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At least 1,027 records · Page 57

Solar Energetic Particle Events Observed by the PAMELA Mission

Despite the significant progress achieved in recent years, the physical mechanisms underlying the origin of solar energetic particles (SEPs) are still a matter of debate. The complex nature of both particle acceleration and transport poses challenges to developing a universal picture of SEP events that encompasses both the low-energy (from tens of keV to a few hundreds of MeV)observations made by space-based instruments and the GeV particles detected by the worldwide network of neutron monitors in ground-level enhancements (GLEs). The high-precision data collected by the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics (PAMELA) satellite experiment offer a unique opportunity to study the SEP fluxes between ∼80 MeV and a few GeV, significantly improving the characterization of the most energetic events. In particular, PAMELA can measure for the first time with good accuracy the spectral features at moderate and high energies, providing important constraints for current SEP models. In addition, the PAMELA observations allow the relationship between low and high-energy particles to be investigated, enabling a clearer view of the SEP origin. No qualitative distinction between the spectral shapes of GLE, sub-GLE and non-GLE events is observed, suggesting that GLEs are not a separate class, but are the subset of a continuous distribution of SEP events that are more intense at high energies. While the spectral forms found are to be consistent with diffusive shock acceleration theory, which predicts spectral rollovers at high energies that are attributed to particles escaping the shock region during acceleration, further work is required to explore the relative influences of acceleration and transport processes on SEP spectra.

Bruno, A.↗

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

B. D. Loomis↗

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

Loomis, B. D.↗

A Deformed Geometry Synthesis Technique for Determining Stacking and Cryogenically Induced Preloads for the Space Launch System

The Space Launch System (SLS) stacking and Core Stage (CS) fueling induce significant preloads that contribute to the liftoff pad separation “twang”. To accurately capture this, an approach is required that can replicate the physics of all SLS physical stacking steps, CS cryogenic shrinkage, associated geometric nonlinearities, and the transient behavior and decay of the preloads with changing boundary conditions as the vehicle separates from the pad. The Deformed Geometry Synthesis (DGS) approach presented here satisfies the above requirements. DGS determines induced preloads by modeling components in their deformed geometry states and then enforcing compatibility by closing the resulting “deadbands”. DGS seamlessly integrates into the multibody modal synthesis framework and does not require the use of artificial external loads to enforce preloads or post-processing steps to remove their influence. Since DGS iterates to solve for the deformed state inclusive of geometric nonlinearities, running linearized parametrics to exercise different potential orientations of ball jointed struts that connect the CS to Boosters for cryo-shrinkage analyses is entirely avoided. Relative to the transient behavior and decay of stacking and cryo-induced preloads with SLS liftoff pad separation, this is an area of considerable interest to the SLS program. To capture this in the most accurate way possible, DGS algorithms are designed to work with Henkel-Mar nonlinear pad separation algorithms which operate on the separating longitudinal and lateral degrees of freedom (DoFs) between the vehicle and the pad. As the separating DoFs release, in whatever manner as dictated by the interface geometries, interface loads and interface flexibilities as well as the external loading on the vehicle, the subject preloads generate a complex twang/decay time-trace as dictated by the physics of the problem. This paper presents DGS numerical verification against the closed-form solution for Timoshenko’s 3 ball-jointed strut preload problem. This problem is then extended by the authors to the geometric nonlinear case where DGS is compared to the Newton-Raphson solution of the nonlinear equations. Next, DGS is utilized to solve the SLS stacking and cryogenic shrinkage coupled loads analyses. Finally, Henkel-Mar pad separation simulations are executed that isolate the impact of the induced preloads’ twang and decay characteristics.

