Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “particle data”

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.

At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Observational test of shock drift and Fermi acceleration on a seed particle population upstream of earth's bow shock

The efficiency of proposed shock acceleration mechanisms as they operate at the bow shock in the presence of a seed energetic particle population was examined using data from simultaneous observations of energetic solar-origin protons, carried out by the IMP 7 and 8 spacecraft in the vicinity of the quasi-parallel (dawn) and quasi-perpendicular (dusk) regions of the earth's bow shock, respectively. The results of observations (which include acceleration effects in the intensities of the energetic protons with energies as high as 4 MeV observed at the vicinity of the dusk bow shock, but no evidence for any particle acceleration at the energy equal to or above 50 keV at the dawn side of the bow shock) indicate that the acceleration of a seed particle population occurs only at the quasi-perpendicular bow shock through shock drift acceleration and that the major source of observed upstream ion populations is the leakage of magnetospheric ions of energies not less than 50 keV, rather than in situ acceleration.

Anagnostopoulos, G. C.↗
DOE OSTI2023

Simultaneous isotopic analysis of fission product Sr, Mo, and Ru in spent nuclear fuel particles by resonance ionization mass spectrometry

Abstract Fission product Sr, Mo, and Ru isotopes in six 10-μm particles of spent fuel from a pressurized water reactor were analyzed by resonance ionization mass spectrometry (RIMS) and evaluated for utility in nuclear material characterization. Previous measurements on these same samples showed widely varying U, Pu, and Am isotopic compositions owing to the samples’ differing irradiation environments within the reactor. This is also seen in Mo and Ru isotopes, which have the added complication of exsolution from the UO 2 fuel matrix. This variability is a hindrance to interpreting data from a collection of particles with incomplete provenance since it is not always possible to assign particles to the same batch of fuel based on isotopic analyses alone. In contrast, the measured 90 Sr/ 88 Sr ratios were indistinguishable across all samples. Strontium isotopic analysis can therefore be used to connect samples with otherwise disparate isotopic compositions, allowing them to be grouped appropriately for interpretation. Strontium isotopic analysis also provides a robust chronometer for determining the time since fuel irradiation. Because of the very high sensitivity of RIMS, only a small fraction of material in each of the 10 μm samples was consumed, leaving the vast majority still available for other analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1994

Statistical characteristics of bursty bulk flow events

Using a common methodology to analyze data from the Active Magnetospheric Particle Tracer Explorer/Ion Release Module (AMPTE/IRM) and International Sun-Earth Explorer 2 (ISEE 2) satellites we report on the statistical properties of bursty bulk flow events (BBFs) in the inner plasma sheet (IPS). A positive correlation between BBFs and the AE index suggests that BBFs are predominantly geomagnetically active time phenomena. Earthward BBFs are more frequent close to midnight and away from Earth, up to a distance of approximately 19 R(sub E). Tailward BBFs are very infrequent in the IRM data set and somewhat less infrequent in the ISEE 2 data set in the region of the satellites' spatial overlap, possibly due to the more active conditions prevailing during the ISEE 2 mission in that region. However, in both data sets the ratio of tailward to earthward BBFs increases with distance from Earth; more than 20% of all BBFs are anti-sunward tailward of X = -19 R(sub E) in the ISEE 2 data set. BBFs are responsible for 60-100% of the measured earthward transport of mass, energy and magnetic flux past the satellite in the regions of maximum occurrence rate, even though they last approximately 10-15% of the IPS observation time there. Thus BBFs represent the primary transport mechanism at those regions. The one-to-one correspondence between BBFs and substorm phase, as well as the relative contribution of BBFs to the total transport observed during substorms are questions that await further investigation based on multi instrument studies of individual events.

Angelopoulos, V.↗
NASA NTRS1993

The wavelength dependence of Martian atmospheric dust radiative properties

One of the key radiative agents in the atmosphere of Mars is the suspended dust particles. A new analysis of two data sets of the Martian atmosphere is being carried out in order to better evaluate the radiative properties of the atmospheric dust particles. The properties of interest are the size distribution, optical constants, and other radiative properties, such as the single-scattering albedo and phase function. Of prime importance is the wavelength dependence of these radiative properties throughout the visible and near-infrared wavelengths. Understanding the wavelength dependence of absorption and scattering characteristics will provide a good definition of the influence that the atmospheric dust has on heating of the atmosphere.

