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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.

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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Atmospheric Ionizing Radiation (AIR) Project Review

The National Council on Radiation Protection and Measurement (NCRP) and the National Academy of Science (NAS) established that the uncertainty in the data and models associated with the high-altitude radiation environment could and should be reduced. In response, the National Aeronautics and Space Administration (NASA) and the U.S. Department of Energy Environmental Measurements Laboratory (EML) created the Atmospheric Ionizing Radiation (AIR) Project under the auspices of the High Speed Research (HSR) Program Office at the Langley Research Center. NASA's HSR Program was developed to address the potential of a second-generation supersonic transport. A critical element focussed on the environmental issues, including the threat to crew and passengers posed by atmospheric radiation. Various international investigators were solicited to contribute instruments to fly on an ER-2 aircraft at altitudes similar to those proposed for the High Speed Civil Transport (HSCT). A list of participating investigators, their institutions, and instruments with quantities measured is presented. The flight series took place at solar minimum (radiation maximum) with northern, southern, and east/west flights. The investigators analyzed their data and presented preliminary results at the AIR Workshop in March, 1998. A review of these results are included.

Singleterry, R. C., Jr.↗
DOE OSTI2021

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta was responsible for leading the effort to develop statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. We regularly consult with Peter Gleckler (LLNL), Mark Taylor (SNL), and Rich Neale (NCAR) to provide additional insight into issues concerning CAM5 model development and multi-model evaluation of the AR5 archive. This grant was originally assigned to Indiana University where both the PI (Huerta) and the Postdoc (Nosedal) worked on the project from March 1, 2012-March 31, 2013.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Collaborative Project: The problem of bias in defining uncertainty in computationally enabled strategies for data-driven climate model development. Final Technical Report.

The objective of the project is to develop strategies for better representing scientific sensibilities within statistical measures of model skill that then can be used within a Bayesian statistical framework for data-driven climate model development and improved measures of model scientific uncertainty. One of the thorny issues in model evaluation is quantifying the effect of biases on climate projections. While any bias is not desirable, only those biases that affect feedbacks affect scatter in climate projections. The effort at the University of Texas is to analyze previously calculated ensembles of CAM3.1 with perturbed parameters to discover how biases affect projections of global warming. The hypothesis is that compensating errors in the control model can be identified by their effect on a combination of processes and that developing metrics that are sensitive to dependencies among state variables would provide a way to select version of climate models that may reduce scatter in climate projections. Gabriel Huerta at the University of New Mexico is responsible for developing statistical methods for evaluating these field dependencies. The UT effort will incorporate these developments into MECS, which is a set of python scripts being developed at the University of Texas for managing the workflow associated with data-driven climate model development over HPC resources. This report reflects the main activities at the University of New Mexico where the PI (Huerta) and the Postdocs (Nosedal, Hattab and Karki) worked on the project.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗
NASA NTRS2017

The Beryllium-10 Abundance in an Unusual Hibonite-Perovskite Refractory Inclusion from Allende: Implications for the Origin of Be-10

