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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 37 records · Page 2

Implicit highly-coupled single-ion Hall-MHD formulation for hybrid particle-in-cell codes

The rudiments of a particle-based single-fluid two-temperature magnetohydrodynamic (MHD) algorithm have been outlined in Thoma et al. (2013). The extension of this algorithm to include the effect of Hall physics is described in this paper. An implicit leapfrog version of the algorithm, which allows timesteps large compared to the resistive decay time and other relevant timescales, has recently been added to a hybrid particle-in-cell code. In standard MHD the Hall term in the generalized Ohm’s law can often be neglected when the Hall parameter is small. This term must, however, be retained in regimes where it is non-negligible. The retention of displacement current in Maxwell’s equations avoids the numerical difficulties associated with the whistler mode, which are encountered in standard explicit Hall-MHD codes, and allows the algorithm to be incorporated into hybrid particle-in-cell codes, for which particles may migrate from a kinetic to fluid to MHD description based upon local ambient plasma conditions. A highly-coupled implicit Hall-MHD formalism is presented, in which displacement current can either be retained or neglected. Even when displacement current is neglected, the highly-coupled implicit formalism avoids the restrictive timesteps for the whistler mode in explicit Hall-MHD codes. A comparison of numerical and analytic dispersion analysis demonstrates the feasibility of this approach and establishes relevant constraints to assure numerical stability. The implementation of the algorithm is described, and test simulation results in 1D and 2D in both linear and nonlinear regimes are presented.

97 MATHEMATICS AND COMPUTING↗

Faraday rotation study of plasma bubbles in GeV wakefield accelerators

We visualize plasma bubbles driven by 0.67 PW laser pulses in a plasma of density ne≈5×1017cm−3 by imaging Faraday rotation patterns imprinted on linearly polarized probe pulses of wavelength λpr=1.05 μm and duration τpr=2 or 1 ps that cross the bubble's path at right angles. When the bubble captures and accelerates tens to hundreds of pC of electron charges, we observe two parallel streaks of length cτpr straddling the drive pulse propagation axis, separated by ∼45 μm, in which probe polarization rotates by 0.3° to more than 5° in opposite directions. Accompanying simulations show that they result from Faraday rotation within portions of dense bubble side walls that are pervaded by the azimuthal magnetic field of accelerating electrons during the probe transit across the bubble. Analysis of the width of the streaks shows that quasi-monoenergetic high-energy electrons and trailing lower energy electrons inside the bubble contribute distinguishable portions of the observed signals, and relativistic flow of sheath electrons suppresses Faraday rotation from the rear of the bubble. The results demonstrate favorable scaling of Faraday rotation diagnostics to 40× lower plasma density than previously demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Power flow in magnetically insulated transmission lines with ion backscatter effects

Ion backscattering off of surfaces in magnetically insulated transmission lines (MITLs) is often ignored in kinetic simulations of MITL power flow. Backscattering reduces ion current losses and the surface impact heating, which dictates the rate at which surface-adsorbed contaminants are liberated into the anode–cathode gap. Backscatter probabilities are difficult to implement in a kinetic code because there are limited data for incident ion energies less than a few keV. This paper presents an analytic model based on the Rutherford scattering formula that reproduces the measured backscatter probabilities at high incident energies and transitions to the highly reflective behavior expected at low incident energies. The backscatter model is implemented in power flow simulations, which are validated with current loss experiments conducted on the 0.4 TW Mykonos accelerator at Sandia National Laboratories. This simulation setup is then used in a high-current Z-machine shot. In conclusion, backscatter effects are found to be unimportant in the low-current Mykonos regime but significantly reduce current losses at the Z-machine scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydro-Mechanical Measurements of Sheared Crystalline Rock Fractures With Applications for EGS Collab Experiments 1 and 2

We present hydro-mechanical measurements that characterize shear on natural fractures in schist, amphibolite, and rhyolite specimens from the enhanced geothermal system (EGS) Collab Project's Experiment 1 and 2 sites (E1 and E2) at the Sanford Underground Research Facility. We employed a triaxial direct shear method augmented with X-ray imaging to perform hydroshearing (injection-induced shearing) and mechanical shearing on naturally fractured specimens at in situ stress conditions. Measurements included fracture permeability, strength, stress-dependent aperture, shear dilation, and frictional strength. Results reveal that in situ natural fractures must be permeable, weak, and shear-oriented to be hydrosheared, and only a subset of the observable in situ fractures were suitable. When sheared, the fracture permeability typically increased by a factor of 10 or more and this increase was retained over time. However, shear slip did not always result in permeability increase. High phyllosilicate content associated with exceptionally weak fractures exhibited poor or even decreased permeability after stimulation. These measurements in combination with site data were used to conduct a slip-tendency analysis for different fracture sets, and we selected the top candidate natural fractures for hydroshearing at the EGS Collab sites. We also found that the lower in situ shear stress and stronger fractures at the E2 site make hydroshearing more challenging than at the E1 site. Overall, the methods and analysis used in our work can be applied to any geothermal project to identify in situ joint sets that are best suited for hydroshearing, which in turn can help to optimize well placement and energy production.

