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At least 109 records · Page 6

Sample fields of the Viking landers, physical properties, and aeolian processes

Surface sampler activities on Mars during the Viking extended mission are considered, including excavation of deep trenches, construction of conical piles of materials, backhoe touchdown experiments, and acquisition of contiguous pictures of the surface beneath number 2 terminal descent engines using mirrors. Results of the Physical Properties Investigation that are relevant to aeolian processes are also discussed. Both pictures and surface sampler data indicate that the surface materials in the sample fields of the Viking landers may be grouped, in order of increasing strength, into drift material, crusty to cloddy material, blocky material and rocks.

Moore, H. J.↗

The context dependence of physics identity: Examining the role of performance/competence, recognition, interest, and sense of belonging for lower and upper female physics undergraduates

Abstract While there is a growing body of work that examines disciplinary identity development, unlike qualitative work in this area, quantitative research has not fully incorporated the importance of different contexts, nor has it uniquely focused on underrepresented groups (in this case, women in physics). This study examines how the constructs posited by prior work as important for physics identity, as well as an additional theorized construct, may interrelate and affect female students' physics identity differently depending on the context. Context in this study refers to two different experiential levels in college. The constructs examined include performance/competence, recognition, and interest, as well as sense of belonging. In particular, we used structural equation modeling to examine the effect that these constructs have on the physics identity of two groups of female physics undergraduates: first year students and senior year students. The results reveal that the relationship of the theorized constructs with physics identity vary between the two groups as well as compared to prior research with broad college student populations (not just physics majors). Unlike broad college student populations, for our sample of female physics undergraduates, interest did not have a direct effect on physics identity while sense of belonging was significant only for senior year students. These results exemplify the importance of examining context or different types of student experiences when studying disciplinary identity development rather than generalizing previous frameworks to all contexts.

Hazari, Zahra↗

ITS Version 6.7: The Integrated TIGER Series of Coupled Electron/Photon Monte Carlo Transport Codes User's Manual

ITS is a powerful software package permitting state-of-the-art Monte Carlo solution of linear time-independent coupled electron/photon radiation transport problems, with or without the presence of macroscopic electric and magnetic fields of arbitrary spatial dependence. Our goal has been to simultaneously maximize operational simplicity and physical accuracy. Through a set of preprocessor directives, the user selects one of the many ITS codes. The ease with which the make system is applied combines with an input scheme based on order-independent descriptive keywords that makes maximum use of defaults and internal error checking to provide experimentalists and theorists alike with a method for the routine but rigorous solution of sophisticated radiation transport problems. Physical rigor is provided by employing accurate cross sections, sampling distributions, and physical models for describing the production and transport of the electron/photon cascade from 1.0 GeV down to 1.0 keV. The availability of source code permits the more sophisticated user to tailor the codes to specific applications and to extend the capabilities of the codes to more complex applications. Version 6, the latest version of ITS, contains (1) improvements to the ITS 5.0 codes, and (2) conversion to Fortran 95. The general user friendliness of the software has been enhanced through memory allocation to reduce the need for users to modify and recompile the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Soil physical and thermal properties from soil samples at multiple locations at Teller Road Site, Seward Peninsula, Alaska, 2019

This dataset contains results of the laboratory analysis of soil samples collected across the watershed located at miles #27 along the Teller road, near Nome, AK. The dataset includes 124 soil samples retrieved from 52 locations during the first week of August 2019. The soil samples were collected in the top 1.2 m of soil with volume known samples, analyzed with a thermal analyser to infer thermal parameters (thermal conductivity, volumetric heat capacity and thermal diffusivity), and then processed in a lab for estimation of their bulk density, water content, carbon and nitrogen content, soil texture, and elemental fractions. This dataset has one csv file and one pdf file.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Some physical properties of Apollo 12 lunar samples

The size distribution of the lunar fines is measured, and small but significant differences are found between the Apollo 11 and 12 samples as well as among the Apollo 12 core samples. The observed differences in grain size distribtuion in the core samples are related to surface transportation processes, and the importance of a sedimentation process versus meteoritic impact gardening of the mare grounds is discussed. The optical and the radio frequency electrical properties are measured and are also found to differ only slightly from Apollo 11 results.

