Compact Solid-State Marx Generator Design
Explore the source record for details and available documents.
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
The Gaussian process (GP) is a widely used method for analyzing large-scale data sets, including spatio-temporal measurements of nonlinear processes that are now commonplace in the environmental sciences. Traditional implementations of GPs involve stationary kernels (also termed covariance functions) that limit their flexibility, and exact methods for inference that prevent application to data sets with more than about 10,000 points. Modern approaches to address stationarity assumptions generally fail to accommodate large data sets, while all attempts to address scalability focus on approximating the Gaussian likelihood, which can involve subjectivity and lead to inaccuracies. In this work, we explicitly derive an alternative kernel that can discover and encode both sparsity and nonstationarity. We embed the kernel within a fully Bayesian GP model and leverage high-performance computing resources to enable the analysis of massive data sets. We demonstrate the favorable performance of our novel kernel relative to existing exact and approximate GP methods across a variety of synthetic data examples. Furthermore, we conduct space–time prediction based on more than 1 million measurements of daily maximum temperature and verify that our results outperform state-of-the-art methods in the Earth sciences. More broadly, having access to exact GPs that use ultra-scalable, sparsity-discovering, nonstationary kernels allows GP methods to truly compete with a wide variety of machine learning methods.
The Princeton Field-Reversed Configuration (PFRC) nuclear fusion reactor concept is an innovative approach to fusion power generation prioritizing low neutron production and small size. Here, a combination of analytical modeling and numerical simulation shows that the novel heating approach generates an FRC with closed field lines. Simulation data from a single-particle Hamiltonian code predicts ms-scale plasma heating in reactor-scale conditions while PIC codes predict formation of warm FRC plasmas from initial mirror fields. The PFRC-1 and PFRC-2 experiments have heated electrons to energies well in excess of 100 eV and plasma durations to 300 ms, more than 10 4 times longer than the predicted tilt instability growth time. From these data, we have created a development plan and anticipated performance metrics for a fusion reactor based on the PFRC concept. The resulting 1–10 MW PFRC reactors would be suitable for diverse applications, from submarines to urban environments to space propulsion. PFRC is a steady-state, driven magnetic confinement device. Plasma, inside a cylindrical array of coils, is confined and heated by external RF antennae. PFRC would be ultra-low radiation due to both its fuel and small size. The choice of advanced fuels, deuterium and helium-3 (D– 3 He), may be enabled by the high-β FRC configuration. The small size of the reactor would enable rapid exhaust of the dangerous tritium ash. Low radiation would make the reactor safer to operate and, in combination with simple geometry and small size, dramatically lowers development and maintenance costs. This review paper gives an introduction to the physics of the PFRC and a summary of the PFRC-2 experiment results to date. It then discusses the future program plan and how PFRC reactors would be commercialized.
Melt wires are a passive sensor used to determine peak temperatures during a test. Traditional melt wires are commonly used in test reactor experiments such as in the Advanced Test Reactor (ATR). However, the conditions within a reactor present significant challenges towards test design due to space limitations and the harsh environment. For example, some test capsules have only a couple millimeters in diameter available for instrumentation, which is too small to accommodate a traditional melt wire package, and they are ultimately filled to capacity when they are immersed in molten metal. To enable instrumentation for space limited applications, peak temperature sensing capabilities paired with additive manufacturing options have been utilized to develop printed melt wires for peak irradiation temperature detection. Here, we report on the fabrication of miniaturized melt wire chips with a melting temperature ~960 °C with printed silver nanoparticle ink. This study will advance the development of unique temperature sensors capable of sensing user specified temperature ranges within the harsh environment of irradiation testing.
