Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data fusion”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above ground biomass for greenhouse gas emissions reporting, and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) are applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

remote sensing↗
DOE OSTI2024

Calculating Reactivity and Fusion Energy Yield

During my time at Lawrence Livermore National Lab, I had the opportunity to intern at the HEDS (High Energy Density Science) Center and become an IFE (Inertial Fusion Energy) summer student for three weeks with Dr. Veronika Kruse as my mentor. Within this time frame, my research project’s goal was to develop an understanding of nuclear fusion while building technical skills in calculating and analyzing the required data. The following report outlines the process of calculating reactivity curves and energy yields of specific fusion reactions. For context, nuclear fusion is when two atomic nuclei combine, and energy is released. NIF (the National Ignition Facility), located at LLNL, uses laser-based inertial confinement fusion to achieve ignition. To simplify the process, NIF uses lasers to heat a small sphere or capsule, made up of primarily deuterium and tritium, to extremely high temperatures and densities to achieve fusion ignition, where more energy is released than the lasers introduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

“Exploring High Energy Interactions with CMS at the LHC”

This High Energy Physics research project achieved its goal of exploring high-energy interactions with 7, 8 and 13 TeV data accumulated by CMS at the Energy Frontier. For the original hadron calorimeter (HCAL) and for its upgrade during Long Shutdown 1 (LS1), the PI helped propose and implement the upgrading the phototubes, new electronics, and fast timing of the hadronic forward (HF) and hadronic outer (HO) calorimeters of CMS, projects which he had forcefully advocated since the inception of CMS. The PI and his colleagues Prof. J. Rohlf and chief electronics engineer E. Hazen, his post-docs A. Heister and S. Girgis, and his graduate students (P. Lawson and D. Arcaro) contributed software tools used in perfecting of μTCA and Advanced Mezzanine Card (AMC13) electronics, the PC board that provides clock, timing and DAQ service for HCAL (and now many other subdetectors and central systems in the upgraded CMS detector). This Task reaped the benefits of these hardware contributions 1) to hermiticity for missing energy searches, and 2) to forward tagging jets for Vector Boson Fusion processes by analyzing and publishing early data, including that for the Higgs discovery and for exotic and supersymmetric searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Sensitivity Study of LIFE Chamber Dynamics (Final Report)

The objective of this research is to investigate the turbulent flow state in a prototype of the LIFE fusion chamber, over many fusion cycles, using high-fidelity three-dimensional computational modeling. A fusion cycle duration is defined here as the time between laser shots (that induce fusion of the fuel stored in the capsule). The main problem of interest discussed in this report is the study of the sensitivity of the flow conditions in the fusion chamber to the radiation parameters used in the BUCKY code (Univ. Wisconsin Madison) that give the initial conditions for the present simulations. Of particular interest is the asymptotic “nth-state” cycle in the model fusion chamber and vacuum vessel assembly. The asymptotic (but unsteady) state was reached by advancing in time an initial value problem with estimated initial data that are thought to be representative of the fusion chamber state (in the mean). These conditions were provided to the Illinois team by LLNL. Many details of the flow solver, strategy and other auxiliary information can be found in a previous report entitled “CFD Simulation in Support of the Dynamic Chamber Systems Strategic Initiative.” Here, several quantities were investigated in detail. First, the global balance of mass in the fusion chamber and vacuum vessel. Second, the state of the density field inside the chamber: turbulence and density spectra, mean and fluctuation of the density. Third, to develop an understanding of the effect of forced recirculation imposed on the chamber-vacuum vessel ensemble, to understand the behavior and distribution of the capsule debris throughout the domain and instantaneous fluxes through the numerous ports and openings of the chamber. Fourth, and finally, to elucidate transport properties near the relatively cold walls of the chamber that might affect the chemistry of the complex fluid mixture from calculated temperature condition on the walls. These four questions have been investigated with different degrees of fidelity (as detailed below) assuming as few simplifications as possible while maintaining many elements of the complex geometry of the fusion chamber. Finally, the simulations do not include the effects of radiation explicitly, which is expected to be critical during the instants immediately after a laser pulse and fusion ignition, and instead a rational “handshake” procedure was developed to derive initial conditions consistent with those produced by BUCKY under different assumptions.

