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At least 1,549 records · Page 86

Determination of the magnetocaloric entropy change by field sweep using a heat flux setup

We report on a simple setup using a heat flux sensor adapted to a Quantum Design Physical Property Measurement System to determine the magnetocaloric entropy change (ΔS). The major differences for the existing setups are the simplicity of this assembly and the ease to obtain the isothermal entropy change either by a field sweep or a temperature sweep process. We discuss the use of these two processes applied to Gd and Gd{sub 5}Ge{sub 2}Si{sub 2} samples. The results are compared to the temperature sweep measurements and they show the advantages of this setup and of the field sweep procedure. We found a significant reduction of ΔS and on the refrigerating cooling power (RCP) at low field changes in a field sweep process when the sample is not driven to the same initial state for each temperature. We show that the field sweep process without any measuring protocol is the only correct way to experimentally determine ΔS and RCP for a practical regenerative refrigerator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Climate variables explain neutral and adaptive variation within salmonid metapopulations: the importance of replication in landscape genetics

Abstract Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population‐specific and pairwise F ST ) within five metapopulations (79 populations, 4583 individuals) of steelhead trout ( Oncorhynchus mykiss ) in the Columbia River Basin, USA . Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate‐related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and F ST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin‐wide to the metapopulation scale). Sensitivity analysis (leave‐one‐population‐out) revealed consistent relationships between climate variables and F ST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes ( N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

Hand, Brian K.↗

Rejecting cosmic background for exclusive charged current quasi elastic neutrino interaction studies with Liquid Argon TPCs; a case study with the MicroBooNE detector

Cosmic ray (CR) interactions can be a challenging source of background for neutrino oscillation and cross-section measurements in surface detectors. We present methods for CR rejection in measurements of charged-current quasielastic-like (CCQE-like) neutrino interactions, with a muon and a proton in the final state, measured using liquid argon time projection chambers (LArTPCs). Using a sample of cosmic data collected with the MicroBooNE detector, mixed with simulated neutrino scattering events, a set of event selection criteria is developed that produces an event sample with minimal contribution from CR background. Depending on the selection criteria used a purity between 50% and 80% can be achieved with a signal selection efficiency between 50% and 25%, with higher purity coming at the expense of lower efficiency. While using a specific dataset from the MicroBooNE detector and selection criteria values optimized for CCQE-like events, the concepts presented here are generic and can be adapted for various studies of exclusive v μ CCQE interactions in LArTPCs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fast response of fungal and prokaryotic communities to climate change manipulation in two contrasting tundra soils

Climate models predict substantial changes in temperature and precipitation patterns across Arctic regions, including increased winter precipitation as snow in the near future. Soil microorganisms are considered key players in organic matter decomposition and regulation of biogeochemical cycles. However, current knowledge regarding their response to future climate changes is limited. Here, we explore the short-term effect of increased snow cover on soil fungal, bacterial and archaeal communities in two tundra sites with contrasting water regimes in Greenland. In order to assess seasonal variation of microbial communities, we collected soil samples four times during the plant-growing season. The analysis revealed that soil microbial communities from two tundra sites differed from each other due to contrasting soil chemical properties. Fungal communities showed higher richness at the dry site whereas richness of prokaryotes was higher at the wet tundra site. We demonstrated that fungal and bacterial communities at both sites were significantly affected by short-term increased snow cover manipulation. Our results showed that fungal community composition was more affected by deeper snow cover compared to prokaryotes. The fungal communities showed changes in both taxonomic and ecological groups in response to climate manipulation. However, the changes were not pronounced at all sampling times which points to the need of multiple sampling in ecosystems where environmental factors show seasonal variation. Further, we showed that effects of increased snow cover were manifested after snow had melted. We demonstrated rapid response of soil fungal and bacterial communities to short-term climate manipulation simulating increased winter precipitation at two tundra sites. In particular, we provide evidence that fungal community composition was more affected by increased snow cover compared to prokaryotes indicating fast adaptability to changing environmental conditions. Since fungi are considered the main decomposers of complex organic matter in terrestrial ecosystems, the stronger response of fungal communities may have implications for organic matter turnover in tundra soils under future climate.

54 ENVIRONMENTAL SCIENCES↗

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗

Methodologies for optimal resource allocation to the national space program and new space utilizations. Volume 2: Resource allocation and smoothing model, programmer's manual

Appendixes are presented that provide model input requirements, a sample case, flow charts, and a program listing. At the beginning of each appendix, descriptive details and technical comments are provided to indicate any special instructions applicable to the use of that appendix. In addition, the program listing includes comment cards that state the purpose of each subroutine in the complete program and describe operations performed within that subroutine. The input requirements includes details on the many options that adapt the program to the specific needs of the analyst for a particular problem.