Gold, T.↗

Sampling Functions from Gaussian Processes and Structured Covariance Gaussian Networks

When learning aerodynamic models from data, it is critical to incorporate estimates of model uncertainty. This motivates the design of probabilistic aerodynamic databases which can be sampled to generate physically and statistically plausible aerodynamic models. In this talk we discuss how to sample deterministic functions from two different kinds of probabilistic models and demonstrate their use. First, Gaussian Process Regressors (GPRs) are a widely used probabilistic kernel-based model which can be thought of as Gaussian distributions over functions. GPRs are generally trained by maximizing the marginal likelihood of seeing the training data over the kernel parameter space. Sample functions are easily generated by drawing points from the Gaussian distribution at desired input points. However, when the points are not known ahead of time, the classical sampling approach is not possible since successive function samples will generate different function realizations. We present an approach for sampling consistent function evaluations from a GPR over multiple samples. Second, we describe a neural network architecture which learns a conditional Gaussian distribution by maximizing the marginal likelihood at each point in the input space. We then discuss and compare several options for generating sample functions which match this distribution. Finally, we demonstrate the use of these probabilistic aerodynamic models in an atmospheric reentry simulation.

Gaussian process regression↗

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE↗

The impact of chromium coatings on Zircaloy cladding deformation behavior under reactivity-initiated accident-like mechanical loading conditions

A reactivity-initiated accident (RIA) occurs when a control rod ejection or control blade drop causes an increase in the fission rate. The injection of energy results in an increase in fuel temperature which in turn causes rapid thermal expansion of the fuel pellet. This thermal expansion may result in pellet-cladding mechanical interaction (PCMI) in which the fuel imparts a mechanical strain to the cladding. PCMI may cause the cladding to fail, and thus, the mechanical response of cladding due to PCMI must be investigated when characterizing new cladding materials. Chromium-coated Zircaloy-4 is a near-term accident-tolerant fuel cladding that exhibits improved high-temperature oxidation resistance. Modified burst testing was utilized to experimentally simulate the effects of PCMI on both uncoated and chromium-coated Zircaloy cladding samples at hot zero power conditions. Samples were coated using either cold spraying or physical vapor deposition to understand the differences in behavior that the coating application method may cause. Digital image correlation was used to analyze images of the deforming specimens to extract the in-situ strain behavior of the cladding. The uncoated specimens burst at hoop strains ranging from 8.8 % to 17.2 %. The cold-spray chromium-coated Zircaloy specimens burst at hoop strains of 7.0 % to 11.0 %. The physical vapor deposition coated tubes burst at hoop strains of 9.1 % to 11.5 %. These results indicate that the chromium coating causes a loss in the ductility of the cladding. Furthermore, the higher burst hoop strains of the physical vapor deposition-coated samples relative to the cold-spray samples indicate that the cold-spraying technique causes more of a loss in ductility than physical vapor deposition. All samples burst at higher hoop strains than those expected to occur in an RIA for fresh cladding.

Accident-tolerant fuel↗

Nuclear Data Covariances and Sampling

In this report, we present an overview of the task of producing sample nuclear data sets for the purpose of exploring the effects of nuclear data uncertainties on physics simulations. These sample data sets (or, as we sometimes call them variations) are produced based on uncertainties specified in the ENDF/B-VIII nuclear data library, although the principles discussed here apply to sampling based on similar libraries, such as JENDL. The uncertainties in ENDF and similar libraries are given in the form of mean values (a mean vector) and a covariance matrix. The components of the mean vector are what are normally thought of as the values of the nuclear data (cross sections, $\bar{v}$, the prompt fission neutron spectrum, etc.) and the covariance matrix contains the information about the uncertainties in these values and correlations between them, including correlations across different energies in a single channel and correlations across different channels.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics

Material identification is critical for understanding the relationship between mechanical properties and the associated mechanical functions. However, material identification is a challenging task, especially when the characteristic of the material is highly nonlinear in nature, as is common in biological tissue. In this work, we identify unknown material properties in continuum solid mechanics via physics-informed neural networks (PINNs). To improve the accuracy and efficiency of PINNs, we develop efficient strategies to nonuniformly sample observational data. We also investigate different approaches to enforce Dirichlet-type boundary conditions (BCs) as soft or hard constraints. Finally, we apply the proposed methods to a diverse set of time-dependent and time-independent solid mechanic examples that span linear elastic and hyperelastic material space. The estimated material parameters achieve relative errors of less than 1%. As such, this work is relevant to diverse applications, including optimizing structural integrity and developing novel materials.