42 ENGINEERING↗
DOE OSTI2025

SciDAC ISEP: Integrated Simulation of Energetic Particles in Burning Plasmas

The objective of the SciDAC Center for Integrated Simulation of Energetic Particles in Burning Plasmas (ISEP) is to improve physics understanding of energetic particle (EP) confinement and EP interactions with burning thermal plasmas through large-scale simulations. The ISEP center will develop a multiscale and multiphysics ISEP framework for a predictive capability of EP physics and deliver an EP module incorporating both first-principles simulations and high fidelity reduced transport models to the fusion whole device modeling (WDM) project. The ISEP framework will enable us to perform long time, global kinetic simulations of EP physics in burning plasmas, by utilizing the full power of the next generation supercomputers. Our research and development activities will build on fruitful collaborations with computer scientists and applied mathematicians to offer enabling technologies for performance scalability, portability, solvers, coupling for integration with the fusion WDM project, and long-term preservation of data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

EMAPS: An Efficient Multiscale Approach to Plasma Systems with Non-MHD Scale Effects

Global interactions of energetic ions with magnetoplasmas and neutral gases lie at the core of many space and laboratory plasma phenomena ranging from solar wind entry into and transport within planetary magnetospheres and exospheres to fast-ion driven instabilities in fusion devices to astrophysics-in-lab experiments. The ability of computational models to properly account for physical effects that underlie such interactions, namely ion kinetic, ion cyclotron, Hall, collisional and ionization processes is important for the success and planning of experimental research in plasma physics. Understanding the physics of energetic ions, in particular their nonlinear resonance interactions with Alfvén waves, is central to improving the heating performance of magnetically confined plasmas for future energy generation. Fluid models are not adequate for high-beta plasmas as they cannot fully capture ion kinetic and cyclotron physics (e.g., ion behavior in the presence of magnetic nulls, shock structures, plasma interpenetration, etc.). Recent results from global reconnection simulations show that even in a MHD-like regime there may be significant differences between kinetic and MHD simulations. Therefore, kinetic modeling becomes essential for meeting modern day challenges in plasma physics. The hybrid approximation is an intermediate approximation between the fluid and fully kinetic approximations. It eliminates light waves, removes the electron inertial temporal and spatial scales from the problem and enables full-orbit ion kinetics. As a result, hybrid codes have become effective tools for exploring ion-scale driven phenomena associated with ion beams, shocks, reconnection and turbulence that control the large-scale behavior of laboratory and space magnetoplasmas. A number of numerical issues, however, make three-dimensional (3D) large-scale hybrid simulations of inhomogeneous magnetized plasmas prohibitively expensive or even impossible. To resolve these difficulties we have developed a novel Event-driven Multiscale Asynchronous Parallel Simulation (EMAPS) technology that replaces time stepping with self-adaptive update events. Local calculations are carried out only on an “as needed basis”. EMAPS (i) guarantees accurate and stable processing of physical variables in time accurate simulations, and (ii) eliminates unnecessary computation. Applying EMAPS to the hybrid model has resulted in the development of a unique parallel code, dimension-independent (compile-time-configurable) HYPERS (Hybrid Parallel Event-Resolved Simulator) that scales to hundreds of thousands of parallel processors. HYPERS advances electromagnetic fields and particles asynchronously on time scales determined by local physical laws and mesh properties. To achieve high computational accuracy in complex device geometries, HYPERS employs high-fidelity Cartesian grids with masked conductive cells. The HYPERS model includes multiple ion species, energy and momentum conserving ion-ion collisions, and provides a number of approximations for plasma resistivity and vacuum regions. Both local and periodic boundary conditions are allowed. The HYPERS solver preserves zero divergence of magnetic field. The project has demonstrated HYPERS capabilities on a number of applications of interest to fusion and astrophysical plasma physics applications listed below. 1. Theta-pinch formation of FRCs The formation, spontaneous spin-up, and stability of theta-pinch formed field-reversed configurations have been studied self-consistently in 3D. The end-to-end hybrid simulations reveal poloidal profiles of implosion-driven fast toroidal plasma rotation and demonstrate three discharge regimes as a function of experimental parameters: the decaying stable configuration, the tilt unstable configuration, and the nonlinear evolution of a fast growing tearing mode. 2. FRC collisions with magnetic mirrors Interactions of fast plasma streams and objects with magnetic obstacles (dipoles, mirrors, etc) lie at the core of many space and laboratory plasma phenomena ranging from magnetoshells and solar wind interactions with planetary magnetospheres to compact fusion plasmas. HYPERS simulations are compared with data from the MSX experiment (LANL) that focuses on the physics of magnetized collisionless shocks through the acceleration and subsequent stagnation of FRC plasmoids against a strong magnetic mirrors and flux-conserving boundaries. 3. Exploding magnetoplasmas Results from hybrid simulations of two experiments at the LAPD and Nevada Terawatt Facility are discussed where short-pulse lasers are used to ablate solid targets to produce plasmas that expand across external magnetic fields. The first simulation recreates flutelike density striations observed at the leading edge of a carbon plasma and predicts an early destruction of the magnetic cavity in agreement with experimental evidence. In the second simulation a polyethylene target is ablated into a mixture of protons and carbon ions. A mechanism is demonstrated that allows protons to penetrate the magnetic field in the form of a collimated flow. The results are compared to experimental data and single-fluid MHD simulations. The EMAPS framework has the potential for wide application in many other engineering and scientific fields, such as climate models, biological systems, electronic devices, seismic events, oil reservation simulators that all involve advancing solutions of partial differential equations in time where the rate of activity can be adapted widely over the spatial domain depending on locally space/time phenomena (“events”).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Resolving small signal measurements in experimental plasma environments using calibrated subtraction of noise signals

