A framework for understanding the fundamental physics of flowfields over forebody type shapes at low speed, high angle of attack conditions with special emphasis on sideslip has been established. Computational Fluid Dynamics (CFD) has been used to study flowfields over experimentally investigated forebodies: the Lament tangent-ogive forebody, the F-5A forebody and the Erickson chine forebody. A modified version of a current advanced code, CFL3D, was used to solve the Euler and thin-layer Navier-Stokes equations. The Navier-Stokes equations used a form of the Baldwin-Lomax turbulence model modified to account for massive crossflow separation. Using the insight provided by the solutions obtained using CFD, together with comparison with limited available data, the aerodynamics of forebodies with positive directional stability has been revealed. An unconventional way of presenting the results is used to illustrate how a positive contribution to directional stability arises. Based on this new understanding, a parametric study was then conducted to determine which shapes promote a positive contribution to directional stability. / Ph. D.

Computational Fluid Dynamics is used to analyze the formation of under-expanded jets and to investigate the three-dimensional flow field associated with the impingement of free jets onto stationary deflectors. This investigation was performed to develop a verified modeling ability for such problems. Predictions were compared with the experimental results obtained by Donaldson and Snedeker [1]. Computational models for free and impinging jets were created according to the data provided in Ref. 1. Numerical results for each of the experiments performed in this benchmark report are presented. Three different turbulent free jets produced by a simple convergent nozzle were analyzed. These include a subsonic jet with p₁/pâ =1 and M₁=0.57, a moderately under-expanded jet with p₁/pâ =1.42 and M₁=1, and a highly under-expanded jet with p₁/pâ =3.57 and M₁=1. The reflecting shocks associated with the moderately under-expanded jet as well as the shock disk associated with the highly under-expanded jet were fully resolved. Velocity profile data predicted at locations downstream of the nozzle exit agreed very well with the experimental results. The impingement of a moderately under-expanded jet with p₁/pâ =1.42 and M₁=1 was also investigated. The interaction of the high speed jet with circular flat plates at angles of 60° and 45° relative to the center axis of the jet are presented. Wall jet velocity profiles on the surface of the flat plate are fully resolved and compare well with experimental results. The CFD solver controls and method used to obtain these results are summarized and justified. / Master of Science

In this thesis, a one-dimensional, two-fluid model is developed in MATLAB-Simulink. The model features a mass, momentum, and energy balance for each fluid--an ideal gas and an incompressible liquid. The simulation may model a straight pipe section, or a pipe section that involves a cross-sectional area change. Rough models of interphase heat transfer and interphase friction are included. Currently, phase change is not modeled in the simulation Also, a single-fluid model was developed before the two-fluid model, as an intermediate step in developing the two-fluid model. The single-phase simulation applies a mass, momentum, and energy balance for the single fluid, and ideal gas. The single-fluid model was validated by incompressible flow, Fanno flow, and isentropic flow models. The incompressible model demonstrated the simulations ability to properly balance pressure and frictional forces. The Fanno flow model showed that the simulation could capture compressibility effects. The isentropic flow model validation verified that the simulation could model area change properly. The two-fluid model was validated using the Homogeneous Equilibrium Model (HEM). An analytical model of HEM flow with frictional pressure drop was developed to compare against the simulation results. To achieve the HEM, interphase effects were tuned so that the liquid and gas phases had similar temperatures and velocities. Under these conditions, the simulation matched the analytical model. The thesis goal is to create a solid foundation for an open-source, one-dimensional, two-fluid model that is easier to use and modify than current nuclear system analysis software. / Master of Science

No / A computational fluid dynamics (CFD) model is used to investigate the droplet formation and deformation under the influence of different parameters. Droplet breakup phenomenon depends on several factors such as viscosity, velocity, pressure difference, and geometry. The most important parameter for droplet breakup is the Weber number (We) which is the ratio of disrupting aerodynamics forces to the surface tension forces. Volume of fluid (VOF) model is used in present work to simulate the droplet breakup. This work presents the effect of liquid velocity, viscosity, and orifice diameters on droplet formation and breakup.

