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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Elevation Change of Drangajokull, Iceland, from Cloud-Cleared ICESat Repeat Profiles and GPS Ground-Survey Data

Located on the Vestfirdir Northwest Fjords), DrangaJokull is the northernmost ice map in Iceland. Currently, the ice cap exceeds 900 m in elevation and covered an area of approx.l46 sq km in August 2004. It was about 204 sq km in area during 1913-1914 and so has lost mass during the 20th century. Drangajokull's size and accessibility for GPS surveys as well as the availability of repeat satellite altimetry profiles since late 2003 make it a good subject for change-detection analysis. The ice cap was surveyed by four GPS-equipped snowmobiles on 19-20 April 2005 and has been profiled in two places by Ice, Cloud. and land Elevation Satellite (ICESat) 'repeat tracks,' fifteen times from late to early 2009. In addition, traditional mass-balance measurements have been taken seasonally at a number of locations across the ice cap and they show positive net mass balances in 2004/2005 through 2006/2007. Mean elevation differences between the temporally-closest ICESat profiles and the GPS-derived digital-elevation model (DEM)(ICESat - DEM) are about 1.1 m but have standard deviations of 3 to 4 m. Differencing all ICESat repeats from the DEM shows that the overall elevation difference trend since 2003 is negative with losses of as much as 1.5 m/a from same season to same season (and similar elevation) data subsets. However, the mass balance assessments by traditional stake re-measurement methods suggest that the elevation changes where ICESat tracks 0046 and 0307 cross Drangajokull are not representative of the whole ice cap. Specifically, the area has experienced positive mass balance years during the time frame when ICESat data indicates substantial losses. This analysis suggests that ICESat-derived elevations may be used for multi-year change detection relative to other data but suggests that large uncertainties remain. These uncertainties may be due to geolocation uncertainty on steep slopes and continuing cloud cover that limits temporal and spatial coverage across the area.

Shuman, Christopher A.↗
NASA NTRS2017

A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data

The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.

Koslovsky, Matthew↗
NASA NTRS2017

Large-scale product of forest height using a new approach from spaceborne repeat-pass SAR interferometry and LIDAR

Spaceborne SAR interferometry (InSAR) has the potential of mapping the forest height on a global scale and a monthly/weekly basis under all weather conditions, which can improve our understanding of the global carbon dynamics. In previous work, repeatpass SAR interferometry from spaceborne sensors is utilized to create large-scale forest height maps (that are particularly interested for large-scale ecological research) based on a newly developed approach. This paper thus serves as a summary paper and also sheds light on the future directions with improved results. In particular, it will be shown that repeat-pass SAR interferometry is able to create a large-scale forest height mosaic product with RMSE 4 m for forest stands on the order of 20 hectares through using the past spaceborne repeat-pass InSAR observations (i.e. JAXA’s ALOS-1 and ALOS-2) combined with sparse airborne lidar training samples over the forested areas in New England, US. Moreover, the results and performance of this approach can be remarkably improved with several enhancement techniques that can be easily satisfied with use of future spaceborne repeat-pass InSAR and lidar missions (e.g. NASA-ISRO’s NISAR and NASA’s GEDI). The methodology described in this paper can be considered as a complimentary tool to the existing PolInSAR technique and also serves as an observing prototype for the future spaceborne missions of repeatpass InSAR in fusion with lidar (e.g. NISAR and GEDI).

Treuhaft, Robert↗
NASA NTRS2022

Resolving the fine structure in the energy landscapes of repeat proteins

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein–protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.

Murilo N. Sanches↗
DOE OSTI2023

Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska

The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can cause dramatic top–down thaw. A challenge in understanding this is to quantify fire-induced thaw settlement at large scales (>1000 km 2 ). In this study, we explored the potential of using Landsat products for a large-scale estimation of fire-induced thaw settlement across a well-studied area representative of ice-rich lowland permafrost in interior Alaska. Six large fires have affected ~1250 km 2 of the area since 2000. We first identified the linkage of fires, burn severity, and land cover response, and then developed an object-based machine learning ensemble approach to estimate fire-induced thaw settlement by relating airborne repeat lidar data to Landsat products. The model delineated thaw settlement patterns across the six fire scars and explained ~65% of the variance in lidar-detected elevation change. Our results indicate a combined application of airborne repeat lidar and Landsat products is a valuable tool for large scale quantification of fire-induced thaw settlement.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Interim Measures Pilot Study Completion Report, South Repeater Building, Solid Waste Management Unit 121, Hydraulic Containment and Groundwater Treatment System for Per- and Polyfluoroalkyl Substances

