Cryogenic propellants are going to be the cornerstone for effective future human space exploration. These propellants need to be stored and maintained at really low temperatures for a long duration. Accurate phase change modeling is necessary for characterizing the thermal state of future cryogenic propellant tanks and for designing systems to alleviate the self pressurization problem. Better understanding about how to properly store and manage cryogenic propellants would help greatly with In-Situ Resource Utilization (ISRU) strategies for future missions to Mars and further. Predicting the fluid flow, heat transfer, and phase change mass transfer in long term cryogenic storage using CFD models is greatly affected by our understanding of the accommodation coefficient. The kinetically limited phase change model governed by the Hertz-Knudsen-Schrage equation is the model of choice for such calculations. The value of the accommodation coefficient required for the model is unknown for cryogenic propellants. Even in the case of water, the value of the accommodation coefficient has been found to vary over three orders of magnitude based on 80 years of measurements. Experiments specifically built to study accommodation coefficient are needed to estimate the value of the accommodation coefficient and understand some of the uncertainties surrounding these models. <div><br></div><div>Two phase change models, viz. the thermally limited and the kinetically limited phase change model are implemented in OpenFOAM. Different approaches to implement the Hertz-Knudsen-Schrage equation in a sharp interface conjugate heat transfer solver are studied. Evaporation and condensation calculations for a liquid hydrogen meniscus inside an aluminum container are compared with experimental measurements. The effect of accommodation coefficient on phase change is then studied with the kinetically limited model by comparing with the thermally limited model and the experimental measurements. The uncertainties associated with the temperature and pressure measurements in the experiment are quantified to show their effect on computational predictions. Since cryogenic propellants are perfectly wetting fluids, modeling the thin-film region close to the contact line leads to a multi-scale computational problem. However, the phase change contribution from the thin-film region is approximated in these computations to show the importance of modeling the contact line region accurately to adequately capture the small local thermodynamics in that region.</div>

The repo rate, which is the key interest rate, set by the central banks has been declining for many years and hitting zero in Sweden in late 2014. We analyse the effectiveness on the economy from a change in the repo rate, comparing two time periods with high and low repo rate environments. We use quarterly data on GDP and its components, between 1994 and 2019. For analysing the effectiveness, we use multiple Auto Regressive Distributed Lag (ARDL) modelling to compute a total of 12 models. In our findings, we saw that the effectiveness of a change in repo rate has been increased in the low repo rate environment, making it harder to increase the rate without harming the economy but also increasing the effect of a decrease in the repo rate. Also, we found that the investment component of GDP may exhibit extra high effectiveness in the low repo rate environment. This method of analysing the repo rates impact on the economy could be used for decision makers regarding monetary policies.

In the past few decades, brake pad-rotor interface friction studies have gained high importance in the automotive industry. The goal of these studies has been to improve the design to maximize the contact area and performance in brakes. In these studies, friction coefficient has always assumed to be the same for linear and rotational motion. In our study, we show that the rotational and linear friction process have different friction coefficients. We use semi-metallic and ceramic brake material pads reduced into brake samples using scaling laws of physics. The samples were mounted on the Universal Mechanical Tester and experimented for linear and rotational friction process against Pearlitic Gray cast iron rotor. From results, it proved friction coefficients of linear movement is always higher than the rotational movement. The linear friction coefficient was found to be 43% higher on an average than the rotational friction coefficient in both the materials tested at 1MPa and 10 mm/s. These results will help industry in gaining better fundamental understanding about the friction coefficients of rotor- brake contact interfaces.

In this master thesis the influence from process parameters within the Chemical vapour deposition process for a Zirconium Carbon-Nitride coating was investigated regarding growth rate, microstructure and texture. The interest in utilizing Zirconium Carbon-Nitride (Zr(C,N)) is due to its low coefficient of thermal expansion (CTE) relative the currently commonly used wear resistant coatings of Titanium-Carbon-Nitride (Ti(C,N)). The process parameters studied in this work is the ratio of the partial pressures of Zirconium tetrachloride over Acetonitrile (ZrCl4/CH3CN), addition of Nitrogen respectively hydrochloric acid, partial pressures of the precursors, reactor temperature and total gas flow. By controlling these process parameters one can control the grain size, growth rate within the reactor and texture of the Zr(C,N) coating deposited.