Not Available
Magnetocaloric heat pumping (MCHP) promises to be more efficient than traditional vapor compression while also eliminating the deleterious effects of gaseous refrigerants. While MCHP devices have shown the temperature spans and efficiencies needed for different heating and cooling applications, they struggle to become commercially viable due to their large size and mass, and resultant high cost. This paper evaluates a baseline MCHP device and explores methods to boost its system power density (SPD). The key components of the baseline system are the gadolinium packed-particle bed active magnetic regenerator (AMR) and a magnetic source composed of permanent magnets and high permeability magnetic steel. To enhance the SPD, the paper evaluates maximizing the AMR volume, opting for first-order magnetocaloric materials, optimizing the magnet and AMR geometry, and reducing the size of magnets and magnetic steel parts. At larger thermal powers, increasing the AMR diameter and the number of magnetic poles were evaluated. Using finite element models, solid models, and estimates of magnetocaloric material performance, thermal powers ranging from 37 W to 44 kW at a nominal 10 K temperature span were projected, and SPD was estimated to improve from 6 W/kg to 81 W/kg. Neglecting end effects, an upper limit of 114 W/g is estimated. Compared to SPD of off-the-shelf compressors with similar environment temperatures, MCHP power density using gadolinium is competitive up to roughly 200 W of cooling power. This is extended to 1 kW when using LaFeSi alloys and up to 3 kW in the limiting case. In conclusion, these results indicate that the performance and mass of MCHP can match that of compressors, which is a critical step toward cost-competitive magnetocaloric technology.
Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, 79 Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3×10 5 yr) and its low adsorption to clay (K D < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na + , Ca 2+ , and a Na + -Ca 2+ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. Further, the results were modeled using a reactive transport modeling approach to determine values of porosity (ε), D e (effective diffusion coefficient), and K D (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (D e =1.68×10 -10 m 2 s -1 ) compared to Na-montmorillonite (De=7.83×10 -11 m 2 s -1 ). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca 2+ compared to Na + , which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (D e = 1.03×10 -11 m 2 s -1 ) > Na–Ca (D e = 2.12×10 -12 m 2 s -1 ) > Na (D e = 1.28×10 -12 m 2 s -1 ). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.
The bacterial cytoplasm is characterized by a distinctive membrane-less organelle, the nucleoid, which harbors the chromosomal DNA. Here, we investigate the steric effects of dynamic processes associated with transcription and translation on the structure of this organelle using coarse-grained molecular dynamics simulations that incorporate out-of-equilibrium reactions. Our model captures the scale of the entire cell and incorporates a reaction-diffusion system for ribosomes and polyribosomes, coupling their nonequilibrium kinetics to DNA excluded volume interactions. Our findings demonstrate that out-of-equilibrium reactions increase the size of the nucleoid and the number of ribosomes in this subcellular region. In addition, we show that nucleoid size is proportional to transcriptional activity. Our model reproduces the time-dependent change in nucleoid size observed in rifampicin treatment experiments, where the pool of polyribosomes is depleted. Furthermore, we find that these active processes are essential for complete sister chromosome separation and correct nucleoid positioning within the cell. Overall, our study reveals the effects of the central dogma processes on the internal organization and localization of bacterial nucleoids.
We report automation of irradiated bismuth target dissolution and astatine recovery from nitric acid media has been achieved at Texas A&M University. This process can be controlled remotely; it does not require any chemical treatment or evaporation of dissolution solution prior to the separation of above-mentioned elements on an extraction chromatography column, making the final product ready within 20 min. The accompanying radio-impurities have been identified and successfully separated from astatine, leading to greater than 99% radiopurity of the desired fractions. The system consists of only one pump and a set of LabVIEW controlled valves, and allows the connection of up to 10 different columns, providing the opportunity to prepare a variety of air dry columns, which can be different column geometries, containing astatine ready for further chemistry or shipment to desired facilities.
Not Available
Based on our latest detailed chemical reaction mechanism, C3MechV4.0, we have developed two reduced reaction mechanisms—C3MechLite and C3MechCore—targeting C 0 –C 3 chemical species including NH 3 . C3MechLite (61 species), contains a number of species comparable to GRI-Mech (53 species), that can accurately predict the combustion characteristics of hydrogen, carbon monoxide, ammonia, methane, natural gas, nitrogen oxides, and their mixtures for a wide range of conditions. C3MechCore (118 species) targets a more comprehensive range of C 0 –C 3 fuels, including ammonia, methanol, ethanol, and dimethyl ether. Both mechanisms demonstrate predictive accuracy comparable to C3MechV4.0 for the combustion characteristics of the target fuels. C3MechLite is designed with a component library structure, enabling further reduction in mechanism size depending on the fuel(s) of interest for 2D/3D numerical simulations. Various combinations of component libraries were validated, and the average prediction error remains within 1 % compared to C3MechLite. Furthermore, the mechanism was applied to 3D LES simulations of H 2 lifted flames and was confirmed to reproduce flame characteristics with high accuracy. C3MechLite and its component library structure enable high-fidelity and computationally efficient chemical kinetic mechanisms, paving the way for application in more complex combustion simulations.