Space Launch System↗

Medium-Sized Helicopter Noise Abatement Flight Test

An extensive flight test campaign was recently completed which aims to reduce the noise generated by helicopters in an effort to improve community acceptance. Using a ground-based microphone array, acoustic measurements were acquired on helicopters in the medium-size vehicle weight class over a number of flight conditions including steady level flight, steady descents, and approaches. While data were collected across four helicopters, the Leonardo AW139 and Sikorsky S-76D will be the focus of this paper. The extent of measured ground noise con- tours was limited due to the site constraints. Thus, the Noise Informed Community Environment Operations Planning System (NICEOPS) in conjunction with the flight test data was used to estimate how changes in the operating procedures impact noise exposure over a wider area during approaches. It was found that even small longitudinal accelerations can have a substantial influence on the noise generation processes during approach and must be modeled appropriately to develop new flight procedures which minimize the acoustic impact on the ground.

Flight Testing↗

Psyche Early Project Verification & Validation Planning Development

The Psyche mission to the asteroid (16) Psyche was selected as the fourteenth mission in the Discovery program in January 2017. The Psyche mission will determine if (16) Psyche is the core of a larger differentiated body. As part of the development of this mission a Verification and Validation (V&V) engineer was assigned early in the project’s design Phase B. This paper will discuss some of the strategies that the Psyche team is using to take full advantage of the early planning for V&V on flight projects and specifically how the Psyche mission is approaching these tasks. This paper will discuss the effects of having a V&V mindset on: 1) The Psyche requirements development process, and how focusing not only on how the team will verify these requirements but also on developing the tools necessary to track and monitor that verification feeds back into the requirement development process. 2) The Psyche testbed development, and how using a verification mindset is useful for identifying holes in the testbed development process, including the required testbed speed and how to think about testbed certification early in the process while encouraging trades and developing relationships with the testbed team. 3) Developing new V&V Tools for Psyche, and how developing tools early in the project development process means that they can influence the development of other requirement and scheduling tools. 4) Verification Activity Planning, which is typically done to a preliminary level during Phase B of the project, and is important for understanding the major testing that is needed to ensure that the system as built represents the design. On Psyche we are not only focused on bringing this planning to a preliminary level, we are also developing a V&V focused schedule to help us de-conflict V&V activities that may require similar resources early on in the program’s development. 5) Validation Planning, for which we are working with the testbed and model development teams to ensure that their models can be effectively validated and that the plans to do so are in place. In this paper we will describe how the Psyche mission is approaching each of these V&V areas and identify lessons that can be taken by other space missions trying to decide how much effort should be put into V&V early in the project lifecycle.

Solish, Benjamin↗

Accounting for the Influence of Decorrelation in Microphone Phased Array Deconvolution Methods

Microphone phased arrays are a common tool for use in aeroacoustic wind tunnel testing. The analysis of acquired array data is known to suffer from decorrelation effects, where the coherence of an acoustic wave measured by a pair of microphones is degraded as the wave passes through a turbulent free shear layer or boundary layer. This paper describes, in detail, how to mitigate the influence of decorrelation effects when processing array data with deconvolution methods. This is done using the DAMAS algorithm as an example, applied to recent airframe noise test data acquired in the NASA Langley 14- by 22-Foot Subsonic Tunnel. Two ways of handling the turbulent propagation modeling, both assuming plane wave propagation, are described. Results show that while turbulence model fit parameters may differ, both methods output extremely similar deconvolution results. Further improvements likely require more accurate mean shear layer data prior to developing more involved turbulence models.

microphone array↗

Aerothermal Effects of Hypersonic Shock Impingement on a Highly Swept Leading Edge

A numerical study is conducted to investigate aerothermal implications of oblique shock impingement on a highly swept leading edge in hypersonic flow, with flow conditions and geometry relevant to non-propulsive leading edge heating on hypersonic cruise vehicles. In contrast to propulsive inlet leading edge shock impingement, which has been subject to extensive historical study, bow shock impingement on a highly swept wing leading edge has received comparatively little attention in the literature. Distinguishing characteristics of this type of flow include a potentially dominant surface heating contribution from crossflow-induced viscous dissipation, possible wall velocity slip and temperature jump effects, and various modes of shock layer thermal nonequilibrium that can interact with shock impingement flowfield structures. One overall goal of this work is to assess the impact of bow shock impingement and related nonequilibrium phenomena for wing leading edge design, materials selection and thermal management. Another goal is to improve understanding – and thereby reduce associated design margins – for the physical processes and mechanisms that may influence wing leading edge heating in the presence of an impinging shock. A combination of direct simulation Monte Carlo and Reynolds-averaged Navier-Stokes analysis is used to assess surface and flowfield characteristics for a series of hypersonic shock impingement problems, based on historical ground tests and related flight conditions. Favorable comparisons are performed with experimental data, and various thermal nonequilibrium effects are quantified.