Turbulent fluxes govern the exchange of momentum, heat and moisture between the Earth’s surface and the overlying air. Computations of these fluxes are crucial, particularly over lakes and seas because most of the earth’s surface consists of water. One of the most common methods of calculating turbu- lent fluxes is the bulk method, where the fluxes are expressed with exchange coefficients. With more knowledge of these coefficients, the fluxes can be determined with a higher accuracy. Consequently, the turbulence structure and the exchange of moisture, momentum and heat between the surface and the overlying air can be better understood. The goal of this study was to compute the neutral exchange co- efficients for drag (CDN), heat (CHN) and moisture (CEN) and investigate their dependency on various atmospheric conditions, based on four years of measurements from Lake Erken, located about 70 km east of Uppsala. The coefficients were evaluated against the wind speed, stratification and time over water TOW (the time that the air is above the water before it reaches the tower). A special analysis was done by studying the variation of the coefficients with the wind speed during the UVCN-regime. Another analysis was done to see if the coefficients may have been influenced by non-local processes, e.g. advection from the surroundings. Additionally, normalized standard deviations for the temperature and humidity were evaluated for different stabilities. The results were compared with estimations by the COARE3.0 algorithm (for the dependency on the wind speed and the stability) in a previous report and other earlier studies.  The results indicated that the neutral exchange coefficients were higher and more dispersed during near neutral stratification and low TOWs. The normalized standard deviations also increased during neutral conditions. The explanation for this could be related to the presence of the UVCN-regime or non-local effects such as advection or entrainment from the surroundings. The wind speed had no ob- vious impact on the coefficients. However, the drag coefficient was larger and more spread out in the wind speed range 1-3 m/s. In comparison to earlier studies, the exchange coefficients were higher and scattered to a greater extent. This may be because of a strong UVCN-regime, sustainable non-local influences, relatively steeper waves than open-sea conditions or outliers in the data.

<p>Technological advancements in electronics industry are driven by innovations in device fabrication techniques and development of novel materials. Halide perovskites are one of the latest additions to the semiconductor family. The performance of solid-state devices based on halide perovskites is now competing with other well-established semiconductors like silicon and gallium arsenide. However, the intrinsic instability of three-dimensional (3D) perovskites poses a great challenge in their widespread commercialization. The soft crystal lattice of hybrid halide perovskites facilitates anionic diffusion which impacts material stability, optoelectronic properties, and solid-state device performance.</p> <p>Two-dimensional (2D) halide perovskites with organic capping layers have been used for improving the extrinsic stability as well as suppressing intrinsic anionic diffusion. Nevertheless, a fundamental understanding of the role of compositional tuning, especially the impact of organic cations, in inhibiting anionic diffusion across the perovskite-ligand interface is missing. In our research, we first developed a library of atomically sharp and flat 2D heterostructures between two arbitrarily determined phase-pure halide perovskite single crystals. This platform was then used to perform a systematic investigation of anionic diffusion mechanism and quantify the impact of structural components on anionic inter-diffusion in halide perovskites. </p> <p>Stark differences were observed in anionic diffusion across 2D halide perovskite lateral and vertical heterostructures. Halide inter-diffusion in lateral heterostructures was found to be similar to the classical Fickian diffusion featuring continuous concentration profile evolution. However, vertical heterostructures show a “quantized” layer-by-layer diffusion behavior governed by a local free energy minimum and ion-blocking effects of the organic cations. For both lateral and vertical migrations, halide diffusion was found to be faster in perovskites with larger inorganic layer thickness. The increment becomes less apparent as the inorganic layer thickness increases, akin to the quantum confinement effect observed for band gaps. Furthermore, we found that bulkier and more rigid π-conjugated organic cations inhibit halide inter-diffusion much more effectively compared to short chain aliphatic cations. These results offer significant insights into the mechanism of anionic diffusion in 2D perovskites and provide a new materials platform for heterostructure assembly and device integration.</p>

