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At least 343 records · Page 19

Final Results of Shuttle MMOD Impact Database

The Shuttle Hypervelocity Impact Database documents damage features on each Orbiter thought to be from micrometeoroids (MM) or orbital debris (OD). Data is divided into tables for crew module windows, payload bay door radiators and thermal protection systems along with other miscellaneous regions. The combined number of records in the database is nearly 3000. Each database record provides impact feature dimensions, location on the vehicle and relevant mission information. Additional detail on the type and size of particle that produced the damage site is provided when sampling data and definitive spectroscopic analysis results are available. Guidelines are described which were used in determining whether impact damage is from micrometeoroid or orbital debris impact based on the findings from scanning electron microscopy chemical analysis. Relationships assumed when converting from observed feature sizes in different shuttle materials to particle sizes will be presented. A small number of significant impacts on the windows, radiators and wing leading edge will be highlighted and discussed in detail, including the hypervelocity impact testing performed to estimate particle sizes that produced the damage.

Hyde, J. L.↗

Model analysis of Space Shuttle dosimetry data

An extensive model analysis of plastic track detector measurements of high-LET particles on the Space Shuttle has been performed. Three Shuttle flights: STS-51F (low-altitude, high-inclination), STS-51J (high-altitude, low-inclination), and STS-61C (low-altitude, low-inclination) are considered. The model includes contributions from trapped protons and Galactic cosmic radiation, as well as target secondary particles. Target secondaries, expected to be of importance in thickly shielded space environments, are found to be a significant component of the measured LET (linear energy transfer) spectra.

Letaw, J. R.↗

Assessing Stratospheric Aerosols Contamination Due to Space Activities

The life cycle of a spacecraft starts and ends in the atmosphere: it interacts with the atmosphere right after the launch and during the atmospheric reentry when it usually mostly ablates. Both phases induce emissions of gases and solid particles, providing a source of these components in the middle atmosphere. Little is known about the exact nature, composition and effects of these emissions on the atmosphere and climate, but their impact is expected to rise as more and more orbiting satellites are launched. Ever since the years 2000, the number of space rockets launched per year has increased by a factor 3 globally. At the same time, the number of satellites launched in orbit around the Earth per year has been multiplied by about 30. One may wonder whether changes in the anthropogenic material injected in the terrestrial stratosphere can be detected and what its influence may be. In order to study the cosmic dust particles arriving on Earth, the NASA Johnson Space Center (JSC) has been systematically collecting solid dust particles from the Earth’s stratosphere by aircraft equipped with dedicated particle collectors since 1981. So far, 25 catalogs have been published, covering campaigns of collection from 1981 to 2020, with a total of 5071 solid particles that have been preliminary characterized and curated. In this work, we use the preliminary classification of the dust particles. Based on SEM images and X-ray EDS composition the collected dust is separated into four groups: C (Cosmic), TCN (Terrestrial Contaminant Natural), TCA (Terrestrial Contaminant Artificial) and AOS (Aluminum Oxide Sphere). The AOS being mostly generated by solid rocket propellant, they also belong to the TCA class. Our analysis of the data published indicates that from 1980 to 2009 the cosmic dust particles typically represent on average 40% of the collection with TCA and TCN corresponding to about 30% each. In the recent years, the TCA fraction has doubled to about 60% of the collection (2010-2020). This increase in anthropogenic particles is likely due to the overall human space activity and its recent increase. We will present the properties of the solid stratospheric dust particles collected and their evolution with time. Future work will be dedicated to better classify the natural and anthropogenic particles collected and described in the existing databases. We will use numerical modelling to produce quantitative estimates of the injected mass, the lifetime of particles in the middle atmosphere (stratosphere) and the relative abundance of the anthropogenic particles with respect to the stratospheric background particle population.

J Lasue↗

Enabling Innovative Analysis on Heterogeneous Clusters through HTCdaskgateway

High energy particle (HEP) physics research is going through fundamental changes as we move to collect larger amounts of data from the Large Hadron Collider (LHC). Analysis facilities and distributed computing, through HTCs, have come together to create the next pythonic generation of analysis by utilizing HTCdaskgateway, a Dask gateway extension, allowing users to spawn workers compatible with both their analysis and heterogeneous clusters in line with authentication requirements. This is enabling physicists to engage with scientific python in ways they had not before because of domain specific C++ tools. An example of HTCdaskgateway’s use is Fermilab’s Elastic Analysis Facility.

