Doctoral Dissertations

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4D combustion and flow diagnostics based on tomographic chemiluminescence (TC) and volumetric laser-induced fluorescence (VLIF)
Wu, Yue (Virginia Tech, 2016-12-02)
Optical diagnostics have become indispensable tools for the study of turbulent flows and flames. However, optical diagnostics developed in the past have been primarily limited to measurements at a point, along a line, or across a two-dimensional (2D) plane; while turbulent flows and flames are inherently four-dimensional (three-dimensional in space and transient in time). As a result, diagnostic techniques which can provide 4D measurement have been long desired. The purpose of this dissertation is to investigate two of such 4D diagnostics both for the fundamental study of turbulent flow and combustion processes and also for the applied research of practical devices. These two diagnostics are respectively code named tomographic chemiluminescence (TC) and volumetric laser induced fluorescence (VLIF). For the TC technique, the emission of light as the result of combustion (i.e. chemiluminescence) is firstly recorded by multiple cameras placed at different orientations. A numerical algorithm is then applied on the data recorded to reconstruct the 4D flame structure. For the VLIF technique, a laser is used to excite a specific species in the flow or flame. The excited species then de-excite to emit light at a wavelength longer than the laser wavelength. The emitted light is then captured by optical sensors and again, the numerical algorithm is applied to reconstruct the flow or flame structure. This dissertation describes the numerical and experimental validation of these two techniques, and explores their capabilities and limitations. It is expected that the results obtained in this dissertation lay the groundwork for further development and expanded application of 4D diagnostics for the study of turbulent flows and combustion processes.
Accelerating a Coupled SPH-FEM Solver through Heterogeneous Computing for use in Fluid-Structure Interaction Problems
Gilbert, John Nicholas (Virginia Tech, 2015-06-08)
This work presents a partitioned approach to simulating free-surface flow interaction with hyper-elastic structures in which a smoothed particle hydrodynamics (SPH) solver is coupled with a finite-element (FEM) solver. SPH is a mesh-free, Lagrangian numerical technique frequently employed to study physical phenomena involving large deformations, such as fragmentation or breaking waves. As a mesh-free Lagrangian method, SPH makes an attractive alternative to traditional grid-based methods for modeling free-surface flows and/or problems with rapid deformations where frequent re-meshing and additional free-surface tracking algorithms are non-trivial. This work continues and extends the earlier coupled 2D SPH-FEM approach of Yang et al. [1,2] by linking a double-precision GPU implementation of a 3D weakly compressible SPH formulation [3] with the open source finite element software Code_Aster [4]. Using this approach, the fluid domain is evolved on the GPU, while the CPU updates the structural domain. Finally, the partitioned solutions are coupled using a traditional staggered algorithm.
Accelerating Conceptual Design Analysis of Marine Vehicles through Deep Learning
Jones, Matthew Cecil (Virginia Tech, 2019-05-02)
Evaluation of the flow field imparted by a marine vehicle reveals the underlying efficiency and performance. However, the relationship between precise design features and their impact on the flow field is not well characterized. The goal of this work is first, to investigate the thermally-stratified near field of a self-propelled marine vehicle to identify the significance of propulsion and hull-form design decisions, and second, to develop a functional mapping between an arbitrary vehicle design and its associated flow field to accelerate the design analysis process. The unsteady Reynolds-Averaged Navier-Stokes equations are solved to compute near-field wake profiles, showing good agreement to experimental data and providing a balance between simulation fidelity and numerical cost, given the database of cases considered. Machine learning through convolutional networks is employed to discover the relationship between vehicle geometries and their associated flow fields with two distinct deep-learning networks. The first network directly maps explicitly-specified geometric design parameters to their corresponding flow fields. The second network considers the vehicle geometries themselves as tensors of geometric volume fractions to implicitly-learn the underlying parameter space. Once trained, both networks effectively generate realistic flow fields, accelerating the design analysis from a process that takes days to one that takes a fraction of a second. The implicit-parameter network successfully learns the underlying parameter space for geometries within the scope of the training data, showing comparable performance to the explicit-parameter network. With additions to the size and variability of the training database, this network has the potential to abstractly generalize the design space for arbitrary geometric inputs, even those beyond the scope of the training data.