Source record↗

Ultrafast Laser Welding and Terahertz Time-domain Spectroscopy of Soda Lime Silicate Glass

Joining and welding techniques of similar and dissimilar materials have reached their limits due to the inflexibility of adapting dielectric materials, e.g., glasses and ceramics, reproducibility for transparent materials, and cycle process time. The ability to join pieces of glasses using laser irradiation allows rapid processing of vacuum insulating glass (VIG) for a widening range of commercial energy-efficient applications. We have used a 1064-nm laser wavelength with 15 picoseconds pulse width and a 155-kHz repetition rate to weld commercial plate glass pieces. The welded samples were characterized via x-ray fluorescence (XRF), time-of-flight secondary ion mass spectrometry (TOF–SIMS), polarimetry, and terahertz time-domain spectroscopy (THz-TDS) to determine the integrity of the weld and chemical changes in the welded areas. Our data shows no significant changes in glass chemistry and structure on average over nano- to micro-scales occurred from the welding process within the limits of the characterization tools. Our results demonstrate successful welding of glass plates without significant changes in the glass chemistry, structure, or properties in the laser-modified region or strains in the bulk glass.

Matthies, Kathleen [ORNL] (ORCID:0009000213135441)↗

A Lagrangian particle method with remeshing for tracer transport on the sphere

A Lagrangian particle method (called LPM) based on the flow map is presented for tracer transport on the sphere. The particles carry tracer values and are located at the centers and vertices of triangular Lagrangian panels. Remeshing is applied to control particle disorder and two schemes are compared, one using direct tracer interpolation and another using inverse flow map interpolation with sampling of the initial tracer density. Test cases include a moving-vortices flow and reversing-deformational flow with both zero and nonzero divergence, as well as smooth and discontinuous tracers. We examine the accuracy of the computed tracer density and tracer integral, and preservation of nonlinear correlation in a pair of tracers. Here, we compare results obtained using LPM and the Lin–Rood finite-volume scheme. An adaptive particle/panel refinement scheme is demonstrated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Autonomous phototaxis of hydrogel swimmers

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.

Science & Technology - Other Topics↗

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe’s terrestrial ecosystems: A review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. Finally, the use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.

54 ENVIRONMENTAL SCIENCES↗

Defining the Direction of Nuclear-Plasma Interaction Research at the National Ignition Facility

Electron-mediated nuclear-plasma interactions (NPIs) have the potential to change nuclear reaction rates in high energy density plasma (HEDP) environments, such as those found in experiments at the National Ignition Facility (NIF), in astrophysical phenomenon, or in nuclear detonations, relative to conventional laboratory measurements on room-temperature targets. Two Discovery Science shots to detect these interactions at the NIF were conducted in January and September 2017 at the conclusion of a campaign to develop the indirect-drive exploding pusher experimental platform and diagnostics. These shots were designed to measure the differential population of a high-spin isomer of 133 Xe of an inplasma versus a control sample, where a non-zero differential would indicate a measurable influence of the plasma on 134 Xe(n,2n) reactions. Preliminary observations from these shots were consistent with a small NPI effect, but improved theoretical understanding coupled with refined data analysis were needed to definitively establish the discovery or lack thereof. Achieving both of these, a statistically-credible NPI was indeed observed at a level predicted by an adapted Monte Carlo gamma-cascade model, a significant lowering by of the isomerto- ground state activity ratio in 133 Xe.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗

Assessing North American Forest Disturbance from the Landsat Archive

Forest disturbances are thought to play a major role in controlling land-atmosphere fluxes of carbon. Under the auspices of the North American Carbon Program, the LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) and NACP-FIA projects have been analyzing the Landsat satellite record to assess rates of forest disturbance across North America. In the LEDAPS project, wall-to-wall Landsat imagery for the period 1975-2000 has been converted to surface reflectance and analyzed for decadal losses (disturbance) or gains (regrowth) in biomass using a spectral "disturbance index". The NACP-FIA project relies on a geographic sample of dense Landsat image time series, allowing both disturbance rates and recovery trends to be characterized. Preliminary results for the 1990's indicate high rates of harvest within the southeastern US, Eastern Canada, and the Pacific Northwest, with spatially averaged (approx.50x50 km) turnover periods as low as 25-40 years. Lower rates of disturbance are found in the Rockies and Northeastern US.

