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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Investigation of the Impedance Characteristics of Perforate Sheet Hole Clustering Over an Array of Uniform Depth Chambers

A series of normal incidence impedance tube tests are conducted to characterize the facesheet impedance differences between uniformly distributed and nonuniformly tightly packed hole layout patterns, defined here as "hole clustering." These hole clustered samples contain the same number of holes as their uniformly distributed counterparts but target edge to edge distances between holes down to 0.01". Resonant frequency shifts between uniformly distributed and hole clustered samples are presented to demonstrate potential design benefits. Mass end correction differences between samples are also shown to better quantify differences in designs, including the effect of acoustic particle velocity. It is found that hole clustered facesheets over an array of uniform depth chambers can provide significant reactance increases at minimal expense to resistance, thereby lowering resonant frequencies. Additionally, moving these hole clustered layouts toward common chamber corners provides additional resonance shifts to lower frequencies.

acoustic liner impedance hole clustering perforate↗
NASA NTRS2016

Radial Profile of the 3.5 kev Line Out to R200 in the Perseus Cluster

The recent discovery of the unidentified emission line at 3.5 keV in galaxies and clusters has attracted great interest from the community. As the origin of the line remains uncertain, we study the surface brightness distribution of the line in the Perseus cluster since that information can be used to identify its origin. We examine the flux distribution of the 3.5 keV line in the deep Suzaku observations of the Perseus cluster in detail. The 3.5 keV line is observed in three concentric annuli in the central observations, although the observations of the outskirts of the cluster did not reveal such a signal. We establish that these detections and the upper limits from the non-detections are consistent with a dark matter decay origin. However, absence of positive detection in the outskirts is also consistent with some unknown astrophysical origin of the line in the dense gas of the Perseus core, as well as with a dark matter origin with a steeper dependence on mass than the dark matter decay. We also comment on several recently published analyses of the 3.5 keV line.

dark matter – elementary particles – galaxies:↗
DOE OSTI2025

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗
NASA NTRS1995

Magnetohydrodynamic turbulence in the solar wind

The fluctuations in magnetic field and plasma velocity in solar wind, which possess many features of fully developed magnetohydrodynamic (MHD) turbulence, are discussed. Direct spacecraft observations from 0.3 to over 20 AU, remote sensing radio scintillation observations, numerical simulations, and various models provide complementary methods that show that the fluctuations in the wind parameters undergo significant dynamical evolution independent of whatever turbulence might exist in the solar photosphere and corona. The Cluster mission, with high time resolution particle and field measurements and its variable separation strategies, should be able to provide data for answering many questions on MHD turbulence.

Goldstein, Melvyn L.↗
NASA NTRS2006

Quantification of Spore-forming Bacteria Carried by Dust Particles

In order to establish a biological contamination transport model for predicting the cross contamination risk during spacecraft assembly and upon landing on Mars, it is important to understand the relationship between spore-forming bacteria and their carrier particles. We conducted air and surface sampling in indoor, outdoor, and cleanroom environments to determine the ratio of spore forming bacteria to their dust particle carriers of different sizes. The number of spore forming bacteria was determined from various size groups of particles in a given environment. Our data also confirms the existence of multiple spores on a single particle and spore clumps. This study will help in developing a better bio-contamination transport model, which in turn will help in determining forward contamination risks for future missions.

particles↗
NASA NTRS1996

Clusters of DNA damage induced by ionizing radiation: formation of short DNA fragments. II. Experimental detection