Accelerating Structural Design and Optimization using Machine Learning
Singh, Karanpreet (Virginia Tech, 2020-01-13)
Machine learning techniques promise to greatly accelerate structural design and optimization. In this thesis, deep learning and active learning techniques are applied to different non-convex structural optimization problems. Finite Element Analysis (FEA) based standard optimization methods for aircraft panels with bio-inspired curvilinear stiffeners are computationally expensive. The main reason for employing many of these standard optimization methods is the ease of their integration with FEA. However, each optimization requires multiple computationally expensive FEA evaluations, making their use impractical at times. To accelerate optimization, the use of Deep Neural Networks (DNNs) is proposed to approximate the FEA buckling response. The results show that DNNs obtained an accuracy of 95% for evaluating the buckling load. The DNN accelerated the optimization by a factor of nearly 200. The presented work demonstrates the potential of DNN-based machine learning algorithms for accelerating the optimization of bio-inspired curvilinearly stiffened panels. But, the approach could have disadvantages for being only specific to similar structural design problems, and requiring large datasets for DNNs training. An adaptive machine learning technique called active learning is used in this thesis to accelerate the evolutionary optimization of complex structures. The active learner helps the Genetic Algorithms (GA) by predicting if the possible design is going to satisfy the required constraints or not. The approach does not need a trained surrogate model prior to the optimization. The active learner adaptively improve its own accuracy during the optimization for saving the required number of FEA evaluations. The results show that the approach has the potential to reduce the total required FEA evaluations by more than 50%. Lastly, the machine learning is used to make recommendations for modeling choices while analyzing a structure using FEA. The decisions about the selection of appropriate modeling techniques are usually based on an analyst's judgement based upon their knowledge and intuition from past experience. The machine learning-based approach provides recommendations within seconds, thus, saving significant computational resources for making accurate design choices.
Accuracy analysis of the semi-analytical method for shape sensitivity analysis
Barthelemy, Bruno (Virginia Polytechnic Institute and State University, 1987)
The semi-analytical method, widely used for calculating derivatives of static response with respect to design variables for structures modeled by finite elements, is studied in this research. The research shows that the method can have serious accuracy problems for shape design variables in structures modeled by beam, plate, truss, frame, and solid elements. Local and global indices are developed to test the accuracy of the semi-analytical method. The local indices provide insight into the problem of large errors for the semi-analytical method. Local error magnification indices are developed for beam and plane truss structures, and several examples showing the severity of the problem are presented. The global index provides us with a general method for checking the accuracy of the semi-analytical method for any type of model. It characterizes the difference in errors between a general finite-difference method and the semi-analytical method. Moreover, a method improving the accuracy of the semi-analytical method (when possible) is provided. Examples are presented showing the use of the global index.
Acoustic scattering analysis for remote sensing of manganese nodules
Ma, Yushieh (Virginia Polytechnic Institute and State University, 1982)
The theory of the scattering of plane waves in a fluid medium by an isotropic elastic sphere representing a manganese nodule is developed. Scattering cross sections were computed using the theory and the results are presented graphically. The scattering cross section and the reflectivity factor govern the characteristic acoustic signature of the Pacific where manganese nodules are present. Preliminary experimental data for the compressional and shear wave speeds in nodule material is given. This data was used in the scattering computations. Limiting cases of Rayleigh scattering and scattering from fixed rigid and fluid spheres are also shown for comparison. It is shown that the rigidity of the nodules dominates the high frequency response. The problem of the multiple scattering of acoustic waves by randomly distributed nodules on the flat ocean bottom is investigated analytically. The statistical description of nodule deposits is given. The concept of the configurational average is introduced in order to obtain the average scattered response. The size averaging is found to be able to smooth the acoustic response in the high frequency region. The plane wave analysis for the multiple scattering problem is justified by the narrow beam investigation. It shows that the beam effect on the average backscattered field can be neglected in the remote sensing. For a planar distribution of nodules, the average scattered field excited by a normally incident plane wave is verified to be plane waves characterized by coherent reflection and transmission coefficients. The multiple scattering effect is found to be a higher order correction to the average scattered field. For a sparse distribution of nodules, the average scattered field can be well evaluated using the single scattering theory in which the scattering process is also shown to be energy conserved. For a dense distribution of nodules, the radial distribution function is used in the Foldy-Lax hierarchy. The result shows that the pair correlation affects the phase of the second order correction term in the expression for the average scattered field when the higher order statistics are truncated using the quasi crystalline approximation.
