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At least 379 records · Page 21

A Comparison of Bearing Measurements to Surface Features Generated Using Stereophotoclinometry and Surface Feature Navigation Techniques

The Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRIS-REx) mission to the asteroid Bennu completed successful two-and-a-half year proximity operations in May 2021. The mission comprehensively mapped Bennu at unprecedented detail and collected a sample of Bennu’s surface to return to Earth. Throughout proximity operations, the OSIRIS-REx navigation team used the maps made of Bennu’s surface to navigate in the Bennu environment with high accuracy through the use of precise and accurate optical navigation data, radiometric data, and force modelling. The primary type of optical navigation measurements extracted from the images captured by OSIRIS-REx (particularly after first entering orbit around Bennu) were observations of known features on Bennu’s surface. Two related but different techniques/tools were used to extract these observations from the images: the Goddard Image Analysis and Navigation Tool Surface Feature Navigation (GIANT SFN) and Stereophotoclinometry (SPC) Autoregister. In this paper we compare the differences between the observables extracted using GIANT SFN and SPC Autoregister, explain the differences, and discuss where each technique is best suited.

Andrew Liounis↗

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗

Finding the lost river gas field - Lineament density analysis in hydrocarbon exploration

A comparative trial analysis of lineament density in 1:500,000 Landsat and 1:48,000 aerial Landsat-simulator images of a gas-field region in West Virginia is presented. The high-contrast, band 4, 5, 7 color composite Landsat image was interpreted independently by two analysts. The slightly different lineament maps were evaluated in terms of lineament-density variation in 10 x 10-km areas, and the resulting areal-variation maps are found to be statistically equivalent. High lineament density is shown to be associated with productive gas wells. Comparison of ground-based substructural contour maps and lineament-density analyses of the Landsat-simulator images reveals good correlation between density maxima or isopleths and substructural features associated with hydrocarbon formations. A hydrocarbon-exploration strategy using both Landsat and aerial images is proposed.

Lang, H. R.↗

Double-Atom Catalysts Featuring Inverse Sandwich Structure for CO 2 Reduction Reaction: A Synergetic First-Principles and Machine Learning Investigation

Electrocatalytic CO 2 reduction reactions (CO 2 RR) based on scalable and highly efficient catalysis provide an attractive strategy for reducing CO 2 emissions. Here in this work, we combined first-principles density functional theory (DFT) and machine learning (ML) to comprehensively explore the potential of double-atom catalysts (DACs) featuring an inverse sandwich structure anchored on defective graphene (gra) to catalyze CO 2 RR to generate C 1 products. We started with five homonuclear M 2 ⊥gra (M = Co, Ni, Rh, Ir, and Pt), followed by 127 heteronuclear MM'⊥gra (M = Co, Ni, Rh, Ir, and Pt, M' = Sc–Au). Stable DACs were screened by evaluating their binding energy, formation energy, and dissolution potential of metal atoms, as well as conducting first-principles molecular dynamics simulations with and without solvent water molecules. Based on DFT calculations, Rh 2 ⊥gra DAC was found to outperform the other four homonuclear DACs and the Rh-based single- and double-atom catalysts of noninverse sandwich structures. Out of the 127 heteronuclear DACs, 14 were found to be stable and have good catalytic performance. An ML approach was adopted to correlate key factors with the activity and stability of the DACs, including the sum of radii of metal and ligand atoms (d M–M' , d M–C , and d M'–C ), the sum and difference of electronegativity of two metal atoms (P M + P M' , P M – P M '), the sum and difference of first ionization energy of two metal atoms (I M + I M' , I M – I M '), the sum and difference of electron affinity of two metal atoms (A M + A M' , A M – A M '), and the number of d-electrons of the two metal atoms (Nd). The obtained ML models were further used to predict 154 potential electrocatalysts out of 784 possible DACs featuring the same inverse sandwich configuration. Overall, this work not only identified promising CO 2 RR DACs featuring the reported inverse sandwich structure but also provided insights into key atomic characteristics associated with high CO 2 RR activity.

