The acoustic emission technique is an effective way to acquire crack information from material bodies at the microscopic level. Monitoring of the acoustic emission events provides a deeper understanding regarding the structural health status of critical constructions such as bridges, railways, pipelines, pressure vessels, etc. Thanks to the acoustic emission monitoring systems, it is possible to avoid catastrophic events and save lives, time, and money. For this reason, efforts to develop new acoustic emission sensor technologies, as well as the use of current acoustic emission sensors in new research fields, will contribute to the limited literature sources. Optical sensing systems provide good alternatives to the existing sensing technologies because of their wide range of detection bandwidths, adaptation to harsh environments, and low sensitivity to electromagnetic interference. For this reason, the first part of this thesis demonstrates an optoacoustic sensing methodology that enables the detection of acoustic emissions by optics. This sensing system consists of thin-film optical filters (TFOF) and an elastic microcavity layer. The sensing mechanism is similar to the Fabry Perot structures and it relies on resonance shifts of the cavity when there is a change in the cavity thickness similar to the Fabry Perot structures. Thus, the design, fabrication, and demonstration steps of a Fabry Perot elastic microcavity have been presented. Throughout the fabrication efforts, a new deposition protocol was developed. This deposition technique has enabled the deposition of TFOF on flexible substrates via the RF-sputtering technique. Thus, a new sensing configuration has been developed using flexible optical components. In the second chapter, an optical sensing methodology based on tunable spectral filters and flexible optical components is introduced. The design, fabrication, realization, and characterization of a proof-of-concept optomechanical sensor have been presented. The design step includes optical, mechanical, and optoacoustic correlation simulations using the Transfer Matrix Method, finite element analysis, and analytical models. Moreover, the fabrication part includes multilayer deposition on silica and flexible substrates using the RF-Sputtering technique and integration of these optical components into a 3D-printed housing together with electronic components. Eventually, the performance evaluation of the optomechanical sensor has been carried out and the experimental results showed that the sensor resonance frequency is around 515 Hz and the sensor is capable of detecting static loadings from 50 Pa to 235 Pa values. In the fourth chapter, seismic vulnerability analysis of a coupled Tank-Piping System has been performed using traditional acoustic emission sensors. Real-time performance evaluation of the pipeline as well as the structural health status of the critical parts were monitored. As a result, deformation levels of each critical part were investigated, and the processing of acoustic emission signals provided a more in-depth view of damage level of the analyzed components. Throughout the thesis, TFOFs are an integral part of this thesis. Therefore, both the design and simulation of TFOFs play a crucial role throughout this research work. The Transfer Matrix Method is used to simulate the optical performance of TFOFs. Moreover, in the final chapter, an automated design framework is presented for the design of TFOFs using a nature-inspired machine learning approach called Genetic algorithm. This design approach enables the design of sophisticated geometric configurations with unique optical capabilities. Therefore, not only the improvement of sensor response but also the new ways in the development of novel optical systems are demonstrated in this final chapter.

The VT i-Ship Lab has been assigned the task of designing and building a Personal Hydrofoil Craft capable of carrying two people, featuring the distinctive capabilities of foiling and diving. This thesis examines the attributes of fully submerged hydrofoils and their prospective advancements. Diverse configurations of fully submerged hydrofoils are scrutinized, accompanied by an exploration of their respective stability characteristics. A comprehensive analysis is conducted on the design space trade-offs, incorporating potential flow-based methodologies such as the lifting line and vortex lattice methods, encompassing considerations for the free surface, structural computations, and propulsion optimization. In conjunction with the design study computational fluid dynamics is employed to verify the estimated values and to fine-tune the system allowing for a robust low-fidelity system that can quickly estimate the appropriate hydrofoil arrangement for the desired conditions. Various hydrofoil and craft configurations are explored discussing the trade-offs with a final design being chosen and a thorough mechanical design pursued. / Master of Science / The VT i-Ship Lab is conducting research on a watercraft known as a "Personal Hydrofoil Craft." This vehicle is designed to carry two people, glide on the water's surface, and dive underwater. Hydrofoil crafts use specialized underwater wings to reduce resistance and enhance efficiency. Our focus is on fully submerged hydrofoils, studying their stability and efficiency. We employ computer simulations and advanced methods to design and optimize these submerged hydrofoils. The goal is to enhance our understanding of their functionality and performance through real-life experiments. This research has the potential to improve watercraft technology, leading to more efficient and stable boats in the future. By exploring the science behind hydrofoil designs, we aim to contribute valuable insights to the field of water transportation.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25013号 / 工博第5190号 / 新制||工||1991(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 泉井 一浩, 教授 小森 雅晴, 教授 井上 康博 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

This thesis discusses a methodology for probabilistic design optimization of aircraft structures subject to a multidisciplinary set of requirements originating from the desire to minimize structural weight while fulfilling the demands for quality, safety, producibility, and affordability. With this design methodology as the framework, a software is developed, which is capable of performing design optimization of metallic built-up beam structures where the material properties, external load, as well as the structural dimensions are treated as probabilistic random variables. The structural and failure analyses are based on analytical and semi-empirical methods whereas the component reliability analysis is based on advanced first-order second moment method. Metrics-based analytical models are used for the manufacturability analysis of individual parts with the total manufacturing cost estimated using models derived from the manufacturing cost / design guide developed by the Battelle¡¯s Columbus Laboratories. The resulting optimization problem is solved using the method of sequential quadratic programming. A wing spar design optimization problem is used as a demonstrative example including a comparison between non-buckling and buckling web design concepts. A sensitivity analysis is performed and the optimization results are used to highlight the tradeoffs among weight, reliability, and manufacturing cost.