Acoustic Tomography and Thrust Estimation on Turbofan Engines
Gillespie, John Lawrie (Virginia Tech, 2023-12-21)
Acoustic sensing provides a possibility of measuring propulsion flow fields non-intrusively, and is of great interest because it may be applicable to cases that are difficult to measure with traditional methods. In this work, some of the successes and limitations of this technique are considered. In the first main result, the acoustic time of flight is shown to be usable along with a calibration curve in order to accurately estimate the thrust of two turbofan engines (1.0-1.5%). In the second, it is shown that acoustic tomography methods that only use the first ray paths to arrive cannot distinguish some relevant propulsion flow fields (i.e., different flow fields can have the same times of flight). In the third result we demonstrate, via the first validated acoustic tomography experiment on a turbofan engine, that a reasonable estimate of the flow can be produced despite this challenge. This is also the first successful use of acoustic tomography to reconstruct a compressible, multi-stream flow.
An active-constraint logic for nonlinear programming
Das, Alok (Virginia Polytechnic Institute and State University, 1982)
The choice of active-constraint logic for screening inequalities has a major impact on the performance of gradient-projection method. It has been found that least-constrained strategies, which keep the number of constraints in the active set as small as possible, are computationally most efficient. However, these strategies are often prone to cycling of constraints between active and inactive status. This occurs mainly due to the violation of some of the constraints, taken as inactive, by the resulting step. This research develops methods for choosing an active set such that constraints in the active set satisfy the Kuhn-Tucker conditions and the resulting step does not violate the linear approximations to any of the constraints satisfied as equalities but considered inactive. Some of the existing active-constraint logics, specifically the dual-violator rule, yield the desired active set when two constraints are satisfied as equalities. However, when three or more constraints are satisfied as equalities, none of the existing logics give the desired active set. A number of general results, which help in the selection of the active set, have been developed in this research. An active-constraint logic has been developed for the case of three constraints. This logic gives the desired active-set. For the general case, when more than three constraints are satisfied as equalities, a separate active-set logic is suggested. This guarantees the nonviolation of the linear approximations to any of the constraints, taken as inactive, by the resulting step. The resulting active-set may not, however, satisfy the Kuhn-Tucker conditions. The efficiency of the proposed logic was tested computationally using quadratic programming problems. Three existing active-set strategies were used for comparision. The proposed logic almost always performed as well or better than the best among the three existing active-set strategies.
Adaptive Controller Development and Evaluation for a 6DOF Controllable Multirotor
Furgiuele, Theresa Chung Wai (Virginia Tech, 2022-10-03)
The omnicopter is a small unmanned aerial vehicle capable of executing decoupled translational and rotational motion (six degree of freedom, 6DOF, motion). The development of controllers for various 6DOF controllable multirotors has been much more limited than development for quadrotors, which makes selecting a controller for a 6DOF multirotor difficult. The omnicopter is subject to various uncertainties and disturbances from hardware changes, structural dynamics, and airflow, making adaptive controllers particularly interesting to investigate. The goal of this research is to design and evaluate the performance of various position and attitude controller combinations for the omnicopter, specifically focusing on adaptive controllers. Simulations are first used to compare combinations of three position controllers, PID, model reference adaptive control, augmented model reference adaptive control (aMRAC), and four attitude controllers, PI/feedback linearization (PIFL), augmented model reference adaptive control, backstepping, and adaptive backstepping (aBack). For the simulations, the omnicopter is commanded to point at and track a stationary aim point as it travels along a $C^0$ continuous trajectory and a trajectory that is $C^1$ continuous. The controllers are stressed by random disturbances and the addition of an unaccounted for suspended mass. The augmented model reference adaptive controller for position control paired with the adaptive backstepping controller for attitude control is shown to be the best controller combination for tracking various trajectories while subject to disturbances. Based on the simulation results, the PID/PIFL and aMRAC/aBack controllers are selected to be compared during three different flight tests. The first flight test is on a $C^1$ continuous trajectory while the omnicopter is commanded to point at and track a stationary aim point. The second flight test is a hover with an unmodeled added weight, and the third is a circular trajectory with a broken blade. As with the simulation results, the adaptive controller is shown to yield better performance than the nonadaptive controller for all scenarios, particularly for position tracking. With an added weight or a broken propeller, the adaptive attitude controller struggles to return to level flight, but is capable of maintaining steady flight when the nonadaptive controller tends to fail. Finally, while model reference adaptive controllers are shown to be effective, their nonlinearity can make them difficult to tune and certify via standard certification methods, such as gain and phase margin. A method for using time delay margin estimates, a potential certification metric, to tune the adaptive parameter tuning gain matrix is shown to be useful when applied to an augmented MRAC controller for a quadrotor.
