Research shows that use of high fidelity simulation (HFS) as a teaching strategy requires extensive amounts of faculty time and financial resources for faculty development and equipment. This project study addressed the challenges encountered in the integration of HFS into a Midwestern metropolitan baccalaureate nursing program. The purpose of this qualitative case study was to explore perceptions of nursing faculty about best practice elements for successful integration of HFS into undergraduate nursing programs. Guiding questions were developed using Donabedian's structure-process-outcome model and focused on faculty perceptions related to successful implementation of simulation in their programs. Purposeful sampling was used to select 22 faculty who had integrated HFS into 5 regional baccalaureate nursing programs in metropolitan areas of 2 Midwestern states. Nine participants completed an online interview tool developed by the researcher and designed to elicit responses to open-ended questions about barriers encountered, methods used to overcome those barriers, first impressions about conducting HFS, perceptions of successful integration, and incentives to using HFS. Data were coded and analyzed to identify themes. Emergent themes included the need to identify specific courses for HFS, ensure participation of faculty teaching didactic courses, use nationally recognized principles for HFS implementation, implement consistent methods of debriefing, and use formal written plans. Findings from the study were used to design a staff development initiative to facilitate planning and establishment of HFS in a nursing curriculum. Positive social change may occur when faculty and administrators use project guidelines to develop sound practices for integrating HFS into the nursing curriculum.

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Simulation and experiential training have been incorporated into medical school training for decades. The utilization of medical simulations has become an invaluable tool in healthcare education and training. However, circumstances such as limited resources, geographical constraints, or global health crises may hinder the feasibility of conducting in-person medical simulations. In these scenarios, virtual medical simulations emerge as a compelling alternative. While there are many ways to accomplish experiential-based learning, many faculty and students feel Socratic learning styles provide the best learning experience. As medical students had just finished a predominantly virtual preclinical year due to the COVID-19 pandemic, the research was interested in understanding students’ perceptions of virtual and in-person experiential learning activities. The primary goal of this study is to compare medical students’ perceptions of the quality and value of in-person versus virtual experiential learning during their pediatric clerkship.

Fast breeder nuclear reactors use liquid metals such as Sodium (Na), Sodium-Potassium (Na-K), and Lead (Pb) as coolants since these liquids have high thermal conductivity, high thermal diffusivity, and lower heat capacity compared to water and air, thus involving low Prandtl numbers (Pr). However, liquid metals solidify at room temperature which poses challenges for experimental studies, making computational fluid dynamics (CFD) is considered a valuable analysis and design tool. Furthermore, the accurate modeling of turbulent heat transfer in low Pr flows remains one of the main challenges due to the gap between momentum and turbulent thermal diffusion. The study aims to address this challenge by enhancing the understanding of liquid metal coolant behavior and improving the accuracy of turbulence models in these types of fluids under different convective conditions. This research consists of two main parts, where the first one encompasses generating a DNS dataset for Reτ = 640, Pr = 0.004, 0.025, and 0.71, and Gr = 0 and 17.4×106 to supplement existing DNS databases, providing a more comprehensive foundation for turbulence models validation, and the second one envelop assessing the predictive capabilities of linear eddy viscosity-based Reynolds average Navier Stokes (RANS), Partially-average Navier stokes (PANS), and large eddy simulation (LES). The assessment covers four test cases ranging from canonical turbulent flow to more complex flow regimes involving separating and reattaching flows under different convective conditions for Reynolds numbers (Re) ranging from 640 to 40,341 and Pr varying from 0.004 up to 0.71. DNS results improve the understanding of Re, Pr, and buoyancy effects on both mean turbulent flows. Analysis reveals that buoyancy enhances heat transfer more significantly for lower Re and Pr. Furthermore, buoyancy alters flow and thermal structures by enhancing and reducing turbulence on both aiding and opposing sides, affecting heat transport. In addition, the assessment of different turbulence models demonstrates the superiority of LES compared to other models where the average of the prediction errors is 6% over all the cases aligning with findings from the excessive literature review.

Nursing faculty are utilizing high-fidelity patient simulation (HPS) with debriefing to help engage nursing students in making competent clinical decisions. This quasi-experimental study examined the use of HPS with debriefing and students’ ability to make nursing care decisions using standardized exams. The experimental group received debriefing after HPS and the control group did not receive debriefing after HPS. The pre- and post-test assessed participants’ ability to make clinical care decisions. The analysis of the pre-test and post-test HESI scores showed that there was no significant difference between the two groups.