30 DIRECT ENERGY CONVERSION↗

Updated Mars Mission Architectures Featuring Nuclear Thermal Propulsion

Nuclear thermal propulsion (NTP) can potentially enable routine human exploration of Mars and the solar system. By using nuclear fission instead of a chemical combustion process, and using hydrogen as the propellant, NTP systems promise rocket efficiencies roughly twice that of the best chemical rocket engines currently available. The most recent major Mars architecture study featuring NTP was the Design Reference Architecture 5.0 (DRA 5.0), performed in 2009. Currently, the predominant transportation options being considered are solar electric propulsion (SEP) and chemical propulsion; however, given NTP's capabilities, an updated architectural analysis is needed. This paper provides a top-level overview of several different architectures featuring updated NTP performance data. New architectures presented include a proposed update to the DRA 5.0 as well as an investigation of architectures based on the current Evolvable Mars Campaign, which is the focus of NASA's current analyses for the Journey to Mars. Architectures investigated leverage the latest information relating to NTP performance and design considerations and address new support elements not available at the time of DRA 5.0, most notably the Orion crew module and the Space Launch System (SLS). The paper provides a top level quantitative comparison of key performance metrics as well as a qualitative discussion of improvements and key challenges still to be addressed. Preliminary results indicate that the updated NTP architectures can significantly reduce the campaign mass and subsequently the costs for assembly and number of launches.

Rodriguez, Mitchell A.↗

Hydropower Capital and O&M Costs: An Exploration of the FERC Form 1 Data

This report explores the potential for using responses from the Federal Energy Regulatory Commission’s (FERC’s) “Electric Utility Annual Report,” also known as FERC Form 1, as a cost database for conventional and pumped storage hydropower (PSH). The report outlines the process used to compile an easy-to-access database from the original FERC Form 1 data and discusses the historical cost/performance data. The steps for developing the database include downloading the annual FoxPro files from the FERC website (FERC, 2020), reading them into an Excel format, and reconciling naming issues across years, repeated entries, and shared assets, among others. The cleaned and compiled Form 1 database is available on Oak Ridge National Laboratory’s (ORNL’s) HydroSource website. For this report, the compiled Form 1 database was linked to two other hydropower databases, the National Inventory of Dams and the ORNL Existing Hydropower Assets, that provide additional information on the characteristics and other features of plants in the Form 1 data. Explorations of the plant characteristics, performance, capital costs, and operation and maintenance (O&M) cost data in the combined database were presented separately for conventional hydropower and PSH projects. Form 1 has several advantages as a hydropower cost database. First, the cost data is reported directly by plant owners. Second, Form 1 provides cost breakdowns of capital and operating costs for large conventional and PSH plants enabling more detailed tracking of hydropower costs compared with typical total cost estimates. Third, although the Form 1 data is not reported by all operational hydropower plants in the United States, the available data represents a wide range of plant characteristics and a sizable proportion of the hydropower fleet (61% of PSH plants and 22% of conventional hydropower plants by capacity). The lower proportion of the conventional hydropower fleet is because Form 1 reporting requirements apply only to private utilities that meet given size thresholds, leaving out federally owned facilities and many smaller hydropower plants. Overall, the Form 1 cost database represents a unique, publicly available database on hydropower asset capital and O&M costs. This report leads to a compiled database for the reporting years 1994 to 2020 that helps resolve issues with accessibility and use of the FERC Form 1 data by hydropower plant owners, project developers, technology developers, and regulators.

13 HYDRO ENERGY↗

Real-World Driving Features for Identifying Intelligent Driver Model Parameters: Preprint

Driver behavior models play a significant role in representing different driving styles and the associated relationships with traffic patterns and vehicle energy consumption in simulation studies. The models often serve as a proxy for baseline human driving when assessing energy-saving strategies that alter vehicle velocity. Such models are especially important in connectivity-enabled energy-saving strategy research because they can easily adapt to changing driving conditions like posted speed limits or change in traffic light state. While numerous driver models exist, parametric driver models provide the flexibility required to represent variability in real-world driving through different combinations of model parameters. These model parameters must be informed by a representative set of parameter values for the driver model to adequately represent a real-world driver. It stands to reason that determining the parameter values from real-world driving data would serve the purpose of representing a real-world driver. While the published literature is replete with techniques and consequences of using real-world driving data to determine parameter values for parametric driver models, none have explored them in the context of using shorter driving features where the parameter values may change over the course of a single trip for the same driver. In this study we consider the “Intelligent Driver Model” (IDM) as the driver behavior model to explore and real-world driving data from the Transportation Secure Data Center (TSDC) maintained at the National Renewable Energy Laboratory (NREL). The TSDC includes real-world travel data from across the United States, from which NREL has created a wide range of driving routes consisting of road features such as speed limits, stop locations and turn locations. The real-world driving data are categorized into different driving regimes and extracted into driving features. The driving features are then used to calibrate the parameter values for the IDM. The distribution of the parameters and the relationships among them are reported. The insights obtained from this study enable judicious usage of IDM or similar parametric driver models to represent baseline human driver behavior in simulations.