Chavez, Elise [U. Wisconsin, Madison (main)]↗

Water vapor oxidation of SiC layer in surrogate TRISO fuel particles

Under accidental conditions for high temperature gas-cooled reactors (HTGR), the SiC layer in tri-structural-isotropic (TRISO) fuel particles can be exposed to water vapor. In this study, oxidation behaviors of surrogate TRISO fuel particles were investigated in a He-20 vol% water vapor mixed atmosphere at temperatures up to 1600 °C. The growth of the crystalline oxide passivation layer with cracks and pores followed a parabolic law with time, where the maximum was 2.3 μm at 1600 °C. The oxide layer and the SiC surface under the oxide became flattened with increasing temperature, as a function of the silica viscosity and the diffusion path of water vapor. Volatilization of the oxide layer was analyzed using a mechanistic model that an inert gas in oxidizing atmospheres could influence the magnitude of volatilization. The fracture load and strength of the oxidized and thinned SiC layer were numerically estimated to decrease from 2.27 to 1.69 N and from 317 to 299 MPa, respectively, with the SiC thickness decrease from 35 to 32 μm. This prediction indicates that the oxidized SiC layer should retain fission products. Additionally, the mechanical integrity of each layer in the TRISO fuel particle after oxidation was evaluated. The results in this work provide important data for the safety analysis of accidental scenarios in HTGRs.

36 MATERIALS SCIENCE↗

Correction to 'Recirculation of energetic particles in Jupiter's magnetosphere'

An error in Pioneer 11 data reduction software has, when present, caused a phase shift of 180 deg in the assignment of spacecraft roll angles. The corrected analysis of the pitch angle distributions of energetic particles in Jupiter's magnetosphere reveals significant proton anisotropies directed toward the planet in the southern hemisphere, contrary to the authors' (1975) original report. In the northern hemisphere, both proton and electron anisotropies are directed away from the planet, as reported previously. The revised data show that the claim of direct evidence for the hypothesis of recirculation of energetic particles in the Jovian magnetosphere is invalid. It is suggested that indirect evidence still supports the hypothesis, although the recirculation process must be weaker than originally envisioned and obscured by other processes.

Sentman, D. D.↗

A simplified integrated framework for predicting the economic impacts of feedstock variations in a catalytic fast pyrolysis conversion process

Feedstock attributes of lignocellulosic biomass, such as particle size, compositional makeup, and moisture content, can vary substantially even within pre-processed materials and have a significant effect on conversion in fast pyrolysis-based processes. However, the economic impacts of these attributes are not well understood. To address this, biomass deconstruction phenomena captured with a versatile particle-scale simulation were linked to techno-economic impacts via reduced-order models. Parametric analysis of the particle-scale model, which was validated using literature data, was used in combination with multiple linear regression models to develop correlations between feedstock attributes and yields of pyrolysis oil, gas, and char. Yields were then correlated with the minimum fuel selling price (MFSP) using a techno-economic model, bridging the gap between physics-based biomass conversion simulations and predictions of MFSP for a catalytic fast-pyrolysis process. Empirical correlations derived from the literature regarding the impact of mineral matter (ash) on oil yield were also considered. The model correlations deployed in the integrated framework capture the impacts of variation in feedstock attributes on the MFSP. Variations in ash were shown to have the biggest impact, varying MFSP by -13%/+22% due to catalytic effects and lower relative amounts of convertible lignocellulosic material. It was also found that, if ash can be controlled to low levels, the increased extractives in forest residues can help compensate for some yield losses associated with increased ash. As a result, other inputs considered (particle size, moisture content, and reactor temperature) had relatively negligible effects on process economics within the ranges analyzed considering particle-scale effects alone.

BIOMASS FUELS↗

Numerical Modelling of the Optical Stochastic Cooling Experiment at IOTA

A proof-of-principle optical-stochastic cooling (OSC) experiment is currently in its commissioning phase at the Fermilab’s IOTA ring. In support of this experiment, we recently implemented an OSC element in the ELEGANT tracking program. The model, based on a semi-analytic description of OSC [*], supports the simulation of a large number of macroparticles (10⁴-10⁶) over many turns (10⁶). This paper showcases the simulation capabilities to investigate the beam dynamics in the presence of cooling (or self-interacting radiation field in general) and quantify the impact of various sources of error (e.g. transverse and phase jitter), guide data analysis.