The performance of many diagnostic and control systems within fusion and other fields of research are often detrimentally affected by spurious noise signals. This is particularly true for those (such as radiation or particle detectors) working with very small signals. Common sources of radiated and conducted noise in experimental fusion environments include the plasma itself and instrumentation. The noise complicates data analysis, as illustrated by noise on signals measured with the heavy ion beam probe (HIBP) installed on the Madison Symmetric Torus. The noise is time-varying and often exceeds the secondary ion beam current (in contrast with previous applications). Analysis of the noise identifies the dominant source as photoelectric emission from the detectors induced by ultraviolet light from the plasma. This has led to the development of a calibrated subtraction technique, which largely removes the undesired temporal noise signals from data. The advantages of the technique for small signal measurement applications are demonstrated through improvements realized on HIBP fluctuation measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Metal droplet erosion and shielding plasma layer under plasma flows typical of transient processes in tokamaks

It is shown that the shielding plasma layer and metal droplet erosion in tokamaks are closely interrelated, because shielding plasma forms from the evaporated metal droplets, while droplet erosion is caused by the shielding plasma flow over the melted metal surface. Analysis of experimental data and theoretical models of these processes is presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Combining In-situ Diagnostics and Data Analytics for Discovery of Process-Structure-Property Relationships in AM parts – A Step Toward Digital Twins

In-situ additive manufacturing (AM) diagnostic tools (e.g., optical/infrared imaging, acoustic, etc.) already exist to correlate process anomalies to printed part defects. This current work aimed to augment existing capabilities by: 1) Incorporating in-situ imaging w/ machine learning (ML) image processing software (ORNL- developed "Peregrine") for AM process anomaly detection 2) Synchronizing multiple in-situ sensors for simultaneous analysis of AM build events 3) Correlating in-situ AM process data, generated part defects and part mechanical properties The key R&D question investigated was to determine if these new combined hardware/software tools could be used to successfully quantify defect distributions for parts build via SNL laser powder bed fusion (LPBF) machines, aiming to better understand data-driven process-structure-property- performance relationships. High resolution optical cameras and acoustic microphones were successfully integrated in two LPBF machines and linked to the Peregrine ML software. The software was successfully calibrated on both machines and used to image hundreds of layers of multiple builds to train the ML software in identifying printed part vs powder. The software's validation accuracy to identify this aspect increased from 56% to 98.8% over three builds. Lighting conditions inside the chamber were found to significantly impact ML algorithm predictions from in-situ sensors, so these were tailored to each machine's internal framework. Finally, 3D part reconstructions were successfully generated for a build from the compressed stack of layer-wise images. Resolution differences nearest and furthest from the optical camera were discussed. Future work aims to improve optical resolution, increase process anomalies identified, and integrate more sensor modalities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Resolution PM2.5 Concentrations Estimation Based on Stacked Ensemble Learning Model Using Multi-Source Satellite TOA Data