Additive Manufacturing in Spacecraft Design and In-Space Robotic Fabrication of Large Structures
Spicer, Randy Lee (Virginia Tech, 2023-08-31)
Additive Manufacturing (AM, 3D printing) has made significant advancements over the past decade and has become a viable alternative to traditional machining techniques. AM offers several advantages over traditional manufacturing techniques including improved geometric freedom, reduction in part lead time, cost savings, enhanced customization, mass reduction, part elimination, and remote production. There are many different AM processes with the most commonly used process being Fused Filament Fabrication (FFF). Small satellites have also made significant advancements over the past two decades with the number of missions launched annually increased by orders of magnitude over that time span. Small satellites offer several advantages compared to traditional spacecraft architectures including increased access to space, lower development costs, and disaggregated architectures. On-orbit manufacturing and assembly have become major research and development topics for government and commercial entities seeking the capability to build very large structures in space. AM is well suited on-orbit manufacturing since the process is highly automated, produces little material waste, and allows for a large degree of geometric freedom. This dissertation seeks to address three major research objectives regarding applications of additive manufacturing in space systems: demonstrate the feasibility of 3D printing an ESPA class satellite using FFF, develop a FFF 3D printer that is capable of operating in high vacuum and characterize its performance, and analyze the coupled dynamics between a satellite and a robot arm used for 3D printing in-space. This dissertation presents the design, finite element analysis, dynamic testing, and model correlation of AdditiveSat, an additively manufactured small satellite fabricated using FFF. This dissertation also presents the design, analysis, and test results for a passively cooled FFF 3D printer capable of manufacturing parts out of engineering grade thermoplastics in the vacuum of space. Finally, this dissertation presents a numerical model of a free-flying small satellite with an attached robotic arm assembly to simulate 3D printing structures on-orbit with analysis of the satellite controls required to control the dynamics of the highly coupled system.
Advanced Instrumentation and Measurements Techniques for Near Surface Flows
Cadel, Daniel R. (Virginia Tech, 2016-09-20)
The development of aerodynamic boundary layers on wind turbine blades is an important consideration in their performance. It can be quite challenging to replicate full scale conditions in laboratory experiments, and advanced diagnostics become valuable in providing data not available from traditional means. A new variant of Doppler global velocimetry (DGV) known as cross-correlation DGV is developed to measure boundary layer profiles on a wind turbine blade airfoil in the large scale Virginia Tech Stability Wind Tunnel. The instrument provides mean velocity vectors with reduced sensitivity to external conditions, a velocity measurement range from 0ms^-1 to over 3000ms^-1, and an absolute uncertainty. Monte Carlo simulations with synthetic signals reveal that the processing routine approaches the Cramér-Rao lower bound in optimized conditions. A custom probe-beam technique is implanted to eliminate laser flare for measuring boundary layer profiles on a DU96-W-180 wind turbine airfoil model. Agreement is seen with laser Doppler velocimetry data within the uncertainty estimated for the DGV profile. Lessons learned from the near-wall flow diagnostics development were applied to a novel benchmark model problem incorporating the relevant physical mechanisms of the high amplitude periodic turbulent flow experienced by turbine blades in the field. The model problem is developed for experimentally motivated computational model development. A circular cylinder generates a periodic turbulent wake, in which a NACA 63215b airfoil with a chord Reynolds number Re_c = 170, 000 is embedded for a reduced frequency k = (pi)fc/V = 1.53. Measurements are performed with particle image velocimetry on the airfoil suction side and in highly magnified planes within the boundary layer. Outside of the viscous region, the Reynolds stress profile is consistent with the prediction of Rapid Distortion Theory (RDT), confirming that the redistribution of normal stresses is an inviscid effect. The fluctuating component of the phase- averaged turbulent boundary layer profiles is described using the exact solution to laminar Stokes flow. A phase lag similar to that in laminar flow is observed with an additional constant phase layer in the buffer region. The phase lag is relevant for modeling the intermittent transition and separation expected at full scale.