43 PARTICLE ACCELERATORS↗

Search for long-lived, massive particles in events with displaced vertices and multiple jets in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for long-lived particles decaying into hadrons is presented. The analysis uses 139 fb –1 of $pp$ collision data collected at $\sqrt{s}$ = 13 TeV by the ATLAS detector at the LHC using events that contain multiple energetic jets and a displaced vertex. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to longlived particles decaying in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are used to set limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and on scenarios with pair-production of supersymmetric particles with long-lived electroweakinos that decay via a small $R$-parity-violating coupling. The pair-production of electroweakinos with masses below 1.5 TeV is excluded for mean proper lifetimes in the range from 0.03 ns to 1 ns. When produced in the decay of $m$($\tilde{g}$) = 2.4 TeV gluinos, electroweakinos with $m$($\tilde{χ}_{1}^{0}$) = 1.5 TeV are excluded with lifetimes in the range of 0.02 ns to 4 ns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The measurement of trace elements in interplanetary dust and cometary particles by ultra-high sensitivity INAA

Today the major elemental composition of interplanetary dust particles (IDPs) is routinely determined in many laboratories. These and mineralogical studies have revealed the presence of at least two major types of IDPs, chondritic and refractory. Preliminary results of a successful attempt to determine abundances of a large suite of trace elements from both chondritic and refractory IDPs are reported. The analytical procedure can be used in the grain-by-grain analysis of returned cometary samples. Chondritic and refractory IDPs are characterized by standard scanning electron microscopy and energy dispersive x ray spectroscopy (SEM-EDX) techniques. With this system, detection limits for many elements are well below picogram levels, and some approach femtogram levels. This technique is non-destructive, although some sample handling is required, so particles can be analyzed by other techniques after instrument neutron activation analysis (INAA) is completed. Data is presently being reduced from the analyses of 7 IDPs. These are U2015E10, U2015F1, W7029-A2, W7029-A3, W7013A8, LACl (all chondritic) and 705 (refractory). So far, 17 different major and trace elements were detected and measured in these particles, including rare earths and some very volatile elements (Br and Zn).

Zolensky, M. E.↗

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks

Machine learning algorithms are heavily relied on to understand the vast amounts of data from high-energy particle collisions at the CERN Large Hadron Collider (LHC). The data from such collision events can naturally be represented with graph structures. Therefore, deep geometric methods, such as graph neural networks (GNNs), have been leveraged for various data analysis tasks in high-energy physics. One typical task is jet tagging, where jets are viewed as point clouds with distinct features and edge connections between their constituent particles. The increasing size and complexity of the LHC particle datasets, as well as the computational models used for their analysis, have greatly motivated the development of alternative fast and efficient computational paradigms such as quantum computation. In addition, to enhance the validity and robustness of deep networks, we can leverage the fundamental symmetries present in the data through the use of invariant inputs and equivariant layers. In this paper, we provide a fair and comprehensive comparison of classical graph neural networks (GNNs) and equivariant graph neural networks (EGNNs) and their quantum counterparts: quantum graph neural networks (QGNNs) and equivariant quantum graph neural networks (EQGNN). The four architectures were benchmarked on a binary classification task to classify the parton-level particle initiating the jet. Based on their area under the curve (AUC) scores, the quantum networks were found to outperform the classical networks. However, seeing the computational advantage of quantum networks in practice may have to wait for the further development of quantum technology and its associated application programming interfaces (APIs).