27 ARPA - Advanced Research Projects Agency-Energy↗

Examining Tropical Convection Features at Storm-Resolving Scales Over the Maritime Continent Region

Global Storm Resolving Models (GSRMs) provide a way to understand weather and climate events across scales for better-informed climate impacts. In this work, we apply the recently developed and validated CAM (Community Atmosphere Model)—MPAS (Model for Prediction Across Scales) modeling framework, based on the open-source Community Earth System Model (CESM2), to examine the tropical convection features at the storm resolving scale over the Maritime Continent region at 3 km horizontal spacing. We target two global numerical experiments during the winter season of 2018 for comparison with observation in the region. Here we focus on the investigation of the representations of the convective systems, precipitation statistics, and tropical cyclone behaviors. We found that regional-refined experiments show more accurate precipitation distributions, diurnal cycles, and better agreement with observations for tropical cyclone features in terms of intensity and strength statistics. We expect the exploration of this work will further advance the development and use of the storm-resolving model in precipitation predictions across scales.

54 ENVIRONMENTAL SCIENCES↗

Lithospheric strength of Ganymede: Clues to early thermal profiles from extensional tectonic features

While it is generally agreed that the strength of a planet's lithosphere is controlled by a combination of brittle sliding and ductile flow laws, predicting the geometry and initial characteristics of faults due to failure from stresses imposed on the lithospheric strength envelope has not been thoroughly explored. Researchers used lithospheric strength envelopes to analyze the extensional features found on Ganymede. This application provides a quantitative means of estimating early thermal profiles on Ganymede, thereby constraining its early thermal evolution.

Golombek, M. P.↗

Geological Evolution of the Ganiki Planitia Quadrangle (V14) on Venus

The Ganiki Planitia quadrangle (25-50degN, 180-210degE) is located north of Atla Regio, south of Vinmara Planitia, and southeast of Atalanta Planitia. The region contains a diverse array of volcanic-, tectonic- and impact-derived features, and the objectives for the ongoing mapping effort are fivefold: 1) explore the formation and evolution of radiating dike swarms within the region, 2) use the diverse array of volcanic deposits to further test the neutral buoyancy hypothesis proposed to explain the origin of reservoir-derived features, 3&4) unravel the volcanic and tectonic evolution in this area, and 5) explore the implications of 1-4 for resurfacing mechanisms. Here we summarize our onging analysis of the material unit stratigraphy in the quadrangle, data central to meeting the aforementioned objectives successfully.

Grosfils, E. B.↗

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

A new Exploration Extravehicular Activity Suit (xEVAS) is being designed to replace the current Extravehicular Mobility Unit (EMU) for the National Aeronautics and Space Administration’s (NASA’s) Artemis program to return astronauts to the lunar surface. This new suit will allow for increased range of motion compared the current EMU and Apollo era suits and will have additional features that will enhance the health and safety of exploration. With the design of lunar missions and the xEVAS progressing, it is important to consider possible injuries and injury mechanisms that could occur in the suit. To address these concerns, the suited Injury Modes and Effects Analysis (IMEA) was developed to outline suited injury scenarios and rank them based on risk score. The IMEA documents possible scenarios and underlying mechanisms of injury while wearing an extravehicular activity (EVA) suit. Tasks during lunar surface EVA as well as training events to prepare for lunar missions were considered as history has shown that more suit injuries occur during training than in flight. Each scenario is ranked with a consequence and likelihood scoring based on our current understanding of the suit and Artemis design reference missions to identify high-risk cases that will drive further work in suited injury. Injuries, mechanisms of injury, and mitigation strategies are evaluated within each scenario. The Suited Injury Summit was held on January 5, 2022, to vet the IMEA with external experts. This was an all-day virtual meeting with the suited injury team, ergonomists, suit engineers, safety engineers, the flight operations directorate, flight doctors, astronauts, astronaut strength, conditioning, and rehabilitation specialists (ASCRS), and external subject matter experts (SMEs). External SMEs consisted of surgeons with varying specialties. The intent of this meeting was to walk through the top injury risks identified in the analysis, identify any gaps that were not captured, and discuss mitigations. With participation from all groups, countless lessons-learned came from the Summit meeting. Using the lessons-learned and discussion from the Summit, the top 10 risks have been identified: neutral buoyancy laboratory training, hand/glove injuries, poor suit fit, field training, specific EVA tasks/design of task, boots/ankle injuries, falls from heights, background radiation, repetitive contact, and ambulation/long-distance ambulation. Mitigation steps have also been determined for each of the top risks. The IMEA and documentation of top risks is a living document. Yearly meetings are planned to update the analysis and reevaluate top risks and mitigations. The IMEA is being used to drive work in suited injury, and this work will continue to evolve with IMEA and lunar mission updates.

