The quest to achieve high resolution in ion mobility spectrometry (IMS) has continued to challenge scientist and engineers in the field of separation science. The low resolution presently attainable in IMS has continued to negatively impact its utility and acceptance. Until now, efforts to improve the resolution have mainly focused on better instrumentation and detection methods. However, since the resolution of IMS is diffusion limited, it makes sense to address this limitation in order to attain high resolution. This dissertation presents a new IMS technique, which utilizes a high electric field and opposing high gas flow velocity with the aim to improve resolution. This approach essentially reduces the residence time of ions in the analyzer. This new technique is called "counter-flow ion mobility analysis" (CIMA). Theoretical modeling of this new technique predicted that a resolution of over 1000 is possible, which is over one order of magnitude better than that of conventional IMS techniques currently used. A wind tunnel was designed and constructed to produce a plug gas flow profile that is needed for CIMA. The test region of the wind tunnel was used as the CIMA analyzer region and was constructed from power circuit boards, PCBs, (top and bottom walls) and conductive plastic side walls. An inclined electric field was created by applying suitable voltages to multiple electrode traces on the PCBs. This inclined field, when resolved into its x- and y-components, was used to oppose the counter-gas flow and transport the ions to the detector, respectively. The results obtained did not show an improvement over conventional IMS techniques because of a limitation in the voltage that could be applied to the analyzer region. However, the results predict that high resolution is possible if (1) the ratio of the electric fields in the horizontal (x direction) to the vertical (y direction) is within the range of 2--0.5, (2) very high electric field and high gas flow velocities are applied, and (3) wall effects in the counter-flow gas profile are eliminated. While the resolution obtained using the present instrumentation is far from what was predicted, the foundation for ultimately achieving high resolution has been laid. The use of a wind tunnel has made the instrumentation possible. As far as the author knows, this is the first time a wind tunnel has been used in chemical measurement instrumentation. Chapter 5 of this dissertation, reports a method developed for predicting the reduced mobility constants, of chemical compounds. This method uses a purely statistical regression analysis for a wide range of compounds which is different from similar methods that use a neural network. The calculated value for this method was 87.4% when calculated values were plotted against experimental K0 values, which was close to the value for the neural network method (i.e., 88.7%).

<p>Gaussian Process Regression (GPR) is a widely used surrogate model in efficient global optimization (EGO) due to its capability to provide uncertainty estimates in the prediction. The cost of creating a GPR model for large data sets is high. On the other hand, neural network (NN) models scale better compared to GPR as the number of samples increase. Unfortunately, the uncertainty estimates for NN prediction are not readily available. In this work, a scalable algorithm is developed for EGO using NN-based prediction and uncertainty (EGONN). Initially, two different NNs are created using two different data sets. The first NN models the output based on the input values in the first data set while the second NN models the prediction error of the first NN using the second data set. The next infill point is added to the first data set based on criteria like expected improvement or prediction uncertainty. EGONN is demonstrated on the optimization of the Forrester function and a constrained Branin function and is compared with EGO. The convergence criteria is based on the maximum number of infill points in both cases. The algorithm is able to reach the optimum point within the given budget. The EGONN is extended to handle constraints explicitly and is utilized for aerodynamic shape optimization of the RAE 2822 airfoil in transonic viscous flow at a free-stream Mach number of 0.734 and a Reynolds number of 6.5 million. The results obtained from EGONN are compared with the results from gradient-based optimization (GBO) using adjoints. The optimum shape obtained from EGONN is comparable to the shape obtained from GBO and is able to eliminate the shock. The drag coefficient is reduced from 200 drag counts to 114 and is close to 110 drag counts obtained from GBO. The EGONN is also extended to handle uncertainty quantification (uqEGONN) using prediction uncertainty as an infill method. The convergence criteria is based on the relative change of summary statistics such as mean and standard deviation of an uncertain quantity. The uqEGONN is tested on Ishigami function with an initial sample size of 100 samples and the algorithm terminates after 70 infill points. The statistics obtained from uqEGONN (using only 170 function evaluations) are close to the values obtained from directly evaluating the function one million times. uqEGONN is demonstrated on to quantifying the uncertainty in the airfoil performance due to geometric variations. The algorithm terminates within 100 computational fluid dynamics (CFD) analyses and the statistics obtained from the algorithm are close to the one obtained from 1000 direct CFD based evaluations.</p>