This Per- and Polyfluoroalkyl Substances (PFAS) Interim Measures Pilot Study Completion Report was prepared for the National Aeronautics and Space Administration by AECOM Technical Services, Inc. under Contract 80KSC019D0010, Task Order 80KSC021F0096. The purpose of this report is to document the pilot study activities at the South Repeater Building, Solid Waste Management Unit (SWMU) 121. This report details the additional assessment activities completed from June 2023 through November 2023 and the subsequent pilot study completed at the South Repeater Building conducted in December 2023 through February 2024. Initial activities were conducted in accordance with the Pilot Study Work Plan (NASA 2023), submitted to the KSC Remediation Team and accepted by the team on October 26, 2023. The objectives of the pilot study were to: • Provide information on aquifer characteristics and to aid in future modeling and remedial design activities to mitigate off-KSC migration of PFAS compounds. • Develop information on characteristics of the surficial aquifer system, specifically transmissivity, storage coefficient, hydraulic conductivity, and vertical hydraulic conductivity. • Obtain data to support construction and calibration of a groundwater flow model. • Acquire design parameters necessary for future remedial design activities, specifically radius of influence, drawdown, flow rates, and pump settings. The following activities were completed to meet the pilot study objectives: • Groundwater and surface water sampling • Geophysical investigation via Hydraulic Profiling Tool (HPT) and soil sampling • Installation of observation and extraction wells via rotosonic techniques • Slug, step, and pump testing activities • Initial modeling efforts for a groundwater hydraulic containment system. Results of the pilot study and modeling activities are being used in the development of a groundwater containment and treatment system for the site.

PFAS↗
NASA NTRS2024

Interim Measures Work Plan: South Repeater Building: Solid Waste Management Unit 121: Hydraulic Containment and Groundwater Treatment System for Per- and Polyfluoroalkyl Substances: Kennedy Space Center, Florida

This document presents the design details of a granular activated carbon (GAC) hydraulic containment and groundwater treatment system Interim Measures Work Plan for the South Repeater Building site (South Repeater, Solid Waste Management Unit 121), located at John F. Kennedy Space Center (KSC), Florida. The interim measures (IM) treatment area includes the source area and downgradient property boundary, which have been impacted by per- and polyfluoroalkyl substances (PFAS). The objectives of the IM are to treat the source area and mitigate PFAS migration to areas outside of KSC boundaries. This document was prepared by AECOM Technical Services, Inc., for the National Aeronautics and Space Administration under Contract 80KSC019D0010, Task Order 80KSC021F0096. The IM consists of the installation and operation of 19 extraction wells and an associated groundwater treatment system. A total of 13 wells will be installed to a depth of 34 feet below land surface (bls) to target the upper medium-grained sand with shell layer. A total of six wells will be installed to a depth of 56 feet bls to target the lower layer of poorly graded sand with shell fragments. The system will be designed to operate each extraction well simultaneously using submersible pumps at flow rates of 5 or 10 gallons per minute (gpm), excluding one extraction well with a flow rate of 30 gpm. The extracted groundwater will be conveyed to a groundwater treatment system, where it will be treated via GAC prior to disposal via infiltration. To evaluate treatment system performance, baseline groundwater sampling will be conducted prior to treatment system startup. Performance monitoring will be completed quarterly for the first year. A total of eight performance monitoring wells will be installed to a depth of 12 feet bls, and eight performance monitoring wells will be installed to a depth of 30 feet bls. In addition to the installation of 16 performance monitoring wells, 12 existing monitoring wells will be incorporated into the performance monitoring program.

groundwater treatment↗
DOE OSTI2022

Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P 7 units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Tetratricopeptide repeat protein SlREC2 positively regulates cold tolerance in tomato

