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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-Energy Density Capacitors for Electric Vehicle Traction Inverters

DC bus capacitors take up substantial space in a traction inverter, limiting the traction drive power density. Thus, several commercial capacitor technologies, under consideration for use as DC bus capacitors for electric vehicle traction inverters, were reviewed for their ability to optimize the volume of traction inverters and are evaluated in this paper. Three promising capacitor technologies--film, ceramic, and PLZT have been selected for detailed experimental characterization. Experimental results for equivalent series resistance, equivalent series inductance, and effective capacitance with respect to DC bias voltage for various operating frequencies and temperatures are presented. The results reveal the superiority of the PLZT capacitor in terms of power density, current conduction capability, and redundancy.

Chowdhury, Shajjad↗
DOE OSTI2024

Slope Efficiency and Voltage Reduction at High Current Densities in AlInGaAs Diode Lasers

Here, the slope efficiency and drive voltage of broad area AlInGaAs laser diodes near 865 nm is observed to decrease significantly under quasi-CW pulsed operation at currents well above threshold, in a manner that cannot be explained by thermal effects or carrier leakage over heterojunction barriers. Simulations show that the slope efficiency reduction is explicable by increased free carrier absorption in the waveguide region. Empirical formulas are presented to represent these effects in a closed analytic form suitable for use in simulators for diode-pumped laser systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Deep Koopman Neural Network for Analyzing High-Energy-Density Simulations of Electrical Wire Explosions

Megaampere-scale electrical wire experiments (EWEs) provide a platform for studying magnetohydrodynamic (MHD) instability growth in magneto-inertial fusion (MIF) devices. Even when nonlinear simulations of these experiments can digitally reproduce much of the experimentally observed instability growth, interpreting the results and understanding mode growth and evolution can be non-trivial. As a first step toward providing better interpretation of these simulation features, this work investigates the use of a deep neural network that uses Koopman operator theory to analyze the dynamics of pulsed-power-driven explosions of EWEs. This deep neural network is trained on 1-D resistive MHD simulations of EWEs. This neural network learns to transform the nonlinear data into a lower-dimensional representation where the time dynamics are linear. Layers of this neural network are shown to learn features of the simulations, including the locations of shock waves and different physical regimes of the simulation. Using the learned features, the network can compress a time state of the simulation consisting of 5120 data point into a 36-parameter lower-dimensional latent space embedding. Furthermore, these embeddings are shown to be clustered in the latent space by initial radius and time state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗
DOE OSTI2026

Systematics of the chemical freeze-out line in the high baryon density regime explored at SIS100

The systematic uncertainties of chemical freeze-out fits at SIS100 energies (Au+Au reactions at $\sqrt{s_{NN}}$ = 3 – 5 GeV) are studied using UrQMD simulations. Although hadron production in UrQMD does not occur on a sharp chemical freeze-out hyper-surface, the extracted fit quality is shown to be very good. The extracted chemical parameters depend on the selected hadron species as well as the underlying equation of state (EoS) of the matter. Including light nuclei and anti-protons in the fit increases the expected freeze-out temperature, while a stiffer EoS increases the obtained chemical potential. Similarly, the baryon densities extracted by the thermal fits depend on the choice of hadrons as well as the underlying equation of state. These results are important for the upcoming CBM@FAIR physics program and highlight that a degree of caution is advised when one relates the chemical freeze-out curve to features on the QCD phase diagram like the critical endpoint or a possible phase transition.

Hofmann, Emma Lilith [GSI Helmholtzzentrum für Sch↗
DOE OSTI2022

Verification and Validation of Two Hydrodynamic Methods for Simulations of High Energy Density Physics Problems

A 3D verification and validation suite of test problems is presented and used to evaluate hydrodynamic methods within a radiation hydrodynamics code, xRAGE. These test problems exercise different levels of complexity, building towards ICF problems which in addition to hydrodynamics also include three temperature plasma physics, thermal conduction, and radiation diffusion. Among the problems in the test suite are the Kidder ball problem, the Verney shell problem, and a 5-material compression problem, which exercise different purely hydrodynamic methods implemented within xRAGE. There is excellent agreement between 2D and 3D XRAGE simulation results and between the xRAGE results and the benchmark solutions. Two 3D ICF test problems are also presented, based on an OMEGA direct drive capsule experiment and on a NIF indirect drive capsule experiment. It is demonstrated that the newer unsplit hydrodynamic method in xRAGE produces more vorticity relative to the older default method. For the indirect drive capsule, the 3D simulations are in reasonable agreement with the experimental values of ion temperature and neutron production.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Ultra-compact hybrid silicon:chalcogenide waveguide temperature sensor

We demonstrate a real-time, reusable, and reversible integrated optical sensor for temperature monitoring within harsh environments. The sensor architecture combines the phase change property of chalcogenide glasses (ChG) with the high-density integration advantages of high index silicon waveguides. To demonstrate sensor feasibility, ChG composition Ge 40 S 60 , which is characterized by a sharp phase transition from amorphous to crystalline phase around 415 °C, is deposited over a 50 µ m section of a single mode optical waveguide. The phase transition changes the behavior of Ge 40 S 60 from a low loss to high loss material, thus significantly affecting the hybrid waveguide loss around the phase transition temperature. A transmission power drop of over 40dB in the crystalline phase compared to the amorphous phase is experimentally measured. Moreover, we recover the amorphous phase through the application of an electrical pulse, thus showing the reversible nature of our compact temperature sensor. Through integrating multiple compositions of ChG with well-defined phases transition temperatures over a silicon waveguide array, it is possible to determine, in real-time, the temperature evolution within a harsh environment, such as within a nuclear reactor cladding.

Badamchi, Bahareh (ORCID:0000000193105300)↗
DOE OSTI2022

Generation and Control of Self-Organized Nonlinear Kinetic Structures in High Energy Density Plasmas in the Presence of Intense Magnetic Fields and Ultrashort Laser Pulses

In the project we investigated mechanisms to sculpt phase space by controlling plasma instabilities. We found that linear theory, which applies in the initial growth phase of an instability, allows for initial conditions that can suppress instabilities. This provides a possible mechanism to release the energy available to an instability on demand. We developed various computational techniques that can reduce computational cost of simulations while maintaining or improving physical fidelity. We considered the Buneman instability in the presence of a ponderomotively driven plasma wave to examine the interplay between an instability and steady-state plasma response.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Developing A New NG Super-Absorbent Polymer (NG-SAP) for a Practical NG Storage System with Low Pressure, Ambient Temperature, and High Energy Density

This R&D project proposed a systematical study to develop a new class of NG super-absorbent polymer (NG-SAP) with the objective to achieve similar CNG volumetric storage level ~250 cm 3 -STP/cm 3 and fast sorption-desorption kinetics at ambient temperature but lower operational pressure (<100 bar). We suggested two consecutive research phases, including (i) a systematical investigation of various polymer systems to identify the suitable classes that can exhibit methane (C1) binding energy in the range of 20-25 kJ/mol and then (ii) focusing on the potential class polymers to identify the specific structure and morphology that can achieve the project objective.In first research phase (1st year), the major tasks included design and synthesis of several representative polymers with various structure attributes, examining their molecular structures, pore morphology, and BET surface area as the prepared samples, and then studying their C1 binding energy and sorption capacity.

03 NATURAL GAS↗