Dissertations and Theses - Aerospace Engineering
http://hdl.handle.net/2142/14800
Tue, 19 Jun 2018 14:51:51 GMT2018-06-19T14:51:51ZWind tunnel study of wind farms with alternating 2- and 3-bladed wind turbines
http://hdl.handle.net/2142/99524
Wind tunnel study of wind farms with alternating 2- and 3-bladed wind turbines
Hayat, Imran
With offshore wind farms gaining substantial momentum in recent years, 2-bladed turbines (2BT) are increasingly becoming a viable alternative to 3-bladed counterparts (3BT). In this wind tunnel study, model wind farms with alternating rows of 3BT and 2BT were explored for potential benefits associated with enhanced momentum available within the arrays and reduced costs due to the reduction of blades. Two arrays of aligned turbines with streamwise separation of five and ten rotor diameter d (Sx = Δx/d =5 and 10) were operated in a turbulent boundary layer flow. They shared the same transverse turbine spacing of Sy = Δy/d =2.5. High-resolution velocity measurements were made with hotwire anemometry at various locations in the wake and the power output of turbines was measured simultaneously. Comparison of the flow between an array with only 3BT and that with alternating 2BT and 3BT shows enhanced mean velocity and reduced turbulence levels for the latter in Sx = 5 case. The pre-multiplied spectra of the flow at selected locations within the wind farm suggest that large energetic structures at top-tip and hub height are dampened by 2BT, with the potential to reduce turbulent loading on downwind turbines. Although the reduced mixing at top tip height behind 2BT causes the momentum recovery rate to diminish, the available momentum at downstream turbine is still higher than corresponding 3BT in the Sx = 5 case. Overall performance gain from marginally enhanced power statistics of 3BT operating in the wake of 2BT is offset by the diminished performance of 2BT inside the farm, resulting in comparable performance between the two configurations.
Two-bladed turbine; Power optimization; Wind farm; Wake
Mon, 11 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/995242017-12-11T00:00:00ZHayat, ImranLimiting factors of the tensile strength of aramid fibers
http://hdl.handle.net/2142/99520
Limiting factors of the tensile strength of aramid fibers
Sahin, Korhan
The correlation between the evolution of crystallite orientation in aramid fibers during loading and their mechanical and failure behavior were investigated. Three types of as-spun aramid fibers and a heat-treated type were employed with initial distributions of crystallite orientations between 16.7º and 9.7º with respect to the fiber axis. These directly correlated with the initial moduli that were between 66 GPa and 119 GPa, with no correlation between the initial crystallite orientation distribution and the tensile strength values that ranged between 3.5 and 4.0 GPa. Cyclic loading of individual, 10 mm long, as-spun filaments increased their initial moduli, all converging to 100 GPa for all fiber types when cycled to 90% of their respective tensile strength values. This modulus value (100 GPa) corresponds to a stable crystallite orientation distribution of 11.6º. On the other hand, the initial unloading modulus of all fiber types when loaded to 90% of their tensile strength converged to ~165 GPa which approaches the theoretical modulus of 220 GPa for monopolymer aramids. This limit value of the unloading modulus also signifies the tightest crystalline domain orientation distribution of 6.6º with respect to the fiber axis. However, this orientation distribution is not retained upon unloading. On the other hand, as-fabricated, post-spun heat-treated fibers had a much higher initial modulus of 120 GPa, and an initial unloading modulus of 170 GPa after mechanical cycling to 90% of their tensile strength value, corresponding to 5.8º domain orientation distribution. In all aramid types, mechanical cycling increased the initial modulus by as much as 54% while leaving the tensile strength of each fiber type unaffected in the narrow range of the aforementioned initial values. Thus, the limiting orientation distribution of ~6º emerges as the controlling factor in tensile failure of this class of fibers. Tension tests conducted at different strain rates showed that the permanent orientation of crystalline domains at high strains/stresses scales inversely with the applied strain rate. Notably, at strain rates of 0.2-0.3 s -1 both as-spun and heat-treated fibers were linearly elastic until failure.
A hypothesis that the fiber tensile strength is controlled by preexisting defects was tested by examining the scaling of the tensile strength with the fiber gauge length for fibers with lengths in the range of 200 µm to 10 mm. Prior works that were limited to fiber gauge lengths longer than 2 mm, have been inconclusive due to large data scatter for short fibers. Controlled tests conducted in this dissertation research with dedicated test apparatuses for small scale experimentation, demonstrated a constant tensile strength for gauge lengths as short as 200 µm, thus, implying that failure does not obey weakest link statistics that are descriptive of critical flaw-induced failure initiation. Notably, in short gauge length fibers (200 µm) of all aramid types failure initiation occurred near the skincore interface, followed by extrusion of the fiber core from the skin. Thus, the microstructural differentiation between the fiber core and the skin presents a likely limiting factor in tensile strength of aramid fibers.
