Organizational Unit:

Daniel Guggenheim School of Aerospace Engineering

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https://hdl.handle.net/1853/70742

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College of Engineering

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Aerospace Design Group

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Aerospace Systems Design Laboratory (ASDL)

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Air Transportation Laboratory

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Cognitive Engineering Center

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Space Systems Design Laboratory (SSDL)

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https://finding-aids.library.gatech.edu/agents/corporate_entities/106

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Publication Search Results

Now showing 1 - 10 of 238

Breakup of liquid droplets

(Georgia Institute of Technology, 2013-12-04) Khare, Prashant

Liquid droplet breakup and dynamics is a phenomena of immense practical importance in a wide variety of applications in science and engineering. Albeit, researchers have been studying this problem for over six decades, the fundamental physics governing droplet deformation and fragmentation is still unknown, not to mention the formulation and development of generalized correlations to predict droplet dynamics. The presence of disparate length and time scales, along with the complex unsteady physics, makes this a formidable problem, theoretically, experimentally and computationally. One of the important applications of interest and the motivation for the current research is a liquid fueled propulsion device, such as diesel, gas turbine or rocket engine. Droplet vaporization and ensuing combustion is accelerated if the droplet size is smaller, which makes any process leading to a reduction in drop size of prime importance in the combustion system design. This thesis is an attempt to address several unanswered questions currently confronting the spray community. Unanswered questions include identification and prediction of breakup modes at varying operating conditions, quantitative description of fundamental processes underlying droplet breakup and generalized correlations for child droplet size distributions and drag coefficient associated with the deformation and fragmentation of Newtonian and non-Newtonian fluids. The present work is aimed at answering the above questions by investigating the detailed flowfield and structure dynamics of liquid droplet breakup process and extracting essential physics governing this complex multiphase phenomena. High-fidelity direct numerical simulations are conducted using a volume-of-fluid (VOF) interface capturing methodology. To isolate the hydrodynamic mechanisms dictating droplet breakup phenomena, evaporation and compressibility are neglected, and numerical studies are performed for incompressible fluids at isothermal conditions. For Newtonian fluids, four different mechanisms are identified- oscillatory, bag, multimode and shear breakup modes. Various events during the deformation and fragmentation process are quantitatively identified and correlations are developed to predict the breakup mechanisms and droplet size distributions for a broad range of operating conditions. It was found that for We > 300 and Oh < 0.1 for rho_l/rho_g = 8.29, the child droplet size distributions can be modeled by a log-normal distribution. A correlation to predict the sauter mean diameter, d32, is also developed, given by d32 / D = 8We^-0.72 / Cd. Temporal evolution of momentum balance and droplet structure are also used to calculate the drag coefficient at each time step from first principles. Results show that the drag coefficient first increases to a maximum as the droplet frontal area increases and then decreases at the initiation of breakup. The drag coefficient reaches a steady value at the end of droplet lifetime, corresponding to the momentum retained by the droplet. A correlation to predict the time-mean drag coefficient given by, Cd / Cd,0 = 2We-^0.175, is developed, which indicates that the time averaged drag coefficient decreases with Weber number. The motivation to study non-Newtonian liquid droplet breakup stems from the various advantages gelled propellants offer as compared to traditional liquid or solid propellants in combustion systems, particularly in rocket engines. It was found that the breakup behavior of pseudoplastic, non-Newtonian liquids is drastically different as compared to Newtonian droplets. Several flow features commonly exhibited by non-Newtonian fluids are observed during the breakup process. The breakup initiates with the formation of beads-in-a-string due to the non-Newtonian nature of the fluid under consideration. This is followed by rapid rotation of the droplet with the appearance of helical instability and liquid budges, which forms the sites for primary and satellite droplet shedding. Child droplet size distribution are also examined and it is found that a Gaussian curve universally characterizes the droplets produced during non-Newtonian droplet breakup process. To put all things in perspective, the objectives of the thesis were two folds: (1) elucidate breakup physics for Newtonian and non-Newtonian liquid droplet deformation and breakup, and (2) develop correlations which can be used in an Eulerian-Lagrangian framework to study large-scale engineering problems. It is hoped that this research contributed to droplet breakup and dynamics literature by providing a more thorough and quantitative understanding of the breakup phenomena of liquid droplets and furnished models which can be used in future research endeavors.
Dynamic modeling of plasma effects during multi-phase detonations near a surface and/or in a magnetic field