58 GEOSCIENCES↗

Preparation of cyclohexene isotopologues and stereoisotopomers from benzene

The hydrogen isotopes deuterium (D) and tritium (T) have become essential tools in chemistry, biology and medicine1. Beyond their widespread use in spectroscopy, mass spectrometry and mechanistic and pharmacokinetic studies, there has been considerable interest in incorporating deuterium into drug molecules1. Deutetrabenazine, a deuterated drug that is promising for the treatment of Huntington’s disease2, was recently approved by the United States’ Food and Drug Administration. The deuterium kinetic isotope effect, which compares the rate of a chemical reaction for a compound with that for its deuterated counterpart, can be substantial1,3,4. The strategic replacement of hydrogen with deuterium can affect both the rate of metabolism and the distribution of metabolites for a compound5, improving the efficacy and safety of a drug. The pharmacokinetics of a deuterated compound depends on the location(s) of deuterium. Although methods are available for deuterium incorporation at both early and late stages of the synthesis of a drug6,7, these processes are often unselective and the stereoisotopic purity can be difficult to measure7,8. Here we describe the preparation of stereoselectively deuterated building blocks for pharmaceutical research. As a proof of concept, we demonstrate a four-step conversion of benzene to cyclohexene with varying degrees of deuterium incorporation, via binding to a tungsten complex. Using different combinations of deuterated and proteated acid and hydride reagents, the deuterated positions on the cyclohexene ring can be controlled precisely. In total, 52 unique stereoisotopomers of cyclohexene are available, in the form of ten different isotopologues. This concept can be extended to prepare discrete stereoisotopomers of functionalized cyclohexenes. Such systematic methods for the preparation of pharmacologically active compounds as discrete stereoisotopomers could improve the pharmacological and toxicological properties of drugs and provide mechanistic information related to their distribution and metabolism in the body.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetic structure and exchange interactions in the Heisenberg pyrochlore antiferromagnet Gd 2 Pt 2 O 7

In this report the Heisenberg pyrochlore antiferromagnet Gd 2 Pt 2 O 7 is one of a series of gadolinium pyrochlore compounds with a variety of B-site cations. Despite the expected simplicity of a spin-only Gd 3+ Heisenberg interaction model, the gadolinium pyrochlore series exhibits various complex magnetic ground states at low temperature. Gd 2 Pt 2 O 7 displays the highest temperature magnetic order of the series with $T_N$=1.6 K, which has been attributed to enhanced superexchange pathways facilitated by empty $5d$ $e_g$ Pt orbitals. In this study, we use various neutron scattering techniques on an isotopically enriched polycrystalline 160 Gd 2 Pt 2 O 7 sample to examine the magnetic structure and spin-wave excitation spectrum below $T_N$ in order to extract the dominant exchange interactions. We find that the ground-state magnetic structure is the Palmer-Chalker state previously seen in Gd 2 Sn 2 O 7 with an associated gapped excitation spectrum consistent with enhanced exchange interactions between further near-neighbor Gd 3+ ions. We confirm this exchange model with analysis of the magnetic diffuse scattering in the paramagnetic regime using polarized neutrons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Role of water in fracture of modified silicate glasses

Decarbonizing the glass industry requires alternative melting technology, as current industrial melting practices rely heavily on fossil fuels. Hydrogen has been proposed as an alternative to carbon-based fuels, but the ensuing consequences on the mechanical behavior of the glass remain to be clarified. A critical distinction between hydrogen and carbon-based fuels is the increased generation of water during combustion, which raises the equilibrium solubility of water in the melt and alters the behavior of the resulting glass. A series of five silicate glasses with 80% silica and variable [Na 2 O]/([H 2 O] + [Na 2 O]) ratios were simulated using molecular dynamics to elucidate the effects of water on fracture. Several fracture toughness calculation methods were used in combination with atomistic fracture simulations to examine the effects of hydroxyl content on fracture behavior. Here, this study reveals that the crack propagation pathway is a key metric to understanding fracture toughness. Notably, the fracture propagation path favors hydrogen sites over sodium sites, offering a possible explanation of the experimentally observed effects of water on fracture properties.

36 MATERIALS SCIENCE↗

Exploring strain rate effects upon 3D materials using high speed in situ X-ray tomoscopy

Cellular materials are ubiquitous in our modern society. They may be stochastic gas-blown foams (e.g., polyurethane), foamed starches (e.g., cereals), or, in this case, 3D printed microlattices. Failure in these materials is often driven by surface or sub-surface defects, which may be nucleated at a surface roughness, an interior void, or inclusion interfaces that may not be typically observable. Obfuscating our understanding further, bulk materials are known to exhibit strain-rate-dependent mechanical response, making a subsurface understanding of damage even more critical. For the first time, an in situ uniaxial mechanical loading stage that simultaneously rotates specimens up to 18 Hz was fielded at a synchrotron for 3D tomographic imaging. This capability opens a plethora of materials science opportunities to explore strain rate effects in materials and examining deformation, fracture, and delamination’s (in composites) for a complete 3D picture (movie) of material response. We demonstrate the deformation of 3D printed polymer lattice structures, of three different material types, at 0.25, 1.1, and 2.2 s −1 strain rates. We successfully imaged the 3D deformation of these materials and can directly compare the same printed structure to the three material types at three strain rates, all in 3D. Material point method simulations were applied to one of the materials to better understand the role of voids on the 3D printed structure’s performance.