97 MATHEMATICS AND COMPUTING↗

Fatigue, Creep-Fatigue, and Thermomechanical Fatigue Life Testing of Alloys

The fatigue crack initiation resistance of an alloy is determined by conducting a series of tests over a range of values of stress amplitude or strain range. The observed number of cycles to failure is plotted against the stress amplitude or strain range to obtain a fatigue curve. The fatigue properties quoted for an alloy are typically the constants used in the equation(s) that describe the fatigue curve. Fatigue lives of interest may be as low as 10(exp 2) or higher than 10(exp 9) cycles. Because of the enormous scatter associated with fatigue, dozens of tests may be needed to confidently establish a fatigue curve, and the cost may run into several thousands of dollars. To further establish the effects on fatigue life of the test temperature, environment, alloy condition, mean stress effects, creep-fatigue effects, thermomechanical cycling, etc. requires an extraordinarily large and usually very costly test matrix. The total effort required to establish the fatigue resistance of an alloy should not be taken lightly. Fatigue crack initiation tests are conducted on relatively small and presumed to be initially crack-free, samples of an alloy that are intended to be representative of the alloy's metallurgical and physical condition. Generally, samples are smooth and have uniformly polished surfaces within the test section. Some may have intentionally machined notches of well-controlled geometry, but the surface at the root of the notch is usually not polished. The purpose of polishing is to attain a reproducible surface finish. This is to eliminate surface finish as an uncontrolled variable. Representative test specimen geometries will be discussed later. Test specimens are cyclically loaded until macroscopically observable cracks initiate and eventually grow to failure. Normally, the fatigue failure life of a specimen is defined as the number of cycles to separation of the specimen into two pieces. Alternative definitions are becoming more common, particularly for low-cycle fatigue testing, wherein some prescribed indication of impending failure due to cracking is adopted. Specific criteria will be described later. As a rule, cracks that develop during testing are not measured nor are the test parameters intentionally altered owing to the presence of cracking.

Halford, Gary R.↗

Pristine Igneous Rocks and the Early Differentiation of Planetary Materials

Our studies are highly interdisciplinary, but are focused on the processes and products of early planetary and asteroidal differentiation, especially the genesis of the ancient lunar crust. Most of the accessible lunar crust consists of materials hybridized by impact-mixing. Rare pristine (unmixed) samples reflect the original genetic diversity of the early crust. We studied the relative importance of internally generated melt (including the putative magma ocean) versus large impact melts in early lunar magmatism, through both sample analysis and physical modeling. Other topics under investigation included: lunar and SNC (martian?) meteorites; igneous meteorites in general; impact breccias, especially metal-rich Apollo samples and polymict eucrites; effects of regolith/megaregolith insulation on thermal evolution and geochronology; and planetary bulk compositions and origins. We investigated the theoretical petrology of impact melts, especially those formed in large masses, such as the unejected parts of the melts of the largest lunar and terrestrial impact basins. We developed constraints on several key effects that variations in melting/displacement ratio (a strong function of both crater size and planetary g) have on impact melt petrology. Modeling results indicate that the impact melt-derived rock in the sampled, megaregolith part of the Moon is probably material that was ejected from deeper average levels than the non-impact-melted material (fragmental breccias and unbrecciated pristine rocks). In the largest lunar impacts, most of the impact melt is of mantle origin and avoids ejection from the crater, while most of the crust, and virtually all of the impact-melted crust, in the area of the crater is ejected. We investigated numerous extraordinary meteorites and Apollo rocks, emphasizing pristine rocks, siderophile and volatile trace elements, and the identification of primary partial melts, as opposed to partial cumulates. Apollo 15 sample 15434,28 is an extraodinarily large glass spherule, nearly if not entirely free of meteoritic contamination, and provides insight into the diversity of mare basalts in the Hadley-Apennine region. Apollo 14 sample 14434 is in many respects a new rock type, intermediate between nonmare gabbronorites and mare basalts. We helped to both plan and implement a consortium to study the Yamato-793605 SNC/martian meteorite.

Warren, Paul H.↗

Electric Field Containerless Processing Technology

The objective of this task is to develop the science and technology base required to design and construct a high temperature electric field positioning module that could be used by materials scientists to conduct containerless science experiments in a low gravity environment. Containerless science modules that employ electric fields to position and manipulate samples offer several advantages over acoustic or electromagnetic systems. The electric field system will operate not only at atmospheric pressures but also in a vacuum, in contrast to the acoustic modules which can only operate in atmosphere where the acoustic forces are sufficient. The electric field technique puts minimum energy into the sample, whereas the electromagnetic system can deposit energy into the sample through eddy current heat as well as physical mixing in the sample. Two types of electric field modules have been constructed and tested to date. One employs a charged sample and uses electrostatic forces to position and control the sample. The second type of module induces electrical polarization of the sample and electric field gradients to position and control the sample.