(Georgia Institute of Technology, 2013-12) Menon, Suresh ; Schulz, Joseph

A multi-physics model has been developed to simulate detonations and condensed-phase explosions in the presence of an external electromagnetic field. To simulate these effects, models for high-temperature gas physics, plasma-production, dispersed-phase mixing, and turbulence have been implemented within the framework of a numerical method capable of simulating magnetohydrodynamic (MHD) flows. This research has leveraged past work in MHD flows, detonations, and turbulence-chemistry interactions to study multi-scale detonation-plasma-field interactions, and has furthered the understanding of many key physical processes of these flows. This work targeted three main basic science objectives: the study of plasma-production by detonations and condensed-phase explosions, the study of MHD instabilities and turbulence relevant to post-detonation flows, and the study of how a detonation is affected by the presence of a magnetic field. Simulations indicate that gaseous detonation waves generate a weakly ionized plasma in the post-detonation region. The average electrical conductivity in the post-detonation flow, however, is of the order of 10-3 S/m, and practical engineering applications involving the use of MHD forces to manipulate the flow for generation of electrical power, propulsive thrust, etc., require higher levels of electrical conductivity. Simulations of mixtures seeded with particles of a low ionization potential show a substantial increase the flow's electrical conductivity. The presence of these particles can adversely affect the detonation propagation. The physics of how an electromagnetic field interacts with the conducting products of a detonation, and how that interaction might affect the stability and propagation of the detonation wave is systematically studied. The magnetic field applied in the direction of detonation propagation affects the detonation through a combined effect of Joule heating and Lorentz force, in some cases altering the cellular structure of the detonation completely by reducing the half-reaction zone thickness. Basic studies of the Richtmyer-Meshkov instability, an important mechanism for the transition to turbulence in explosions, are used to elucidate several salient features of these types of MHD flows. Namely, simulations show that the presence of a dispersed phase alters the mixing growth-rates of the instability, and furthermore, an applied magnetic field is shown to either suppress or enhance fluid mixing.
A study of premixed, shock-induced combustion with application to hypervelocity flight

(Georgia Institute of Technology, 2013-11-19) Axdahl, Erik Lee

One of the current goals of research in hypersonic, airbreathing propulsion is access to higher Mach numbers. A strong driver of this goal is the desire to integrate a scramjet engine into a transatmospheric vehicle airframe in order to improve performance to low Earth orbit (LEO) or the performance of a semi-global transport. An engine concept designed to access hypervelocity speeds in excess of Mach 10 is the shock-induced combustion ramjet (i.e. shcramjet). This dissertation presents numerical studies simulating the physics of a shcramjet vehicle traveling at hypervelocity speeds with the goal of understanding the physics of fuel injection, wall autoignition mitigation, and combustion instability in this flow regime. This research presents several unique contributions to the literature. First, different classes of injection are compared at the same flow conditions to evaluate their suitability for forebody injection. A novel comparison methodology is presented that allows for a technically defensible means of identifying outperforming concepts. Second, potential wall cooling schemes are identified and simulated in a parametric manner in order to identify promising autoignition mitigation methods. Finally, the presence of instabilities in the shock-induced combustion zone of the flowpath are assessed and the analysis of fundamental physics of blunt-body premixed, shock-induced combustion is accelerated through the reformulation of the Navier Stokes equations into a rapid analysis framework. The usefulness of such a framework for conducting parametric studies is demonstrated.
Robust aircraft subsystem conceptual architecting