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<p> This thesis contributes significantly towards the development of a robust algorithm for design sensitivity analysis and the optimization of microwave structures. Based on the frequency-domain finite-element method, the approach provides accurate sensitivity information using both 2-D and 3-D formulations. It also significantly accelerates the optimization process.</p> <p> The design sensitivity analysis method greatly influences the efficiency and accuracy of gradient-based optimization by providing the response gradient (response Jacobians) for the whole range of parameter values. However, common commercial electromagnetic simulators provide only specific engineering responses, such as Z- or S-parameters. No sensitivity information is made available for further exploration of the design-parameter space. It is common to compute the design sensitivities from the response themselves using finite-difference or higher-order approximations at the response level. Consequently, for each design parameter of interest, at least one additional full-wave analysis is performed. However, when the number of design parameters becomes large, the simulation time becomes prohibitive for electromagnetic design procedures.</p> <p> The self-adjoint sensitivity analysis (SASA) is so far the most efficient way to extract the sensitivity information for the network parameters with the finite-element method. As an improvement of the adjoint-variable method (AVM), it eliminates the additional (adjoint) system analyses. With one single full-wave analysis, the sensitivities with respect to all design parameters are computed. This significantly improves the efficiency of the sensitivity computations. Through our proposed method, the finite-difference frequency-domain self-adjoint sensitivity analysis (FDFD-SASA), the process is further improved by eliminating the need for exporting the system matrix, thus improving both compatibility and computation time. The only requirement for integrating the sensitivity solver with the commercial EM simulators is the ability to access the field solution at the user-defined grid points. The sensitivity information is obtained by simple manipulation of the field solution as a post-process and hence, it adds little or no overhead to the simulation time.</p> <p> We explore the feasibility of implementing our newly proposed method using field solutions from a frequency-domain commercial solver HFSS v 11. We confirm the accuracy of the FDFD-SASA for shape parameters of metallic structures. Both 2-D and 3-D examples are presented, where the reference results are provided through the traditional finite-difference approximations. Also, the efficiency of the FDFD-SASA is validated by a filter design example, exploiting gradient-based optimization algorithm.</p> / Thesis / Master of Applied Science (MASc)

Through this research, a robust aircraft design methodology is developed for analysis and optimization of the Air Vehicle (AV) segment of Unmanned Aerial Vehicle (UAV) systems. The analysis functionality of the AV design is integrated with a Genetic Algorithm (GA) to form an integrated Multi-disciplinary Design Optimization (MDO) methodology for optimal AV design synthesis. This research fills the gap in integrated subsonic fixed-wing UAV AV MDO methods. No known single methodology captures all of the phenomena of interest over the wide range of UAV families considered here. Key advancements include: 1) parametric Low Reynolds Number (LRN) airfoil aerodynamics formulation, 2) UAV systems mass properties definition, 3) wing structural weight methods, 4) self-optimizing flight performance model, 5) automated geometry algorithms, and 6) optimizer integration. Multiple methods are provided for many disciplines to enable flexibility in functionality, level of detail, computational expediency, and accuracy. The AV design methods are calibrated against the High-Altitude Long-Endurance (HALE) Global Hawk, Medium-Altitude Endurance (MAE) Predator, and Tactical Shadow 200 classes, which exhibit significant variations in mission performance requirements and scale from one another. Technology impacts on the design of the three UAV classes are evaluated from a representative system technology year through 2025. Avionics, subsystems, aerodynamics, design, payloads, propulsion, and structures technology trends are assembled or derived from a variety of sources. The technology investigation serves the purposes of validating the effectiveness of the integrated AV design methods and to highlight design implications of technology insertion through future years. Flight performance, payload performance, and other attributes within a vehicle family are fixed such that the changes in the AV designs represent technology differences alone, and not requirements evolution. The optimizer seeks to minimize AV design gross weight for a given mission requirement and technology set. All three UAV families show significant design gross weight reductions as technology improves. The predicted design gross weight in 2025 for each class is: 1) 12.9% relative to the 1994 Global Hawk, 2) 6.26% relative to the 1994 Predator, and 3) 26.3% relative to the 2000 Shadow 200. The degree of technology improvement and ranking of contributing technologies differs among the vehicle families. The design gross weight is sensitive to technologies that directly affect the non-varying weights for all cases, especially payload and avionics/subsystems technologies. Additionally, the propulsion technology strongly affects the high performance Global Hawk and Predator families, which have high fuel mass fractions relative to the Tactical Shadow 200 family. The overall technology synergy experienced 10-11 years after the initial technology year is 6.68% for Global Hawk, 7.09% for Predator, and 4.22% for the Shadow 200, which means that the technology trends interact favorably in all cases. The Global Hawk and Shadow 200 families exhibited niche behavior, where some vehicles attained higher aerodynamic performance while others attained lower structural mass fractions. The high aerodynamic performance Global Hawk vehicles had high aspect ratio wings with sweep, while the low structural mass fraction vehicles had straight, relatively low aspect ratios and smaller wing spans. The high aerodynamic performance Shadow 200 vehicles had relatively low wing loadings and large wing spans, while the lower structural mass fraction counterparts sought to minimize physical size. / Ph. D.