Teresa Reiber↗

Development of the Suited Injury Modes and Effects Analysis for Identification of Top Injury Risks in Lunar Missions and Training

A new Exploration Extravehicular Activity Suit (xEVAS) is being designed to replace the current Extravehicular Mobility Unit (EMU) for the National Aeronautics and Space Administration’s (NASA’s) Artemis program to return astronauts to the lunar surface. This new suit will allow for increased range of motion compared the current EMU and Apollo era suits and will have additional features that will enhance the health and safety of exploration. With the design of lunar missions and the xEVAS progressing, it is important to consider possible injuries and injury mechanisms that could occur in the suit. To address these concerns, the suited Injury Modes and Effects Analysis (IMEA) was developed to outline suited injury scenarios and rank them based on risk score. The IMEA documents possible scenarios and underlying mechanisms of injury while wearing an extravehicular activity (EVA) suit. Tasks during lunar surface EVA as well as training events to prepare for lunar missions were considered as history has shown that more suit injuries occur during training than in flight. Each scenario is ranked with a consequence and likelihood scoring based on our current understanding of the suit and Artemis design reference missions to identify high-risk cases that will drive further work in suited injury. Injuries, mechanisms of injury, and mitigation strategies are evaluated within each scenario. The Suited Injury Summit was held on January 5, 2022, to vet the IMEA with external experts. This was an all-day virtual meeting with the suited injury team, ergonomists, suit engineers, safety engineers, the flight operations directorate, flight doctors, astronauts, astronaut strength, conditioning, and rehabilitation specialists (ASCRS), and external subject matter experts (SMEs). External SMEs consisted of surgeons with varying specialties. The intent of this meeting was to walk through the top injury risks identified in the analysis, identify any gaps that were not captured, and discuss mitigations. With participation from all groups, countless lessons-learned came from the Summit meeting. Using the lessons-learned and discussion from the Summit, the top 10 risks have been identified: neutral buoyancy laboratory training, hand/glove injuries, poor suit fit, field training, specific EVA tasks/design of task, boots/ankle injuries, falls from heights, background radiation, repetitive contact, and ambulation/long-distance ambulation. Mitigation steps have also been determined for each of the top risks. The IMEA and documentation of top risks is a living document. Yearly meetings are planned to update the analysis and reevaluate top risks and mitigations. The IMEA is being used to drive work in suited injury, and this work will continue to evolve with IMEA and lunar mission updates.

Tessa Reiber↗

Development of a Microlith® Catalytic Oxidizer for Exploration Trace Contaminant Control

The state-of-the-art in long mission duration spacecraft trace contaminant control processes rely on high-temperature catalytic oxidation for light contaminant removal. Target compounds for oxidation include metabolic methane, carbon monoxide, and low molecular weight volatile organics such as formaldehyde and methanol. Precision Combustion, Inc. and NASA Marshall Space Flight Center have been developing and testing prototype high temperature catalytic oxidizers based on PCI’s patented Microlith® technology to meet the requirements of future spaceflight exploration missions. To this end, our latest generation Microlith oxidizer, featuring an integrated heat recuperator, was subjected to endurance testing to simulate catalyst ageing over a Mars transit mission duration. Periodic reactor health testing indicates our approach results in a robust contaminant control solution for exploration missions beyond low earth orbit. Based on the demonstrated performance of this unit, a next-generation prototype was designed to meet exploration contaminant load control demands while upgrading the prototype form and fit to match flight-compatible interfaces. Prototype design considerations intended to reduce power consumption, impacting process thermal and hydraulic performance, are discussed herein.

Trace Contaminant Control↗

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗

Centimeter to Decimeter Size Spherical and Cylindrical Features in Gale Crater Sediments

The Curiosity rover traverse in Gale crater has explored a large series of sedimentary deposits in an ancient lake on Mars. Over the nine kilometers of traverse a recurrent observation has been southward-dipping sedimentary strata, from Shaler at the edge of Yellowknife Bay to the striated units near the Kimberley. Within the sedimentary strata cm- to decimeter- size hollow spheroidal objects and some apparent cylindrical objects have been observed. These features have not been seen by previous landed missions. The first of these were observed on sol 122 in the Gillespie Lake member at Yellowknife Bay. Additional hollow features were observed in the Point Lake outcrop in the same area. More recently a spherical and apparently hollow object, Winnipesaukee, was observed by ChemCam and Mastcam on sol 653. Here we describe the settings, morphology, and associated compositions, and we discuss possible origins of these objects.

Wiens, R. C.↗

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