Propulsion systems are exposed to a variety of foreign objects that can significantly damage or impact their performance. These threats can range from severe dangers such as sandstorms and volcanic eruptions, which can induce engine failure in minutes, to condensation and moisture during ground tests that can negatively impact the engine's fuel efficiency. While numerous computational and experimental studies have investigated the effects of particle ingestion on the component level, an accurate in-situ measurement technique is needed for a systematic understanding of the effects and real-time engine health monitoring. Optical measurement techniques are attractive for this application due to their non-intrusive nature. However, conventional optical particle measurement methods assume the particle to be spherical, which introduces large errors for measuring particles with complex and irregular shapes, such as sand, volcanic ash, and ice crystals. The light-particle interaction contains information on the desired parameters, such as particle shape and size. The research presented in this dissertation uses this idea for a novel particle sensor concept. Scattering and extinction of light by particles are chosen as crucial features that can identify the particle as its unique signature. Numerical tools are used to simulate the scattering and extinction for particles the sensor is expected to encounter. Machine learning models are trained using the data to use scattering and extinction as inputs and estimate the particle parameters. Different types and applications of supervised machine learning models were investigated, including a layered approach with numerous models and a generalized approach with a single neural network. The particle sensor is first demonstrated using data found in the literature. This study confirmed the importance of non-spherical particles in the library to guide the machine learning models. Further demonstrations are made at a full engine and wind tunnel scale to measure injected condensation and sand sprays, respectively. The mass flow rates of the ingested material were calculated using the model outputs and validated. / Doctor of Philosophy / Foreign objects ingested into gas turbines can cause serious damage and degrade their performance. Threats can range from sand, dust, and volcanic ash to condensation on ground and high altitude ice crystals. On the component level, experiments and simulations have been performed to establish the performance decrease and risks to continued operations. However, there is a need for a real-time and non-intrusive measurement technique for the ingested mass. While there are established optical methods applicable for this use, these existing methods assume the particle shape to be spherical. The light-particle interaction contains information on the desired parameters, such as particle shape and size. Optical measurements of these interactions, such as scattering and extinction, can serve as "fingerprints" that can be used to estimate particle parameters. A novel particle measurement technique utilizing supervised machine learning models is presented. The models are trained using a library containing numerically calculated scattering and extinction data. Laser scattering and extinction measurements are used as inputs for the models. This new technique is first demonstrated by sizing particles found in a particle scattering database in the literature. The method's versatility and ruggedness are then demonstrated by accurately estimating the volume flow rate of a spray nozzle spraying water into a research engine. Additionally, the mass flow of sand particles is measured using this technique in a high-speed wind tunnel, in a similar environment to an engine inlet.

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Aircraft propulsion systems can be exposed to a variety of solid particulates while operating in either arid or other hazardous environments. For conventional takeoff and landing aircraft, debris can be ingested directly into the gas turbine powerplant which is exposed to the ambient environment. For helicopters and other vertical takeoff and landing (VTOL) aircraft, rotor down wash presents a particular threat during takeoff and landing operations as significant amounts of groundlevel particles can be entrained in the surrounding air and subsequently ingested into the engine. Prolonged exposure to particle ingestion events leads to premature engine wear and, in extreme cases, rapid engine failure. Expanding our current understanding of these events is the first step to enabling engine manufacturers to mitigate these damage mechanisms through novel engine designs. The work described in this dissertation is aimed at increasing the scientific understanding of these ingestion events through the development of two distinct diagnostic instruments. First, an anisokinetic particle sampling probe is designed to be used for in-situ particle sampling inside of a gas turbine engine compressor. Offtake of particles during engine operation in dusty conditions will provide researchers with an improved understanding of particle breakage tendency and component erosion susceptibility. Both experimental and numerical investigations of the probe present a comprehensive realization of probe performance characteristics. Secondly, a novel particle visualization technique is developed to provide users with particle distribution and particle mass flow estimates at the inlet of a gas turbine engine. This technique yields both time-resolved and time-averaged quantities, allowing users to have a comprehensive account of particles entering the engine. / Doctor of Philosophy / Foreign debris ingested into aircraft engines can cause serious damage and degrade their performance. The source of these ingested particles may be from atmospherically suspended ash due to volcanic eruption, high altitude ice crystals, or ground-level sand and dust. Both conventional takeoff and landing aircraft and vertical takeoff and landing (VTOL) aircraft are at risk. In extreme cases, exposure to a particle-laden atmosphere has resulted in catastrophic engine failure and loss of life. For this reason, researchers are intensely focused on mitigating the effects of these harmful particulates. The work described in this dissertation establishes two novel diagnostic capabilities. These are aimed at providing the research community with an increased understanding of how particles enter an aircraft powerplant as well as describe the behavior of these particles as they traverse the initial stages of an engine. The first instrument described is a particle sampling probe which is meant to be inserted into the compressor section of a gas turbine engine. This probe will offtake particles as they enter the engine after they have had an opportunity to interact with the rotating components of the compressor. In doing so, researchers gain an improved understanding of particle breakage tendency and component erosion susceptibility. The second instrument provides a snapshot of particle distribution at the inlet of the engine as well as estimates of total particle mass flow. This capability allows researchers to have a precise understanding of the quantity of ingested material as well as a qualitative understanding of how the inflow distribution of particles looks. Each of the developed tools represent a first step to enabling engine manufacturers to mitigate these damage mechanisms through novel engine designs.

abstract: Structural stability and performance of structural materials is important for energy production, whether renewable or non renewable, to have uninterrupted energy supply, that is economically feasible and safe. High temperature metallic materials used in the turbines of AORA, an Israel-based clean energy producer, often experience high temperature, high stress and foreign object damage (FOD). In this study, efforts were made to study the effects of FOD on the fatigue life of these materials and to understand their failure mechanisms. The foreign objects/debris recovered by AORA were characterized using Powder X-ray Diffraction (XRD) and Energy Dispersive Spectroscopy (EDS) to identify composition and phases. To perform foreign object damage experiment a gas gun was built and results of XRD and EDS were used to select particles to mimic FOD in lab experiments for two materials of interest to AORA: Hastelloy X and SS 347. Electron Backscattering Diffraction, hardness and tensile tests were also performed to characterize microstructure and mechanical properties. Fatigue tests using at high temperature were performed on dog bone samples with and without FOD and the fracture surfaces and well as the regions affected by FOD were analyzed using Scanning Electron Microscopy (SEM) to understand the failure mechanism. The findings of these study indicate that FOD is causing multiple secondary cracks at and around the impact sites, which can potentially grow to coalesce and remove pieces of material, and the multisite damage could also lead to lower fatigue lives, despite the fact that the FOD site was not always the most favorable for initiation of the fatal fatigue crack. It was also seen by the effect of FOD on fatigue life that SS 347 is more susceptible to FOD than Hastelloy X. / Dissertation/Thesis / Masters Thesis Materials Science and Engineering 2016