(Georgia Institute of Technology, 2013-11-19) Jackson, David Wayne

Aircraft subsystems are key components in modern aircraft, the impact and significance of which have been constantly increasing. Furthermore, the architecture selection of these subsystems has overall system-level effects. Despite the significant effects of architecture selections, existing methods for determining the architecture, especially early in design, are similar to the use of traditional point solutions. Currently, aircraft subsystems are rarely examined during the conceptual design phase, despite the fact that this phase has a significant influence on aircraft cost and performance. For this reason, there is a critical need to examine subsystem architecture trades and investigate the design space during the conceptual design of an aircraft. Traditionally, after the aircraft conceptual design phase, subsystems are developed in a process that begins with the point selection of the architecture, then continues with its development and analysis, and concludes in the detailed development of the subsystems. The choice of the point design of the architecture to be developed can be made using simplified models to explore the design space. This method known as conceptual architecting is explored in this dissertation. This dissertation also focuses on bringing actuation subsystem architecture trades into conceptual design because of the significant cost impact of this design phase and the interdependence of vehicle sizing with the subsystems impact on the aircraft. The extent of these interdependencies is examined and found to be significant. As a result, this coupling must be captured to enable better informed decision making. A methodology to examine the design space of aircraft subsystem architectures during the conceptual design of aircraft, while incorporating this coupling, is presented herein and applied specifically to actuation architectures.
Requirement analysis framework of naval military system for expeditionary warfare

(Georgia Institute of Technology, 2013-11-19) Lee, Hyun Seop

Military systems are getting more complex due to the demands of various types of missions, rapidly evolving technologies, and budgetary constraints. In order to support complex military systems, there is a need to develop a new naval logistic asset that can respond to global missions effectively. This development is based on the requirement which must be satisfice-able within the budgetary constraints, address pressing real world needs, and allow designers to innovate. This research is conducted to produce feasible and viable requirements for naval logistic assets in complex military systems. The process to find these requirements has diverse uncertainties about logistics, environment and missions. To understand and address these uncertainties, this research includes instability analysis, operational analysis, sea state analysis and disembarkation analysis. By the adaptive Monte-Carlo simulation with maximum entropy, uncertainties are considered with corresponding probabilistic distribution. From Monte-Carlo simulation, the concept of Probabilistic Logistic Utility (PLU) was created as a measure of logistic ability. To demonstrate the usability of this research, this procedure is applied to a Medium Exploratory Connector (MEC) which is an Office of Naval Research (ONR) innovative naval prototype. Finally, the preliminary design and multi-criteria decision-making method become capable of including requirements considering uncertainties.
An efficient approach for high-fidelity modeling incorporating contour-based sampling and uncertainty

(Georgia Institute of Technology, 2013-11-18) Crowley, Daniel R.

During the design process for an aerospace vehicle, decision-makers must have an accurate understanding of how each choice will affect the vehicle and its performance. This understanding is based on experiments and, increasingly often, computer models. In general, as a computer model captures a greater number of phenomena, its results become more accurate for a broader range of problems. This improved accuracy typically comes at the cost of significantly increased computational expense per analysis. Although rapid analysis tools have been developed that are sufficient for many design efforts, those tools may not be accurate enough for revolutionary concepts subject to grueling flight conditions such as transonic or supersonic flight and extreme angles of attack. At such conditions, the simplifying assumptions of the rapid tools no longer hold. Accurate analysis of such concepts would require models that do not make those simplifying assumptions, with the corresponding increases in computational effort per analysis. As computational costs rise, exploration of the design space can become exceedingly expensive. If this expense cannot be reduced, decision-makers would be forced to choose between a thorough exploration of the design space using inaccurate models, or the analysis of a sparse set of options using accurate models. This problem is exacerbated as the number of free parameters increases, limiting the number of trades that can be investigated in a given time. In the face of limited resources, it can become critically important that only the most useful experiments be performed, which raises multiple questions: how can the most useful experiments be identified, and how can experimental results be used in the most effective manner? This research effort focuses on identifying and applying techniques which could address these questions. The demonstration problem for this effort was the modeling of a reusable booster vehicle, which would be subject to a wide range of flight conditions while returning to its launch site after staging. Contour-based sampling, an adaptive sampling technique, seeks cases that will improve the prediction accuracy of surrogate models for particular ranges of the responses of interest. In the case of the reusable booster, contour-based sampling was used to emphasize configurations with small pitching moments; the broad design space included many configurations which produced uncontrollable aerodynamic moments for at least one flight condition. By emphasizing designs that were likely to trim over the entire trajectory, contour-based sampling improves the predictive accuracy of surrogate models for such designs while minimizing the number of analyses required. The simplified models mentioned above, although less accurate for extreme flight conditions, can still be useful for analyzing performance at more common flight conditions. The simplified models may also offer insight into trends in the response behavior. Data from these simplified models can be combined with more accurate results to produce useful surrogate models with better accuracy than the simplified models but at less cost than if only expensive analyses were used. Of the data fusion techniques evaluated, Ghoreyshi cokriging was found to be the most effective for the problem at hand. Lastly, uncertainty present in the data was found to negatively affect predictive accuracy of surrogate models. Most surrogate modeling techniques neglect uncertainty in the data and treat all cases as deterministic. This is plausible, especially for data produced by computer analyses which are assumed to be perfectly repeatable and thus truly deterministic. However, a number of sources of uncertainty, such as solver iteration or surrogate model prediction accuracy, can introduce noise to the data. If these sources of uncertainty could be captured and incorporated when surrogate models are trained, the resulting surrogate models would be less susceptible to that noise and correspondingly have better predictive accuracy. This was accomplished in the present effort by capturing the uncertainty information via nuggets added to the Kriging model. By combining these techniques, surrogate models could be created which exhibited better predictive accuracy while selecting the most informative experiments possible. This significantly reduced the computational effort expended compared to a more standard approach using space-filling samples and data from a single source. The relative contributions of each technique were identified, and observations were made pertaining to the most effective way to apply the separate and combined methods.
Computational fluid dynamics and analytical modeling of supersonic retropropulsion flowfield structures across a wide range of potential vehicle configurations