Nepal has experienced severe fine particulate matter (PM2.5) pollution in recent years. However, few studies have focused on the distribution of PM2.5 and its variations in Nepal. Although many researchers have developed PM2.5 estimation models, these models have mainly focused on the kilometer scale, which cannot provide accurate spatial distribution of PM2.5 pollution. Based on Gaofen-1/6 and Landsat-8/9 satellite data, we developed a stacked ensemble learning model (named XGBLL) combined with meteorological data, ground PM2.5 concentrations, ground elevation, and population data. The model includes two layers: a XGBoost and Light GBM model in the first layer, and a linear regression model in the second layer. The accuracy of XGBLL model is better than that of a single model, and the fusion of multi-source satellite remote sensing data effectively improves the spatial coverage of PM2.5 concentrations. Besides, the spatial distribution of the daily mean PM2.5 concentrations in the Kathmandu region under different air conditions was analyzed. The validation results showed that the monthly averaged dataset was accurate (R2 = 0.80 and root mean square error = 7.07). In addition, compared to previous satellite PM2.5 datasets in Nepal, the dataset produced in this study achieved superior accuracy and spatial resolution.

Environmental Sciences & Ecology↗
DOE OSTI2016

Development of the radial neutron camera system for the HL-2A tokamak

A new radial neutron camera system has been developed and operated recently in the HL-2A tokamak to measure the spatial and time resolved 2.5 MeV D-D fusion neutron, enhancing the understanding of the energetic-ion physics. The camera mainly consists of a multichannel collimator, liquid-scintillation detectors, shielding systems, and a data acquisition system. Measurements of the D-D fusion neutrons using the camera have been successfully performed during the 2015 HL-2A experiment campaign. The measurements show that the distribution of the fusion neutrons in the HL-2A plasma has a peaked profile, suggesting that the neutral beam injection beam ions in the plasma have a peaked distribution. It also suggests that the neutrons are primarily produced from beam-target reactions in the plasma core region. The measurement results from the neutron camera are well consistent with the results of both a standard {sup 235}U fission chamber and NUBEAM neutron calculations. In this paper, the new radial neutron camera system on HL-2A and the first experimental results are described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
DOE OSTI2024

EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D

We introduce EFIT-Prime, a novel machine learning surrogate model for EFIT (Equilibrium FIT) that integrates probabilistic and physics-informed methodologies to overcome typical limitations associated with deterministic and ad hoc neural network architectures. EFIT-Prime utilizes a neural architecture search-based deep ensemble for robust uncertainty quantification, providing scalable and efficient neural architectures that comprehensively quantify both data and model uncertainties. Physically informed by the Grad–Shafranov equation, EFIT-Prime applies a constraint on the current density J tor and a smoothness constraint on the first derivative of the poloidal flux, ensuring physically plausible solutions. Furthermore, the spatial location of the diagnostics is explicitly incorporated in the inputs to account for their spatial correlation. Extensive evaluations demonstrate EFIT-Prime's accuracy and robustness across diverse scenarios, most notably showing good generalization on negative-triangularity discharges that were excluded from training. Timing studies indicate an ensemble inference time of 15 ms for predicting a new equilibrium, offering the possibility of plasma control in real-time, if the model is optimized for speed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Ebolavirus Glycoprotein Fc Fusion Protein Protects Guinea Pigs against Lethal Challenge