Energy management systems (EMSs), implemented in the electronic control unit (ECU) of an actual vehicle with electri ed powertrain, is a much simpler version of the theoretically developed EMS. Such simpli cation is done to accommodate the EMS within the given memory constraint and computational capacity of the ECU. The simpli cation should ensure reasonable performance compared to theoretical EMS under real-life driving scenarios. The process of simpli cation must be effective to create a versatile and utilitarian EMS. The reinforcement learning-based controllers feature pro table characteristics in optimizing the performance of controllable physical systems as they do not mandatorily require a mathematical model of system dynamics (i.e. they are model-free). Quite naturally, it can aspired to testify such prowess of reinforcement learning-based controllers in achieving near-global optimal performance for energy management system (supervisory) of electri ed powertrains. Before deployment of any supervisory controller as a mainstream controller, they should be essentially scrutinized through various levels of virtual simulation platforms with an ascending order of physical system emulating-capability. The controller evolves from a mathematical concept to an utilitarian embedded system through a series of these levels where it undergoes gradual transformation to finally become apposite for a real physical system. Implementation of the control strategy in a Simulink-based forward simulation model could be the first stage of the aforementioned evolution process. This brief will delineate all the steps required for implementing an reinforcement learning-based supervisory controller in a forward simulation model of a hybrid electric vehicle. A novel framework of loss-minimization based instantaneous optimal strategy is introduced for the energy management system of a multi-mode hybrid electric powertrain in this brief. The loss-minimization strategy is flexible enough to be implemented in any architecture of electrified powertrains. It is mathematically proven that the overall system loss minimization is equivalent to the minimization of fuel consumption. An online simulation framework is developed in this article to evaluate the performance of a multi-mode electrified powertrain equipped with more than one power source. An electrically variable transmission with two planetary gear-set has been chosen as the centerpiece of the powertrain considering the versatility and future prospects of such transmissions. It is noteworthy to mention that a novel architecture topology selected for this dissertation is engendered through a series of rigorous screening process whose workflow is presented here with brevity. One of the legitimate concern of multi-mode transmission is it's proclivity to contribute discontinuity of power-flow in the downstream of the powertrain. Mode-shift events can be predominantly held responsible for engendering such discontinuity. Advent of dynamic coordinated control as a technique for ameliorating such discontinuity has been substantiated by many scholars in literature. Hence, a system-level coordinated control is employed within the energy management system which governs the mode schedule of the multi-mode powertrain in real-time simulation. / Thesis / Doctor of Philosophy (PhD)

Simulation, in its many forms, has been a part of nursing education and practice for many years. The use of games, computer-assisted instruction, standardized patients, virtual reality, and low-fidelity to high-fidelity mannequins have appeared in the past 40 years, whereas anatomical models, partial task trainers, and role playing were used earlier. A historical examination of these many forms of simulation in nursing is presented, followed by a discussion of the roles of simulation in both nursing education and practice. A viewpoint concerning the future of simulation in nursing concludes this article.

We manipulate two superconducting qubits using digital microwave electronics. Starting fromtheir characterization, we develop a real-time reset scheme and implement the iSwap gate. Thequbits’ parameters are obtained using standard single-qubit characterization techniques, such asRabi and Ramsey oscillations and frequency sweep of the resonators. We also characterized theexperimental setup, including finding the working point of a Josephson Parametric Amplifierand the coupler between the two qubits. We solve the linear differential equations that modelthe resonator, in order to design a high-fidelity, single-shot qubit-measurement pulse shape,which actively empties the cavity. Using this pulse, we achieve a readout assignment fidelity of99.9%. The readout is formed in real-time using template matching. In addition, we implementa conditional reset of the qubit’s state in 1.4 μs, which resets the excited state population from5.4% to 0.5%. We simulate the cavity using QuTip to further optimize the readout pulse.Furthermore, we characterize the third energy level of the qubit to implement a qutrit readoutand observe a second excited state population of 0.3%, in accordance with theory. Finally,we implement the iSwap gate that, together with single-qubit gates, constitute a set of universalquantum gates, where we swap the 95.4% of the quantum state between the qubits in 690 ns. Allexperiments, including the pulse events and synchronization of the readout and feedback, wereperformed using a digital microwave platform based on a radio-frequency-on-a-chip system,and implemented using a Python interface. / Vi manipulerar två supraledande kvantbitar med digital mikrovågselektronik. Vi utgår frånderas karakterisering och utvecklar en realtidsåterställningsschema och implementerar iSwap-grinden. Kvantbitarnas parametrar erhålls med standardtekniker för karakterisering av enskildakvantbitar, såsom Rabi- och Ramsey-svängningar och frekvenssvep av resonatorerna. Vikaraketeriserar även den experimentella uppställningen, där vi finner arbetspunkten för enJosephson-parametrisk förstärkare, samt kopplaren mellan de två kvantbitarna. Vi löser delinjära differentialekvationerna som modellerar resonatorn, i syfte att designa en pulsformför en enkelmätning av en kvantbit med hög tillförlitlighet som aktivt tömmer kaviteten.Med denna puls uppnår vi en avläsningstillförlitlighet på 99,9 %. Avläsningspulsen bildas irealtid med hjälp av mallmatchning. Därtill implementerar vi en villkorlig återställning avkvantbitens tillstånd på 1,4 μs, vilket återställer den exciterade tillståndspopulationen från 5,4 %till 0,5 %. Vi simulerar kaviteten med QuTip för att ytterligare optimera avläsningspulsen.Dessutom karakteriserar vi den tredje energinivån på kvantbiten för att implementera enså-kallad qutrit-avläsning och observerar en andraexciterad tillståndspopulation på 0,3 %,i enlighet med teorin. Slutligen implementerar vi iSwap-grinden som, tillsammans medgrindarna för enskilda kvantbitar, utgör en uppsättning universella kvantgrindar, är vi byter95,4 % av kvanttillståndet mellan våra kvantbitarna på 0,6 μs. Alla experiment, såsompulshändelserna och synkroniseringen av avläsningspulsen och återkopplingspulsen, utfördesmed hjälp av en digital mikrovågsplattform, baserad på ett radiofrekvens-på-ett-chip-system,och implementerades med ett Python-gränssnitt.