Beryllium-10 (decays to B-10, t1/2 = t(sub 1/2) = 1.3 Myr) 1.3 Myr) is a radionuclide that exclusively requires a is a radionuclide that exclusively requires a spallation origin. Therefore, one could obtain important insights into the irradiation environment in the solar nebula by understanding the distribution and abundance of this radionuclide in meteoritic inclusions. Most previous data are derived from B isotopic analysis of coarse-grained CV3 Ca-Al-rich Inclusions (CAIs) that have AL-26.Al-27 Al close to the canonical level of 5 x 10 (exp -5) and inferred Be-10/Be-9 ratios between 4 x 10(exp -4) and 1 x 10 (exp -2=3) [1-5]. Al-26-depleted FUN (Fractionaed and Unknown Nuclear anomalies) CAIs are less studied due to their rarity. FUN CAIs are thought to have formed prior to homogenization of Al-26/Al-27 Al and stable isotope anomalies (e.g., Ti-50) in the solar nebula, and thus represent one of the oldest Solar System solids [6]. So far, only three FUN CAIs (Axtell 2771, KT-1 and HAL) from CV3 chondrites have been measured for Be-10. They are characterized by variable Be-10/Be-9 ratios between (2.7−4.4) × 10(exp -4) [4,7]. Another group of rare, Al-26-free and and isotopically more anomalous inclusions, namely platy hibonite crystals (PLACs) from CM2 chondrites, have well-defined Be-10/Be-9 = (5.3 +/- 1.0) x 10 (exp -4) [9]. Al-26-free CAIs appear to have lower Be-1-/Be-9 than Al-26-bearing CAIs, although large analytical errors associated with some data would allow for an apparent overlap. It has been argued that the observed Be-10 variation resulted from the in-situ production of this radionuclide in CAIs (or their precursors) by irradiation, and the ratio difference simply reflects the fluctuation in projectile fluences [e.g., 9]. Another observation in support of this explanation comes from these CAIs' initial B-10/B-11 ratios, most of which are higher than the chondritic value 0.2478 [10]. This has been interpreted as a result of mixing between spallogenic B (B-10/B-11 = 0.4, co-produced with Be-10 in the irradiated solids) and a chondritic component [5,8]. Alternatively, given that all the inferred ratios, most of which are higher than chondritic value 0.2478 [10]. This has been interpreted as a result of mixing between spallogenic B (B-10/B-11 = 0.4, co-produced with Be-10 in the irradiated solics) and a chondritic component [5,8], Alternatively, given that all the inferred ratios in CAIs never fall below 3x10(exp -4), it has been proposed that the Solar System formed with baseline Be-10/Be-9 at this level, which originated from cosmic ray irradiation of the parental molecular cloud, and any value higher than this is a result of additional in-situ spallation [4,11]. Although not explicitly stated in this model, one would expect that inclusions that incorporated the background Be-10 abundance should form with the chondritic B isotopic ratio. However, the three FUN CAIs all have supra-chondritic B-10/B-11 indicative of the presence of a spallogenic component. To test whether some Be-10 did come into the solar nebula by inheritance,a better understanding of Be-10/Be-9 and initial B-10/B-11 in Al-26-free isotopically anomalous samples is needed. Here we present the result of Be10−B-10 system in an unsual hibonite-perovskite inclusion SHAL (son of HAL) from Allende.

Liu, M-C.↗
NASA NTRSDate not supplied

Lunar Search & Rescue Applications of Lunar GNSS

Accurate lunar navigation and timing knowledge provides for the development of safety-critical services in the cislunar and lunar surface domain. Currently under development, the Goddard Space Flight Center’s (GSFC) Search and Rescue Mission Office is investigating and integrating search and rescue (SAR) capability into planned and future lunar communication and navigation interfaces. Lunar Search and Rescue (LunaSAR) development has a stated end-goal for assured, reliable, and timely indication of distress events for a wide variety of lunar surface users, including government-sponsored, commercial, and international users. LunaSAR performance requirements are modelled after the current terrestrial Cospas-Sarsat distress notification system, leveraging an internationally robust global navigation satellite system (GNSS) ecosystem as a core element of survivor locating capability. This presentation will discuss NASA’s work to develop user-focused distress messaging capabilities including infusion of example sensor data for triggering of automated distress alerts coupled with location-tagging. Additionally, the presentation will examine overall message structures, rotating fields for use in bi-directional distress messaging, and specific use cases based on NASA’s lunar exploration and lunar communication relay architectures. Modelling and simulation of LunaSAR use by individual lunar explorers will be discussed, based on notional industry and government design reference missions and mission considerations. Results from GSFC-funded Internal Research and Development (IRAD) efforts will be detailed, including successful distress message formulation simulating the ingestion of example legacy space suit telemetry fields. Hardware-in-the-loop testing using high-reliability software defined radio (SDR) modules serve as an example of IRAD successes and the framework for technical requirements. Architectural development and technical evolution from 2020 to 2021 included alignment of LunaSAR distress waveforms with ongoing NASA LunaNet interoperability development, as well as engagement with NASA Lunar Spectrum authorities for allocation of UHF-band distress frequencies on the lunar surface. S-Band and UHF-band transmission characteristics will be detailed, along with band-specific applications of each emission type. Additionally, examples of ingestion and formatting of GNSS signals (using historical terrestrial National Marine Electronics Association-formatted GNSS data) will be detailed, underscoring lunar user needs for a common lunar GNSS receiver output message framework. Maturity and ability to support evolving lunar exploration goals has been demonstrated and will be detailed, with maturity gaps such as position, navigation, and timing (PNT) and lunar reference frames identified within the context of distress message generation. Provision of LunaSAR services for lunar surface users represents a new era of ensured safety for lunar explorers and builds off of forty years of the Cospas-Sarsat program, underscoring the importance of lunar GNSS for safety-critical applications and growing interest in safe, reliable lunar surface operations. Enabled by new GNSS systems being developed by government and industry partners, NASA will continue to evolve and integrate lunar GNSS types into distress message generation, with a focus on compact and efficient message transmission over various lunar communication links. When fielded, LunaSAR will be the first dedicated search and rescue notification system employed on another celestial body. Robust lunar navigation and timing services form the core of LunaSAR capabilities, allowing for system syncing with time-dominant sensors, and high-accuracy location of those in distress while engaged in lunar surface activities.