36 MATERIALS SCIENCE↗

Hybrid machine learning/physics-based approach for predicting oxide glass-forming ability

Predicting the liquid compositions that will vitrify at experimentally accessible quench rates remains one of the grand challenges in the field of condensed matter physics. This glass-forming ability can be quantified as the critical quench rate needed to suppress crystallization. Knowledge of this critical quench rate also informs which glass composition could be used for new applications. There have been several physical and empirical models presented in the literature to predict the critical quench rate/glass forming ability. These models range from those theoretically derived to those quantified only through experimental characterization. In this work, we instead propose a new method to calculate the critical quench rate using the recently developed toy landscape model combined with machine learning. The toy landscape model accesses the underlying physics that control the vitrification behavior by directly simulating the liquid thermodynamics and kinetics. In conclusion, the results are discussed in terms of industrial impact, physical insights, and how the glass science community can develop improved predictions of glass-forming ability.

Crystallization↗

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Scaling Up Energy Efficiency Investment in Emerging Markets - Private Sector Perspectives

Since 2000, electricity demand has flattened and decoupled from Gross Domestic Product (GDP) growth in the Organization for Economic Cooperation and Development (OECD) countries. This trend is anticipated to continue for the next several decades and is largely attributed to the implementation of energy efficiency measures. However, non-OECD countries (emerging markets) have experienced, and are projected to continue experiencing, increasing electricity demands. If the world is to meet the requirements of the Paris Agreement, annual investments in clean energy and energy efficiency need to increase by a factor of six by 2050, compared to 2015. Information presented in this paper is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment including microgrid development, energy efficiency, smart grid development, and utility-scale wind and solar in emerging markets. Through literature review, a survey, and a series of webinar dialogues, USAID and the U.S. Department of Energy National Renewable Energy Laboratory (NREL) solicited input from private sector actors, including developers, project financiers, manufacturers and technical assistance service providers, on the challenges they face to market entry in emerging markets, and their suggestions for improving market competitiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Smart Grids in Emerging Markets - Private Sector Perspectives

Information presented in this report is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment in emerging markets as it relates to smart grids. Through literature review, a survey, and a series of webinar dialogues, the U.S. Agency for International Development (USAID) and the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) solicited input from private sector actors, including developers, project financiers, manufacturers, and technical assistance service providers on the challenges they face to market entry in developing and emerging markets, and their suggestions for improving market competitiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Copacabana: a probabilistic membership assignment method for galaxy clusters

Cosmological analyses using galaxy clusters in optical/near-infrared photometric surveys require robust characterization of their galaxy content. Precisely determining which galaxies belong to a cluster is crucial. In this paper, we present the COlor Probabilistic Assignment of Clusters And BAyesiaN Analysis (Copacabana) algorithm. Copacabana computes membership probabilities for all galaxies within an aperture centred on the cluster using photometric redshifts, colours, and projected radial probability density functions. We use simulations to validate Copacabana and we show that it achieves up to 89 per cent membership accuracy with a mild dependence on photometric redshift uncertainties and choice of aperture size. We find that the precision of the photometric redshifts has the largest impact on the determination of the membership probabilities followed by the choice of the cluster aperture size. We also quantify how much these uncertainties in the membership probabilities affect the stellar mass–cluster mass scaling relation, a relation that directly impacts cosmology. Using the sum of the stellar masses weighted by membership probabilities (⁠μ * ⁠) as the observable, we find that Copacabana can reach an accuracy of 0.06 dex in the measurement of the scaling relation at low redshift for a Legacy Survey of Space and Time type survey. These results indicate the potential of Copacabana and μ * to be used in cosmological analyses of optically selected clusters in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗

Quantifying Message Aggregation Optimisations for Energy Savings in PGAS Models

Upon breaking past the exascale barrier, HPC systems are facing their greatest challenge yet - a power wall that must be addressed through new methods in both hardware and software. While energy costs are becoming a major issue at all levels, of particular concern is that of the network, as the relative cost of moving data is increasing faster than ever. The partitioned global address space (PGAS) model is critical within certain HPC domains, but is known to suffer from the small message problem, where irregular many-to-many access patterns result in congesting the network with excessive numbers of small messages. To address this, the conveyor aggregation library was developed to defer individual messages and group them for subsequent bulk processing. In this paper, we investigate its impact on energy use related to the network, with a focus on the Slingshot 11 interconnect. We will demonstrate that this strategy is not only highly performant, but also crucial to reducing energy footprints to remain within target power envelopes.

Welch, Aaron [ORNL]↗