direct simulation Monte Carlo↗

Bridging the time scale in exascale computing of chemical systems (Final Technical Report)

This report summarizes the work carried out with support of the United States Department of Energy under Award DE-SC0019441. The theme of this project was to develop and apply methods that allowed for the acceleration of atomistic calculations, particularly in challenging areas such as multiphase systems, electrified interfaces, uncertainty estimation, and applications requiring chemical accuracy, which tend to be applications where simulation time is severely bottlenecked by the computational time requirements. Much of the focus was on the application of emerging machine-learning methodologies, although a wide range of methodologies were employed. This report has two major sections. The first focuses on the methodological advances themselves. Within this part, we report a number of major advances, a few examples of which are described here. We report the first machine-learning scheme for the acceleration of electronically grand-canonical calculations (that is, those applicable to electrochemistry). We report new methods of performing transfer learning, in which physics-based priors can be used to provide predictions, often with uncertainty estimates, of images well outside of training sets; we also offer ways to fine-tune these transfer-learning models. We provide a new systematic means to generate and apply minimal training data sets to very large (10,000’s of atoms) systems, with only small training sets appropriate for electronic structure. We developed new methodologies to integrate surface vibrations into surface adsorption calculations. We made advances to the applicability of diffusion Monte Carlo methods to allow (learned) force prediction, finite-size error correction, and force-free means of searching for transition states. We integrated machine-learned atomistic predictions into mechanism generation codes. Additionally, we released new software including AmpTorch, a modernized version of our original atomistic machine-learning code Amp. The second part of this report focuses on the scientific applications that accompanied, and were often enabled by, the methodological advances described earlier. A few examples follow, but full details are in the individual chapters of the report. For example, we developed a general theory of phonon-induced friction on molecular adsorbates. We showed fundamentally how solvent influences the adsorption and desorption process and how it differs from the processes typically involved at the solid–gas interface, making aqueous-phase and electrocatalysis different from traditional thermocatalysis. We examined how metal–insulator and magnetic transitions can be probed, and accelerated exciton dynamics via Frenkel Hamiltonian parameters. We showed that the nearsighted force-training approach, developed within this project, can predict both the stability and reactivity of large nanoparticles, and can also lead to insights on catalyst coverage on binding energies and entropies. These applied studies, which generally integrated with our method development, allowed us to push forward the theoretical understanding of several reaction classes.

08 HYDROGEN↗

Are the U.S. Biorefineries Over the Hurdle of 2000 Ton Daily Throughput Yet?

The efficient utilization of lignocellulosic biomass for biofuel and biochemical production is hindered by material handling issues such as clogging and segregation among other challenges. Preprocessing methods such as drying, screening, and milling have improved conversion yield but have not sufficiently enhanced flowability, especially herbaceous biomass. The poor flowability of herbaceous biomass is rooted in some particle attributes that remain less altered by those methods, e.g., irregular particle shape, high roughness, and high compressibility, making it hard to scale up throughput to a key benchmark for a biorefinery – 2000 ton per day. Applying additional preprocessing methods like pelletization and torrefaction to drastically change those particle attributes can improve flow and handling but has not been comprehensively verified through test. The flowability of herbaceous biomass feedstock formats generated by three different preprocessing methods was recently assessed at Idaho National Laboratory’s Biomass Feedstock National User Facility: first, loose particles size reduced from as-received materials; second, pellets produced from an efficient densification process; and third, powders milled from torrefied pellets. Benchmarking tests including static angle of repose, basic flow energy measured in a powder rheometer, and discharge flow in an adjustable hopper, were conducted to evaluate those feedstock formats. Beyond the capacity of existing experimental apparatuses, a digital engineering approach involving flow simulations and AI models were used to identity the material attributes and processing parameters that have dominant influences on flow throughput. Techno-economic analysis focusing on hopper flow as a typical material handling operation was conducted for those feedstock formats. Perspectives will be discussed on whether the 2000-ton daily throughput for a biorefinery is achievable at an acceptable cost by using any of the tested preprocessing methods.

