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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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DTX Explorer is a tool to generate interactive data visualizations of Darshan I/O traces collected from HPC applications. Its goal is to provide an easy and interactive way for researchers and developers to explore their application's I/O behavior and detect possible I/O bottlenecks that are impacting performance.
In recent years, new measurement systems have been deployed to monitor and quantify methane emissions from the natural gas sector. Large-eddy simulation (LES) has complemented measurement campaigns by serving as a controlled environment in which to study plume dynamics and sampling strategies. However, with few comparisons with controlled-release experiments, the accuracy of LES for modeling natural gas emissions is poorly characterized. In this paper, we evaluate LES from the Weather Research and Forecasting (WRF) Model against Project Prairie Grass campaign measurements and surface layer similarity theory. Using WRF-LES, we simulate continuous emissions from 30 near-surface trace gas sources in two stability regimes: strong convection and weak convection. We examine the impact of grid resolutions ranging from 6.25 to 52 m in the horizontal dimension on model results. We evaluate performance in a statistical framework, calculating fractional bias and conducting Welch’s t tests. WRF-LES accurately simulates observed surface concentrations at 100 m and beyond under strong convection; simulated concentrations pass t tests in this region irrespective of grid resolution. However, in weakly convective conditions with strong winds, WRF-LES substantially overpredicts concentrations—the magnitude of fractional bias often exceeds 30%, and all but one t test fails. The good performance of WRF-LES under strong convection correlates with agreement with local free convection theory and a minimal amount of parameterized turbulent kinetic energy. The poor performance under weak convection corresponds to misalignment with Monin–Obukhov similarity theory and a significant amount of parameterized turbulent kinetic energy.
The design of an optical diagnostic system to localize the radiation front in a mid-leg pumped divertor configuration on DIII-D is presented. Divertor detachment is a key mechanism for handling power exhaust in tokamaks, and mid-leg pumping offers a promising approach to radiatively dissipate power while maintaining acceptable core performance. To predict the location of the radiation front and design a spectroscopic diagnostic to measure its position, a database of SOLPS-ITER simulations across a range of input powers and gas puffing rates representative of DIII-D operation was employed. These simulations provide self-consistent plasma backgrounds for a Cherab-Raysect synthetic diagnostic framework, which incorporates detailed tokamak geometry and physically accurate ray-tracing. Synthetic simulations of optical sightlines and viewing cone geometry were used to calculate line-integrated emission from the plasma, particularly of the C III 465 nm line, to serve as a proxy for the T e ≈ 7 − 10 eV temperature region associated with the onset and evolution of divertor detachment. Neutral deuterium emission is also evaluated for comparison. The synthetic diagnostic is used to assess the performance of existing DIII-D optical systems, including filterscopes and the Multichord Divertor Spectrometer, and to optimize line-of-sight placement within mechanical and installation constraints. The results provide quantitative guidance for diagnostic implementation on DIII-D and demonstrate the advantage of integrated synthetic diagnostics for divertor design studies and future advanced divertor concepts.
Nickel-rich layered oxides LiNi x Co y Mn 1-x-y O 2 (x≥0.8) have been recognized as the preferred cathode materials to develop lithium-ion batteries with high energy density (>300Wh kg -1 ). However, the poor cycling stability and rate capability stemming from intergranular cracks and sluggish kinetics hinder their commercialization. To address such issues, a multi-scale boron penetration strategy is designed and applied on the polycrystalline LiNi 0.83 Co 0.11 Mn 0.06 O 2 particles that are pre-treated with pore construction. The lithium-ion conductive lithium borate in grain gaps functions as the grain binder that can bear the strain/stress from anisotropic contraction/expansion, and provides more pathways for lithium-ion diffusion. As a result, the intergranular cracks are ameliorated and the lithium-ion diffusion kinetics is improved. Moreover, the coating layer separates the sensitive cathode surface and electrolyte, helping to suppress the parasitic reactions and related gas evolution. In addition, the enhanced structural stability is acquired by strong B-O bonds with trace boron doping. As a result, the boron-modified sample with an optimized boron content of 0.5% (B5-NCM) exhibits a higher initial discharge capacity of 205.5mAh g -1 at 0.1C (1C=200mA g -1 ) and improved capacity retention of 81.7% after 100 cycles at 1C. Furthermore, the rate performance is distinctly enhanced by high lithium-ion conductive LBO (175.6mAh g -1 for B5-NCM and 154.6mAh g -1 for B0-NCM at 5C).
Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m 2 , 500–600 W/m 2 , and 900–1000 W/m 2 . These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m 2 ) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.
Here, the role of ambient oxygen gas (O 2 ) on molecular and nanoparticle formation and agglomeration was studied in laser ablation plumes. As a lab-scale surrogate to a high explosion detonation event, nanosecond laser ablation of an aluminum alloy (AA6061) target was performed in atmospheric pressure conditions. Optical emission spectroscopy and two mass spectrometry techniques were used to monitor the early to late stages of plasma generation to track the evolution of atoms, molecules, clusters, nanoparticles, and agglomerates. The experiments were performed under atmospheric pressure air, atmospheric pressure nitrogen, and 20% and 5% O 2 (balance N 2 ), the latter specifically with in situ mass spectrometry. Electron microscopy was performed ex situ to identify crystal structure and elemental distributions in individual nanoparticles. We find that the presence of ≈20% O 2 leads to strong AlO emission, whereas in a flowing N 2 environment (with trace O 2 ), AlN and strong, unreacted Al emissions are present. In situ mass spectrometry reveals that as O 2 availability increases, Al oxide cluster size increases. Nanoparticle agglomerates formed in air are found to be larger than those formed under N 2 gas. High-resolution transmission electron microscopy demonstrates that Al 2 O 3 and AlN nanoparticle agglomerates are formed in both environments; indicating that the presence of trace O 2 can lead to Al 2 O 3 nanoparticle formation. The present results highlight that the availability of O 2 in the ambient gas significantly impacts spectral signatures, cluster size, and nanoparticle agglomeration behavior. These results are relevant to understanding debris formation in an explosion event, and interpreting data from forensic investigations.
X-ray spectropolarimetry is a diagnostics technique suitable for measuring intense electron beams and strong magnetic fields in hot, dense plasmas. To increase the accuracy achievable, we investigated the possibility of measuring both orthogonal components of linear polarization simultaneously using a single crystal. We demonstrated experimentally for the first time that crystals with cubic symmetry can be used as polarizing beam splitters. We also found that the polarization-splitting planes in cubic crystals can be accessed in two crystal orientations, a property that can be used to decrease the clutter in polarized spectra. In parallel, we developed a ray-tracing code and are working to add the crystal reflectivity to instrument modeling codes, to help us interpret the spectra and to design spectroscopic and spectropolarimetric instruments. This work is motivated by the need to perform measurements of important quantities in difficult experimental conditions, such as the axial magnetic field at stagnation in magnetized liner inertial fusion loads.
High-energy neutrinos are unique messengers of the high-energy universe, tracing the processes of cosmic ray acceleration. This work presents analyses focusing on time-dependent neutrino point-source searches. A scan of the whole sky, making no prior assumption about source candidates, is performed, looking for a space and time clustering of high-energy neutrinos in data collected by the IceCube Neutrino Observatory between 2012 and 2017. No statistically significant evidence for a time-dependent neutrino signal is found with this search during this period, as all results are consistent with the background expectation. Within this study period, the blazar 3C 279, showed strong variability, inducing a very prominent gamma-ray flare observed in 2015 June. This event motivated a dedicated study of the blazar, which consists of searching for a time-dependent neutrino signal correlated with the gamma-ray emission. No evidence for a time-dependent signal is found. Hence, an upper limit on the neutrino fluence is derived, allowing us to constrain a hadronic emission model.
