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At least 343 records · Page 19

Tempering kinetics during multilayer laser additive manufacturing of a ferritic steel

Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for Grade 91 steel, and as a result, the effects of repeated thermal cycles on properties for different processing conditions cannot be determined. Here we evaluate the tempering kinetics by determining the constant terms in the Johnson Mehl Avrami kinetic equation from the tempering data available in the literature and the thermal cycles computed using a rigorously-tested heat and fluid flow model of multi-layer additive manufacturing. The raw tempering data are cleaned using a neural network to enhance accuracy. The lower layers experience repeating cycles of heating and cooling when the upper layers are added. As a result, the hardness is reduced owing to the tempering of martensite. In contrast, martensite formed in the upper layers is not tempered to the same extent and the hardness remains high. Therefore, the hardness of the part increases with the distance from the substrate. Variations in the heat input at different laser powers and scanning speeds significantly affect the extent of tempering. Finally, since the method used here can provide a quantitative understanding of the tempering of martensite and the spatial variation in hardness, it can be used to tailor the microstructure and hardness of heat treatable printed metallic parts.

36 MATERIALS SCIENCE↗

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

Reproducibility and Replication of Experimental Particle Physics Results

Recently, much attention has been focused on the replicability of scientific results, causing scientists, statisticians, and journal editors to examine closely their methodologies and publishing criteria. Experimental particle physicists have been aware of the precursors of non-replicable research for many decades and have many safeguards to ensure that the published results are as reliable as possible. The experiments require large investments of time and effort to design, construct, and operate. Large collaborations produce and check the results, and many papers are signed by more than three thousand authors. This paper gives an introduction to what experimental particle physics is and to some of the tools that are used to analyze the data. It describes the procedures used to ensure that results can be computationally reproduced, both by collaborators and by non-collaborators. It describes the status of publicly available data sets and analysis tools that aid in reproduction and recasting of experimental results. It also describes methods particle physicists use to maximize the reliability of the results, which increases the probability that they can be replicated by other collaborations or even the same collaborations with more data and new personnel. Examples of results that were later found to be false are given, both with failed replication attempts and one with alarmingly successful replications. While some of the characteristics of particle physics experiments are unique, many of the procedures and techniques can be and are used in other fields.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comprehensive Review of 2$β$ Decay Half-Lives

The double-beta (2β)-decay is the rarest nuclear physics process, and its experimental half-lives (T 1/2 ) exceed the age of the Universe from nine to fourteen orders of magnitude. Double-beta decay was observed, and its half-life was measured in 14 parent nuclei using direct, radiochemical, and geochemical methods. The decay observables are analyzed using the Evaluated Nuclear Structure Data File (ENSDF) procedures, and the recommended T 1/2 were deduced. Using the calculated values of phase factors, the effective nuclear matrix elements were extracted and compared with available data. Thousands of theoretical and experimental works have been dedicated to these topics in the last 85 years, and we present two data sets of recommended values to encapsulate the results.

2β-decay↗

Recent Experience with the CMS Data Management System

The CMS[1] experiment manages a large-scale data infrastructure, currently handling over 200 PB of disk and 500 PB of tape storage and transferring more than 1 PB of data per day on average between various WLCG[2] sites. Utilizing Rucio[3] for high-level data management, FTS[4] for data transfers, and a variety of storage and network technologies at the sites, CMS confronts inevitable challenges due to the system’s growing scale and evolving nature. Key challenges include managing transfer and storage failures, optimizing data distribution across different storages based on production and analysis needs, implementing necessary technology upgrades and migrations, and efficiently handling user requests. The data management team has established comprehensive monitoring to supervise this system and has successfully addressed many of these challenges. The team’s efforts aim to ensure data availability and protection, minimize failures and manual interventions, maximize transfer throughput and resource utilization, and provide reliable user support. This paper details the operational experience of CMS with its data management system in recent years, focusing on the encountered challenges, the effective strategies employed to overcome them and the ongoing challenges as we prepare for future demands.