09 - BIOMASS FUELS↗

Tuning the spin dynamics and magnetic phase transitions of the Cantor alloy via composition and sample processing protocols: A muon spin relaxation study

CrMnFeCoNi, also called the Cantor alloy, is a well-known high-entropy alloy whose magnetic properties have recently become a focus of attention. Here, we present a detailed muon spin relaxation study of the influence of chemical composition and sample processing protocols on the magnetic phase transitions and spin dynamics of several different Cantor alloy samples. Specific samples studied include a pristine equiatomic sample, samples with deficient and excess Mn content, and equiatomic samples magnetized in a field of 9 T or plastically deformed in pressures up to 0.5 GPa. The results confirm the sensitive dependence of the transition temperature on composition and demonstrate that post-synthesis pressure treatments cause the transition to become significantly less homogeneous throughout the sample volume. In addition, we observe critical spin dynamics in the vicinity of the transition in all samples, reminiscent of canonical spin glasses and magnetic materials with ideal continuous phase transitions. Application of an external magnetic field suppresses the critical dynamics in the Mn-deficient sample, while the equiatomic and Mn-rich samples show more robust critical dynamics. The spin-flip thermal activation energy in the paramagnetic phase increases with Mn content, ranging from 3.1⁢(3) × 10 -21 J for 0% Mn to 1.2⁢(2) × 10 -20 J for 30% Mn content. These results shed light on critical magnetic behavior in environments of extreme chemical disorder and demonstrate the tunability of spin dynamics in the Cantor alloy via chemical composition and sample processing.

36 MATERIALS SCIENCE↗

Control of machining-induced residual stress via tool geometry and process parameter modification

Distortion generated in machined, monolithic, thin-walled aerospace components due to residual stresses leads to significant material and economic waste in the manufacturing industry. Inherent residual stress (IRS) present in stock materials combines with machining-induced residual stress (MIRS) to influence the final machined part distortion. It is hypothesized that MIRS can be controlled, based on the part geometry, through deliberate cutting tool geometry and process parameter modifications to negate the effect of IRS on distortion, consequently resulting in distortion-free parts. A finite element (FE) orthogonal cutting model is developed to study how tool geometry and process parameters influence machining-induced residual stress (MIRS). Orthogonal cutting experiments are performed on Al 7075-T651 samples to measure cutting forces and MIRS. A cutting force dynamometer is used to measure forces during cutting and a novel digital image correlation (DIC) based hole drilling technique is employed to measure the near-surface residual stress (RS) in the cut samples. These data are subsequently utilized to validate the FE prediction model. Various cases of cutting simulations involving different depths of cut, tool tip radii, and rake angles are performed to study their effects on RS. Similar to prior literature, increasing the depth of cut, tool tip radius, or rake angle is found to promote the formation of near-surface tensile stresses. The competing effects of material plowing and temperature are shown to determine the type of RS at the end of the cut. Moreover, a window of variation of RS (up to ± 400 MPa) is estimated within the given range of conditions, allowing for the control of MIRS through tool and process modification.

Mathews, Ritin [ORNL] (ORCID:0000000301440828)↗

The meteorological environment of the tropospheric ozone maximum over the tropical South Atlantic Ocean

