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Daniel Guggenheim School of Aerospace Engineering
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ItemEvaluation of Convolutional Neural Networks for Modeling Blast Propagation in Multi-room Bunkers(Georgia Institute of Technology, 2023-12-15) Luo, FelixThe rapid evaluation of blasts in enclosed geometrically complex spaces has long eluded the design of safer blast-resistant structures. Traditional methods of determining blast responses in enclosed geometrically complex spaces oftentimes rely on the use of traditional computational fluid dynamics (CFD) solvers to compute the entire flow field of the structure. This method has an enormous computational burden, especially considering that blasts are highly transient in nature and require the transient pressure fluctuations to be determined to formulate an accurate blast response prediction. However, more efficient methods of blast evaluation are desired such that parametric sweeps or optimization processes can be performed at low cost to provide a tool for iterative design. To rectify this gap in capabilities, a convolutional neural network based (CNN) model was developed to provide rapid blast predictions for 2D structures to establish this capability to aid in the design of more blast resistant structures. This approach leverages the inherent spatial awareness of CNNs to provide predictions for peak pressures since blasts in enclosed spaces are highly dependent on the spatial relationships between blast locations and wall location. This approach provides a nearly 5,000 times speed up against CFD simulations used within this study with good convergence of errors, correlation coefficients, predicted and truth values and distributions in all situational evaluations. These computational advantages, in part, comes from using the CNN based model to directly predict peak pressures whereas traditional CFD solvers require iterations to propagate fluid flows over time. However, some limitations do exist with respect to higher errors, such as model training costs, and the capability to predict 3D structures. Nonetheless, the results provide a characterization of the capabilities CNN based models in predicting peak pressures from blasts in enclosed spaces. From these evaluations and studies, a model which can provide significant computational savings while maintaining a similar accuracy can be obtained, which enables the rapid iterative design of more blast resistant structures.
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ItemReshock Gas Curtain Mixing Study(Georgia Institute of Technology, 2022-06-25) Risley, Karl RobertThe current work investigates the behavior of gas curtain instabilities. A gas curtain can be visualized as an A − B − A domain, where A and B are light and heavy fluids respectively, creating a ”curtain” of heavy fluid B that is surrounded by a light fluid A. Specifically, the behavior of gas curtains following an initial shock passage and the passage of a reflected shock (reshock) through the entirety of the curtain are investigated. A gas curtain instability commonly occurs physically in a wide range of applications such as during afterburning of an explosion, inertial confinement fusion, and even supernovae explosions. Previous studies have emphasized that the physics occurring during the reshock of a gas curtain are far more complex than the behavior of a re-shock Richtmyer-Meshkov Instability, due to the interactions between the two interfaces and wave reverberations occurring. The current work attempts to understand the relationship between a gas curtain’s initial conditions and its behavior to reshock through two-dimensional numerical simulations that utilize the viscous Navier-Stokes equations. More specifically, the current work isolates the effects of the curtain’s initial thickness and shape on the post reshock mixing layer growth rate and molecular mixing of the curtain. The results for all cases indicate that the post-reshock growth rate of the curtain’s width is a function of initial thickness. The sensitivity of the curtain’s post-reshock growth rate to the initial thickness, however, depends on the curtain’s initial perturbation shape. As the initial thickness of the curtain is decreased, the interactions between the curtain’s interfaces grow in strength and impede perturbation growth, thus reducing the post reshock growth rate of the curtain’s structure width. Similarly, the results strongly suggest that a reduction in initial curtain thickness increases the late-time asymptotic molecular mixing fraction value. This result is significant, especially for reacting flows, because it indicates that faster combustion (or afterburning in an explosion) could be reached with the thinning of the gas curtain in flow systems.
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ItemUNCERTAINTY QUANTIFICATION OF DIMP PYROLYSIS KINETICS(Georgia Institute of Technology, 2022-05-13) Patel, PavanTo develop effective explosives and strategies for the rapid destruction of sarin stockpiles, a reliable understanding of sarin’s chemical kinetics is needed. Kinetic mechanisms of sarin simulants such as di-isopropyl methyl phosphonate (DIMP) are developed instead because they have a similar chemical structure as sarin and are less toxic. A detailed DIMP kinetics mechanism has been developed in the past; however, there is a considerable amount of uncertainty surrounding it. This uncertainty manifests through the choice of pathways, and their respective reaction rates, leading to large variations in outcomes predicted through simulations. Out of the many reaction pathways involved in the decomposition of DIMP, the initiating steps are the most crucial. Out of the two possible initiating pathways in the destruction of DIMP, the lower activation energy pathway is dominant for all temperatures. The purpose of this study is to investigate the uncertainties associated with the dominant initiating pathways of the DIMP kinetics mechanism. Propagating rate parameter uncertainties of the dominant pathway through computational models yields large uncertainties in predicting DIMP survivability at different temperatures. The prediction uncertainties are larger at lower temperatures than at high temperatures. This can significantly impact the ability to precisely predict collateral damage caused by partially destroyed DIMP in the far-field of an explosion. After reducing these rate parameter uncertainties, using Bayesian inference, the prediction uncertainties were within reasonable limits. The results here provide a reduced subspace for uncertainties associated with the first and most important step in the breakdown of DIMP, which shall enable more reliable predictions.
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ItemInvestigating Lean Blowout of an Alternative Jet Fuel in a Gas Turbine Combustor(Georgia Institute of Technology, 2022-01-05) Narayanan, VijayIn the global effort to reduce the climate impact of combustion emissions, sustainable aviation fuels offer the ease and reliability of conventional petroleum-derived jet fuels without the significant pollutant effects. Ongoing research efforts include experimental testing of alternative jet fuels to identify fuel candidates that produce less pollutant combustion products and are cheaper and environmentally cleaner to source than conventional jet fuels. Fuel lean combustion already reduces the emissions of jet engines and increases fuel efficiency, but lean blowout (LBO) can occur at reduced throttle and minimum power scenarios such as descent. Lean blowout (LBO) has been identified as a critical figure of merit to ensure the stability of alternative jet fuels in the place of conventional fuels. This work aimed to further understand the LBO phenomenon, leveraging computational studies of the alternative fuel designated C-5 by the National Jet Fuel Combustion Program (NJFCP). The fuel sensitivity of LBO has been established by the NJFCP’s participants recently. In this thesis, the chemical kinetics for C-5 is first verified using zerodimensional (0-D) and one-dimensional (1-D) studies and then this is followed by three dimensional (3D) large-eddy simulations (LES). In LES to observe LBO, a direct-step and gradual equivalence ratio reduction were separately employed to assess fuel sensitivity of LBO against available experimental data. The time histories of pressure, temperature, and composition were analyzed for precursor signatures of LBO both inside and outside the flame. Localized extinction, a reduction in the vortex breakdown bubble size and magnitude, and a reduction in the exhaust velocity were all observed to occur during the LBO event.
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ItemLES of Turbulent Premixed Flame Kernel Formation and Development(Georgia Institute of Technology, 2020-12-17) Lambert, AlexanderSpark ignition of flammable mixtures is highly sensitive to early and local conditions. Kernel formation and subsequent flame development are largely governed by turbulent conditions and interactions with igniter geometry. In order to investigate this phenomenon, the use of Large Eddy Simulation (LES) is examined for (1) modelling spherical turbulent flame development, and (2) simulating spark ignition in a channel with either laminar or turbulent inflow. A comparison between LES spherical flame simulation is made to FSD-LES results as well as experimental measurements from previous studies. For spark ignition experiments, we characterize the temporal evolution of the ignition process, and demonstrate the dependence on early velocity fluctuations and local conditions.