<p>Two-phase modeling and simulation capabilities are strongly dependent on the accuracy of flow regime identification methods. Flow regimes have traditionally been determined through visual observation, resulting in subjective classifications that are susceptible to inconsistencies and disagreements between researchers. Since the majority of two-phase flow studies have been concentrated around vertical and horizontal pipe orientations, flow patterns in inclined pipes are not well-understood. Moreover, they may not be adequately described by conventional flow regimes which were conceptualized for vertical and horizontal flows. Recent work has explored applying machine learning methods to vertical and horizontal flow regime identification to help remedy the subjectivity of classification. Such methods have not, however, been successfully applied to inclined flow orientations. In this study, two novel unsupervised machine learning methods are proposed: a modular configuration of multiple machine learning algorithms that is adaptable to different pipe orientations, and a second universal approach consisting of several layered algorithms which is capable of performing flow regime classification for data spanning multiple orientations. To support this endeavor, an experimental database is established using a dual-ring impedance meter. The signals obtained by the impedance meter are capable of conveying distinct features of the various flow patterns observed in vertical, horizontal, and inclined pipes. Inputs to the unsupervised learning algorithms consist of statistical measures computed from these signals. A novel conceptualization for flow pattern classification is developed, which maps three statistical parameters from the data to red, green, and blue primary color intensities. By combining the three components, a flow pattern map can be developed wherein similar colors are produced by flow conditions with like statistics, transforming the way flow regimes are represented on a flow regime map. The resulting dynamic RGB flow pattern map provides a physical representation of gradual changes in flow patterns as they transition from one regime to another. By replacing the static transition boundaries with physically informed, dynamic gradients between flow patterns, transitional flow patterns may be described with far greater accuracy. This study demonstrates the effectiveness of the proposed method in generating objective flow regime maps, providing a basis for further research on the characterization of two-phase flow patterns in inclined pipes. The three proposed methods are compared and evaluated against flow regime maps found in literature.</p>

<p>Uncertainty analysis is of great use both for calculating outputs that are more akin to real<br> flight, and for optimization to more robust shapes. However, implementation of uncertainty<br> has been a longstanding challenge in the field of aerodynamics due to the computational cost<br> of simulations. Geometric uncertainty in particular is often left unexplored in favor of uncer-<br> tainties in freestream parameters, turbulence models, or computational error. Therefore, this<br> work proposes a method of geometric uncertainty analysis for aerodynamic shapes that miti-<br> gates the barriers to its feasible computation. The process takes a two- or three-dimensional<br> shape and utilizes a combination of multifidelity meshes and Gaussian process regression<br> (GPR) surrogates in a multifidelity Monte Carlo (MFMC) algorithm. Multifidelity meshes<br> allow for finer sampling with a given budget, making the surrogates more accurate. GPR<br> surrogates are made practical to use by parameterizing major factors in geometric uncer-<br> tainty with only four variables in 2-D and five in 3-D. In both cases, two parameters control<br> the heights of steps that occur on the top and bottom of airfoils where leading and trailing<br> edge devices are attached. Two more parameters control the height and length of waves<br> that can occur in an ideally smooth shape during manufacturing. A fifth parameter controls<br> the depth of span-wise skin buckling waves along a 3-D wing. Parameters are defined to<br> be uniformly distributed with a maximum size of 0.4 mm and 0.15 mm for steps and waves<br> to remain within common manufacturing tolerances. The analysis chain is demonstrated<br> with two test cases. The first, the RAE2822 airfoil, uses transonic freestream parameters<br> set by the ADODG Benchmark Case 2. The results show a mean drag of nearly 10 counts<br> above the deterministic case with fixed lift, and a 2 count increase for a fixed angle of attack<br> version of the case. Each case also has small variations in lift and angle of attack of about<br> 0.5 counts and 0.08◦, respectively. Variances for each of the three tracked outputs show that<br> more variability is possible, and even likely. The ONERA M6 transonic wing, popular due<br> to the extensive experimental data available for computational validation, is the second test<br> case. Variation is found to be less substantial here, with a mean drag increase of 0.5 counts,<br> and a mean lift increase of 0.1 counts. Furthermore, the MFMC algorithm enables accurate<br> results with only a few hours of wall time in addition to GPR training. </p>