The basic 30-nm chromatin fiber in the mammalian cell consists of an unknown (possibly helical) arrangement of nucleosomes, with about 1.2 kb of DNA per 10-nm length of fiber. Track-structure considerations suggest that interactions of single delta rays or high-LET particles with the chromatin fiber might result in the formation of multiple lesions spread over a few kilobases of DNA (see the accompanying paper: W.R. Holley and A. Chatterjee, Radiat. Res. 145, 188-199, 1996). In particular, multiple DNA double-strand breaks and single-strand breaks may form. To test this experimentally, primary human fibroblasts were labeled with [3H]thymidine and exposed at 0 degrees C to X rays or accelerated nitrogen or iron ions in the LET range of 97-440 keV/microns. DNA was isolated inside agarose plugs and subjected to agarose gel electrophoresis under conditions that allowed good separation of 0.1-2 kb size DNA. The bulk of DNA remained in the well or migrated only a small distance into the gel. It was found that DNA fragments in the expected size range were formed linearly with dose with an efficiency that increased with LET. A comparison of the yield of such fragments with the yield of total DNA double-strand breaks suggests that for the high-LET ions a substantial proportion (20-90%) of DNA double-strand breaks are accompanied within 0.1-2 kb by at least one additional DNA double-strand break. It is shown that these results are in good agreement with theoretical calculations based on treating the 30-nm chromatin fiber as the target for ionizing particles. Theoretical considerations also predict that the clusters will contain numerous single-strand breaks and base damages. It is proposed that such clusters be designated "regionally multiply damaged sites." Postirradiation incubation at 37 degrees C resulted in a decline in the number of short DNA fragments, suggesting a repair activity. The biological significance of regionally multiply damaged sites is presently unknown.

Non-NASA Center↗
NASA NTRS1999

Kinetics and Structure of Superagglomerates Produced by Silane and Acetylene

The evolution of smoke in a laminar diffusion flame involves several steps. The first step is particle inception/nucleation in the high-temperature fuel-rich region of the flame followed by surface growth and coagulation/coalescence of the small particles. As the primary spheres grow in size and lose hydrogen, the colliding particles no longer coalesce but retain their identity as a cluster of primary spheres, termed an agglomerate. Finally, in the upper portion of the flame, the particles enter an oxidizing environment which may lead to partial or complete burnout of the agglomerates. Currently there is no quantitative model for describing the growth of smoke agglomerates up to superagglomerates with an overall dimension of 10 microns and greater. Such particles are produced during the burning of acetylene and fuels containing benzene rings such as toluene and polystyrene. In the case of polystyrene, smoke agglomerates in excess of 1 mm have been observed "raining" out from large fires. Evidence of the formation of superagglomerates in a laminar acetylene/air diffusion flame has been recently reported. Acetylene was chosen as the fuel since the particulate loading in acetylene/air diffusion flames is very high. Photographs were obtained by Sorensen using a microsecond xenon lamp of the "stream" of soot just above the flame. For low flow rates of acetylene, only submicrometer soot clusters are produced and they give rise to the homogeneous appearance of the soot stream. When the flow rate is increased to 1.7 cu cm/s, soot clusters up to 10 microns are formed and they are responsible for the graininess and at a flow rate of 3.4 cu cm/s, a web of interconnected clusters as large as the width of the flame is seen. This interconnecting web of superagglomerates is described as a gel state by Sorensen et al (1998). This is the first observation of a gel for a gas phase system. It was observed that this gel state immediately breaks up into agglomerates due to buoyancy induced turbulence and gravitational sedimentation.

Mulholland, G. W.↗
NASA NTRS1993

Variations in Venus cloud particle properties: A new view of Venus's cloud morphology as observed by Galileo Near-Infrared Mapping Spectrometer

Using Venus nightside data obtained by the Galileo Near-Infrared Mapping Spectrometer (NIMS), we have studied the correlation of 1.74 and 2.30 micrometer radiation which is transmitted through the clouds. Since the scattering and absorption properties of the cloud particles are different at these two wavelengths, one can distinguish between abundance variations and variations in the properties of the cloud particles themselves. The correlation of intensities shows a clustering of data into five distinct branches. Using radiative transfer calculations, we interpret these branches as regions of distinct but different mixes of Mode 2' and 3 particles. The data and calculations indicate large differences in these modal ratios, the active cloud regions varying in content from nearly pure Mode 2' particles to almost wholly Mode 3. The spatial distribution of these branches shows large scale sizes and both hemispheric symmetries and asymmetries. High-latitude concentrations of large particles are seen in both hemispheres and there is banded structure of small particles seen in both the North and South which may be related. The mean particle size in the Northern Hemisphere is greater than found in the South. If these different branch regions are due to mixing of vertically stratified source regions (e.g. photochemical and condensation source mechanisms), then the mixing must be coherent over very large spatial scales.