No / A comprehensive study of the internal flow field for the prilling application in a perforated rotating bucket has been carried out. Computational Fluid Dynamics (CFD) is used to investigate the flow field of urea melt inside the perforated rotating bucket. The bucket is mounted at the top of the prilling tower. In prilling process, urea melt is sprayed by the perforated rotating bucket to produce the urea droplets, which falls down due to gravity. These drops fall down through a cooling medium and solidify into prills. The velocity field in the bucket is very important to study, as it has great effect on the heat and mass transfer performance in prilling process. ANSYS 14.0 CFD package is used to simulate and Design Modeler and Catia V5 are used for geometrical model of the perforated prilling bucket. Velocity distribution on different planes are obtained and discussed.

Among the many factors that effect the atomization of a fuel spray in a com- bustion chamber, the flow characteristics of the fuel inside the injector nozzle play significant roles. The enthalpy of the entering fuel can be elevated such that it is higher than the local or downstream saturation enthalpy, which will result in the flash-boiling of the liquid. The phase change process dramatically effects the flow rate and has the potential to cause subsonic two-phase choking. The timescale over which this occurs is comparable to the flow-through time of the nozzle and hence any attempt to model this phenomenon needs to be done as a finite rate process. In the past the Homogeneous Relaxation Model (HRM) has been successfully employed to model the vaporization in one dimension. Here a full three dimensional imple- mentation of the HRM model is presented. Validations have been presented with experiments using water as working fluid. For the external spray modeling, where the fuel is said to be flash boiling, the phase change process plays a role alongside the aerodynamic breakup of the liquid and must be considered for obtaining the fuel spray characteristics. In this study the HRM model is coupled with Linearized Sheet Instability Analysis (LISA) model, for primary atomization, and with Taylor Analogy Breakup (TAB) model for secondary breakup. The aerodynamic breakup model and phase change based breakup model are designed as competing processes. The mechanism which satisfies its breakup criterion first during time integration is used to predict resulting drop sizes.

The use of moment-closure methods to predict continuum and moderately rarefied flow offers many modelling and numerical advantages over traditional methods. The maximum-entropy family of moment closures offers models described by hyperbolic systems of balance laws. In particular, the twenty-one moment model of the maximum-entropy hierarchy offers a hyperbolic treatment of viscous flows exhibiting heat transfer. This twenty-one moment model has the ability to provide accurate solutions where the Navier-Stokes equations lose physical validity due to the solution being too far from local equilibrium. Furthermore, its first-order hyperbolic nature offers the potential for improved numerical accuracy as well as a decreased sensitivity to mesh quality. Unfortunately, higher-order maximum-entropy closures cannot be expressed in closed form. The only known affordable option is to propose approximations. Previous approximations to the fourteen-moment maximum-entropy model have been proposed [McDonald and Torrilhon, 2014]. Although this fourteen-moment model also predicts viscous flow with heat transfer, the necessary moments to close the system renders it more difficult to approximate accurately than the twenty-one moment model. The proposed approximation for the fourteen-moment model also has realizable states for which hyperbolicity is lost. Unfortunately, the velocity distribution function associated with the twenty-one moment model is an exponential of a fourth-order polynomial. Such a function cannot be integrated in closed form, resulting in closing fluxes that can only be obtained through complex numerical methods. The goal of this work is to present a new approximation to the closing fluxes that respect the maximum-entropy philosophy as closely as possible. Preliminary results show that a proposed approximation is able to provide shock predictions that are in good agreement with the Boltzmann equation and surpassing the prediction of the Navier-Stokes equations. Furthermore, Couette flow results as well as lid-driven cavity flows are computed using a novel approach to Knudsen layer boundary conditions. A dispersion analysis as well as an investigation of the hyperbolicity of the model is also shown. The Couette flow results are compared against Navier-Stokes and the free-molecular analytical solutions for a varying Knudsen number, for which the twenty-one moment model show good agreement over the domain. The shock-tube problem is also computed for different Knudsen numbers. The results are compared with the one obtained by directly solving the BGK equation. Finally, the lid-driven cavity flow computed with the twenty-one moment model shows good agreement with the direct simulation Monte-Carlo (DSMC) solution.