Advanced Linear Model Predictive Control For Helicopter Shipboard Maneuvers
Greer, William Bryce (Virginia Tech, 2019-10-22)
This dissertation focuses on implementing and analyzing advanced methods of model predictive control to control helicopters into stable flight near a ship and perform a soft touchdown from that state. A shrinking horizon model predictive control method is presented which can target specific states at specific times and take into account several important factors during landing. This controller is then used in simulation to perform a touchdown maneuver on a ship for a helicopter by targeting a landed state at a specific time. Increasing levels of fidelity are considered in the simulations. Computational power required reduces the closer the helicopter starts to the landing pad. An infinite horizon model predictive controller which allows simultaneous cost on state tracking, control energy, and control rates and allows tracking of an arbitrary equilibrium to infinity is then presented. It is applied in simulation to control a helicopter initially in a random flight condition far from a ship to slowly transition to stable flight near the ship, holding an arbitrary rough position relative to the ship indefinitely at the end. Three different target positions are simulated. This infinite horizon control method can be used to prepare for landing procedures that desire starting with the helicopter in some specific position in close proximity to the landing pad, such as the finite horizon method of landing control described previously which should start with the helicopter close to the ship to reduce computation power required. A method of constructing a landing envelope is then presented and used to construct a landing envelope for the finite horizon landing controller. A pre-existing method of combining linear controllers to account for nonlinearity is then slightly modified and used on implementations of the finite horizon landing controller to make a control that takes into account some of the nonlinearity of the problem. This control is tested in simulation.
Advancements of Stepped Planing Hulls
Lee, Evan Joseph (Virginia Tech, 2014-12-09)
The straight line calm water performance of stepped planing hulls has been studied experimentally, by prediction method, and numerically. A model test was conducted to provide a systematic understanding of the effects that displacement and step location have on the performance of a stepped planing hull. Ten different step configurations were tested at three different displacements and over a range of four different speeds in calm water. Seven of these configurations were tested at two different Longitudinal Center of Gravity (LCG) locations. Of all the configurations tested, the stepped hull configurations showed reduced resistance compared to the unstepped hull. The configurations with the largest step height aft showed the least amount of resistance over the speed range tested. Increasing displacement and shifting LCG had similar effects on craft performance for both stepped and unstepped hulls. The current stepped hull prediction method was expanded to include a three dimension wave profile and the ability for the stagnation line to cross the step. Using previous model test data and existing two dimension wave profile equations, a single equation was developed to predict the three dimension wave profile aft of a step. Formulations were added to Savitsky's planing prediction method to include very high speed craft and chines dry conditions. Lastly, two simulations were performed using two computational fluid dynamics numerical tools, OpenFOAM, and NFA. The results of these simulations were compared to the experimental test results to assess each code's relative strengths and weaknesses for use in detail design of stepped planing craft.
Advances in Aero-Propulsive Modeling for Fixed-Wing and eVTOL Aircraft Using Experimental Data
Simmons, Benjamin Mason (Virginia Tech, 2023-07-09)
Small unmanned aircraft and electric vertical takeoff and landing (eVTOL) aircraft have recently emerged as vehicles able to perform new missions and stimulate future air transportation methods. This dissertation presents several system identification research advancements for these modern aircraft configurations enabling accurate mathematical model development for flight dynamics simulations based on wind-tunnel and flight-test data. The first part of the dissertation focuses on advances in flight-test system identification methods using small, fixed-wing, remotely-piloted, electric, propeller-driven aircraft. A generalized approach for flight dynamics model development for small fixed-wing aircraft from flight data is described and is followed by presentation of novel flight-test system identification applications, including: aero-propulsive model development for propeller aircraft and nonlinear dynamic model identification without mass properties. The second part of the dissertation builds on established fixed-wing and rotary-wing aircraft system identification methods to develop modeling strategies for transitioning, distributed propulsion, eVTOL aircraft. Novel wind-tunnel experiment designs and aero-propulsive modeling approaches are developed using a subscale, tandem tilt-wing, eVTOL aircraft, leveraging design of experiments and response surface methodology techniques. Additionally, a method applying orthogonal phase-optimized multisine input excitations to aircraft control effectors in wind-tunnel testing is developed to improve test efficiency and identified model utility. Finally, the culmination of this dissertation is synthesis of the techniques described throughout the document to form a flight-test system identification approach for eVTOL aircraft that is demonstrated using a high-fidelity flight dynamics simulation. The research findings highlighted throughout the dissertation constitute substantial progress in efficient empirical aircraft modeling strategies that are applicable to many current and future aeronautical vehicles enabling accurate flight simulation development, which can subsequently be used to foster advancement in many other pertinent technology areas.