Öztürk, Hasan [CERN]↗

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

59 BASIC BIOLOGICAL SCIENCES↗

Models of $J/\varPsi$ photo-production reactions on the nucleon

The J/Ψ photo-production reactions on the nucleon can provide information on the roles of gluons in determining the J/Ψ-nucleon (J/Ψ-N) interactions and the structure of the nucleon. The information on the J/Ψ-N interactions is needed to test lattice QCD (LQCD) calculations and to understand the nucleon resonances such as N*(P c ) recently reported by the LHCb Collaboration. In addition, it is also needed to investigate the production of nuclei with hidden charms and to extract the gluon distributions in nuclei. The main purpose of this article is to review six models of the γ+p→J/Ψ+p reaction which have been and can be applied to analyze the data from Thomas Jefferson National Accelerator Facility (JLab). Here, the formulae for each model are given and used to obtain the results to show the extent to which the available data can be described. The models presented include the Pomeron-exchange model of Donnachie and Landshoff (Pom-DL) and its extensions to include J/Ψ-N potentials extracted from LQCD (Pom-pot) and to also use the constituent quark model (CQM) to account for the quark substructure of J/Ψ (Pom-CQM). The other three models are developed from applying the perturbative QCD approach to calculate the two-gluon exchange using the generalized parton distribution (GPD) of the nucleon (GPD-based), two- and three-gluon exchanges using the parton distribution of the nucleon (2g+3g), and the exchanges of scalar (0 ++ ) and tensor (2 ++ ) glueballs within the holographic formulation (holog). The results of investigating the excitation of the nucleon resonances N*(P c ) in the γ+p→J/Ψ+p reactions are also given. We demonstrate that the differences between these six models can be unambiguously distinguished and the N* can be better studied by using the forthcoming JLab data at large |t| and at energies very near the J/Ψ production threshold. Possible improvements of the considered models are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Evaluation of Hanford 200 West Area Tank Farms (241-S/241-SX-/241-U tank farms) Physical Properties Data for Use in Development of West Area Tank Treatment (WATT) Processing

With the recent acceptance of West Area Tank Treatment disposition alternative for 200 West Area tanks at the Hanford Site by the State of Washington and the U.S. Department of Energy, a review was initiated to identify the physical properties data available in the literature for the Hanford 241-S, 241-SX, and 241-U tank farms. The literature reviewed indicated that there is a relatively small set of useful data on physical properties of 200 West Area tanks, and the data that do exist are biased around a narrow range of tank samples. Much of the testing between the 1990s and mid-2010s was intended to support either enhanced sludge washing or feed delivery to the Pretreatment Facility at the Hanford Waste Treatment and Immobilization Plant. As such, some physical properties of 200 West Area samples were measured under conditions that are no longer relevant. Because of the distinctly different nature of many past processes at the 200 West Area compared to the 200 East Area, insight from waste testing in the 200 East Area waste should be used with caution, as there may be significantly different qualities in the physical properties data between these two areas (both in situ and as measured in laboratory analyses). Based on this assessment, there is a need to collect additional physical property data to support planning for 200 West Area retrievals.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nuclear Data Sheets for A=123

Experimental nuclear structure and decay data are evaluated for all of 15 known nuclides of mass 123 (Ru, Rh, Pd, Ag, Cd, In, Sn, Sb, Te, I, Xe, Cs, Ba, La, Ce). For each nuclide, detailed evaluated spectroscopic information is presented in each reaction and decay, and the best values combining all available data are recommended for level properties, γ and β radiations, and other spectroscopic properties. No excited states have been identified in 123 Ru, 123 Rh and 123 Pd. For 123 Ag, the long-predicted 1/2 – β-emitting isomer has been identified at 60-keV by 2019Ch24 recently, resolving unknown excitation energies in the level scheme that was previously available only from isomeric decays of two isomers (202 ns and 393 ns) with the position and spin-parity of the former remaining unknown. Significant discrepancies exist between data on high-spin sequences based on 11/2 (–) isomer in 123 Cd (2002Hw01 and 2016Re05), which needs to be resolved with further experimental investigation. In 123 Cs, the 114-ns isomer as the πg 9/2 bandhead proposed at 231.6+x by 2000Gi12 has been resolved by 2004Si26 and 2004Si27 to be the 328-keV level that is proposed by 2000Gi12 as a separate level. Excited states in 123 La and 123 Ce have only been studied via (HI, xnγ) reactions, with their base levels and thus excitation energies remaining unknown. The β– decay schemes for daughter nuclide 123 Cd, 123 In and 123 Sn and the ε decay schemes for 123 Xe, 123 Cs and 123 Ba are considered incomplete due to large gaps between the highest observed excited levels and the Q-values. 123 Sn, 123 Sb, 123 Te and 123 I are the most extensively studied nuclides via various reactions and decays. Furthermore, this work supersedes earlier full evaluations of A=123 by 2004Oh11, 1993Oh12, 1980Ta02 and 1972Au10.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Multiyear Gridded Data Ensemble of Surface Biogenic Carbon Fluxes for North America: Evaluation and Analysis of Results