Finally, the shear strength of the fiber core was measured for the first time with novel experiments that were designed and implemented with the aid of surface micromachined Microelectromechanical Systems (MEMS) devices. Edge notches were milled out in individual fibers using a focused ion beam to generate a zone of uniform shear stress along the fiber, when the latter was subjected to uniaxial tension. The optimum specimen design and specimen geometry were guided by a finite element analysis to shape the notch tip such that the stress singularity is eliminated and a uniform shear dominant plane is achieved. These unique but also challenging experiments were carried out on aramid fibers with the lowest orientation of 16.7º resulting in average shear strength of 85±7.6 MPa.
In conclusion, this dissertation research established new experimental tools and methods to investigate the origin of failure initiation in aramid fibers manufactured under different conditions. A limiting orientation distribution angle was established for all aramid grades, including those that were subjected to heat treatment, while the skin-core interface was identified as the weak interface where failure may take place.
Kevlar aramid fiber; Fiber skin; Fiber core; Size effect; Strain rate effect; Shear strength
Fri, 08 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/995202017-12-08T00:00:00ZSahin, KorhanWave management in 1D and 2D granular systems: designs for stress wave mitigation and control
http://hdl.handle.net/2142/99492
Wave management in 1D and 2D granular systems: designs for stress wave mitigation and control
Waymel, Robert Frank
Controlling stress waves during impact beyond merely dissipating their energy through material fracture, fragmentation, yielding etc., has been a significant focus of research in recent years. Materials exhibiting stress wave control characteristics would enable novel applications, such as for example stress wave focusing, deflection, annihilation, etc. that otherwise may not be present. Ordered granular media are one material group that has shown promise in this respect as they have been shown, at least in the elastic range, to possess very different wave propagation properties than continuous solids, such as the ability to sustain solitary waves – constant width and shape but variable speed waves. This dissertation investigates several granular systems, based on metallic spherical granules, that have been designed specifically to study certain aspects of wave propagation management. The first portion of this work investigates manipulating wave propagation in 1D granular chains. One design is easily altered between two configurations by a slight tilt in a gravitational field, and acts as a switch for wave propagation with peak amplitude on the order 10s of N: in one configuration, a solitary wave passes through unaltered, while in the other configuration, the travelling wave is significantly attenuated. A second design acts as a low pass force filter for high amplitude solitary waves (10s of kN) which is achieved through the use of preconditioned contacts – a process in which the granule contacts are loaded (beyond yield) to some peak force prior to use such that no further plasticity will occur in situ if the peak amplitude of the propagating wave is less than the peak preconditioning load.
The second portion of this work investigates elasto-plastic wave propagation in 2D granular square and hexagonal packings. The input wave experiences significant dissipation within as few as five contacts due to plastic dissipation at the granule contacts. The wave propagation patterns are determined to be similar to their elastic counterparts. The diameter tolerance is determined to be a primary source of scatter in the data.
The final part of this dissertation suggests designs to tailor the wave propagation within a granular packing. A numerical optimization scheme is utilized to determine the placement of cylindrical intruders at select interstitial locations within a square packing to accomplish momentum or force maximizations/minimizations at certain regions in the packing. The numerical and experimental results are similar with respect to the wave arrival time and peak forces experienced at certain locations within the packing. Several configurations demonstrate the ability to tailor the wave propagation in the granular packing through the use of interstitial cylinders, which laterally couple the square system. For some optimization scenarios, the numerical scheme does not outperform the baseline test cases. Thus, an iterative scheme is developed by forbidding intruders at certain locations, in effect changing the initial conditions of the optimization problem, and rerunning the optimization. The iterative scheme is shown to improve the results of the optimization.
A second method of tailoring elasto-plastic wave propagation is by preconditioning select contacts within a hexagonal packing. Depending on the orientation of the preconditioned contacts, the wave can be laterally deflected or allowed to pass through the packing with less attenuation. Interfacial packings, in which only a portion of the packing has preconditioned contacts, clearly illustrate the effect of the preconditioned contacts on the wave propagation behavior.