Masek, Jeffrey G.↗

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗

A mechanism of adaptation to hypergravity in the statocyst of Aplysia californica

The gravity-sensing organ of Aplysia californica consists of bilaterally paired statocysts containing statoconia, which are granules composed of calcium carbonate crystals in an organic matrix. In early embryonic development, Aplysia contain a single granule called a statolith, and as the animal matures, statoconia production takes place. The objective of this study was to determine the effect of hypergravity on statoconia production and homeostasis and explore a possible physiologic mechanism for regulating this process. Embryonic Aplysia were exposed to normogravity or 3 x g or 5.7 x g and each day samples were analyzed for changes in statocyst, statolith, and body dimensions until they hatched. In addition, early metamorphosed Aplysia (developmental stages 7-10) were exposed to hypergravity (2 x g) for 3 weeks, and statoconia number and statocyst and statoconia volumes were determined. We also determined the effects of hypergravity on statoconia production and homeostasis in statocysts isolated from developmental stage 10 Aplysia. Since prior studies demonstrated that urease was important in the regulation of statocyst pH and statoconia formation, we also evaluated the effect of hypergravity on urease activity. The results show that hypergravity decreased statolith and body diameter in embryonic Aplysia in a magnitude-dependent fashion. In early metamorphosed Aplysia, hypergravity decreased statoconia number and volume. Similarly, there was an inhibition of statoconia production and a decrease in statoconia volume in isolated statocysts exposed to hypergravity in culture. Urease activity in statocysts decreased after exposure to hypergravity and was correlated with the decrease in statoconia production observed. In short, there was a decrease in statoconia production with exposure to hypergravity both in vivo and in vitro and a decrease in urease activity. It is concluded that exposure to hypergravity downregulates urease activity, resulting in a significant decrease in the formation of statoconia.

NASA Program Space Biology↗

Nutritional Status Assessment (SMO 016E)

The Nutritional Status Assessment Supplemental Medical Objective was initiated to expand nominal clinical nutrition testing of ISS astronauts, and to gain a better understanding of the time course of changes in nutritional status during flight. The primary activity of this effort was collecting blood and urine samples during flight for analysis after return to Earth. Samples were subjected to a battery of tests. The resulting data provide a comprehensive survey of how nutritional status and related systems are affected by 4-6 months of space flight. Analysis of these data has yielded many findings to date, including: Vision. Documented evidence that biochemical markers involved in one-carbon metabolism were altered in crewmembers who experienced vision-related issues during and after flight (1). Iron, Oxidative Stress, and Bone. In-flight data document a clear association of increased iron stores, markers of oxidative damage to DNA, and bone loss (2). Exercise. Documented that well-nourished crewmembers performing heavy resistance exercise returned from ISS with bone mineral densities unchanged from preflight (3). Furthermore, the response of bone to space flight and exercise countermeasures was the same in men and women (4). Body Mass. Crewmembers lose 2-5% of their body mass in the first month of flight, and maintain the lower body mass during flight (5). Additionally, the two devices to measure body mass on orbit, the SLAMMD and BMMD, provide similar results (5). Cytokines. Findings indicated that a pattern of persistent physiological adaptations occurs during space flight that includes shifts in immune and hormonal regulation (6). Fish/Bone. Documented a relationship between fish intake and bone loss in astronauts (that is, those who ate more fish lost less bone) (7). Vitamin K. Documented that in generally well-fed and otherwise healthy individuals, vitamin K status and bone vitamin K-dependent proteins are unaffected by space flight (and bed rest) (8). Testosterone. Documented that blood concentrations of testosterone were unchanged during flight, but a transient decline occurred after landing (9). Calcium. Nutrition SMO data contributed to the ISS Program by helping understand how and why the Urine Processor Assembly clogged with calcium sulfate precipitate (10). Sample Processing. Ground-based analytical testing results have also been published (11).

Smith, S. M.↗

Persistent Octrees for Parallel Mesh Refinement Through Non-Volatile Byte-Addressable Memory

We report that octree-based mesh adaptation has enabled simulations of complex physical phenomena. Existing meshing algorithms were proposed with the assumption that computer memory is volatile. Consequently, for failure recovery, the in-core algorithms need to save memory states as snapshots with slow file I/Os. The out-of-core algorithms store octants on disks for persistence. However, neither of them was designed to leverage unique characteristics of non-volatile byte-addressable memory (NVBM). In this paper, we propose a novel data structure Distributed Persistent Merged octree (DPM-octree) for both meshing and in-memory storage of persistent octrees using NVBM. It is a multi-version data structure and can recover from failures using its earlier persistent version stored in NVBM. In addition, we design a feature-directed sampling approach to help dynamically transform the DPM-octree layout for reducing NVBM-induced memory write latency. DPM-octree uses parity trees which are created using erasure coding and stored in NVBM to support low-latency in-memory octant recovery after data loss. DPM-octree has been successfully integrated with Gerris software for simulation of fluid dynamics. Finally, our experimental results with real-world scientific workloads show that DPM-octree scales up to 1.1 billion mesh elements with 1000 processors on the Titan supercomputer.

97 MATHEMATICS AND COMPUTING↗