Accurate and fine-scale estimates of biogenic carbon fluxes are critical for measuring and monitoring the biosphere's responses and feedback to the climate system. Currently available data products from flux towers and model-intercomparison projects struggle to adequately represent spatiotemporal dynamics of surface biogenic carbon fluxes, and to quantify their uncertainties, which also are crucial to atmospheric inversion systems. To address these gaps, we introduce a new perturbed-parameter model ensemble with the CASA model to estimate surface biogenic carbon fluxes at monthly and 3-hourly scales for North America at ~500-m and 5-km resolutions. We first use the Extended Fourier Amplitude Sensitivity Testing to choose the three most sensitive parameters to be perturbed, maximum light use efficiency (E max ), optimal temperature of photosynthesis (T opt ), and temperature response of respiration (Q 10 ). The initial range for each parameter is broadly sampled for the L1 ensemble, but then we pruned E max with site-level primary productivity to derive an L2 ensemble with narrower uncertainty ranges. Ensembles are strongly correlated with site-level results at both monthly and 3-hourly scales, and the spread across L1/L2 ensemble members encompasses the range of AmeriFlux observations. Monthly variability in the L2 ensemble mean is 85% of the observed variability. The L2 ensemble outperforms diverse data products with the highest Taylor skill scores at diurnal to annual scales. Finally, the ensemble's seasonality agrees well with other models for most biome types and in high and middle latitudes, but inconsistencies are found in subtropical and tropical ecoregions and for annual totals over North America.

54 ENVIRONMENTAL SCIENCES↗

A Scalable Space-Time Domain Decomposition Approach for Solving Large Scale Nonlinear Regularized Inverse Ill Posed Problems in 4D Variational Data Assimilation

We address the development of innovative algorithms designed to solve the strong-constraint Four Dimensional Variational Data Assimilation (4DVar DA) problems in large scale applications. We present a space-time decomposition approach which employs the whole domain decomposition, i.e. both along the spacial and temporal direction in the overlapping case, and the partitioning of both the solution and the operator. Starting from the global functional defined on the entire domain, we get to a sort of regularized local functionals on the set of sub domains providing the order reduction of both the predictive and the Data Assimilation models. The algorithm convergence is developed. Performance in terms of reduction of time complexity and algorithmic scalability is discussed on the Shallow Water Equations on the sphere. The number of state variables in the model, the number of observations in an assimilation cycle, as well as numerical parameters as the discretization step in time and in space domain are defined on the basis of discretization grid used by data available at repository Ocean Synthesis/Reanalysis Directory of Hamburg University.

97 MATHEMATICS AND COMPUTING↗

Measuring the oscillator strength of intercombination lines of helium-like V ions in a laser-produced-plasma

In this work, we present results of measurements of the oscillator strength of intercombination lines of He-like Vanadium ions in high energy density (HED) laser-produced-plasmas and compare them with the simulations from commonly used codes and data from the NIST database. Whilst not yet sufficiently accurate to constrain different trusted atomic-physics models for the particular system studied, our results are in agreement with the available data within experimental error bars, yet differ from cruder approximations of the oscillator strength used in certain atomic-kinetics packages, suggesting that this general method could be further extended to be used as a measurement of the oscillator strength of additional atomic transitions under the extreme conditions that are achieved in HED experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An automated multi-component gas adsorption system (MC GAS)

The knowledge gap on adsorption of complex mixtures in the literature relative to single component data represents a persistent obstacle to developing accurate process models for adsorption separations. The collection of mixed gas adsorption data is an imminent need for improved understanding of the behavior of adsorbent systems in these diverse adsorption applications. Current approaches to understanding mixture adsorption using predictive theories based on pure component adsorption experiments often fail to capture the behavior of more complex, non-ideal systems. In this work, we present an automated volumetric instrument for the measurement of mixed gas adsorption isotherms. This instrument was validated by comparison to other in-house instruments and data available in the literature, and the binary adsorption measurements were found to be thermodynamically consistent. The automation of this instrument allows for rapid collection of high-quality mixture adsorption data.

47 OTHER INSTRUMENTATION↗

Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

Aykac, Deniz↗

Lidar Buoy Data Dictionary: For the 2020 – 2021 California Deployments

Pacific Northwest National Laboratory (PNNL) manages two AXYS WindSentinel™ buoys (Buoys #120 and #130) on behalf of the U.S. Department of Energy (DOE) that collect a comprehensive set of meteorological and oceanographic (metocean) data to support resource characterization for wind energy offshore. The buoys have been deployed off the California coast in partnership with the Bureau of Ocean Energy Management (BOEM) from September 2020 through October 2021. One buoy was deployed within the Morro Bay Call Area offshore central California; the other buoy was deployed within the Humboldt Call Area off the coast of northern California. The measurements from the buoys are used to characterize the metocean conditions near potential locations for offshore wind lease areas and are uploaded to DOE’s Data Archive and Portal (DAP). Plots are updated on the DAP webpage to visualize the recent metocean measurements. This document serves as a data dictionary – or reference guide – for understanding and interpreting the data available from the buoys. This document includes: (1) specifications for the buoy instrumentation (Section 2.0) (2) description of each plot and definition of measured parameters (Section 3.0) (3) description of data files and naming convention (Appendix A) (4) reference guide of measurements and variables (Appendix B).