Search and Rescue↗
DOE OSTI2022

Quantitative assessment of fitting errors associated with streak camera noise in Thomson scattering data analysis

Thomson scattering measurements in high energy density experiments are often recorded using optical streak cameras. In the low-signal regime, noise introduced by the streak camera can become an important and sometimes the dominant source of measurement uncertainty. In this paper, we present a formal method of accounting for the presence of streak camera noise in our measurements. We present a phenomenological description of the noise generation mechanisms and present a statistical model that may be used to construct the covariance matrix associated with a given measurement. This model is benchmarked against simulations of streak camera images. We demonstrate how this covariance may then be used to weight fitting of the data and provide quantitative assessments of the uncertainty in the fitting parameters determined by the best fit to the data and build confidence in the ability to make statistically significant measurements in the low-signal regime, where spatial correlations in the noise become apparent. These methods will have general applicability to other measurements made using optical streak cameras.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Viper Science Operations: Lunar Dynamic Science Table and ‘Tracker’ Tool.

Introduction: The NASA VIPER lunar rover mission [1] presents a unique operational paradigm within the history of robotic spaceflight. The proximity of the Moon to the Earth and the terrain elements (surface characteristics, light/shadow dynamics, communication links) of the Lunar South Polar landing site create unprecedented operational conditions between these two planetary bodies. Apollo era lunar science and exploration included humans in situ to operate instruments and assimilate observational inputs in real-time. Previous lunar orbital missions have worked to operational timescales, e.g., decisional timelines and communication exchanges, that were weeks in duration. Mars rover missions have worked to operational timescales, e.g., decisional timelines and communication exchanges between Mars and Earth, that were hours, days, and weeks in length. In the case of the VIPER mission, our operational decisioning for rover driving and instrument commanding will be compressed to minute-scale timeframes. These operational conditions will directly impact the workflow and speed with which the VIPER Science Team (VST) will be required to synthesize and analyze data and produce timely science-driven decisions throughout surface mission operations [2]. The VST in the VIPER Mission Science Center (MSC) and the Mission Operations Center (MOC) shall provide mission-enhancing scientific input to guide traverse planning and drill site confirmation/selection throughout surface operations. Further, the VST input will be of vital importance to the mission’s ability to maximize science return and to meet broader NASA objectives for future lunar ISRU and exploration activities. Specifically, the VST in the MSC and MOC will provide science-driven, consensus-based, timely input and decision-making to enhance mission operations and align mission science return with broader Agency goals. They will enable the characterization of the distribution (lateral and vertical extent, concentration, variability), form (chemical/physical state of these reservoirs of lunar water and key isotopes), and context (e.g., accessibility/overburden, environment, soil mechanics, trafficability, and temperatures) of lunar polar volatiles and water content for the VIPER mission. Additionally, the MSC will be selecting or reconfirming the location and path towards and from the third drill site (Drill Site Charlie) within each Science Station [6]. To enable scientific decision-making within the operational paradigm of the VIPER lunar rover mission requires detailed articulation of the VST’s scientific objectives and goals, and the operationalization of these objectives and goals through their association with specific data products, tasks, and decisional procedures. Further, defining and tracking scientific success metrics throughout surface operations will enable the VST to have a quantified understanding of the mission’s evolving ability to accomplish the stated scientific objectives and goals both during and after the mission. This abstract provides an overview of the methods and development activities towards defining, operationalizing, and tracking scientific objectives and goals throughout VIPER surface operations. Specifically, we focus on the VIPER Lunar Dynamic Science Table (LDST) and the VIPER “Tracker” tool.