A turbulence model was developed for computing surface velocity coefficients and discharge under steady, uniform flow conditions for rectangular and compound open-channel cross sections. Reynolds-Average Navier-Stokes (RANS) equations, Reynolds stress equations, and kinetic energy and dissipation equations were applied in the model using the finite-volume method with the SIMPLER algorithm. The models show graphical results of the velocity distributions in the longitudinal bed slope direction, secondary velocities, pressure, turbulence kinetic energy, and kinetic energy dissipation rate across the cross section. Also, the surface velocity coefficients were computed at increments of one-eighth of the base width from the vertical walls to the center of the cross section, and the submergence depth of the floating object from zero to 30 cm, with a 5-cm depth increment. Four different sets of Reynolds stress equations (one set by Boussinesq hypothesis and three sets of algebraic stress model) were used to calculate the results. Only one version of the algebraic stress model was successful in predicting the depression of the maximum streamwise velocity below the water surface. The model was calibrated and verified using laboratory data collected at Utah State University. Calculated discharges from the turbulence model had very good agreement with the laboratory data. The surface velocity coefficients from model results were generally lower than the results from the laboratory data, but higher than the values published by the United States Bureau of Reclamation. Standard cross sections of rectangular and compound cross sections were defined to simulate the model results and model sensitivity to parameter changes. The model results were summarized to show the relationship between surface velocity coefficient and channel characteristics compared with the published values by the USBR. For rectangular cross sections, the coefficients from the model are higher than the published USBR values. But the coefficients from the model and USBR are in very close agreement for the tested compound cross sections. The published coefficients by the USBR are a function of only average water depth. However, the model results show that the coefficients are also related to channel size, surface roughness height, float submergence depth, and lateral location of the float object. These factors should be included in the determination of the surface velocity coefficient to improve the discharge estimations from the application of the float method.

This study was designed to discover developmental trends in task persistence (TP). It was hoped that the results would suggest when and for what groups a task persistence (TP) curriculum is crucial. To study this development a sample of two, four, and six year old children were given a "work" task. The task required 120 subjects (Ss) to sort and fold 33 items of clothing and linen. After the task instructions and demonstration, the experimenter did not intervene with reinforcers or further directions. The dependent variables investigated were time spent on the task, time spent away from the task, and number of tasks completed. The independent variables were age, race (Black and White), sex, and social class (advantaged and disadvantaged). The data were analyzed with analysis of variance, Pearson's Product-Moment Correlation, and chi square. The results indicated that older children spent significantly more time on task and significantly less time away from task than younger children. Black children spent significantly more time (than White children) on and away from the task at all ages. Advantaged children spent significantly more time (than disadvantaged children) on task at all ages and significantly less time away from task at ages two and four. Advantaged and disadvantaged subjects were not differentiated by the time spent away from the task at age six. These results imply that task persistence training programs could begin as early as age two. They also suggest that certain subgroups (i.e., disadvantaged White) may require more intensive task persistence training then other subgroups (i.e., advantaged Black). Completion of tasks (CT) significantly differentiated six year olds from two and four year olds, but failed to differentiate two and four year olds. Tasks were completed significantly more often at ages two and four by males than females and by advantaged than disadvantaged children. However, these differences disappeared by age six. Since the differences faded at age six, the use of completion of tasks training as a general curriculum goal may not be warranted. Some of the most surprising results were described by the significant correlation coefficients. The total time spent on the task was negatively related to completion of task. Completion of task was positively related to the time spent away from the task and number of times away from task. These findings suggest that brief periods of absence from a task may improve the chances of completing the task. Therefore, optimal "work" performance for early childhood education may be realized by programming frequent, brief "breaks." A secondary purpose of the study was to investigate verbalizations expressed during the experimental sessions. To study this variable, a verbatim record was established and maintained for each subject. The verbalizations were then totaled and classified as task relevant or irrelevant. The results were analyzed with an analysis of variance (age x race x sex x social class) and Pearson's Product Moment Correlation. Although the number of verbalizations increased with age, the differences between ages four and six were not significant. This finding may reflect a shift to covert verbal mediation during "work" performance on or about age four. The developmental patterns of verbalizations were different for boys and girls. The girls used more overt verbalizations (than boys) at ages two and four; however, at age six the girls' number of verbalizations decreased noticeably. The verbalizations of boys increased with age. At age six, they used more verbalizations than the girls. The writer concluded that this finding reflected advanced verbalization skills in the girls. If the conclusion is valid, the results may mean that overt verbalizations are more necessary for boys to organize their experiences. White children used significantly more task relevant verbalizations than Black children. This suggests that early childhood educational programs for predominately Black populations may need to stress task relevant verbalization training more than programs which serve predominately White populations. Disadvantaged children used more task irrelevant verbalizations at ages two and six than advantaged children. Apparently, they need extra emphasis on task oriented verbalization training. When considered with the previous paragraph, the disadvantaged Black population has the greatest need for task relevant verbalization training.