(Georgia Institute of Technology, 2013-11-15) Cordell, Christopher E.

For the past four decades, Mars missions have relied on Viking heritage technology for supersonic descent. Extending the use of propulsion, which is required for Mars subsonic deceleration, into the supersonic regime allows the ability to land larger payload masses. Wind tunnel and computational experiments on subscale supersonic retropropulsion models have shown a complex aerodynamic flow field characterized by the interaction of underexpanded jet plumes exhausting from nozzles on the vehicle with the supersonic freestream. Understanding the impact of vehicle and nozzle configuration on this interaction is critical for analyzing the performance of a supersonic retropropulsion system, as deceleration will have components provided by both the aerodynamic drag of the vehicle and thrust from the nozzles. This investigation focuses on the validity of steady state computational approaches to analyze supersonic retropropulsion flowfield structures and their effect on vehicle aerodynamics. Wind tunnel data for a single nozzle and a multiple nozzle configuration are used to validate a steady state, turbulent computational fluid dynamics approach to modeling supersonic retropropulsion. An analytic approximation to determine plume and bow shock structure in the flow field is also developed, enabling rapid assessment of flowfield structure for use in improved grid generation and as a configuration screening tool. Results for both the computational fluid dynamics and analytic approaches show good agreement with the experimental datasets. Potential limitations of the two methods are identified based on the comparisons with available data. Six additional geometries are defined to investigate the extensibility of the analytical model and determine the variation of supersonic retropropulsion performance with configuration. These validation geometries are split into two categories: three geometries with nozzles located on the vehicle forebody at varying nozzle cant angles, and three geometries with nozzles located on the vehicle aftbody at varying nozzle cant angles and number of nozzles. The forebody nozzle configurations show that nozzle cant angle is a significant driver in performance of a vehicle employing supersonic retropropulsion. Aerodynamic drag preservation for a given thrust level increases with increasing cant angle. However, increasing the cant angle reduces the contribution of thrust to deceleration. The tradeoff between these two contributions to the deceleration force is examined, noting that performance improvements are possible with modest nozzle cant angles. Static pitch stability characteristics are investigated for the lowest and highest cant angle configurations. The aftbody nozzle configuration results show that removing the plume flow from the region forward of the vehicle results in less interaction with the bow shock structure. This impacts aerodynamic performance, as the surface pressure remains relatively undisturbed for all thrust values examined. Static pitch stability characteristics for each of the aftbody nozzle configurations are investigated; noting that supersonic retropropulsion for these configurations exhibits a transition point from static stability to instability as a function of this center of mass location along the axis.
A hybrid probabilistic method to estimate design margin

(Georgia Institute of Technology, 2013-11-15) Robertson, Bradford E.