Darlene Sze Shien Lim↗
NASA NTRS2010

The Applied Meteorology Unit: Nineteen Years Successfully Transitioning Research into Operations for America's Space Program

The Applied Meteorology Unit (AMU) provides technology transition and technique development to improve operational weather support to the Space Shuttle and the entire American space program. The AMU is funded and managed by NASA and operated by a contractor that provides five meteorologists with a diverse mix of advanced degrees, operational experience, and associated skills including data processing, statistics, and the development of graphical user interfaces. The AMU's primary customers are the U.S. Air Force 45th Weather Squadron at Patrick Air Force Base, the National Weather Service Spaceflight Meteorology Group at NASA Johnson Space Center, and the National Weather Service Melbourne FL Forecast Office. The AMU has transitioned research into operations for nineteen years and worked on a wide range of topics, including new forecasting techniques for lightning probability, synoptic peak winds,.convective winds, and summer severe weather; satellite tools to predict anvil cloud trajectories and evaluate camera line of sight for Space Shuttle launch; optimized radar scan strategies; evaluated and implemented local numerical models; evaluated weather sensors; and many more. The AMU has completed 113 projects with 5 more scheduled to be completed by the end of 2010. During this rich history, the AMU and its customers have learned many lessons on how to effectively transition research into operations. Some of these lessons learned include collocating with the operational customer and periodically visiting geographically separated customers, operator submitted projects, consensus tasking process, use of operator primary advocates for each project, customer AMU liaisons with experience in both operations and research, flexibility in adapting the project plan based on lessons learned during the project, and incorporating training and other transition assistance into the project plans. Operator involvement has been critical to the AMU's remarkable success and many awards from NASA, the National Weather Association, and two citations from the Navy's Center of Excellence for Best Manufacturing Practices. This paper will present the AMU's proven methods and explain how they may be applied by other organizations to effectively transition research into operations.

Madura, John T.↗
DOE OSTI2016

use of cross-section covariance information in uncertainty analysis at modeling HTGR neutron physics - 18551

This work is aimed at improvement of high temperature gas cooled reactors (HTGR) neutron physics design calculations by application of uncertainty analysis with the use of cross-section covariance information. Methodology and codes for preparation of multigroup libraries of covariance information for individual isotopes from the basic 44-group binary library of SCALE-6 code system were developed. A 69-group library of covariance information in a special format for main isotopes and elements typical for HTGR was generated. This library can be used for estimation of uncertainties associated with nuclear data in analysis of HTGR neutron physics with design codes. As an example, calculations of one-group cross-section uncertainties for fission and capture reactions for main isotopes of the MHTGR-350 benchmark, as well as uncertainties of the multiplication factor (k{sub ∞}) for the MHTGR-350 fuel compact cell model and fuel block model were performed. These uncertainties were estimated by the developed technology with the use of WIMS-D code (technology SUW) and modules of SCALE-6 code system, namely, by TSUNAMI, KENO-VI and SAMS. The eight most important reactions on isotopes for MHTGR-350 benchmark were identified, namely: {sup 10}B(capt), {sup 238}U(n,γ), ν{sub 5}, {sup 235}U(n,γ), {sup 238}U(el), {sup nat}C(el), {sup 235}U(fiss)-{sup 235}U(n,γ) and {sup 235}U(fiss). It is shown that the main contribution in the uncertainty of multiplication factor of the fuel block model gives the reaction {sup 10}B(capt) ((n,α)+(n,γ)). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Data for: Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events