The Nb 3 Sn wires received from LBNL include the original round wires as well as the extracted wires from Rutherford cables. Total of 12 samples were prepared and heat treated. Five of them were tested for electric field versus current (E-I), among them 4 samples were further tested for electric field versus magnetic field (E-H). E-I traces were measured in magnetic field between 5 T and 8 T at 4.2 K. The critical currents of these sample are between 924 A and 993 A at 5 T. E-H measurements were performed at currents between 900 and 1500 A at 4.2 K. The stability currents, which is defined as the maximum current without quench during the E-H test, are determined to be between 1100 A and 1400 A. A separate Excel file presenting all the critical current and E-H curves is attached.
Pulse-like signals are ubiquitous in the field of single molecule analysis, e.g., electrical or optical pulses caused by analyte translocations in nanopores. The primary challenge in processing pulse-like signals is to capture the pulses in noisy backgrounds, but current methods are subjectively based on a user-defined threshold for pulse recognition. Here, we propose a generalized machine-learning based method, named pulse detection transformer (PETR), for pulse detection. PETR determines the start and end time points of individual pulses, thereby singling out pulse segments in a time-sequential trace. It is objective without needing to specify any threshold. It provides a generalized interface for downstream algorithms for specific application scenarios. PETR is validated using both simulated and experimental nanopore translocation data. It returns a competitive performance in detecting pulses through assessing them with several standard metrics. Finally, the generalization nature of the PETR output is demonstrated using two representative algorithms for feature extraction.
A computing module is described herein, wherein the computing module is configured to perform acts including generating a digital signature for a printed circuit board (PCB), wherein the digital signature is based upon a sensor signal generated by a sensor that is electrically coupled to at least one of a trace of the PCB or an electrical component of the PCB. The acts further include determining that the PCB is authentic and is free of tampering based upon the digital signature. The acts additionally include outputting an indication that the PCB is authentic and is free of tampering responsive to determining that the PCB is authentic and is free of tampering.
Ocean surface gravity waves are an important component of air-sea interaction, influencing energy, momentum, and gas exchanges across the ocean-atmosphere interface. In specific applications such as refraction by ocean currents or bathymetry, ray tracing provides a computationally efficient way to gain insight into wave propagation. In this paper, we introduce Mantaray, an open-source software package implemented in Rust, with a Python interface, that solves the ray equations for ocean surface gravity waves. Mantaray is designed for performance, robustness, and ease of use. The package is modular to facilitate further development and can currently be applied to both idealized and realistic wave propagation problems (Fig. 1).
Abstract Comprehensive studies of energy and particle balances in the transition to plasma detachment in an alternative divertor configuration with long outer legs are shown. Numerical simulations are performed with the 2D code suite SOLPS 4.3, using a disconnected double null grid with narrow, tightly baffled long poloidal leg divertors at the outer lower target and outer upper target. A particle count scan is performed using the ‘closed gas box’ model, where the tunable parameter in the simulations is the total number of deuterium particles in the simulation space and all other parameters are held fixed, including a constant input power and trace neon impurity radiation, to assess the physics of the transition to detachment in the system as the particle count increases. Three main aspects of the physics of divertor detachment are addressed: the criteria for the local onset of divertor detachment in each of the divertors, the distribution of heat flux and other plasma parameters between the four divertors as each divertor transitions to detachment, and the role of perpendicular transport in the transition to the detached regime. A synergistic mechanism by which the cross-field transport is reduced by factors associated with the onset of plasma recombination effects is identified. These results are compared to the existing understanding of the physics of the transition to plasma detachment in standard divertors.
One strategy to fit larger problems on NISQ devices is to exploit a tradeoff between circuit width and circuit depth. Unfortunately, this tradeoff still limits the size of tractable problems since the increased depth is often not realizable before noise dominates. Here, we develop qubit-efficient quantum algorithms for entanglement spectroscopy which avoid this tradeoff. In particular, we develop algorithms for computing the trace of the n -th power of the density operator of a quantum system, T r ( ρ n ) , (related to the Rényi entropy of order n ) that use fewer qubits than any previous efficient algorithm while achieving similar performance in the presence of noise, thus enabling spectroscopy of larger quantum systems on NISQ devices. Our algorithms, which require a number of qubits independent of n , are variants of previous algorithms with width proportional to n , an asymptotic difference. The crucial ingredient in these new algorithms is the ability to measure and reinitialize subsets of qubits in the course of the computation, allowing us to reuse qubits and increase the circuit depth without suffering the usual noisy consequences. We also introduce the notion of effective circuit depth as a generalization of standard circuit depth suitable for circuits with qubit resets. This tool helps explain the noise-resilience of our qubit-efficient algorithms and should aid in designing future algorithms. We perform numerical simulations to compare our algorithms to the original variants and show they perform similarly when subjected to noise. Additionally, we experimentally implement one of our qubit-efficient algorithms on the Honeywell System Model H0, estimating T r ( ρ n ) for larger n than possible with previous algorithms.