Pollack, J. B.↗
NASA NTRS2016

More Than the Sum of the Parts: Satellite Aerosol Remote Sensing, and Its Relationship to Sub-Orbital Measurements and Models

Space-borne instruments are providing increasing amounts of data relating to global aerosol spectral optical depth, horizontal and vertical distribution, and very loose, but spatially and temporally extensive, constraints on particle micro-physical properties. The data sets, and many of the underlying techniques, are evolving rapidly. They represent a vast amount of information, potentially useful to the AAAR community. However, there are also issues, some quite subtle, that scientific users must take into consideration. This tutorial will provide one view of the answers to the following four questions: 1) What satellite-derived aerosol products are available? 2) What are their strengths and limitations? 3) How are they being used now? 4) How might they be used in conjunction with each other, with sub-orbital measurements, and with models to address cutting-edge aerosol questions?

satellite remote sensing↗
DOE OSTI2020

Time-Sequenced Flow Field Prediction in an Optima Spark-Ignition Direct-Injection Engine Using Bidirectional Recurrent Neural Network (bi-RNN) with Long Short-Term Memory

To further improve the energy conversion efficiency of internal combustion engine, the transient and complex air flow movement inside the cylinder needs to be better understood and controlled. Although the in-cylinder flow fields are highly stochastic with strong cycle-to-cycle fluctuations, machine learning can still provide an efficient way to learn and regress the complex flow movement process inside the cylinder. In this work, a bidirectional recurrent neural network (bi-RNN) model with long short-term memory was applied to predict the in-cylinder flow fields at different time steps using training data from mull-cycle particle image velocimetry (PIV) measurements. To evaluate the agreement between the true and predicted flow fields, structure and magnitude comparison indices are calculated both globally and locally. The comparison results show that the bi-RNN model can accurately predict the bulk flow and vortex motions from early intake stroke to compression stroke. This work demonstrates that the machine learning model has the potential to predict the underlying dynamics of the interaction between in-cylinder flows and provides a reliable way to improve temporal resolution in PIV flow data to better reveal transient in-cylinder flow features.

Bi-RNN model↗
NASA NTRS1973

Propagation anisotropies of solar flare protons and electrons at low energies in interplanetary space.

Flux anisotropies in interplanetary space were investigated for protons with E greater than 0.66 MeV and electrons with E greater than 400 keV. Data were taken from the University of Chicago charged-particle telescope aboard the deep-space probe Pioneer 7 and from the Goddard Space Flight Center magnetometer aboard the same spacecraft. Flux anisotropies lying to the east of the average interplanetary magnetic field direction were first reported by McCracken et al. (1971), late in a solar particle event, for proton energies greater than 7.5 MeV. This work extends this investigation to much lower proton energies, studies the proton and electron anisotropies during both early and late phases of a particle event, and makes use of detailed magnetic field data. The investigation consists of two parts, a study of many periods taken at random during solar events, for both protons and electrons, and a detailed analysis of one period, early in an event, during which the magnetic field was near the solar direction.

Pyle, K. R.↗
NASA NTRS1992

A detailed petrological analysis of hydrated, low-nickel, nonchondritic stratospheric dust particles

A detailed petrological analysis of three low-Ni, K-bearing, nonchondritic stratospheric dust particles is performed, and these particles are compared to products of high-energy, explosive (Plinian-type) volcanic events. The analytical electron microscope (AEM) analyses show pervasive layer silicates, carbonate and goethite, and chemical fractionation in the matrix of these particles similar to hydrothermal alteration in volcanic ejecta. Along with low Ni content and the presence of potassium, the texture and mineralogy of particles L2001-18, L2001-20, and L2002 C2 are similar to at least two nonchondritic stratospheric dust particles of the igneous subgroup for which an extraterrestrial origin has been suggested based on their minor- and trace-element abundances. The petrological characteristics of some low-Ni, K-bearing nonchondritic stratospheric dust particles supports a probable terrestrial volcanic origin, but the AEM data alone cannot exclude an extraterrestrial origin for these particles.

Rietmeijer, Frans J. M.↗
DOE OSTI2025

A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System

The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.