<p>Free surface flows, characterized by a deformable interface between two immiscible fluids or between a liquid and a gas, play a pivotal role in numerous natural phenomena and industrial processes. The fluid-fluid interface dynamics, governed by the complex interplay of forces such as inertia, capillary force, viscous force, and possibly elastic force, significantly influence the behavior of the fluids involved. Examples of free surface flows can be observed in everyday situations, such as droplet formation from a faucet, propagation and breaking of ocean waves, and tear films that coat the eye. An in-depth understanding of free surface flows and fluid-fluid interface dynamics has extensive implications for optimizing applications like inkjet printing, coating, spraying, and droplet formation while providing insights into the intricate behavior of natural fluid systems. Most of these applications, except for coating, involve abrupt and catastrophic topological changes of interfaces present in processes such as drop breakup, sheet rupture, and drop impact, where small droplets form from liquid sheets or filaments.</p> <p>This thesis examines the dynamics of contracting liquid filaments through computational means. Previous computational simulations have assumed that initially the fluid within the filament is quiescent which, however, may not typically be the case in practical applications. Here, the effect of a realistic, non-zero initial velocity profile is considered with the hypothesis that the fact that the fluid is already in motion when it starts to contract may result in significant alterations in the filament’s final fate vis-a-vis whether it breaks up into multiple small droplets or contracts into a sphere as its ends retract toward each other. The transient system of governing equations, the three-dimensional but axisymmetric (3DA) Navier-Stokes and continuity equations subjected to interfacial boundary conditions, are solved using rigorous and robust numerical algorithms in both fully 3DA and one-dimensional (1D) settings using the Galerkin finite element (GFEM) method. The simulation results are then used to construct comprehensive phase diagrams to delineate regions where filaments break up into smaller droplets from those where filaments contract to spheres without breakup.</p> <p>Polymer additives are often present in practical applications involving filament contraction and breakup. The presence of polymer molecules in an otherwise Newtonian solvent gives rise to non-Newtonian rheology. In this thesis, the dynamics of filaments containing polymer additives are analyzed using a 1D algorithm that is developed specifically for simulating viscoelastic free surface flows where the fluid’s rheology is described by the oft-used Oldroyd-B model. In real-world applications, filaments produced from nozzles are expected to be prestressed at the instant when they are created and begin to contract. It is demonstrated that the retraction velocity of tips of highly viscous, prestressed filaments is significantly increased compared to filaments in which the polymer molecules are initially relaxed and Newtonian filaments. This enhancement is explained by examining the value of f σ: D (σ: Elastic stress; D: Rate-of-strain tensor), which can be positive or negative. This quantity is positive when the flow does work on the polymer molecules but negative when the molecules do work on the flow, i.e., when elastic recoiling or unloading takes place. In prestressed filaments, elastic unloading takes place because σ: D < 0. The elastic stresses work by pulling the fluid in axially and pushing it out radially, thereby drastically increasing the tip velocity.  However, this enhancement in contraction velocity is not observed in low to intermediate viscosity prestressed filaments and whose Newtonian counterparts typically experience end-pinching. It has been established by others that end-pinching can be precluded in either filaments of intermediate viscosity or surfactant-laden filaments of low viscosity through a process known as escape from end-pinching. In this study, we demonstrate that a similar escape can also occur in prestressed viscoelastic filaments of low-to-intermediate viscosity, as revealed by one-dimensional numerical simulations and rationalized by examining when and where the elastic recoil takes place.</p> <p>Beyond cylindrical filaments, thin liquid films or planar liquid sheets are also prevalent in atomization, curtain coating, and other processes where liquid sheet stability has been a subject of extensive research. Numerous authors have examined wave formation and growth leading to sheet breakup. Free liquid films or sheets without edges or caps at their two ends, which typically have two free surfaces and are surrounded by air or sometimes another liquid, can destabilize and rupture due to intermolecular van der Waals attractive forces, despite the stabilizing influence of surface tension. In this thesis, the dynamics of contracting free films or sheets with caps---two-dimensional (2D) drops---of Newtonian fluids is examined without considering van der Waals forces to confirm or refute the hypothesis that such systems can rupture due to finite-amplitude perturbations even in the absence of intermolecular forces. In particular, both two-dimensional and one-dimensional high-accuracy simulations are employed to demonstrate that unlike inviscid 2D drops that can rupture in the absence of van der Waals forces, 2D drops or sheets can escape from pinch-off due to the action of viscous forces which are present in real systems no matter how small their viscosity. The reopening of the interface and escape from pinch-off in 2D drops and sheets are explained by demonstrating the key role played by vorticity. New power-law relations or scaling laws are obtained as a function of Ohnesorge number (ratio of viscous to the square root of the product of inertial and capillary forces) for the value of the minimum film thickness for which 2D drops or sheets stop thinning and after which the interface begins to reopen. Simple yet powerful arguments are presented rationalizing these scaling laws. It is expected that these power-law relations should be of great interest to experimentalists who study such phenomena by high-speed visualization experiments.</p> <p>Some of the motivation for this thesis research comes from crop spraying applications in which achieving zero or negligible drift is highly desirable. To further the understanding of fluid mechanics underpinning current and future drift reduction technologies, a simplified experimental setup is adopted to generate liquid sheets and analyze their disintegration into droplets. This new setup is both simpler and more universal than commonly utilized experimental systems that use single or multiple nozzles to generate liquid sheets and spray droplets from the disintegration of free liquid films. In the current experiments, droplets of test fluids are made to collide with or impact the top planar surface of a solid cylinder or rod. A series of MATLAB codes are developed and employed to extract droplet size distributions from images that are obtained from high-speed visualization experiments. The experimental setup and the means of data analysis are then used to probe the effect of fluid properties on the dynamics of sheet disintegration and droplet size distributions. It is hoped that future researchers will be able to combine what has been done in this thesis by simulations and in this chapter via experimental observations to develop an improved mechanistic understanding of spray formation.</p>