Atmospheric flow patterns are examined over the South Atlantic Ocean where a maximum of tropospheric ozone has been observed just west of southern Africa. We investigate the flow climatology during October and perform a case study for six days during October 1989. Horizontal and vertical motions are examined and used to prepare 3D backward trajectories from the region of greatest ozone. An initially zonally symmetric distribution of ozone is treated as a passive tracer and advected by 3D flows forecast by the global model. Results from the passive tracer simulation indicate that 3D advection alone can produce a maximum of tropospheric ozone in the observed location. In addition, the trajectories suggest that by-products of biomass burning could be transported to the area of maximum ozone. Low-level flow from commonly observed regions of burning in Africa streams westward to the area of interest. Over Brazil, if the burning by-products are carried into the upper troposphere by convective process, they then could be transported eastward to the ozone feature in approximately five days. There is considerable subsidence over the tropical southern Atlantic, such that stratospheric influences also are a factor in producing the ozone maximum. Both planetary-scale and transient synoptic-scale circulation features play major roles in the various transport processes that influence the region. In summary, the observed tropospheric ozone maximum appears to be caused by a complex set of horizontal and vertical advections, transport from regions of biomass burning, and stratospheric influences.

Krishnamurti, T. N.↗

Electrostatic Barriers to Nanoparticle Accessibility of a Porous Matrix

Translocation from one cavity to another through a narrow constriction (i.e., a “hole”) represents the fundamental elementary process underlying hindered mass transport of nanoparticles and macromolecules within many natural and synthetic porous materials, including intracellular environments. This process is complex and may be influenced by long-range (e.g., electrostatic) particle–wall interactions, transient adsorption/desorption, surface diffusion, and hydrodynamic effects. In this study, we used a three-dimensional (3D) tracking method to explicitly visualize the process of nanoparticle diffusion within periodic porous nanostructures, where electrostatic interactions were mediated via ionic strength. The effects of electrostatic interactions on nanoparticle transport were surprisingly large. For example, an increase in the Debye length of only a few nanometers (in a material with a hole diameter of ~100 nm) increased the mean cavity escape time 3-fold. A combination of computational and experimental analyses indicated that this hindered cavity escape was due to an electrostatic energy barrier in the region of the hole, which was quantitatively explained using DLVO theory. These findings explicitly demonstrate that the cavity escape process was barrier-limited and dominated by electrostatic effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Bosilovich, Michael G.↗

An Initial Evaluation of the Elevated-Temperature Cyclic Properties of Optimized 316H Stainless Steel Fabricated by Powder Metallurgy Hot Isostatic Pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is a mature advanced manufacturing technology, which can consolidate metallic powder under high temperature and pressure to generate near-net shape components. This process can lower production costs and reduce component lead times for nuclear reactor construction and can be readily deployed in the near term for microreactor components because of their smaller size. The purpose of this work is to continue the evaluation of elevated-temperature cyclic material properties for PM-HIP 316H stainless steel. Prior scoping results have shown that the commercially procured PM-HIP stainless-steel materials have reduced creep-fatigue performance compared to wrought 316 stainless steels. To better understand how PM-HIP processed material properties compare to traditional manufacturing methods, additional billets of PM-HIP 316H stainless steel were procured and tested. This testing is necessary to understand how elevated-temperature properties are influenced by the PM-HIP process and what data are needed for incorporating PM HIP 316H into the American Society of Mechanical Engineers Boiler Pressure Vessel Code, Section III, Division 5 for high temperature reactor construction. Specifically, an additional PM-HIP 316H stainless steel billet with lower oxygen and nitrogen concentrations was fabricated by the Nuclear Advanced Manufacturing Research Centre of the United Kingdom and tested to understand if elevated-temperature cyclic properties can be improved. The creep-fatigue resistance of the material from this new billet did not show appreciable improvement compared to prior testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Gene drive by Fusarium SKC1 is dependent on its competing allele

The Fusarium verticillioides SKC1 gene driver is transmitted to offspring in a biased manner through spore killing. The mechanism that allows SKC1 to kill non-SKC1 offspring while sparing others is poorly understood. Here we report that gene drive by SKC1 is dependent on SKC1's competing allele. We propose that SKC1's competing allele influences the ability of a genome defense process to detect SKC1, and we provide evidence that this genome defense process is meiotic silencing by unpaired DNA (MSUD). Furthermore, our findings suggest that the successful deployment of gene drivers to control pathogenic fungi will require researchers to consider how competing alleles influence the ability of gene drivers to be detected by genome defense processes.

59 BASIC BIOLOGICAL SCIENCES↗