Carlson, R. W.↗
DOE OSTI2025

Environmental controls on the kinetics of iron-sulfur cluster nucleation and nanoparticle formation

Anoxic, sulfidic conditions have been prevalent since the early Proterozoic and favor aqueous iron-sulfur (FeS aq ) clusters as a major fraction of the soluble, reduced iron and sulfur pool. FeS aq cluster formation and nucleation is driven by the high affinity between ferrous iron (Fe(II)) and sulfide (HS − ), ultimately yielding particles that precipitate as iron sulfide minerals. FeS aq clusters were recently shown to be bioavailable sources of iron and sulfur for a variety of anaerobes, yet little is known of the factors that influence the kinetics of their formation and nucleation. Here we apply computational and spectroscopic approaches to investigate the dynamics of FeS aq nucleation, cluster growth, precipitation, and redissolution as a function of Fe(II)/HS − concentration, temperature, and pH. Experiments were conducted under excess HS − to mimic euxinic conditions common to contemporary anaerobic aquatic ecosystems and those of the Proterozoic. Density functional theory calculations reveal the key role of water oxygen-iron interactions in stabilizing small FeS aq clusters and promoting solubility. Dynamic light scattering revealed a concentration-dependent increase in the kinetics of FeS aq nucleation and cluster aggregation. Increasing temperature promoted FeS aq cluster nucleation and aggregation while also enhancing dissolution. Alkaline pH also promoted FeS aq nucleation and cluster aggregation. At 25 °C, pH 7.0, and at reactant concentrations of 30 µM, FeS aq clusters < 10 nm in diameter remained in solution for > 2 h. These results underscore the importance of temperature, pH, and reactant concentration in the kinetics of FeS aq nucleation and cluster growth that, in turn, influence their bioavailability in anaerobic ecosystems.

Aquatic ecosystems↗
DOE OSTI2025

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2005

Microwave Signatures of Melting/Refreezing Snow: Observations and Modeling Using Dense Medium Radiative Transfer Theory

Microwave brightness temperatures of snow covered terrains can be modeled by means of the Dense Radiative Transfer Medium Theory (DMRT). In a dense medium, such as snow, the assumption of independent scattering is no longer valid and the scattering of correlated scatterers must be considered. In the DMRT, this is done considering a pair distribution function of the particles position. In the electromagnetic model, the snowpack is simulated as a homogeneous layer having effective permittivity and albedo calculated through the DMRT. In order to account for clustering of snow crystals, a model of cohesive particles can be applied, where the cohesion between the particles is described by means of a dimensionless parameters called stickiness (z), representing a measure of the inversion of the attraction of the particles. The lower the z the higher the stickiness. In this study, microwave signatures of melting and refreezing cycles of seasonal snowpacks at high altitudes are studied by means of both experimental and modeling tools. Radiometric data were collected 24 hours per day by the University of Michigan Tower Mounted Radiometer System (TMRS). The brightness temperatures collected by means of the TMRS are simulated by means of a multi-layer electromagnetic model based on the dense medium theory with the inputs to the model derived from the data collected at the snow pits and from the meteorological station. The paper is structured as follows: in the first Section the temperature profiles recorded by the meteorological station and the snow pit data are presented and analyzed; in the second Section, the characteristics of the radiometric system used to collect the brightness temperatures are reported together with the temporal behavior of the recorded brightness temperatures; in the successive Section the multi-layer DMRT-based electromagnetic model is described; in the fourth Section the comparison between modeled and measured brightness temperatures is discussed. We dedicate the last Section to the conclusions and future works.

Tedesco, Marco↗
NASA NTRS1985

Cluster-cluster clustering

The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales.