<p>  </p> <p>The study of two-phase flow in different orientations can allow for greater understanding of the fundamentals of two-phase flow dynamics. While a large amount of work has been performed for vertical flows and recent work has been done for horizontal flows, limited research has been done studying inclined upward two-phase flows between those two orientations. Studying two-phase flows at various inclinations is important for developing physical models and simulations of two-phase flow systems and understanding the changes between what is observed for symmetric vertical flows and asymmetric horizontal flows. The present work seeks to systematically characterize the effects of inclination on adiabatic concurrent air-water two-phase flows in straight pipes. An experimental database is established for local and global two-phase flow parameters in a novel inclinable 25.4 mm inner diameter test facility using four-sensor conductivity probes, high speed video capabilities, a ring-type impedance meter, a pressure transducer, and a gamma densitometer. Rotatable measurement ports are employed to allow for local conductivity probe measurements across the flow profile to capture asymmetric parameter distributions during experiments without stopping the flow. Some of the major effects of inclination are investigated, including the effects on flow regime transition, bubble distribution, frictional pressure loss, and relative motion between the two phases. Flow visualization and machine-learning methods are employed to identify the transitions between flow regimes for inclined orientations, and these transitions are compared against existing theoretical flow regime transition criteria proposed in literature. The theoretical transitions in literature agree well with both methods for vertical flow, but additional work is necessary for angles between 0 degrees and 60 degrees. The effect of inclination on two-phase frictional pressure drop is explored, and a novel adaption of the Lockhart-Martinelli pressure drop correlation is proposed, which is able to predict the pressure drop for the conditions investigated with an absolute percent difference of 2.6%. To explore the relationships between orientation, void fraction, and relative motion, one-dimensional drift flux analyses are performed for the data at each angle investigated. It is observed that the relative velocity between phases decreases as the angle is reduced, with a relative velocity near zero at some intermediate angles and a negative relative velocity for near-horizontal orientations.  Existing modeling capabilities that have been developed for vertical and horizontal flows are evaluated based on the local two-phase parameters collected at multiple orientations. The performance of the one-dimensional interfacial area transport equation for vertical and horizontal flows is tested against experimental data and a novel model for horizontal and inclined-upward bubbly flows is proposed. Finally, an evaluation of existing momentum transfer relations is performed for the two-fluid model using three-dimensional computational fluid dynamics tools for horizontal and inclined. The prediction of the void fraction distribution and gas velocity profiles are compared against experimental data, and improvements to the lift force model are identified based on changes in the relative velocity between phases. </p>