This dataset contains data and code associated with the paper Patel et al. "Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events".The coastal terrestrial-aquatic interface (TAI) is a highly dynamic system characterized by strong physical, chemical, and biological gradients. In particular, shifting soil redox conditions and consumption of terminal electron acceptors, due in part to dynamic hydrologic conditions, is a strong driver of carbon availability and transformations across TAIs. However, while redox dynamics are well described, our ability to quantitatively forecast rates of oxic to anoxic shifts in soils with different characteristics and inundation regimes is limited. We integrated field measurements, laboratory incubations, and model simulations to improve mechanistic understanding of oxygen consumption dynamics in coastal soils. Continuous in situ monitoring unexpectedly revealed that flooding caused temporary spikes in subsurface dissolved oxygen followed by rapid consumption in the wetlands. To further investigate these mechanisms in a controlled setting, we performed laboratory incubations using surface and subsurface soils from a TAI gradient (defined here as upland forest to transitional forest to wetland) in Western Lake Erie to measure oxygen consumption rates in TAI soils during flood events. In our experiments, wetland soils reached anoxia the fastest, in ∼ 9 h on average, whereas upland soils turned anoxic in ∼ 18 h. Subsurface upland soils did not turn anoxic even after two weeks of saturation in the lab, and their oxygen consumption patterns suggested carbon and/or nutrient limitation. These results are consistent with in-situ groundwater redox and oxygen measurements in the field, where wetland soils exhibited the highest rates of oxygen consumption along the TAI. Model simulations of oxygen consumption suggested that oxygen consumption had stronger abiotic controls in wetland soils but stronger biotic controls in upland soils, providing a useful framework for future incubation experiments. Microbial activity is a strong driver of oxygen consumption in TAI soils, although it is constrained by the availability of dissolved carbon in subsurface soils.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/COMPASS-DOE/cmps-time_to_anoxia (DOI: 10.5281/zenodo.10815374).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Determination of airplane aerodynamic parameters from flight data at high angles of attack

The problem of determining airplane aerodynamic model equations and estimating the associated parameters from flight data taken at high angles of attack is addressed. Two representations of the aerodynamic function based on the polynomial and spline representations are given. Then the technique of building an adequate model using a stepwise regression is presented with examples demonstrating the construction of the model and various approaches to model verification.

Klein, V.↗
DOE OSTI2022

Volcano infrasound: progress and future directions

Over the past two decades (2000–2020), volcano infrasound (acoustic waves with frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of academic research to a useful monitoring tool. As a result, infrasound is routinely used by volcano observatories around the world to detect, locate, and characterize volcanic activity. It is particularly useful in confirming subaerial activity and monitoring remote eruptions, and it has shown promise in forecasting paroxysmal activity at open-vent systems. Fundamental research on volcano infrasound is providing substantial new insights on eruption dynamics and volcanic processes and will continue to do so over the next decade. The increased availability of infrasound sensors will expand observations of varied eruption styles, and the associated increase in data volume will make machine learning workflows more feasible. More sophisticated modeling will be applied to examine infrasound source and propagation effects from local to global distances, leading to improved infrasound-derived estimates of eruption properties. Future work will use infrasound to detect, locate, and characterize moving flows, such as pyroclastic density currents, lahars, rockfalls, lava flows, and avalanches. Infrasound observations will be further integrated with other data streams, such as seismic, ground- and satellite-based thermal and visual imagery, geodetic, lightning, and gas data. The volcano infrasound community should continue efforts to make data and codes accessible and to improve diversity, equity, and inclusion in the field. In summary, the next decade of volcano infrasound research will continue to advance our understanding of complex volcano processes through increased data availability, sensor technologies, enhanced modeling capabilities, and novel data analysis methods that will improve hazard detection and mitigation.