09 - BIOMASS FUELS↗
DOE OSTI2022

Biomass char gasification kinetic rates compared to data, including ash effects

This investigation provides both experimental and theoretical analyses of biomass char gasification kinetics over 1150–1350 °C in the environment of CO 2 , H 2 O and combinations of these reactants. The experimental data include continuous measurements of particle mass, external and internal temperatures, shape, and size with periodic but not continuous measurements of char porosity, pore size distribution, and pore surface area. The model describes heterogeneous char gasification for poplar wood, corn stover and switchgrass in different shapes and industrially relevant sizes (12.5 mm and smaller). Nonlinear least-squares regression produces optimized power-law model parameters for global kinetics that describe biomass char gasification with respect to both CO 2 and H 2 O separately and in combination. A single set of kinetic parameters describes reaction rates for all three fuels. Model simulations agree with measured data at all stages of char conversion even though the observed mass loss rates change significantly with conversion. In conclusion, the change in rate with conversion depends strongly on ash content, and this investigation provides a simple and theoretically based reaction rate expression that includes the effect of inert ash occupying an increasing portion of the reactive surface with increased conversion.

09 BIOMASS FUELS↗
DOE OSTI2022

Exploring cryo-electron microscopy with molecular dynamics

Single particle analysis cryo-electron microscopy (EM) and molecular dynamics (MD) have been complimentary methods since cryo-EM was first applied to the field of structural biology. The relationship started by biasing structural models to fit low-resolution cryo-EM maps of large macromolecular complexes not amenable to crystallization. The connection between cryo-EM and MD evolved as cryo-EM maps improved in resolution, allowing advanced sampling algorithms to simultaneously refine backbone and sidechains. Moving beyond a single static snapshot, modern inferencing approaches integrate cryo-EM and MD to generate structural ensembles from cryo-EM map data or directly from the particle images themselves. We summarize the recent history of MD innovations in the area of cryo-EM modeling. The merits for the myriad of MD based cryo-EM modeling methods are discussed, as well as, the discoveries that were made possible by the integration of molecular modeling with cryo-EM. Lastly, current challenges and potential opportunities are reviewed.

Biochemistry & Molecular Biology↗
DOE OSTI2020

A new waveform analysis technique to extract good energy and position resolution from a dual-axis duo-lateral position-sensitive detector

The dual-axis duo-lateral position-sensitive silicon detector was developed to detect charged particles with high quality position and energy resolution. When these detectors were used with conventional signal processing electronics, an empirically determined correction was used to improve energy resolution. In this work, the waveforms from the detector after preamplification are studied in detail to investigate position information contained in the waveforms. A 7.22 MeV/nucleon alpha particle beam was impinged directly on a masked dual-axis duo-lateral detector. Data obtained using a 228 Th alpha particle source was also used. Here, by studying the waveform characteristics that give rise to the position-dependent distortions, a new summed trigger analysis method has been developed to significantly improve linearity in position reconstruction without sacrificing energy resolution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Energy landscapes from cryo-EM snapshots: a benchmarking study

Abstract Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, function proceeds along minimum-energy pathways on one or more energy landscapes, because higher-energy conformations are only weakly occupied. With the growing interest in identifying functional trajectories, the need for reliable mapping of energy landscapes has become paramount. In response, various data-analytical tools for determining structural variability are emerging. A key question concerns the veracity with which each data-analytical tool can extract functionally relevant conformational trajectories from a collection of single-particle cryo-EM snapshots. Using synthetic data as an independently known ground truth, we benchmark the ability of four leading algorithms to determine biomolecular energy landscapes and identify the functionally relevant conformational paths on these landscapes. Such benchmarking is essential for systematic progress toward atomic-level movies of continuous biomolecular function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Catalog of the Highest-energy Cosmic Rays Recorded during Phase I of Operation of the Pierre Auger Observatory

A catalog containing details of the highest-energy cosmic rays recorded through the detection of extensive air showers at the Pierre Auger Observatory is presented with the aim of opening the data to detailed examination. Descriptions of the 100 showers created by the highest-energy particles recorded between 2004 January 1 and 2020 December 31 are given for cosmic rays that have energies in the range 78–166 EeV. Details are also given on a further nine very energetic events that have been used in the calibration procedure adopted to determine the energy of each primary. A sky plot of the arrival directions of the most energetic particles is shown. No interpretations of the data are offered.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2017