Ordered granular media; Plasticity; Two-dimensional; Solitary wave
Mon, 04 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/994922017-12-04T00:00:00ZWaymel, Robert FrankObserving and modelling the legless jumping mechanism of click beetles for bio-inspired robotic design
http://hdl.handle.net/2142/99439
Observing and modelling the legless jumping mechanism of click beetles for bio-inspired robotic design
Bolmin, Ophelia
Click beetles (Coleoptera: Elateridae) have evolved a unique jumping mechanism to right themselves when on their dorsal side without using their legs or any other appendages. This work describes and analyzes the stages of the click beetle jump using high-speed video recordings and scanning electron micrographs of six beetle species, namely Alaus oculatus, Ampedus linteus, Hemicrepidius sp., Melanactes sp., Melanotus spp. and Parallelosthetus attenuatus.
The jump of the click beetle is divided into three consecutive stages: the pre-jump stage (energy storage), and the take-off and airborne stages (energy release). Morphological measurements of the previously mentioned species as well as three additional species, namely Agriotes sp., Athous sp. and Lacon discoideus are taken, and isometric scaling across the species is observed.
The body of the click beetle is considered as two masses linked by a hinge. Dynamic and kinematic models of the jump stages are developed. Non-dimensional analysis of the airborne stage is used to analyze the jump and identify the contribution of kinematic and morphological governing parameters. An energetics model is developed to describe the energy exchanges between the three stages of the jump. Kinematic and dynamic models are used to calculate the hinge stiffness and the elastic energy stored in the body during the jump.
The derived models provide a framework that will be used for the design of a click beetle inspired self-righting robot.
Legless jumping; Click beetle inspired robot
Fri, 15 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/994392017-12-15T00:00:00ZBolmin, OpheliaMaximum entropy quadratic model to characterize chemical non-equilibrium in re-entry flows
http://hdl.handle.net/2142/99436
Maximum entropy quadratic model to characterize chemical non-equilibrium in re-entry flows
Sharma Priyadarshini, Maitreyee
This thesis presents the study of an advanced non-equilibrium model for state-specific chemical kinetics based on method of moments. The focus of this project is on the rovibrational chemical kinetics of the N2-N system. Internal excitation, dissociation, recombination and energy transfer reactions, which are important processes in aerothermodynamics, are studied. The kinetic and thermodynamic data is obtained from ab-initio calculations performed at NASA Ames Research Center. Previous analysis of the population distribution revealed that the population of the low lying energy levels of nitrogen molecules strongly deviates from a Boltzmann distribution, and the non-equilibrium distribution exhibits significant curvature. By invoking the maximum entropy principle subject to a series of constraints, the logarithm of distribution function is reconstructed using quadratic functions in the internal energy space of the molecular species. The results of the numerical simulations for an ideal chemical reactor show that the quadratic model captures the excitation and dissociation profiles accurately by using only three to seven groups thereby reducing the computational costs for non-equilibrium flow simulations significantly.
Non-equilibrium flows; Reduced order modeling; Method of moments
Fri, 15 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/994362017-12-15T00:00:00ZSharma Priyadarshini, MaitreyeeDimensional reduction in nonlinear estimation of multiscale systems
http://hdl.handle.net/2142/99320
Dimensional reduction in nonlinear estimation of multiscale systems
Yeong, Hoong Chieh
State or signal estimation of stochastic systems based on measurement data is an important problem in many areas of science and engineering. The true signal is usually hidden, evolving according to its own dynamics, and observations are usually corrupted and possibly incomplete. The goal is to obtain optimal estimates of the signal based on noisy observations. When the dynamical model of the signal is completely known, the theory of filtering provides a recursive algorithm for estimating the conditional density (the filter) of the signal. Particle filters have been well established for the implementation of nonlinear filtering in applications. However, computational issues arise in high dimensions due to large number of particles being required to represent the signal density. The work done in this research attempts to address this issue by combining stochastic averaging with filtering techniques to develop a reduced-dimension particle filtering method for partially observed multiscale diffusion processes. When the dynamical model contains unknown parameters, the parameters need to be estimated along with the hidden states. The parameter estimation problem overlaps with the filtering problem for state estimation. In this research, the theory of maximum likelihood estimation is used to study dimensional reduction in the parameter estimation problem. The main contribution of this work are 1) a theoretical basis for a reduced-dimension filter, 2) a proposed numerical scheme for the reduced-dimension filter, 3) a theoretical basis for reduced-dimension parameter estimation in a special multiscale setting, and 4) a time-varying characterization of the information shared between signal and observations in the reduced-dimension filter.