This thesis studies novel and efficient computational sampling methods for appli- cations in three types of stochastic inversion problems: seismic waveform inversion, filtering problems, and static parameter estimation. A primary goal of a large class of seismic inverse problems is to detect parameters that characterize an earthquake. We are interested to solve this task by analyzing the full displacement time series at a given set of seismographs, but approaching the full waveform inversion with the standard Monte Carlo (MC) method is prohibitively expensive. So we study tools that can make this computation feasible. As part of the inversion problem, we must evaluate the misfit between recorded and synthetic seismograms efficiently. We employ as misfit function the Wasserstein metric origi- nally suggested to measure the distance between probability distributions, which is becoming increasingly popular in seismic inversion. To compute the expected values of the misfits, we use a sampling algorithm called Multi-Level Monte Carlo (MLMC). MLMC performs most of the sampling at a coarse space-time resolution, with only a few corrections at finer scales, without compromising the overall accuracy. We further investigate the Wasserstein metric and MLMC method in the context of filtering problems for partially observed diffusions with observations at periodic time intervals. Particle filters can be enhanced by considering hierarchies of discretizations to reduce the computational effort to achieve a given tolerance. This methodology is called Multi-Level Particle Filter (MLPF). However, particle filters, and consequently MLPFs, suffer from particle ensemble collapse, which requires the implementation of a resampling step. We suggest for one-dimensional processes a resampling procedure based on optimal Wasserstein coupling. We show that it is beneficial in terms of computational costs compared to standard resampling procedures. Finally, we consider static parameter estimation for a class of continuous-time state-space models. Unbiasedness of the gradient of the log-likelihood is an important property for gradient ascent (descent) methods to ensure their convergence. We propose a novel unbiased estimator of the gradient of the log-likelihood based on a double-randomization scheme. We use this estimator in the stochastic gradient ascent method to recover unknown parameters of the dynamics.

The Abraham Solvation Parameter Model (ASPM) is a linear, free-energy relationship that can be used to predict various solute properties based on solute-solvent interactions. The ASPM has been used to predict log (K or Cs,organic/Cs,gas) values, as well as log (P or Cs,organic/Cs,water) values for solute transfer into the following organic solvents: 2-methoxyethanol, 2-ethoxyethanol, 2-propoxyethanol, 2-isopropoxyethanol and 2-butoxyethanol. The derived log (K or Cs,organic/Cs,gas) correlations describe the experimental data to within 0.14 log units (or less). The derived log (P or Cs,organic/Cs,water) correlations describe the experimental data to within 0.16 log units (or less). The ASPM has also been used to predict the enthalpies of solvation of organic solutes dissolved in the following solvents: acetic acid, dimethyl carbonate, diethyl carbonate, 1-butanol, 1-pentanol, 1-hexanol. The derived enthalpy of solvation correlations, using the L solute descriptor, describe the experimental data to within 2.50 log units (or less). The derived enthalpy of solvation correlations, using the V solute descriptor, describe the experimental data to within 3.10 log units (or less). Validation analyses have been performed on several of the correlations; and, as long as the solute descriptors fall within the given ranges as reported, the original correlations show good predictive ability for determining 1) solute transfer into, and 2) enthalpy of solvation for the aforementioned solvents.