The method accounts for the systematic application of sweep and dihedral as well as the three-dimensional inverse calculation of the camber-line distributions along blade height. To achieve improved efficiency the regions close to the end-walls and the tip and hub gap have to be adapted to the flow environment. The recent report described in detail the theoretical background of the compressor blade flow and compressor blade design. Based on that, two inviscid panel methods for the fully three-dimensional design of compressor blades are described. The panel methods are applied to define a methodology for the effective application of sweep, dihedral and inverse camber-line calculation in a three-dimensional blade design process. Afterwards the findings are used to design a highly-loaded single-stage low-speed research compressor rotor. The validity of the presented design method is proven with CFD and test results.

Additive manufacturing (AM) technology is a key emerging field transforming how customized products with complex shapes are manufactured. AM is the process of layering materials to produce objects from three-dimensional (3D) models. AM technology can be used to print objects with complicated geometries and a broad range of material properties. However, the issue of ensuring the quality of printed products during the process remains an obstacle to industry-level adoption. Furthermore, the characteristics of AM processes typically involve complex process dynamics and interactions between machine parameters and desired qualities. The issues associated with quality assurance in AM processes underscore the need for research into smart quality assurance systems. To study the complex physics behind process interaction challenges in AM processes, this dissertation proposes the development of a data-driven smart quality assurance framework that incorporates in-process sensing and machine learning-based modeling by correlating the relationships among parameters, signatures, and quality. High-fidelity AM simulation data and the increasing use of sensors in AM processes help simulate and monitor the occurrence of defects during a process and open doors for data-driven approaches such as machine learning to make inferences about quality and predict possible failure consequences. To address the research gaps associated with quality assurance for AM processes, this dissertation proposes several data-driven approaches based on the design of experiments (DoE), forward prediction modeling, and an inverse design methodology. The proposed approaches were validated for AM processes such as fused filament fabrication (FFF) using polymer and hydrogel materials and laser powder bed fusion (LPBF) using common metal materials. The following three novel smart quality assurance systems based on a parameter–signature–quality (PSQ) framework are proposed: 1. A customized in-process sensing platform with a DOE-based process optimization approach was proposed to learn and optimize the relationships among process parameters, process signatures, and parts quality during bioprinting processes. This approach was applied to layer porosity quantification and quality assurance for polymer and hydrogel scaffold printing using an FFF process. 2. A data-driven surrogate model that can be informed using high-fidelity physical-based modeling was proposed to develop a parameter–signature–quality framework for the forward prediction problem of estimating the quality of metal additive-printed parts. The framework was applied to residual stress prediction for metal parts based on process parameters and thermal history with reheating effects simulated for the LPBF process. 3. Deep-ensemble-based neural networks with active learning for predicting and recommending a set of optimal process parameter values were developed to optimize optimal process parameter values for achieving the inverse design of desired mechanical responses of final built parts in metal AM processes with fewer training samples. The methodology was applied to metal AM process simulation in which the optimal process parameter values of multiple desired mechanical responses are recommended based on a smaller number of simulation samples. / Doctor of Philosophy / Additive manufacturing (AM) is the process of layering materials to produce objects from three-dimensional (3D) models. AM technology can be used to print objects with complicated geometries and a broad range of material properties. However, the issue of ensuring the quality of printed products during the process remains a challenge to industry-level adoption. Furthermore, the characteristics of AM processes typically involve complex process dynamics and interactions between machine parameters and the desired quality. The issues associated with quality assurance in AM processes underscore the need for research into smart quality assurance systems. To study the complex physics behind process interaction challenges in AM processes, this dissertation proposes a data-driven smart quality assurance framework that incorporates in-process sensing and machine-learning-based modeling by correlating the relationships among process parameters, sensor signatures, and parts quality. Several data-driven approaches based on the design of experiments (DoE), forward prediction modeling, and an inverse design methodology are proposed to address the research gaps associated with implementing a smart quality assurance system for AM processes. The proposed parameter–signature–quality (PSQ) framework was validated using bioprinting and metal AM processes for printing with polymer, hydrogel, and metal materials.

A new approach to the discovery of high absorbing semiconductors for solar cells was taken by working under a set of design principles and taking a systemic methodology. Three transition metal chalcogenides at varying states of development were evaluated within this framework. Iron pyrite (FeS���) is well known to demonstrate excellent absorption, but the coexistence with metallic iron sulfides was found to disrupt its semiconducting properties. Manganese diselenide (MnSe���), a material heavily researched for its magnetic properties, is proposed as a high absorbing alternative to iron pyrite that lacks destructive impurity phases. For the first time, a MnSe��� thin film was synthesized and the optical properties were characterized. Finally, CuTaS���, a known but never characterized material, is also proposed as a high absorbing semiconductor based on the design principles and experimental results. / Graduation date: 2013

<p>The main goal of this thesis research is to expand the range of unique properties of phase transforming cellular materials (PXCMs), a new class of architected materials, and to extend their applicability both in the engineering disciplines and in the medical field. A novel aspect of PXCMs is their unique energy dissipation during loading via a snapping mechanism associated with a geometric transition between one stable configuration to another stable configuration at the unit cell level. Phase transformation is analogous to displacive transformations, such as martensitic transformations in shape memory alloys, with no change in configurational entropy. To accomplish this goal, three problem areas are addressed with the first exploring the effects of length scale as added structural hierarchy on material properties and energy dissipation, the second providing an analysis of the durability of architected materials via a novel additive manufacturing method, and the third, an extension into the medical field. Two examples are provided that demonstrate the effects of length scale as added structural hierarchy on material properties, and a machine learning approach for the feasible design of materials with additional levels of structural hierarchy is presented. A simple design approach coupled with a novel additive manufacturing method is discussed for the design of architected materials with high durability. Lastly, a concept for de-clogging bile stents via a temperature driven, shape-memory mechanism inspired by peristaltic locomotion in the human esophagus is presented.</p>