17 WIND ENERGY↗

Nuclear Data Sheets for A=64

The evaluated experimental data are presented and evaluated for 13 known nuclides of mass 64 (Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, As, Se). For each nuclide, the best values combining all available data are recommended for spectroscopic properties. No excited states have been identified in 64 Ti, 64 As, and 64 Se. Only one excited state in 64 V as an isomer, and three in 64 Cr have been identified. Data for excited states in 64 Mn, 64 Fe, and 64 Co remain limited. 64 Ni, 64 Cu, and 64 Zn are the most studied nuclides through various reactions and decays, followed by 64 Ga and 64 Ge. In the opinion of the evaluators, there are several incomplete or discrepant aspects of the high-spin portion of the level scheme for 64 Zn above ≈5 MeV excitation which need to be resolved in further experiments using large γ-detector arrays. The decay schemes of 64 Ti β - , 64 As ε and 64 Se ε are unknown, while very little information is available for 64 V β - and 64 Cr β - . The decay schemes of 64 Mn β - , 64 Fe β - , 64 Co β - and 64Ge ε are somewhat better known, but still considered incomplete by evaluators. The decay scheme of 64 Ga ε decay is known in detail, however there is the possibility of additional levels populated above 4713 keV, as the Q(ε) value is 7171 keV. The β - , β + and ε decay modes of 64 Cu are well known, as this radionuclide is of great importance in applications, for example, as a dosimeter for neutron flux determination in nuclear reactors, and as a radiopharmaceutical for positron emission tomography (PET). This work supersedes earlier full evaluations of A=64 by 2007Si04, 1996Si12, 1991Si03, 1979Ha35 and 1974Au04.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Jupiter missions as probes of dark matter

Jupiter, the fascinating largest planet in the solar system, has been visited by nine spacecraft, which have collected a significant amount of data about Jovian properties. In this paper, we show that one type of the in situ measurements on the relativistic electron fluxes could be used to probe dark matter (DM) and dark mediator between the dark sector and our visible world. Jupiter, with its immense weight and cool core, could be an ideal capturer for DM with masses around the GeV scale. The captured DM particles could annihilate into long-lived dark mediators such as dark photons, which subsequently decay into electrons and positrons outside Jupiter. The charged particles, trapped by the Jovian magnetic field, have been measured in Jupiter missions such as the Galileo probe and the Juno orbiter. We use the data available to set upper bounds on the cross section of DM scattering off nucleons, σ χn , for dark mediators with lifetime of order $O$ (0.1–1) s. The results show that data from Jupiter missions already probe regions in the parameter space un- or under-explored by existing DM searches, e.g., constrain σχn of order (10 –41 –10 –39 ) cm 2 for 1 GeV DM dominantly annihilating into e + e – through dark mediators. This study serves as an example and an initial step to explore the full physics potential of the large planetary datasets from Jupiter missions. We also outline several other potential directions related to secondary products of electrons, positron signals and solar axions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A data engineering approach for sustainable chemical end-of-life management

The presence of chemicals causing significant adverse human health and environmental effects during end-of-life (EoL) stages is a challenge for implementing sustainable management efforts and transitioning towards a safer circular life cycle. Conducting chemical risk evaluation and exposure assessment of potential EoL scenarios can help understand the chemical EoL management chain for its safer utilization in a circular life-cycle environment. However, the first step is to track the chemical flows, estimate releases, and potential exposure pathways. Hence, this work proposes an EoL data engineering approach to perform chemical flow analysis and screening to support risk evaluation and exposure assessment for designing a safer circular life cycle of chemicals. This work uses publicly-available data to identify potential post-recycling scenarios (e.g., industrial processing/use operations), estimate inter-industry chemical transfers, and exposure pathways to chemicals of interest. Furthermore, a case study demonstration shows how the data engineering framework identifies, estimates, and tracks chemical flow transfers from EoL stage facilities (e.g., recycling and recovery) to upstream chemical life cycle stage facilities (e.g., manufacturing). Also, the proposed framework considers current regulatory constraints on closing the recycling loop operations and provides a range of values for the flow allocated to post-recycling uses associated with occupational exposure and fugitive air releases from EoL operations.

54 ENVIRONMENTAL SCIENCES↗