<p dir="ltr">This research focuses on understanding and improving various metal additive manufacturing processes. The first half is dedicated to experimental investigations and methods for improving the laser cladding of aluminum alloys. The second half is dedicated to high-fidelity modeling of the laser melting process and methods for reducing the computational burden.</p><p dir="ltr">First, laser cladding is a surface enhancement and repair process in which a high-powered laser beam is used to deposit a thin (0.05 mm to 2 mm) layer of material onto a metal substrate with no cracking, minimal porosity, and satisfactory mechanical properties. In this work, a 4 kW High Power Diode Laser (HPDL) is used with off-axis powder injection to deposit single-tracks of aluminum alloy 6061 powder on a 6061-T6511 substrate. The process parameters were varied to identify the possible processing window in which a successful clad is achieved. Geometrical characteristics were correlated to the processing parameters and the trends were discussed. Microhardness testing was employed to examine the mechanical properties of the clad in the as-deposited and precipitation heat-treated conditions. Transmission electron microscopy (TEM) was used to investigate the precipitate structures in the clad and substrate as an explanation for the hardness variations. Experiments were completed on two substrate widths to understand the effect of domain size on the process map, layer size, and hardness.</p><p dir="ltr">Second, a method to deposit quench-sensitive age-hardening aluminum alloy clads is presented, which produces a hardness similar to the T6 temper without the requirement of solution heat treatment. A high-powered diode laser is scanned across the workpiece surface and material feedstock is delivered and melted via off-axis powder injection. The cladding process is immediately followed by quenching with liquid nitrogen, which improves the cooling rate of the quench-sensitive material and increases the hardness response to subsequent precipitation heat treatment. The method was demonstrated on the laser cladding of aluminum alloy 6061 powder on 6061-T6511 extruded bar substrates of 12.7 mm thickness. Single-track single-layer clads were deposited at a laser power of 3746 W, scan speed of 5 mm/s, and powder feed rate of 18 g/min. The in-situ liquid nitrogen quenching improved the clad hardness by 15.7% from 73.1 HV to 84.6 HV and the heat-affected zone hardness by 19.3% from 87.1 HV to 103.9 HV. Extending the process to multi-track multi-layer cladding further increased the clad hardness to 89.3 HV, close to the T6 temper hardness of 90 HV. Transmission electron microscopy revealed the increased precipitate density in the liquid nitrogen quenched clads was responsible for the higher hardness.</p><p dir="ltr">Third, a high-fidelity model of the molten pool dynamics during the laser melting of metals is presented for accurate prediction of the molten pool size and morphology at operating conditions relevant to laser powder bed fusion. The goal of this research is to improve the accuracy of previous models, present a thorough experimental validation, and quantify the model's sensitivity to various properties and parameters. The model is based on an OpenFOAM compressible Volume-of-Fluid (VOF) solver that is modified to include the physics relevant to laser melting. Improvements to previous works include the utilization of a compressible solver to incorporate temperature-dependent density, implementation of temperature-dependent surface tension and viscosity, utilization of the geometric isoAdvector VOF method, selection of a least squares method for the gradient calculations, and careful selection of physically accurate material properties. These model improvements resulted in accurate prediction of the molten pool depth and width (mean absolute error of 7% and 5%, respectively) across eleven operating conditions spanning the conduction and keyhole regimes with laser powers ranging from 100 W to 325 W and scan speeds from 250 mm/s to 1,200 mm/s. The validation included in-house experiments on 304 L stainless steel and experiments from the National Institute of Standards and Technology on Inconel 718. Incorporating the large density change from the ambient temperature to vaporization temperature and utilizing a least squares scheme for the gradient calculation were identified as important factors for the predictive accuracy of the model. The model sensitivity to the wide range of literature values for laser absorptivity, liquid thermal conductivity, and vaporization temperature was quantified. Literature sources were analyzed to identify the most physically accurate property values and reduce the impact of their variability on model predictions.</p><p dir="ltr">Finally, an original surrogate model is presented for the accurate and computationally efficient prediction of molten pool size in multi-track laser melting over a large domain at operating conditions relevant to laser powder bed fusion. The thermal models available for the laser melting process range from heat conduction models to high-fidelity computational fluid dynamics (CFD) models. High-fidelity models provide a comprehensive treatment of the relevant physics of heat conduction, fluid flow, solidification, vaporization, laser propagation, etc. A carefully implemented high-fidelity model is capable of accurately predicting the molten pool dynamics in a broad range of operating conditions. However, the high computational expense limits their application to a few short tracks on small domains. Conduction models, on the other hand, are orders of magnitude cheaper to evaluate but lack the necessary physics for accurate predictions. This research presents a surrogate model that combines the computational efficiency of the conduction model with the accuracy of the high-fidelity model. A conduction model and high-fidelity model are simulated over a small scan pattern to generate training data of the highly transient molten pool depth and width. A surrogate model, consisting of a fuzzy basis function network, is trained with the aforementioned data. The conduction model is then simulated over a larger scan pattern, the results are input into the trained surrogate model, thereby outputting high-fidelity predictions of the molten pool size over a larger scan pattern. Comparison with experimental results shows this surrogate modeling framework provides reasonably accurate predictions of the molten pool size and is a valid way to extend computationally intensive high-fidelity models to larger and more industrially relevant scan patterns.</p>