Weight growth has been a significant factor in nearly every space and launch vehicle development program. In order to account for weight growth, program managers allocate a design margin. However, methods of estimating design margin are not well suited for the task of assigning a design margin for a novel concept. In order to address this problem, a hybrid method of estimating margin is developed. This hybrid method utilizes range estimating, a well-developed method for conducting a bottom-up weight analysis, and a new forecasting technique known as executable morphological analysis. Executable morphological analysis extends morphological analysis in order to extract quantitative information from the morphological field. Specifically, the morphological field is extended by adding attributes (probability and mass impact) to each condition. This extended morphological field is populated with alternate baseline options with corresponding probabilities of occurrence and impact. The overall impact of alternate baseline options can then be estimated by running a Monte Carlo analysis over the extended morphological field. This methodology was applied to two sample problems. First, the historical design changes of the Space Shuttle Orbiter were evaluated utilizing original mass estimates. Additionally, the FAST reference flight system F served as the basis for a complete sample problem; both range estimating and executable morphological analysis were performed utilizing the work breakdown structure created during the conceptual design of this vehicle.
Statistical methods for reconstruction of entry, descent, and landing performance with application to vehicle design

(Georgia Institute of Technology, 2013-11-06) Dutta, Soumyo

There is significant uncertainty in our knowledge of the Martian atmosphere and the aerodynamics of the Mars entry, descent, and landing (EDL) systems. These uncertainties result in conservatism in the design of the EDL vehicles leading to higher system masses and a broad range of performance predictions. Data from flight instrumentation onboard Mars EDL systems can be used to quantify these uncertainties, but the existing dataset is sparse and many parameters of interest have not been previously observable. Many past EDL reconstructions neither utilize statistical information about the uncertainty of the measured data nor quantify the uncertainty of the estimated parameters. Statistical estimation methods can blend together disparate data types to improve the reconstruction of parameters of interest for the vehicle. For example, integrating data obtained from aeroshell-mounted pressure transducers, inertial measurement unit, and radar altimeter can improve the estimates of the trajectory, atmospheric profile, and aerodynamic coefficients, while also quantifying the uncertainty in these estimates. These same statistical methods can be leveraged to improve current engineering models in order to reduce conservatism in future EDL vehicle design. The work in this thesis presents a comprehensive methodology for parameter reconstruction and uncertainty quantification while blending dissimilar Mars EDL datasets. Statistical estimation methods applied include the Extended Kalman Filter, Unscented Kalman Filter, and Adaptive Filter. The estimators are applied in a manner in which the observability of the parameters of interest is maximized while using the sparse, disparate EDL dataset. The methodology is validated with simulated data and then applied to estimate the EDL performance of the 2012 Mars Science Laboratory. The reconstruction methodology is also utilized as a tool for improving vehicle design and reducing design conservatism. A novel method of optimizing the design of future EDL atmospheric data systems is presented by leveraging the reconstruction methodology. The methodology identifies important design trends and the point of diminishing returns of atmospheric data sensors that are critical in improving the reconstruction performance for future EDL vehicles. The impact of the estimation methodology on aerodynamic and atmospheric engineering models is also studied and suggestions are made for future EDL instrumentation.
Inverse estimation methodology for the analysis of aeroheating and thermal protection system data

(Georgia Institute of Technology, 2013-11-06) Mahzari, Milad

Thermal Protection System (TPS) is required to shield an atmospheric entry vehicle against the high surface heating environment experienced during hypersonic flight. There are significant uncertainties in the tools and models currently used for the prediction of entry aeroheating and TPS material thermal response. These uncertainties can be reduced using experimental data. Analysis of TPS ground and flight data has been traditionally performed in a direct fashion. Direct analyses center upon comparison of the computational model predictions to data. Qualitative conclusions about model validity may be drawn based on this comparison and a limited number of model parameters may be iteratively adjusted to obtain a better match between predictions and data. The goal of this thesis is to develop a more rigorous methodology for the estimation of surface heating and TPS material response using inverse estimation theory. Built on theoretical developments made in related fields, this methodology enables the estimation of uncertainties in both the aeroheating environment and material properties from experimental temperature data. Unlike direct methods, the methodology developed here is capable of estimating a large number of independent parameters simultaneously and reconstructing the time-dependent surface heating profile in an automated fashion. This methodology is applied to flight data obtained from thermocouples embedded in the Mars Pathfinder and Mars Science Laboratory entry vehicle heatshields.