Advances In Computational Fluid Dynamics: Turbulent Separated Flows And Transonic Potential Flows
Neel, Reece E. (Virginia Tech, 1997-06-06)
Computational solutions are presented for flows ranging from incompressible viscous flows to inviscid transonic flows. The viscous flow problems are solved using the incompressible Navier-Stokes equations while the inviscid solutions are attained using the full potential equation. Results for the viscous flow problems focus on turbulence modeling when separation is present. The main focus for the inviscid results is the development of an unstructured solution algorithm. The subject dealing with turbulence modeling for separated flows is discussed first. Two different test cases are presented. The first flow is a low-speed converging-diverging duct with a rapid expansion, creating a large separated flow region. The second case is the flow around a stationary hydrofoil subject to small, oscillating hydrofoils. Both cases are computed first in a steady state environment, and then with unsteady flow conditions imposed. A special characteristic of the two problems being studied is the presence of strong adverse pressure gradients leading to flow detachment and separation. For the flows with separation, numerical solutions are obtained by solving the incompressible Navier-Stokes equations. These equations are solved in a time accurate manner using the method of artificial compressibility. The algorithm used is a finite volume, upwind differencing scheme based on flux-difference splitting of the convective terms. The Johnson and King turbulence model is employed for modeling the turbulent flow. Modifications to the Johnson and King turbulence model are also suggested. These changes to the model focus mainly on the normal stress production of energy and the strong adverse pressure gradient associated with separating flows. The performance of the Johnson and King model and its modifications, along with the Baldwin-Lomax model, are presented in the results. The modifications had an impact on moving the flow detachment location further downstream, and increased the sensitivity of the boundary layer profile to unsteady flow conditions. Following this discussion is the numerical solution of the full potential equation. The full potential equation assumes inviscid, irrotational flow and can be applied to problems where viscous effects are small compared to the inviscid flow field and weak normal shocks. The development of a code is presented which solves the full potential equation in a finite volume, cell centered formulation. The unique feature about this code is that solutions are attained on unstructured grids. Solutions are computed in either two or three dimensions. The grid has the flexibility of being made up of tetrahedra, hexahedra, or prisms. The flow regime spans from low subsonic speeds up to transonic flows. For transonic problems, the density is upwinded using a density biasing technique. If lift is being produced, the Kutta-Joukowski condition is enforced for circulation. An implicit algorithm is employed based upon the Generalized Minimum Residual method. To accelerate convergence, the Generalized Minimum Residual method is preconditioned. These and other problems associated with solving the full potential equation on an unstructured mesh are discussed. Results are presented for subsonic and transonic flows over bumps, airfoils, and wings to demonstrate the unstructured algorithm presented here.