Ebola virus (EBOV), a member of the Filoviridae that can cause severe hemorrhagic fever in humans and nonhuman primates, poses a significant threat to the public health. Currently, there are no licensed vaccines or therapeutics to prevent and treat EBOV infection. Several vaccines based on the EBOV glycoprotein (GP) are under development, including vectored, virus-like particles, and protein-based subunit vaccines. We previously demonstrated that a subunit vaccine containing the extracellular domain of the Ebola ebolavirus (EBOV) GP fused to the Fc fragment of human IgG1 (EBOVgp-Fc) protected mice against EBOV lethal challenge. Here, we show that the EBOVgp-Fc vaccine formulated with QS-21, alum, or polyinosinic-polycytidylic acid-poly-L-lysine carboxymethylcellulose (poly-ICLC) adjuvants induced strong humoral immune responses in guinea pigs. The vaccinated animals developed anti-GP total antibody titers of approximately 10 5 –10 6 and neutralizing antibody titers of approximately 10 3 as assessed by a BSL-2 neutralization assay based on vesicular stomatitis virus (VSV) pseudotypes. The poly-ICLC formulated EBOVgp-Fc vaccine protected all the guinea pigs against EBOV lethal challenge performed under BSL-4 conditions whereas the same vaccine formulated with QS-21 or alum only induced partial protection. Vaccination with a mucin-deletedEBOVgp-Fc construct formulated with QS-21 adjuvant did not have a significant effect in anti-GP antibody levels and protection against EBOV lethal challenge compared to the full-lengthGP construct. The bulk of the humoral response induced by the EBOVgp-Fc vaccine was directed against epitopes outside the EBOV mucin region. Our findings indicate that different adjuvants can eliciting varying levels of protection against lethal EBOV challenge in guinea pigs vaccinated with EBOVgp-Fc,and suggest that levels of total anti-GP antibodies elicit by protein-based GP subunit vaccines do not correlate with protection. In conclusion, our data further support the development of Fc fusions of GP as a candidate vaccine for human use.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Interpreting and reporting 40 Ar/ 39 Ar geochronologic data

The 40Ar/39Ar dating method is among the most versatile of geochronometers, having the potential to date a broad variety of K-bearing materials spanning from the time of Earth’s formation into the historical realm. Measurements using modern noble-gas mass spectrometers are now producing 40Ar/39Ar dates with analytical uncertainties of ~1%, thereby providing precise time constraints for a wide range of geologic and extraterrestrial processes. Analyses of increasingly smaller subsamples have revealed age dispersion in many materials, including some minerals used as neutron fluence monitors. Accordingly, interpretive strategies are evolving to address observed dispersion in dates from a single sample. Moreover, inferring a geologically meaningful “age” from a measured “date” or set of dates is dependent on the geological problem being addressed and the salient assumptions associated with each set of data. We highlight requirements for collateral information that will better constrain the interpretation of 40Ar/39Ar data sets, including those associated with single-crystal fusion analyses, incremental heating experiments, and in situ analyses of microsampled domains. To ensure the utility and viability of published results, we emphasize previous recommendations for reporting 40Ar/39Ar data and the related essential metadata, with the amendment that data conform to evolving standards of being findable, accessible, interoperable, and reusable (FAIR) by both humans and computers. Our examples provide guidance for the presentation and interpretation of 40 Ar/ 39 Ar dates to maximize their interdisciplinary usage, reproducibility, and longevity.

58 GEOSCIENCES↗
NASA NTRS1993

Monitoring land use and degradation using satellite and airborne data

In July 1990 AVIRIS and AIRSAR data were collected over the Manix Basin Area of the Mojave Desert to study land degradation in an arid area where centerpivot irrigation had been in use. The Manix Basin is located NE of Barstow, California, along Interstate-15 at 34 deg 57 min N 116 deg 35 min W. This region was covered by a series of lakes during the Late Pleistocence and Early Holocene. Beginning in the 1960's, areas were cleared of the native creosote bush-dominated plant community to be used for agricultural purposes. Starting in 1972 fields have been abandoned due to the increased cost of electricity needed to pump the irrigation water, with some fields abandoned as recently as 1988 and 1992. These circumstances provide a time series of abandoned fields which provide the possibility of studying the processes which act on agricultural fields in arid regions when they are abandoned. Ray et al. reported that polarimetric SAR (AIRSAR) could detect that the concentric circular planting furrows plowed on these fields persists for a few years after abandonment and then disappear over time and that wind ripples which form on these fields over time due to wind erosion can be detected with polarimetric radar. Ray et al. used Landsat Thematic Mapper (TM) bandpasses to generate NDVI images of the Manix Basin which showed that the fields abandoned for only a few years had higher NDVI's than the undisturbed desert while the fields abandoned for a longer time had NDVI levels lower than that of the undisturbed desert. The purpose of this study is to use a fusion of a time series of satellite data with airborne data to provide a context for the airborne data. The satellite data time series will additionally help to validate the observation and analysis of time-dependent processes observed in the single AVIRIS image of fields abandoned for different periods of time.

Ray, Terrill W.↗