In order to improve the continuous casting process of steel, it’s important to have an understanding of the fuid mechanics of the casting process. As experiments on a real caster are usually impractical, both physical and numerical modeling are important for creating this understanding. This report concerns itself with the creation of a numerical model of a physical model of a slab caster, which uses eutectic bismuth-tin alloy to simulate steel, and is built and operated by Swerim in Luleå, Sweden. The geometry of the model was constructed in Siemens NX, and meshing was done using Ansys Meshing. The CFD model itself was made in Ansys Fluent, and data from previous experiments on the physical model was used to verify it. The numerical model does not model any discrete phases in the liquid metal, including slag, argon fow, solid particles or any form of phase transition or heat transfer. The model uses a pump to continuously recirculate the liquid metal into the tundish, from where it fows down into the mold. Qualitatively, the model shows the expected double-roll fow pattern in the mold, and also pressure gradients in the SEN entry region which are consistent with experimental data. Verifcation was done using experimentally determined pump curves, for which the model shows reasonable behavior for mass fows above roughly 20 kg/s, but deviates somewhat below this value. Verifcation was also done using data for mass fows out of the tundish, which is regulated by the stopper position. Here, a large discrepancy between experimental and simulated data is present. Several explanations for this discrepancy were investigated, including the possibility of improper calibration of the stopper positional tracking and incorrect data for dynamic viscosity of the alloy, but the most likely explanation is that cavitation occurs in the SEN entry region due to a large pressure drop which occurs in this region. Cavitation is not implemented in the model, which leads to incorrect mass fow out of the tundish. If this fow is to be accurately captured, it is likely necessary to implement cavitation modeling in future versions of the numerical model.

As the world becomes increasingly interconnected, modernized, and populated, the demand for energy across the globe is growing at an unprecedented rate. This growth in energy demand has an undeniable impact on increasingly pressing social issues including, climate change, energy security, energy economy, atmospheric chemistry, and air quality. Finding a way to address these issues on a rapid timescale is more important than ever. A common thread running through all of these challenges is that they can be partially or fully addressed with the development of new chemical energy conversion technologies which, in turn, rely on a comprehensive understanding of gas phase kinetics. Examples of promising technologies include renewable fuels (i.e. methanol and hydrogen) and/or reliable, efficient, and clean engines that can accommodate renewable fuels. The development of such technology would enable the use of renewable fuels, thereby reducing emissions and cutting down on harmful byproducts released into the atmosphere. Computational simulations have become a powerful approach for developing and advancing energy technology in a safe, efficient, and effective manner. These computational approaches model reacting flows and are generally known as computational fluid dynamics (CFD). However, in order for these CFD simulations to work effectively and make meaningful predictions, the sub-models used to describe the underlying chemistry (gas phase kinetics) must be accurate; information about underlying chemistry is provided to computational simulations via a chemical kinetic model/mechanism, which describes the chemical reactions that drive the fuel oxidation within the system being simulated. Regarding combustion specifically, the reliability of predictive simulations depends on the availability of accurate data and models not only for chemical kinetics, but also thermochemistry and transport. Further complicating the problem, combustion and chemical kinetics provide a unique challenge in regard to obtaining accurate predictive models; underlying chemical kinetics mechanisms may require unprecedented accuracy to obtain truly predictive combustion modeling. For example, it has been shown in computational simulations that uncertainties in any of several kinetic parameters can yield uncertainties large enough in the physical system being modeled to cause system failure, thereby reducing the effectiveness of computational design approaches that could accelerate technology development. Hence, a strong need exists to develop a method that significantly reduces uncertainties in chemical kinetics parameters to meet the accuracy demands of advanced computational design tools. To this end, it is useful to draw on inspiration from existing methods in the field of combustion and chemical kinetics as well as tangential fields; the most compelling inspiration can be found in the field of thermochemistry in the form of the Active Thermochemical Tables (ATcT). This work presents a novel, analogous approach for chemical kinetics called MultiScale Informatics, or MSI for short. The MSI approach identifies optimized values and quantified uncertainties for a set of molecular parameters (within theoretical kinetics calculations), rate parameters, and physical model parameters (within simulations of experimental observables) as informed by data from various sources and scales. The overarching objectives of this work are to demonstrate how the MSI approach can be used to determine physically meaningful optimized kinetics parameters and quantified uncertainties, unravel webs of interconnected rate constants in complex reaction systems, resolve discrepancies among data sets, and touch on key elements of MSI’s implementation. To demonstrate how these objectives are met, the MSI approach is used to explore the kinetics of three reaction sub-systems. The studies of these sub-systems will demonstrate some key elements of this approach including: the importance of raw data for quantifying the information content of experimental data, the utility of theoretical kinetics calculations for constraining experimental interpretations and providing an independent data source, and the subtleties of target data selection for avoiding unphysical parameter adjustments to match data affected by structural uncertainties. For the first sub-system explored (CH₃ + HO₂), the MSI approach is applied to carefully selected (mostly raw) experimental data and yields an opposite temperature dependence for the channel-specific CH3 + HO2 rate constants as compared to a previous rate-parameter optimization. While both optimization studies use the same theoretical calculations to constrain model parameters, only the present optimization, which incorporates theory directly into the model structure, yields results that are consistent with theoretical calculations. For the second sub-system explored (HO₂ + HO₂), the MSI approach is applied to carefully selected experimental data, leveraging the hydrogen reaction system from the first study with the addition of high level theory calculations for the reaction of HO₂ + HO₂. Recent high-level theoretical calculations predict a mild temperature dependence for HO₂ + HO₂, which is inconsistent with state-of-the-art experimental determinations that upheld the stronger temperature dependence observed in early experiments. Via MSI analysis of the theoretical and experimental data, alternative interpretations of the raw experimental data that uses HO₂ + HO₂ rate constants nearly identical to theoretical predictions are identified – implying that the theoretical and experimental data are actually consistent, at least when considering the raw data from experiments. Similar analyses of typical signals from low-temperature experiments indicate that an HOOOOH intermediate – identified by recent theory but absent from earlier interpretations – yields modest effects that are smaller than, but may have contributed to, the scatter in data among different experiments. More generally, the findings demonstrate that modern chemical theories and experiments have progressed to a point where meaningful comparison requires joint consideration of their data simultaneously. The third sub-system explored builds a larger web of interconnected reaction systems in an attempt to achieve data redundancy and demonstrate how interpreting coupled reaction systems is necessary to accurately determine many key rate constants. The ability of the MSI method to interpret raw experimental data and untangle rate constant reaction systems is demonstrated. The study also reinforces how implementing theory into the model structure is imperative to yield results that are consistent with experimental data as well as theoretical calculations and achieve physically realistic branching ratios. Finally, this work will present how results from all the studied reaction systems culminate into a complex hydrogen/syngas combustion model validated against data from various combustion experiments.