Barnes, J.↗
NASA NTRS2004

Interactive Terascale Particle Visualization

This paper describes the methods used to produce an interactive visualization of a 2 TB computational fluid dynamics (CFD) data set using particle tracing (streaklines). We use the method introduced by Bruckschen et al. [2001] that pre-computes a large number of particles, stores them on disk using a space-filling curve ordering that minimizes seeks, and then retrieves and displays the particles according to the user's command. We describe how the particle computation can be performed using a PC cluster, how the algorithm can be adapted to work with a multi-block curvilinear mesh, and how the out-of-core visualization can be scaled to 296 billion particles while still achieving interactive performance on PG hardware. Compared to the earlier work, our data set size and total number of particles are an order of magnitude larger. We also describe a new compression technique that allows the lossless compression of the particles by 41% and speeds the particle retrieval by about 30%.

Ellsworth, David↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2024

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

Angular momentum↗
DOE OSTI2025

Measuring Nuclear Clusters in the Short-Baseline Near Detector

The Short-Baseline Near Detector (SBND) is the first Liquid Argon Time Projection Chamber (LArTPC) with high enough resolution and large enough neutrino flux to measure the cross-section for production of heavier-than-proton fragments in neutrino interactions. SBND is an 112-ton LArTPC, and lies 110 m downstream from the Booster Neutrino Beam target, where it is collecting more than two million neutrino interactions per year. As a result of both the intranuclear cascade and nuclear de-excitation, neutrino interactions with argon can produce nuclear clusters such as deuterons, tritons, helions and alpha particles, which have so far only been seen as vertex activity or mis-reconstructed as protons. With LArTPC technology's excellent reconstruction capabilities and SBND's unprecedented neutrino statistics, a measurement of these nuclear clusters could distinguish between nuclear models and improve neutrino energy reconstruction. This poster presents the status of simulation and reconstruction of nuclear clusters in SBND.

Beever, Anna L. [Unlisted, US] (ORCID:000900069339↗
DOE OSTI2024

A new “gold standard”: Perturbative triples corrections in unitary coupled cluster theory and prospects for quantum computing

A major difficulty in quantum simulation is the adequate treatment of a large collection of entangled particles, synonymous with electron correlation in electronic structure theory, with coupled cluster (CC) theory being the leading framework for dealing with this problem. Augmenting computationally affordable low-rank approximations in CC theory with a perturbative account of higher-rank excitations is a tractable and effective way of accounting for the missing electron correlation in those approximations. This is perhaps best exemplified by the “gold standard” CCSD(T) method, which bolsters the baseline CCSD with the effects of triple excitations using considerations from many-body perturbation theory (MBPT). Despite this established success, such a synergy between MBPT and the unitary analog of CC theory (UCC) has not been explored. In this work, we propose a similar approach wherein converged UCCSD amplitudes are leveraged to evaluate energy corrections associated with triple excitations, leading to the UCCSD[T] method. In terms of quantum computing, this correction represents an entirely classical post-processing step that improves the energy estimate by accounting for triple excitation effects without necessitating new quantum algorithm developments or increasing demand for quantum resources. The rationale behind this choice is shown to be rigorous by studying the properties of finite-order UCC energy functionals, and our efforts do not support the addition of the fifth-order contributions as in the (T) correction. We assess the performance of these approaches on a collection of small molecules and demonstrate the benefits of harnessing the inherent synergy between MBPT and UCC theories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A study of nuclear structure of light nuclei at the electron–ion collider

Understanding the substructure of atomic nuclei, particularly the clustering of nucleons inside them, is essential for comprehending nuclear dynamics. Various cluster configurations can emerge depending on excitation energy, the number and types of core clusters, and the presence of excess neutrons. Despite the prevalence of tightly bound cluster formations in low-lying states, understanding the correlation between clusters and their formation mechanisms remains incomplete. This exploring study investigates nuclear clustering at the electron–ion collider (EIC) using simulations based on the modified BeAGLE model. By simulating collisions involving e+ 9 Be, e+ 12 C, and e+ 16 O nuclei, we find that the average energy of particles and the system size ratios of particles at forward rapidity exhibit sensitivity to alpha clustering and its various configurations. These findings offer valuable insights into the dynamics of nuclear clustering and its implications for future studies at the EIC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