Forestano, Roy T. (ORCID:0000000203552076)↗

The Last Journey. I. An Extreme-scale Simulation on the Mira Supercomputer

The Last Journey is a large-volume, gravity-only, cosmological N-body simulation evolving more than 1.24 trillion particles in a periodic box with a side length of 5.025 Gpc. It was implemented using the HACC simulation and analysis framework on the BG/Q system Mira. The cosmological parameters are chosen to be consistent with the results from the Planck satellite. A range of analysis tools have been run in situ to enable a diverse set of science projects and, at the same time, keep the resulting data amount manageable. Analysis outputs have been generated starting at redshift z ~ 10 to allow for construction of synthetic galaxy catalogs using a semianalytic modeling approach in postprocessing. As part of our in situ analysis pipeline, we employ a new method for tracking halo substructures, introducing the concept of subhalo cores. The production of multiwavelength synthetic sky maps is facilitated by generating particle light cones in situ, also beginning at z ~ 10. We provide an overview of the simulation setup and generated data products; a first set of analysis results is presented. A subset of the data is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Effects of interplanetary shock waves on energetic charged particles

Experimental data on the influence of interplanetary perpendicular and oblique shock waves on the ambient energetic protons are presented along with a theoretical analysis of the acceleration of particles in almost perpendicular shock waves. It was found that low-energy protons can be accelerated in perpendicular shock waves by repeated crossings of the shock front up to a maximum energy given by the product of their initial energy times the ratio of the magnetic fields. High-energy protons need to stay at the shock front for longer times than low-energy protons in order to reach the same relative energy gain. In the theoretical study of proton acceleration at almost perpendicular shock waves, it was found that protons reflected at shock waves with the angle between the upstream magnetic field and the shock normal greater than about 80 deg achieve large energy gains at the shock front. The larger this angle, the higher the energy gain. However, the reflection and energization of protons at these shock waves is not 'instantaneous', neither is it a one-step process: it is performed through repeated crossings of the shock front.

Sarris, E. T.↗

Analysis of auroral particle fluxes

The study is reported of electron and proton precipitation in different auroral forms from data obtained by the TWINS 1 and 2. The measurement of the energy spectra and pitch angle distributions of auroral electrons is discussed along with the auroral electron code for predicting the scattering and energy loss of electrons covering the complete auroral energy spectrum.

Chappell, C. R.↗

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗

Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH 4 , CO, and H 2 for chemical looping combustion

In this work, three kinetic models are developed and calibrated for the complete multi-step reduction of an Fe-based oxygen carrier (OC) particle with CH 4 , CO, and H 2 , using data from thermogravimetric analysis. The complete reduction rate profiles exhibit complex dynamics whose trajectory is significantly different depending on the reducing gas. A Bayesian model building and parameter estimation framework is applied for simultaneous parameter and model structure uncertainty quantification. The final models show excellent agreement between model predictions and calibration data, as well as new data not used for calibration (for the reduction of the OC with CH 4 ). Parameter uncertainty is quantified by determining joint posterior distribution, and model structure uncertainty is addressed by incorporating Gaussian process stochastic functions (represented by Bayesian smoothing splines) into the kinetic models. The final kinetic models with discrepancy functions are readily employable in equation-oriented simulation and optimization platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elliptic multipoles and the modeling of narrow-gap bend magnets in accelerators

We highlight the virtues of 2D elliptic-multipole field expansions in modeling the magnetic fields of narrow-aperture, straight-axis bending magnets with parallel faces, addressing the limitations of the conventional circular multipole series when the beam-orbit sagitta exceeds the magnet's vertical half-gap. The elliptic multipoles provide a convenient way to represent the field in all aspects of the magnet development (design, particle-tracking simulations, measurements). We propose a numerically robust method of data analysis to determine the elliptic (or circular) multipoles from stretched-wire measurements with the wire moving on an arbitrary path.

Venturini, Marco↗

Measurements of multiplicity fluctuations of identified hadrons in inelastic proton–proton interactions at the CERN Super Proton Synchrotron

Measurements of multiplicity fluctuations of identified hadrons produced in inelastic p+p interactions at 31, 40, 80, and 158 $\text {Ge}\text {V}/c$ beam momentum are presented. Three different measures of multiplicity fluctuations are used: the scaled variance $\omega $ and strongly intensive measures $\Sigma $ and $\Delta $. These fluctuation measures involve second and first moments of joint multiplicity distributions. Data analysis is preformed using the Identity method which corrects for incomplete particle identification. Strongly intensive quantities are calculated in order to allow for a direct comparison to corresponding results on nucleus–nucleus collisions. The results for different hadron types are shown as a function of collision energy. A comparison with predictions of string-resonance Monte-Carlo models: Epos, Smash and Venus, is also presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