58 GEOSCIENCES↗
DOE OSTI2015

ABCD2 identifies a subclass of peroxisomes in mouse adipose tissue

Highlights: • We examined the D2 localization and the proteome of D2-containing compartment in mouse adipose tissue. • We confirmed the presence of D2 on a subcellular compartment that has typical structure as a microperoxisome. • We demonstrated the scarcity of peroxisome markers on D2-containing compartment. • The D2-containing compartment may be a subpopulation of peroxisome in mouse adipose tissue. • Proteomic data suggests potential association between D2-containing compartment and mitochondria and ER. - Abstract: ATP-binding cassette transporter D2 (D2) is an ABC half transporter that is thought to promote the transport of very long-chain fatty acyl-CoAs into peroxisomes. Both D2 and peroxisomes increase during adipogenesis. Although peroxisomes are essential to both catabolic and anabolic lipid metabolism, their function, and that of D2, in adipose tissues remain largely unknown. Here, we investigated the D2 localization and the proteome of D2-containing organelles, in adipose tissue. Centrifugation of mouse adipose homogenates generated a fraction enriched with D2, but deficient in peroxisome markers including catalase, PEX19, and ABCD3 (D3). Electron microscopic imaging of this fraction confirmed the presence of D2 protein on an organelle with a dense matrix and a diameter of ∼200 nm, the typical structure and size of a microperoxisome. D2 and PEX19 antibodies recognized distinct structures in mouse adipose. Immunoisolation of the D2-containing compartment confirmed the scarcity of PEX19 and proteomic profiling revealed the presence of proteins associated with peroxisome, endoplasmic reticulum (ER), and mitochondria. D2 is localized to a distinct class of peroxisomes that lack many peroxisome proteins, and may associate physically with mitochondria and the ER.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A pectin methyltransferase modulates polysaccharide dynamics and interactions in Arabidopsis primary cell walls: Evidence from solid-state NMR

Plant cell walls contain cellulose embedded in matrix polysaccharides. Understanding carbohydrate structures and interactions is critical to the production of biofuel and biomaterials using these natural resources. Here we present a solid-state NMR study of cellulose and pectin in 13 C-labeled cell walls of Arabidopsis wild-type and mutant plants. Using 1D 13 C and 2D 13 C– 13 C correlation experiments, we detected a highly branched arabinan structure in qua2 and tsd2 samples, two allelic mutants for a pectin methyltransferase. Both mutants show close physical association between cellulose and the backbones of pectic homogalacturonan and rhamnogalacturonan-I. Relaxation and dipolar order parameters revealed enhanced microsecond dynamics due to polymer disorder in the mutants, but restricted motional amplitudes due to tighter pectin-cellulose associations. These molecular data shed light on polymer structure and packing in these two pectin mutants, helping to elucidate how pectin could influence cell wall architecture at the nanoscale, cell wall mechanics, and plant growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Delineating the mechanism of anti-Lassa virus GPC-A neutralizing antibodies

Lassa virus (LASV) is the etiologic agent of Lassa Fever, a hemorrhagic disease that is endemic to West Africa. During LASV infection, LASV glycoprotein (GP) engages with multiple host receptors for cell entry. Neutralizing antibodies against GP are rare and principally target quaternary epitopes displayed only on the metastable, pre-fusion conformation of GP. Currently, the structural features of the neutralizing GPC-A antibody competition group are understudied. Structures of two GPC-A antibodies presented here demonstrate that they bind the side of the pre-fusion GP trimer, bridging the GP1 and GP2 subunits. Complementary biochemical analyses indicate that antibody 25.10C, which is broadly specific, neutralizes by inhibiting binding of the endosomal receptor LAMP1 and also by blocking membrane fusion. The other GPC-A antibody, 36.1F, which is lineage-specific, prevents LAMP1 association only. These data illuminate a site of vulnerability on LASV GP and will guide efforts to elicit broadly reactive therapeutics and vaccines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

It's not just the food you eat: Environmental factors in the development of food allergies

The dramatic rise in the prevalence of food allergy and food allergy-associated anaphylaxis in the past few decades has fueled investigative interest into understanding this puzzling trend. Here, we review the question as to whether important external environmental determinants beyond dietary habits and exposure to food allergens are involved. This review will summarize our current understanding of these environment determinants, derived from the latest experimental and epidemiological research. Specifically, we will review the role of exposures that affect skin barrier function, development of a diverse microbiome, and food processing. Additional exposures of concern are insufficient sunlight, endocrine disrupting chemicals and pesticides, and use of specific pharmaceutical agents that may drive or modify the risk for food allergy. Despite limitations in the quantity and quality of research to date, many new epidemiological associations and experimental data in support of this paradigm have emerged.

54 ENVIRONMENTAL SCIENCES↗