Radiation Impact on Pharmaceutical Stability: Retrospective Data Review

Historical studies performed by the JSC Pharmacotherapeutics Discipline suggest that exposure to spaceflight conditions may compromise the safety and efficacy of some medications. Follow-on studies have revealed that affected medications demonstrate reductions in active pharmaceutical ingredient (API) concentrations and altered release characteristics. It was hypothesized that the changes in API potency and release were from the medication's exposure to the harsh environmental conditions of spaceflight. Subsequent review of the spaceflight environmental control records from the time of these studies indicated that temperature and humidity levels aboard all spacecraft remained within United States Pharmacopeia (USP) recommended ranges to maintain optimal pharmaceutical stability. Therefore, space radiation was presumed to be the source of observed drug degradation. The Pharmacotherapeutics Discipline conducted a ground analog radiation experiment in 2006 at the NASA Space Radiation Laboratory (NSRL) at Brookhaven to validate this theory and to characterize the effects of high-energy radioactive particles on pharmaceutical stability. These data were never published. Recently, the Exploration Medical Capability (ExMC) Element finalized a research plan (RP) aimed at providing a safe and effective medication formulary for exploration spaceflight. As ExMC begins to design new flight and ground analog radiation studies, further analysis of the 2006 NSRL study data is essential for the characterization of the impact of radiation on medication potency and efficacy in the exploration spaceflight environment.

Daniels, V. R.↗
DOE OSTI2020

Advantages and Limits of Metagenomic Assembly and Binning of a Giant Virus

ABSTRACT Giant viruses have large genomes, often within the size range of cellular organisms. This distinguishes them from most other viruses and demands additional effort for the successful recovery of their genomes from environmental sequence data. Here, we tested the performance of genome-resolved metagenomics on a recently isolated giant virus, Fadolivirus, by spiking it into an environmental sample from which two other giant viruses were isolated. At high spike-in levels, metagenome assembly and binning led to the successful genomic recovery of Fadolivirus from the sample. A complementary survey of the major capsid protein indicated the presence of other giant viruses in the sample matrix but did not detect the two isolated from this sample. Our results indicate that genome-resolved metagenomics is a valid approach for the recovery of near-complete giant virus genomes given that sufficient clonal particles are present. However, our data also underline that a vast majority of giant viruses remain currently undetected, even in an era of terabase-scale metagenomics. IMPORTANCE The discovery of large and giant nucleocytoplasmic large DNA viruses (NCLDV) with genomes in the megabase range and equipped with a wide variety of features typically associated with cellular organisms was one of the most unexpected, intriguing, and spectacular breakthroughs in virology. Recent studies suggest that these viruses are highly abundant in the oceans, freshwater, and soil, impact the biology and ecology of their eukaryotic hosts, and ultimately affect global nutrient cycles. Genome-resolved metagenomics is becoming an increasingly popular tool to assess the diversity and coding potential of giant viruses, but this approach is currently lacking validation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors

This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX experiment tracking detectors. The limitations of a 15 kHz maximum trigger rate imposed by the calorimeters can be negated by intelligent use of streaming technology in the tracking system. The approach efficiently identifies low momentum rare heavy flavor events in high-rate p+p collisions (3MHz), using Graph Neural Network (GNN) and High Level Synthesis for Machine Learning (hls4ml). Success at sPHENIX promises immediate benefits, minimizing resources and accelerating the heavy-flavor measurements. The approach is transferable to other fields. For the EIC, we develop a DIS-electron tagger using Artificial Intelligence - Machine Learning (AI-ML) algorithms for real-time identification, showcasing the transformative potential of AI and FPGA technologies in high-energy nuclear and particle experiments real-time data processing pipelines.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Can standard cosmological models explain the observed Abell cluster bulk flow?

Lauer and Postman (LP) observed that all Abell clusters with redshifts less than 15,000 km/s appear to be participating in a bulk flow of 689 km/s with respect to the cosmic microwave background. We find this result difficult to reconcile with all popular models for large-scale structure formation that assume Gaussian initial conditions. This conclusion is based on Monte Carlo realizations of the LP data, drawn from large particle-mesh N-body simulations for six different models of the initial power spectrum (standard, tilted, and Omega(sub 0) = 0.3 cold dark matter, and two variants of the primordial baryon isocurvature model). We have taken special care to treat properly the longest-wavelength components of the power spectra. The simulations are sampled, 'observed,' and analyzed as identically as possible to the LP cluster sample. Large-scale bulk flows as measured from clusters in the simulations are in excellent agreement with those measured from the grid: the clusters do not exhibit any strong velocity bias on large scales. Bulk flows with amplitude as large as that reported by LP are not uncommon in the Monte Carlo data stes; the distribution of measured bulk flows before error bias subtraction is rougly Maxwellian, with a peak around 400 km/s. However the chi squared of the observed bulk flow, taking into account the anisotropy of the error ellipsoid, is much more difficult to match in the simulations. The models examined are ruled out at confidence levels between 94% and 98%.

Strauss, Michael A.↗