Looking at this work, we expand upon the Tomographic Absorption Reconstruction and Density Inference Scheme (TARDIS) in order to include multiple tracers while reconstructing matter density fields at Cosmic Noon (z ~ 2–3). In particular, we jointly reconstruct the underlying density field from simulated Lyα forest observations at z ~ 2.5 and an overlapping galaxy survey. We find that these data are synergistic, with the Lyα forest providing reconstruction of low-density regions and galaxy surveys tracing the density peaks. We find a more accurate power spectra reconstruction going to higher scales when fitting these two data sets simultaneously than when using either one individually. When applied to cosmic web analysis, we find that performing the joint analysis is equivalent to an Lγα survey with significantly increased sight-line spacing. Because we reconstruct the velocity field and matter field jointly, we demonstrate the ability to evolve the mock observed volume further to z = 0, allowing us to create a rigorous definition of a “protocluster” as regions that will evolve into clusters. We apply our reconstructions to study protocluster structure and evolution, finding for realistic survey parameters that we can provide accurate mass estimates of the z ≈ 2 structures and their z = 0 fate.
In this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results identified hardware level parameters that significantly enhance discharge repeatability and improve overall plasma performance under operational conditions.
Scattered-beam collimation is a very useful method to reduce unwanted backgrounds and to boost the desired sample signal instead. This approach is of particular interest for samples contained within a complex environment that gives rise to much unwanted parasitic scatter. As neutron scattering instrument and techniques advances, small samples are becoming of more and more interest, which necessitates optimized collimation. Here, in this work, we describe a concept for the design and fabrication of advanced scattered-beam collimation 3D printed from B 4 C specifically tailored for samples contained within a complex environment. This concept is demonstrated through the use of a diamond anvil cell for high pressure experimentation, a technique that very typically requires small samples. The collimators here are designed through a modeling procedure via Monte Carlo neutron ray tracing that encompasses the entire system: the instrument, the complex environment and the collimator. Since the first approach of simply scaling up of the print-size was not successful, a novel concept of a multi-part alternate-blade collimator was developed. This approach addresses printing constraints but gives greater flexibility in design. Its performance is computationally compared against an unprintable progressively tighter blade collimator to assess the effect of alternating blades. No strong difference was observed. Its performance was validated through experimentation at the Spallation Neutron Source. The results emphasize the critical importance of ultra-high precision alignment while showing good overall agreement between simulation and experiment and underscore the feasibility of the method and its real-world application.
We characterize the GPU energy usage of two widely adopted exascale-ready applications representing two classes of particle and mesh solvers: (i) QMCPACK, a quantum Monte Carlo package, and (ii) AMReX-Castro, an adaptive mesh astrophysical code. We analyze power, temperature, utilization, and energy traces from double-/single (mixed)-precision benchmarks on NVIDIA’s A100 and H100 and AMD’s MI250X GPUs using queries in NVML and rocm_smi_lib, respectively. We explore application-specific metrics to provide insights on energy vs. performance trade-offs. Our results suggest that mixed-precision energy savings range between 6–25% on QMCPACK and 45% on AMReX-Castro. Also, we found gaps in the AMD tooling used on Frontier GPUs that need to be understood, while query resolutions on NVML have little variability between 1 ms-1 s. Overall, application level knowledge is crucial to define energy-cost/science-benefit opportunities for the codesign of future supercomputer architectures in the post-Moore era.