Aerodynamic and Aeroacoustic Analysis of Low Reynolds Number Propellers Using Higher-Order RANS Transition Turbulence Modeling
Pisharoti, Naina (Virginia Tech, 2024-06-05)
The advent of advanced vehicle concepts involving Urban Air Mobility (UAM) and small Unmanned Aerial Systems (sUAS) has brought about a new class of rotorcraft technology which operate predominantly in low-Reynolds ($Re$) number regimes. In such regimes, the flow experiences complex boundary layer phenomena like laminar separation, flow transition and reattachment. These effects are known to greatly alter the flow at and near the rotor wall, influencing its aerodynamic performance as well as the noise generated. Capturing these effects in our computational models is necessary to further our understanding of rotor aerodynamics and acoustics. The current study has introduced a novel RANS transition turbulence model, SSG/LRR-$\omega$-$\gamma$, that is capable of modeling different modes of transition involving natural, bypass, separation-induced and crossflow transition. The model framework uses a Reynolds stress transport model, SSG/LRR-$\omega$, as the base turbulence formulation and is coupled with Menter's $\gamma$ transition model. It was validated using a number of canonical cases that exhibited different transition mechanisms and the model performed equivalently or better than existing state-of-the-art transition models. It is worthy to note that the proposed model was able to perform well in three-dimensional flows, demonstrated using the case of a prolate spheroid. This underscores the capability of Reynolds stress models to accurately capture complex flow curvatures, improving upon the capabilities of linear eddy viscosity models. The transition model, integrated into OpenFOAM, was then employed to analyze two different UAV propellers. The rotor flow was examined using a URANS simulation with an overset grid. The objective was twofold: firstly, to validate the predictions generated by the proposed model for low-Reynolds number (low-$Re$) rotors, and secondly, to evaluate its effectiveness across a range of operating conditions. Comparisons were drawn against established fully turbulent and transition models. The analysis showed that transition models in general tended to be consistent in their predictions and less sensitive to changing operating conditions when compared to fully turbulent models. They also demonstrated the ability to accurately predict the mechanisms leading to separation and transition. Further, the proposed transition model demonstrated superior capability in capturing detailed flow features, particularly in the wake, compared to other fully turbulent and transition models, which is attributed to its Galilean invariant framework. To leverage the boundary layer information obtained from the proposed model, a semi-empirical broadband noise prediction method was implemented. This method utilized boundary layer data predicted by URANS simulations to estimate blade self-noise. An evaluation of the fully turbulent $k$-$\omega$ SST model and the proposed transition model revealed that both exhibited reasonable accuracy at lower rotor advance ratios. However, the transition model performed better at higher advance ratios. It was also observed that CFD-based approaches provided superior prediction accuracy compared to lower-fidelity aerodynamic models in the context of blade self-noise prediction Finally, the proposed aerodynamic and acoustic computational framework was applied to a design case study of swept propellers to understand the advantages of blade sweep on rotor aerodynamics and noise. A qualitative analysis of the flow suggested that the swept rotor exhibited lower levels of blade wake interaction compared to the unswept geometry, in line with the experimental observations.
Aerodynamic Design Sensitivities on an Unstructured Mesh Using the Navier-Stokes Equations and a Discrete Adjoint Formulation
Nielsen, Eric John (Virginia Tech, 1998-11-16)
A discrete adjoint method is developed and demonstrated for aerodynamic design optimization on unstructured grids. The governing equations are the three-dimensional Reynolds-averaged Navier-Stokes equations coupled with a one-equation turbulence model. A discussion of the numerical implementation of the flow and adjoint equations is presented. Both compressible and incompressible solvers are differentiated, and the accuracy of the sensitivity derivatives is verified by comparing with gradients obtained using finite differences and a complex-variable approach. Several simplifying approximations to the complete linearization of the residual are also presented. A first-order approximation to the dependent variables is implemented in the adjoint and design equations, and the effect of a "frozen" eddy viscosity and neglecting mesh sensitivity terms is also examined. The resulting derivatives from these approximations are all shown to be inaccurate and often of incorrect sign. However, a partially-converged adjoint solution is shown to be sufficient for computing accurate sensitivity derivatives, yielding a potentially large cost savings in the design process. The convergence rate of the adjoint solver is compared to that of the flow solver. For inviscid adjoint solutions, the cost is roughly one to four times that of a flow solution, whereas for turbulent computations, this ratio can reach as high as ten. Sample optimizations are performed for inviscid and turbulent transonic flows over an ONERA M6 wing, and drag reductions are demonstrated.
Aerodynamic Heating of a Hypersonic Naval Projectile Launched At Sea Level
Mabbett, Arthur Andrew (Virginia Tech, 2007-04-10)
Hypersonic flight at sea-level conditions induces severe thermal loads not seen by any other type of current hypersonic system. Appropriate design of the hypersonic round requires a solid understanding of the thermal environment. Numerous codes were obtained and assessed for their applicability to the problem under study, and outside of the GASP Conjugate Heat Transfer module, Navier-Stokes code from Aerosoft, Inc., no efficient codes are available that can model the aerodynamic heating response for a fully detailed projectile, including all subassemblies, over an entire trajectory. Although the codes obtained were not applicable to a fully detailed thermal soak analyses they were useful in providing insight into ablation effects. These initial trade studies indicated that ablation of up to 1.25 inches could be expected for a Carbon-Carbon nosetip in this flight environment. In order to capture the thermal soak effects a new methodology (BMA) was required. This methodology couples the Sandia aerodynamic heating codes with a full thermal finite element model of the desired projectile, using the finite element code ANSYS from ANSYS, Inc. Since ablation can be treated elsewhere it was not included in the BMA methodology. Various trajectories of quadrant elevations of 0.5, 10, 30, 50, and 80 degrees were analyzed to determine thermal time histories and maximum operating temperatures. All of the trajectories have the same launch condition, Mach 8 sea-level, and therefore will undergo the same initial thermal spike in temperature at the nose-tip of approximately 3,100 K (5600R). Of the five trajectories analyzed the maximum internal temperatures experienced occurred for the 50 degree quadrant elevation trajectory. This trajectory experienced temperatures in excess of 1,000 K (1800R) for more than 80% of its flight time. The BMA methodology was validated by comparisons with experiment and computational fluid solutions with an uncertainty of 10% at a cost savings of over three orders of magnitude.