The results of this research are in the context of slow-fast stochastic systems driven by Brownian motion, in which the timescales of the rates of change of different state/signal components differ by orders of magnitude. The multiscale filtering problem is studied via the Zakai equation that describes the time evolution of the nonlinear filter. We construct a lower dimensional Zakai equation for estimation of the slow signal component and show that the solution of the lower dimensional equation converges to that of the original Zakai equation in the wide timescales separation limit. The convergence is shown to be at a rate proportional to the square root of the timescales separation factor (ratio of characteristic timescale of the fast component to that of the slow). A numerical scheme to approximate the reduced-dimension filter (the solution to the lower dimensional Zakai equation) is also constructed. This scheme combines a particle filtering algorithm with an existing multiscale numerical integration scheme. The reduced filter dimension can restore the feasibility of particle filters in certain high dimensional problems and lowers computational costs by appropriately averaging out fast scale components. The particle filtering scheme is adapted to discrete-, sparse-time observations by constructing an optimal importance sampling (proposal) density. In between observation assimilation times, particles are gradually driven towards locations most representative of the next observation by solving a stochastic optimal control problem. This scheme is found to be beneficial especially when the signal dynamics is chaotic, and small errors in estimation can grow at exponentially rates in between observation assimilation times.
The second aspect of nonlinear estimation in this work is in the setting in which stationary, deterministic model parameters are unknown. The theory of maximum likelihood estimation is combined with the reduced-dimension filtering results for the study of parameter estimation in the slow-fast dynamical system setting. Using the nonlinear filters convergence result, a lower-dimensional filtered likelihood function is constructed and shown to converge to the original filtered likelihood function in the wide timescales separation limit. For a special setting in which the slow diffusion is independent of the fast component, the maximum likelihood estimate using the reduced dimension filtered likelihood function is shown to be consistent, i.e. it converges to the true model parameter in the limit of sufficiently large observation set.
The third aspect of this work concerns quantifying the uncertainty in the lower-dimensional state space of the reduced-dimension filter, given observations on the state space of the original multiscale signal. Well-known concepts of entropy and mutual information from information theory are utilized. Specifically, the time rate of change of uncertainty of the lower-dimensional state given observations is determined. The time rate of change of mutual information between the two then follows. From these, the effects of deterministic signal dynamics, diffusion effects, and information derived from observations on change in uncertainty and/or information over time can be identified and quantified. Uncertainty is found to grow according to the deterministic “volumetric growth” rate and the square of signal noise amplitude, while decreased by the square of the average information derived from observations.
Nonlinear filtering; Homogenization; Stochastic partial differential equation; Particle filter; Maximum likelihood estimation; Mutual information
Thu, 09 Nov 2017 00:00:00 GMThttp://hdl.handle.net/2142/993202017-11-09T00:00:00ZYeong, Hoong ChiehVortex-induced vibration of a linearly-sprung cylinder with nonlinear energy sinks
http://hdl.handle.net/2142/99300
Vortex-induced vibration of a linearly-sprung cylinder with nonlinear energy sinks
Blanchard, Antoine
We investigate the effect of coupling an essentially nonlinear and dissipative attachment to a linearly-sprung circular cylinder undergoing rectilinear vortex-induced vibration (VIV) normal to the mean flow. The attachment is a nonlinear energy sink (NES). The essentially nonlinear coupling between the rectilinear motion of the cylinder and the motion of the NES allows for efficient, one-way transfer of kinetic energy from the former to the latter, where it is dissipated through a process known as targeted energy transfer. We use a spectral-element approach to compute the flow and the rigid-body quantities, and show that for values of the Reynolds number in the laminar regime (20 ≤ Re ≤ 350) and well into the turbulent regime (Re ≈ 10,000), the addition of an NES to a linearly-sprung cylinder undergoing transverse VIV gives rise to a variety of physical phenomena not seen otherwise.
We consider two NES configurations, namely, a rotational NES and a translational NES. The former consists of a mass allowed to rotate about the cylinder axis, with its rotational motion being linearly damped. The latter consists of a mass allowed to translate in the direction of travel of the cylinder, with its rectilinear motion being restrained by a cubic spring and a linear viscous damper.