Abstract Cold stress is a key environmental constraint that dramatically affects the growth, productivity, and quality of tomato (Solanum lycopersicum); however, the underlying molecular mechanisms of cold tolerance remain poorly understood. In this study, we identified REDUCED CHLOROPLAST COVERAGE 2 (SlREC2) encoding a tetratricopeptide repeat protein that positively regulates tomato cold tolerance. Disruption of SlREC2 largely reduced abscisic acid (ABA) levels, photoprotection, and the expression of C-REPEAT BINDING FACTOR (CBF)-pathway genes in tomato plants under cold stress. ABA deficiency in the notabilis (not) mutant, which carries a mutation in 9-CIS-EPOXYCAROTENOID DIOXYGENASE 1 (SlNCED1), strongly inhibited the cold tolerance of SlREC2-silenced plants and empty vector control plants and resulted in a similar phenotype. In addition, foliar application of ABA rescued the cold tolerance of SlREC2-silenced plants, which confirms that SlNCED1-mediated ABA accumulation is required for SlREC2-regulated cold tolerance. Strikingly, SlREC2 physically interacted with β-RING CAROTENE HYDROXYLASE 1b (SlBCH1b), a key regulatory enzyme in the xanthophyll cycle. Disruption of SlBCH1b severely impaired photoprotection, ABA accumulation, and CBF-pathway gene expression in tomato plants under cold stress. Taken together, this study reveals that SlREC2 interacts with SlBCH1b to enhance cold tolerance in tomato via integration of SlNCED1-mediated ABA accumulation, photoprotection, and the CBF-pathway, thus providing further genetic knowledge for breeding cold-resistant tomato varieties.

Zhang, Ying (ORCID:0000000169841164)↗
DOE OSTI2024

A Science Gateway for the Repeatable Analysis of Machine Learning Predicted Gravity Anomalies

In recent years, deep learning has become an increasingly popular alternative for modeling in geoscience applications due to its scalability and efficiency. However, the interpretability, compute, data volume, and hyperparameter tuning requirements of deep learning models make development and monitoring difficult. Furthermore, model explainability and communicating results obtained by these models to users or domain experts is a challenge, as domain experts in geoscience also need to have a deep understanding of how those models function in order to support their scientific works. Here, we describe a science gateway and machine learning pipeline for predicting gravity anomalies from geophysical data. The gateway, built on open-source technologies, provides a holistic view of the pipeline through interactive visualizations aimed at enabling efficient exploratory data analysis. The repeatability, reproducibility, and monitoring capabilities of this overall system allow us to iterate and analyze at scale. Using this pipeline and gateway, we can repeatedly produce accurate high-resolution gravity anomaly datasets. By describing the underlying technologies, implementation, and results, here we provide a foundation for the broader adoption of science gateways into cross-cutting geoscience and machine learning research projects as a means to improve the scientific discovery and collaboration in the geophysics and computational sciences community.

58 GEOSCIENCES↗
DOE OSTI2023

Multiple mechanisms explain loss of anthocyanins from betalain‐pigmented Caryophyllales, including repeated wholesale loss of a key anthocyanidin synthesis enzyme

Summary In this study, we investigate the genetic mechanisms responsible for the loss of anthocyanins in betalain‐pigmented Caryophyllales, considering our hypothesis of multiple transitions to betalain pigmentation. Utilizing transcriptomic and genomic datasets across 357 species and 31 families, we scrutinize 18 flavonoid pathway genes and six regulatory genes spanning four transitions to betalain pigmentation. We examined evidence for hypotheses of wholesale gene loss, modified gene function, altered gene expression, and degeneration of the MBW (MYB‐bHLH‐WD40) trasnscription factor complex, within betalain‐pigmented lineages. Our analyses reveal that most flavonoid synthesis genes remain conserved in betalain‐pigmented lineages, with the notable exception of TT19 orthologs, essential for the final step in anthocyanidin synthesis, which appear to have been repeatedly and entirely lost. Additional late‐stage flavonoid pathway genes upstream of TT19 also manifest strikingly reduced expression in betalain‐pigmented species. Additionally, we find repeated loss and alteration in the MBW transcription complex essential for canonical anthocyanin synthesis. Consequently, the loss and exclusion of anthocyanins in betalain‐pigmented species appear to be orchestrated through several mechanisms: loss of a key enzyme, downregulation of synthesis genes, and degeneration of regulatory complexes. These changes have occurred iteratively in Caryophyllales, often coinciding with evolutionary transitions to betalain pigmentation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quantum Network Repeater Simulation Package (QNPack) v1.0.0

Existing quantum network testbeds and prototypes are typically implemented in laboratory experiments with limited functionality and operate in a tightly coupled manner. These characteristics make it difficult to evaluate the behavior of emerging quantum platforms and protocols beyond local resource limitations. The QNPack software enables full-stack modeling of quantum repeater networks that allows researchers to simulate new approaches, and understand emergent behaviors, from local to national scales. Novel capabilities include: (1) performant and accurate quantum models that can be executed as independent simulations, which will allow users to characterize specific analog quantum processes, quantum devices, and protocols, (2) a modular and extensible approach to the simulation architecture to accommodate new quantum technologies, protocols, and topologies as they are developed across the quantum repeater generations under evaluation, and (3) a focus on managing the interactions between the simulation framework sub-components so that they may be re-used and composed in flexible ways.