<p> Wire-wrapped rod bundles are often used in nuclear reactors operating in a fast neutron spectrum, as designers seek to minimize neutron scattering by packing the fuel pins into a hexagonal lattice. Bundles with many rods have extensively been studied as representative of large fuel assemblies, however far fewer experiments have investigated bundles with 7 rods (7-pin bundles). The large difference in subchannel number between these bundles leads to 7-pin bundles having different pressure drop characteristics. The Versatile Test Reactor (VTR) sodium cartridge loop proposes to use a 7-pin bundle as its experimental core region, highlighting the need for additional data and models. The current work seeks to establish a better understanding of the pressure drop in 7-pin wire-wrapped rod bundles through scaled experiments and a novel pressure drop model. A scaling analysis is first performed to demonstrate the applicability of water experiments to the VTR sodium cartridge loop, before an experimental test facility is designed and constructed. Experiments are then performed at a range of Reynolds numbers to determine the pressure drop. Current models are able to predict the data well, but are complex and can be difficult to use. A comparatively simpler model is developed, based on exact laminar solutions of a simplified rod bundle, which also offers a theoretical lower bound for the pressure drop in wire-wrapped bundles. The proposed model compares well with the existing experimental database, able to predict bundle friction factor with an average absolute percent difference of 10.8%. This accuracy is also similar to existing correlations, while relying on fewer empirical coefficients. The theoretical lower bound is also used to identify several datasets in literature that may feature data that is systemically lower than the true pressure drop, which agrees with previous observations in literature. </p>

<p>Future long-duration space missions will take humans farther from the support resources of Earth than ever before. These missions will require microgravity surgical technologies in the case of an emergency that necessitates medical intervention. This experiment integrated three different surgical technologies for testing in weightlessness on parabolic flights: a surgical containment dome, a multi-function surgical wand, and a microgravity blood-air separator. Two fluid loops were utilized: one in which the surgical wand, containment dome, and a wound model were used to provide a realistic mixture of blood simulant and air to the blood-air separator. The other fluid loop used prescribed mixture ratios of air and blood to test the performance of the separator under varying conditions. The results of this experiment showed that the multi-functional surgical tool and dome functioned as designed. In addition, each separator successfully separated the blood and air from the mixture, allowing for future blood transfusion. With this demonstration, each system used in this experiment qualifies as technology readiness level 6. Advancing the technology readiness level of these technologies further will require long duration zero-g testing on-orbit before inclusion in authentic space mission emergency surgical strategy. </p>

<p>In this study, universal databases and semi-empirical correlations are developed for cryogenic two-phase heat transfer and pressure drop in heated tubes undergoing flow boiling.</p>

<p>Fibre suspensions in the fluid medium are common in industry, biology, and the environment. Industrial examples of concentrated suspensions include fresh concrete, uncured solid rocket fuel, and biomass slurries; natural examples include silt transfer in rivers and red blood cells in the blood.  These suspensions often include a Newtonian fluid as their suspending medium; still, these suspensions exhibit a plethora of non-Newtonian properties, such as yield stresses, rate-dependent rheology, and normal stresses, to name a few. Other than volume fraction, the type of fiber material, the presence of fluid-fiber or fiber-fiber interactions such as hydrodynamic, Brownian, colloidal, frictional, chemical, and/or electrostatic determine the rheological behavior of suspension. The average inter-fiber gaps between the neighboring fibers decrease significantly as the suspension volume fraction move towards a concentrated regime. As a result, in this regime, inter-fiber interactions become dominant.  Moreover, the surface asperities are present on the fiber surface even in the case of so-called smooth fibers, as fibers in real suspensions are not perfectly smooth. Hence, contact forces arising from the direct touching of the fibers become one of the essential factors in determining the rheology of suspensions.</p> <p>We first describe the causes of yield stress, shear thinning, and normal stress differences in fibre suspensions. We model the fibers as inextensible continuous flexible slender bodies with the Euler-Bernoulli beam equation governing their dynamics suspended in an incompressible Newtonian fluid. The fiber dynamics and fluid flow coupling is achieved using the immersed boundary method (IBM). In addition, the fiber surface roughness lead to inter-fiber contacts resulting in normal and tangential forces between the fibers, which follow Coulomb’s law of<br> friction. The surface roughness is modeled as hemispherical protrusions on the fiber surfaces. In addition to the comparison of the computational model to the experimental results, we demonstrate that attractive interactions lead to yield stress and shear thinning rheology.</p> <p>Furthermore, we investigate the effects of fiber aspect ratio, roughness, flexibility, and volume fraction on the rheology of concentrated suspensions. We find that the suspension viscosity increases with increasing the volume fraction, roughness, fiber rigidity, and aspect ratio. The increase in relative viscosity is the macroscopic manifestation of a similar increase  in the microscopic contact contribution with these parameters. In addition, we observe positive and negative first and second normal stress differences, respectively, in agreement with previous experiments. Lastly, we propose a modified Maron-Pierce law to quantify the the jamming volume fraction with varying fiber aspect ratio and roughness. Additionally, we provide a constitutive model to calculate the viscosity at various volume fractions, aspect ratios, and shear rates.</p>