We show that, in a range of Re values (20 ≤ Re ≤ 100) in which the flow is expected to be two-dimensional and laminar, a rotational NES leads to phenomena as diverse as passive VIV suppression, partial stabilization of the vortex street formed downstream of the cylinder, drag reduction, capture of the trajectory on underlying slow-invariant resonance manifolds, and coexistence of multiple long-time solutions. We also investigate the extent to which a rotational NES affects the linear stability of the steady, symmetric, motionless-cylinder solution, as well as the onset of three-dimensionality in the wake. We additionally present preliminary evidence that, in the turbulent regime, the rotational NES displays great potential for being used not only as a VIV suppression device, but also as an efficient hydrokinetic energy harvester.
For a translational NES, at a value of the Reynolds number slightly above the fixed-cylinder Hopf bifurcation, we construct a reduced-order model (ROM) of the fluid–structure interaction based on a wake oscillator, asymptotic analysis of which predicts the existence of complete and partial VIV-suppression mechanisms, relaxation cycles, as well as Hopf and Shilnikov bifurcations. These outcomes are confirmed by numerical integration of the ROM and comparison against spectral-element computations of the full-order system.
Vortex-induced vibration; Nonlinear energy sink
Fri, 06 Oct 2017 00:00:00 GMThttp://hdl.handle.net/2142/993002017-10-06T00:00:00ZBlanchard, AntoineGraphical SLAM for urban UAV navigation
http://hdl.handle.net/2142/99287
Graphical SLAM for urban UAV navigation
Chen, Derek
In recent years, there has been rising interest in commercial applications of Unmanned Air Vehicles (UAVs). Examples of their usage include aerial photography, infrastructure inspection and emergency first response. For widespread commercial adoption of these applications to occur, UAV navigation must be made safe and reliable. In open-sky environments, Global Positioning System (GPS) receivers are most commonly used to provide accurate and globally referenced positioning for UAVs. However, many applications, such as consumer product delivery, require UAVs to operate in densely populated urban environments. In these environments, buildings and structures reflect and block GPS signals, leading to multipath and low satellite visibility. These factors create GPS-challenged environments that result in large errors in UAV positioning or make GPS unavailable. To improve urban GPS, one approach uses environment modeling such as 3D city models to mitigate the effects of multipath and NLOS errors. Others pair GPS with odometry measurements from relative positioning sensors, such as Light Detection and Ranging (LiDAR) sensors. LiDAR-based odometry provides an accurate relative navigation solution in GPS-challenged environments, but requires distinguishable features in the surrounding environment and is susceptible to drift and biases. As a result, there is a need for sensor fusion techniques that can provide reliable and robust positioning in urban environments.
In this thesis, we apply a Simultaneous Localization and Mapping (SLAM) approach to fuse GPS pseudorange measurements with LiDAR point clouds and 3D building footprint data of the existing region, for UAV trajectory estimation and environment mapping. Our approach consists of three main aspects: graphical modeling, map-based processing, and inference.
First, we use a probabilistic graph, specifically a directed acyclic graph, to model the trajectory of a UAV. Nodes in the graph represent states of the UAV or GPS satellites; while edges represent relations between states created by sensor measurements. We then use the graph to structure our environment maps. We represent our environment in two mapping formats: a point cloud map and an urban building map. The point cloud map is formulated by anchoring each collected LiDAR point cloud with their respective state. The result is a large point cloud collected throughout the trajectory of the UAV. The urban building map is a geometric representation of the large scale structures in the environment. It is first initialized with available sources of 3D building model data for the navigating region. In this work, we use Champaign building footprint data from the State of Illinois data portal. We then run plane fitting algorithms on the collected point clouds at each state to update the urban building map. As the UAV navigates, the graph is populated by additional nodes and corresponding LiDAR measurements, allowing for SLAM of the environment.
Next, we apply the formulated maps in two ways: mitigation of errors resultant from reflected GPS signals; and map matching with existing or previously collected maps of the region.
The urban building map is first initialized with city building footprint data. We then draw line-of-sight vectors to from the UAV to each satellite and identify NLOS satellites from intersections with the urban building map. Next, we use density of surrounding buildings to identify potential satellite measurements affected by multipath. After identifying multipath-affected GPS measurements, we propose a multipath model via covariance adjustment to deweigh their effects on the UAV state estimate.
We then append our graph with additional map matching edges. Based on the probabilistic distribution of a state, we generate and propagate particles representing potential states of the UAV. Then using the urban map, we compare the expected buildings observed by each particle with the buildings observed from the LiDAR measurements. We find the most likely particle and use it as a constraint measurement in the graph. We then compare the point cloud collected at each time step with the point cloud map to perform loop closure and create constraint measurements to the initial position of the UAV.