Kissel, Ezra [Lawrence Berkeley National Laborator↗
DOE OSTI2023

Low-velocity repeated impact behaviors of Polymer Fiber Reinforced Plastics (PFRPs)

Modern fiber-reinforced composites have become ubiquitous across multiple industries due to their excellent weight-to-strength ratio. Typically glass or carbon fibers are widely used. While Glass or Carbon Fiber-Reinforced Plastics (GFPRs or CFPRs) have good stiffness, strength, and fatigue life, they are expensive and difficult to recycle. Researchers are exploring Polymer Fiber-Reinforced Plastics (PFRPs) as an alternative solution. PFRPs utilize polymer fibers and a polymer matrix. A wide range of materials options is available, including low-cost thermoplastics such as polyethylene or polypropylene. These thermoplastics are easy to handle and recyclable without special methods. Manufacturing parts using thermoplastics are well-established as well. However, their mechanical performances have not been extensively studied compared to GFRPs or CFRPs. This study examines the low-velocity impact resistance of PFRPs made of different thermoplastics. The low-velocity impacts are applied through a drop-weight tower. The experiment is divided into two cases: a single perforation impact and low-energy repeated impacts. Energy absorption and the number of impacts to failure are measured. The results are compared to traditional CFRPs which have a thermoset matrix. The PFRPs demonstrate energy absorption capabilities comparable to or greater than those of CFRPs with respect to specimen thickness and density. Additionally, the PFRPs show significantly higher impacts-to-failure than the CFRPs in low-energy repeated impact tests. This is particularly noteworthy considering that the PFRPs are much simpler and more economical to manufacture than CFRPs. To further

Ko, Seunghyun↗
DOE OSTI2023

Tandem repeats in giant archaeal Borg elements undergo rapid evolution and create new intrinsically disordered regions in proteins

Borgs are huge, linear extrachromosomal elements associated with anaerobic methane-oxidizing archaea. Striking features of Borg genomes are pervasive tandem direct repeat (TR) regions. Here, we present six new Borg genomes and investigate the characteristics of TRs in all ten complete Borg genomes. We find that TR regions are rapidly evolving, recently formed, arise independently, and are virtually absent in host Methanoperedens genomes. Flanking partial repeats and A-enriched character constrain the TR formation mechanism. TRs can be in intergenic regions, where they might serve as regulatory RNAs, or in open reading frames (ORFs). TRs in ORFs are under very strong selective pressure, leading to perfect amino acid TRs (aaTRs) that are commonly intrinsically disordered regions. Proteins with aaTRs are often extracellular or membrane proteins, and functionally similar or homologous proteins often have aaTRs composed of the same amino acids. We propose that Borg aaTR-proteins functionally diversify Methanoperedens and all TRs are crucial for specific Borg–host associations and possibly cospeciation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structure-aware annotation of leucine-rich repeat domains

Protein domain annotation is typically done by predictive models such as HMMs trained on sequence motifs. However, sequence-based annotation methods are prone to error, particularly in calling domain boundaries and motifs within them. These methods are limited by a lack of structural information accessible to the model. With the advent of deep learning-based protein structure prediction, existing sequenced-based domain annotation methods can be improved by taking into account the geometry of protein structures. We develop dimensionality reduction methods to annotate repeat units of the Leucine Rich Repeat solenoid domain. The methods are able to correct mistakes made by existing machine learning-based annotation tools and enable the automated detection of hairpin loops and structural anomalies in the solenoid. The methods are applied to 127 predicted structures of LRR-containing intracellular innate immune proteins in the model plant Arabidopsis thaliana and validated against a benchmark dataset of 172 manually-annotated LRR domains.

Xu, Boyan↗
DOE OSTI2024

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