Aerodynamic Interactions in Vortex Tube Separator Arrays
Acharya, Aditya Sudhindra (Virginia Tech, 2023-06-22)
Helicopter turboshaft engines may ingest large amounts of foreign particles (most commonly sand/dust), which can cause significant compressor blade damage and even engine failure. In many helicopters, this issue is mitigated by separating the particles from the intake airstream. An effective device for engine air-particle separation is the vortex tube separator (VTS), which uses centrifugal forces in a vortical flow to radially filter foreign particles from a duct with an annular exit. Dozens or hundreds of these devices are linked together on a shared manifold known as a VTS array. There is a distinct lack of scientific literature regarding these arrays, which likely feature significantly more complex flowfields than singular VTSs due to aerodynamic interactions between the devices. The research presented in this dissertation identifies and explains flow features unique to arrays by means of an experimental investigation downstream of various VTS configurations in a wind tunnel. Mean PIV flowfields reveal that the VTS array rapidly generates a strong central recirculation zone while a single VTS does not, implying the existence of axial flow gradients within associated separators that could affect filtration efficiency. The key factor here is the global swirl intensity, which is increased in array flows due to high angular momentum contributions from separators that are radially distant from the duct center. A preliminary momentum integral model is constructed to predict the onset of recirculation in VTS flows. Analysis is then extended to the unsteady flowfield, where it is shown that VTS-generated turbulence contains only low levels of anisotropy. Spectral proper orthogonal decomposition is conducted on the array flow; it reveals the existence of low-frequency harmonic behavior composed of back-and-forth pumping motions downstream of the central VTS. Additionally, a unique precession motion is found in the same region at a slightly higher frequency. Similar precessing vortex cores have been shown to reduce separation efficiency in other cyclone separators. Both of these coherent structures may be associated with the central recirculation zone and may interfere with VTS array filtration given their timescales relative to potential particle relaxation timescales. This dissertation opens the door for future experimental and computational studies of fluid and particle dynamics in VTS flows with the goal of improving VTS array-specific design philosophies.
Aerodynamic Modeling in Nonlinear Regions, including Stall Spins, for Fixed-Wing Unmanned Aircraft from Experimental Flight Data
Gresham, James Louis (Virginia Tech, 2022-06-28)
With the proliferation of unmanned aircraft designed for national security and commercial purposes, opportunities exist to create high-fidelity aerodynamic models with flight test techniques developed specifically for remotely piloted aircraft. Then, highly maneuverable unmanned aircraft can be employed to their greatest potential in a safe manner using advanced control laws. In this dissertation, novel techniques are used to identify nonlinear, coupled, aerodynamic models for fixed-wing, unmanned aircraft from flight test data alone. Included are quasi-steady and unsteady nominal flight models, aero-propulsive models, and spinning flight models. A novel flight test technique for unmanned aircraft, excitation with remote uncorrelated pilot inputs, is developed for use in nominal and nonlinear flight regimes. Orthogonal phase-optimized multisine excitation signals are also used as inputs while collecting gliding, aero-propulsive, and spinning flight data. A novel vector decomposition of explanatory variables leads to an elegant model structure for stall spin flight data analysis and spin aerodynamic modeling. Results for each model developed show good agreement between model predictions and validation flight data. Two novel applications of aerodynamic modeling are discussed including energy-based nonlinear directional control and a spin flight path control law for use as a flight termination system. Experimental and simulation results from these applications demonstrate the utility of high-fidelity models developed from flight data.

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Browsing Doctoral Dissertations by Department "Aerospace and Ocean Engineering"

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