Afterwards, we take a probabilistic approach towards trajectory estimation in the graphical inference step. Using the edges directed at the UAV nodes in the graph, we formulate a joint probability that represents the likelihood of the state estimate given the collected measurements. We then perform inference on the graph and formulate a Maximum A Posteriori (MAP) estimate of the UAV trajectory. Since the collected LiDAR point clouds are anchored at the corresponding state estimates, we simultaneously optimize for the maps generated by the system.
Finally, we experimentally validate our algorithm by presenting the results of a series of UAV flight tests in both GPS-challenged and GPS-friendly environments near and on the University of Illinois at Urbana-Champaign campus. We show that our probabilistic graphical sensor fusion approach provides an accurate and available navigation solution that allows a UAV to navigate an urban environment under the presence of GPS signal reflections and occlusions.
Navigation; Global Positioning System (GPS)
Fri, 08 Sep 2017 00:00:00 GMThttp://hdl.handle.net/2142/992872017-09-08T00:00:00ZChen, DerekSpacecraft trajectory design utilizing resonance orbits in a hybrid optimal control framework
http://hdl.handle.net/2142/99268
Spacecraft trajectory design utilizing resonance orbits in a hybrid optimal control framework
Bunce, Devin T
Low-energy trajectories are a growing subset of trajectory design, particularly in the three-body space. These trajectories use the inherent stability and instability of certain orbits as a means of fuel efficient transfers. Traditionally, work on these types of trajectories has taken a very “hands on” approach from the astrodynamicist, i.e. requiring intuition and fine tweaking of parameters. This work details preliminary efforts to incorporate resonance orbits, their invariant manifolds, and associated families into an automated global optimization tool in order to create solutions of optimal impulsive spacecraft trajectories in multi-body environments. Previous work using this tool has shown the ability to use other key dynamical structures of the circular restricted three-body problem (e.g. Euler-Lagrange point orbits and their invariant manifolds) within the same automated global optimization framework to produce low-energy trajectory solutions. This work outlines necessary dynamical systems theory. Described next is how to generate resonance orbits of the first species by providing examples of the Earth-Moon and Jupiter-Europa systems. Finally shown is how these structures are used within the optimization framework. Several non-trivial impulsive trajectory problems from low-Earth to resonance orbits, resonance to resonance transfers, and resonance to Euler-Lagrange point orbit transfers are shown with Pareto front solutions.
Optimal trajectories; Resonance orbits; Hybrid optimal control
Fri, 15 Dec 2017 00:00:00 GMThttp://hdl.handle.net/2142/992682017-12-15T00:00:00ZBunce, Devin TDirect numerical simulation of human phonation
http://hdl.handle.net/2142/99180
Direct numerical simulation of human phonation
Saurabh, Shakti
The generation and propagation of the human voice is studied using direct numerical simulation. A full body domain is employed for the purpose of directly computing the sound in the region past the speaker's mouth. The air in the vocal tract is modeled as a compressible and viscous fluid interacting with the vocal folds (VFs). The vocal fold tissue material properties are multi-layered, with varying stiffness, and a finite-strain model is utilized and implemented in a quadratic finite element code. The fluid-solid domains are coupled through a boundary-fitted interface and utilize a Poisson equation-based mesh deformation method. The domain includes an anatomically relevant vocal tract geometry, either in two dimensions or in three dimensions. Adult and two-year-old child anatomy inspired simulations are performed. Phonation simulations using a non-linear hyper elastic, linear elastic and viscoelastic models of the VFs are performed and compared. The sensitivity of phonation to the VF Poisson's ratio is also evaluated.
Simulations are employed to investigate voice disorders related to vocal fold stiffness asymmetry and unilateral vocal fold paralysis (UVFP). Additionally, an analysis is performed for medialization laryngoplasty, a well known surgical treatment for UVFP. Phonation onset is determined from all the simulations as a measure of degree of voice disorder with phonation threshold pressure (PTP) as a key parameter for the quantification.
The computational model developed is demonstrated to be consistent with prior measurements and sufficiently sensitive to be used in future studies involving VF pathologies, surgical procedures to restore voice, and/or closed loop models of voice, speech and perception.
Vocal folds (VF); Unilateral vocal fold paralysis (UVFP); Phonation threshold pressure (PTP); Medialization laryngoplasty; Fluid-structure interaction (FSI); Phonation
Tue, 19 Sep 2017 00:00:00 GMThttp://hdl.handle.net/2142/991802017-09-19T00:00:00ZSaurabh, Shakti