Thermoelectric generators convert heat energy to electricity and can be used for waste heat recovery, enabling sustainable development. Selective Laser Melting (SLM) based additive manufacturing process is a scalable and flexible method that has shown promising results in manufacturing high ZT Bi2T e3 material and is possible to be extended to other material classes such as M g2Si. The physical phenomena of melting and solidification were investi- gated for SLM-based manufacturing of thermoelectric (M g2Si) powders through comprehen- sive numerical models developed in MATLAB. In this study, Computational Fluid Dynamics (CFD)-based techniques were employed to solve conservation equations, enabling a detailed understanding of thermofluid dynamics, including the temperature evolution and the con- vection currents of the liquid melt within the molten pool. This approach was critical for optimizing processing parameters in our investigation, which were also used for printing the M g2Si powders using SLM. Additionally, a phase field-based model was developed to sim- ulate the directional solidification of the M g2Si in MATLAB. Microstructural parameters like the Secondary and Primary Dendritic Arm Spacing were studied to correlate the effects of processing parameters to the microstructure of M g2Si. / Master of Science / Thermoelectric generators are devices that transform heat energy into electricity, offering a way to capture and utilize waste heat for sustainable purposes. A cutting-edge manufacturing method called Selective Laser Melting (SLM) has shown great potential in creating high-performance materials like Bi2T e3 for thermoelectric applications. Researchers are now exploring the extension of this technique to other materials, such as Mg2Si. This study delves into the intricate process of melting and solidifying Mg2Si powders using SLM. Advanced computer models were created in MATLAB, to simulate these processes in detail. By employing Computational Fluid Dynamics (CFD) techniques, heat and fluid flow within the molten material was also closely examined. These simulations were vital for fine-tuning the printing settings used to fabricate Mg2Si powders via SLM. Moreover, a specialized model based on phase field theory was developed to mimic the solidification of Mg2Si. The effects of changing manufacturing parameters on the microstructure of the final product were examined. Understanding these microstructural aspects is crucial for optimizing the manufacturing process and ultimately enhancing the performance of Mg2Si for thermoelectric applications.