Indiana University-Purdue University Indianapolis (IUPUI) / In this thesis, an explicit time integration code which integrates multibody dynamics and the discrete element method is used for modelling the excavation and moving operation of cohesive soft soil (such as mud and snow) by bulldozers. A soft cohesive soil material model (that includes normal and tangential inter-particle force models) is used that can account for soil compressibility, plasticity, fracture, friction, viscosity and gain in cohesive strength due to compression. In addition, a time relaxation sub-model for the soil plastic deformation and cohesive strength is added in order to account for loss in soil cohesive strength and reduced bulk density due to tension or removal of the compression. This is essential in earth moving applications since the soil that is dug typically becomes loose soil that has lower shear strength and lower bulk density (larger volume) than compacted soil. If the model does not account for loss of soil shear strength then the dug soil pile in front of the blade of a bulldozer will have an artificially high shear strength. A penalty technique is used to impose joint and normal contact constraints. An asperity-based friction model is used to model contact and joint friction. A Cartesian Eulerian grid contact search algorithm is used to allow fast contact detection between particles. A recursive bounding box contact search algorithm is used to allow fast contact detection between the particles and polygonal contact surfaces. A multibody dynamics bulldozer model is created which includes the chassis/body, C-frame, blade, wheels and hydraulic actuators. The components are modelled as rigid bodies and are connected using revolute and prismatic joints. Rotary actuators along with PD (Proportional-Derivative) controllers are used to drive the wheels. Linear actuators along with PD controllers are used to drive the hydraulic actuators. Polygonal contact surfaces are defined for the tires and blade to model the interaction between the soil and the bulldozer. Simulations of a bulldozer performing typical shallow digging operations in a cohesive soil are presented. The simulation of a rear wheel drive bulldozer shows that, it has a limited digging capacity compared to the 4-wheel drive bulldozer. The effect of the relaxation parameter can be easily observed from the variation in the Bulldozer's velocity. The higher the relaxation parameter, the higher is the bulldozer's velocity while it is crossing over the soil patch. For the low penetration depth run the bulldozer takes less time compared to high penetration depth. Also higher magnitudes of torques at front and rear wheels can be observed in case of high penetration depth. The model is used to predict the wheel torque, wheel speed, vehicle speed and actuator forces during shallow digging operations on three types of soils and at two blade penetration depths. The model presented can be used to predict the motion, loads and required actuators forces and to improve the design of the various bulldozer components such as the blade, tires, engine and hydraulic actuators.