Elleman, D. D.↗

Colloidally separated samples from Allende residues - Noble gases, carbon and an ESCA-study

Results are presented which strengthen the hypothesis of heterogeneity among the carbon- and nitrogen-bearing phases of the Allende meteorite. These data also highlight the possibility of performing physical separations yielding samples in which some of the noble gas- and carbon-bearing phases are extraordinarily predominant over others. The conclusion, based on mass and isotope balance arguments, that a significant portion of the carbonaceous matter in Allende is likely to be gas-poor or gas-free need not weaken the case for carbonaceous carriers for the major noble gas components. The concept that acid-soluble carbonaceous phases contain a multiplicity of components, each of which may have formed under a multiplicity of different physical-chemical conditions, is reemphasized by the results of the present study.

Ott, U.↗

Connecting radio emission to AGN wind properties with broad absorption line quasars

ABSTRACT Broad absorption line quasars (BALQSOs) show strong signatures of powerful outflows, with the potential to alter the cosmic history of their host galaxies. These signatures are only seen in ∼10 per cent of optically selected quasars, although the fraction significantly increases in IR and radio selected samples. A proven physical explanation for this observed fraction has yet to be found, along with a determination of why this fraction increases at radio wavelengths. We present the largest sample of radio matched BALQSOs using the LOFAR Two-metre Sky Survey Data Release 2 and employ it to investigate radio properties of BALQSOs. Within the DR2 footprint, there are 3537 BALQSOs from Sloan Digital Sky Survey DR12 with continuum signal-to-noise ≥5. We find radio-detections for 1108 BALQSOs, with an important subpopulation of 120 LoBALs, an unprecedented sample size for radio matched BALQSOs given the sky coverage to date. BALQSOs are a radio-quiet population that show an increase of ×1.50 radio-detection fraction compared to non-BALQSOs. LoBALs show an increase of ×2.22 that of non-BALQSO quasars. We show that this detection fraction correlates with wind-strength, reddening, and C iv emission properties of BALQSOs and that these features may be connected, although no single property can fully explain the enhanced radio detection fraction. We create composite spectra for subclasses of BALQSOs based on wind strength and colour, finding differences in the absorption profiles of radio-detected and radio-undetected sources, particularly for LoBALs. Overall, we favour a wind-ISM interaction explanation for the increased radio-detection fraction of BALQSOs.

79 ASTRONOMY AND ASTROPHYSICS↗

An Interdisciplinary Method for the Visualization of Novel High-Resolution Precision Photography and Micro-XCT Data Sets of NASA's Apollo Lunar Samples and Antarctic Meteorite Samples to Create Combined Research-Grade 3D Virtual Samples for the Benefit of Astromaterials Collections Conservation, Curation, Scientific Research and Education

New technologies make possible the advancement of documentation and visualization practices that can enhance conservation and curation protocols for NASA's Astromaterials Collections. With increasing demands for accessibility to updated comprehensive data, and with new sample return missions on the horizon, it is of primary importance to develop new standards for contemporary documentation and visualization methodologies. Our interdisciplinary team has expertise in the fields of heritage conservation practices, professional photography, photogrammetry, imaging science, application engineering, data curation, geoscience, and astromaterials curation. Our objective is to create virtual 3D reconstructions of Apollo Lunar and Antarctic Meteorite samples that are a fusion of two state-of-the-art data sets: the interior view of the sample by collecting Micro-XCT data and the exterior view of the sample by collecting high-resolution precision photography data. These new data provide researchers an information-rich visualization of both compositional and textural information prior to any physical sub-sampling. Since January 2013 we have developed a process that resulted in the successful creation of the first image-based 3D reconstruction of an Apollo Lunar Sample correlated to a 3D reconstruction of the same sample's Micro- XCT data, illustrating that this technique is both operationally possible and functionally beneficial. In May of 2016 we began a 3-year research period during which we aim to produce Virtual Astromaterials Samples for 60 high-priority Apollo Lunar and Antarctic Meteorite samples and serve them on NASA's Astromaterials Acquisition and Curation website. Our research demonstrates that research-grade Virtual Astromaterials Samples are beneficial in preserving for posterity a precise 3D reconstruction of the sample prior to sub-sampling, which greatly improves documentation practices, provides unique and novel visualization of the sample's interior and exterior features, offers scientists a preliminary research tool for targeted sub-sample requests, and additionally is a visually engaging interactive tool for bringing astromaterials science to the public.

Blumenfeld, E. H.↗