Bridging the Gap: Evaluating Past Water Levels at Jezero Crater, Mars through Orbital and In Situ Data
No abstract provided
Brown, Adrian↗
SEARCH · Engineering Papers
Results for “Data gaps”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Human Research Program Human Health Countermeasures Element Extravehicular Activity (EVA) Risk Standing Review Panel (SRP)
The Extravehicular Activity (EVA) Risk Standing Review Panel (SRP) was favorably impressed by the operational risk management approach taken by the Human Research Program (HRP) Integrated Research Plan (IRP) to address the stated life sciences issues. The life sciences community at the Johnson Space Center (JSC) seems to be focused on operational risk management. This approach is more likely to provide risk managers with the information they need at the time they need it. Concerning the information provided to the SRP by the EVA Physiology, Systems, and Performance Project (EPSP), it is obvious that a great deal of productive activity is under way. Evaluation of this information was hampered by the fact that it often was not organized in a fashion that reflects the "Gaps and Tasks" approach of the overall Human Health Countermeasures (HHC) effort, and that a substantial proportion of the briefing concerned subjects that, while interesting, are not part of the HHC Element (e.g., the pressurized rover presentation). Additionally, no information was provided on several of the tasks or how they related to work underway or already accomplished. This situation left the SRP having to guess at the efforts and relationship to other elements, and made it hard to easily map the EVA Project efforts currently underway, and the data collected thus far, to the gaps and tasks in the IRP. It seems that integration of the EPSP project into the HHC Element could be improved. Along these lines, we were concerned that our SRP was split off from the other participating SRPs at an early stage in the overall agenda for the meeting. In reality, the concerns of EPSP and other projects share much common ground. For example, the commonality of the concerns of the EVA and exercise physiology groups is obvious, both in terms of what reduced exercise capacity can do to EVA capability, and how the exercise performed during an EVA could contribute to an overall exercise countermeasure prescription.
Norfleet, William↗
Filling gaps in bacterial catabolic pathways with computation and high-throughput genetics
To discover novel catabolic enzymes and transporters, we combined high-throughput genetic data from 29 bacteria with an automated tool to find gaps in their catabolic pathways. GapMind for carbon sources automatically annotates the uptake and catabolism of 62 compounds in bacterial and archaeal genomes. For the compounds that are utilized by the 29 bacteria, we systematically examined the gaps in GapMind’s predicted pathways, and we used the mutant fitness data to find additional genes that were involved in their utilization. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server ( http://papers.genomics.lbl.gov/carbon ) and takes just 30 seconds for the typical genome.
59 BASIC BIOLOGICAL SCIENCES↗
Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess
The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model (γEM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of γEMs with increasing parametric freedom. We calculate the fractional contribution (f src ) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the γEM. For the simplest γEM, we obtain fsrc = 0.10 ± 0.07, while the most complex model yields f src = 0.79 ± 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed γEM. The quoted results for f src do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated γEM iterations. We quantify the reality gap between our γEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed γEMs have gaps to reality. Finally, our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked "out of domain" uncertainties in future interpretations.
79 ASTRONOMY AND ASTROPHYSICS↗
Detection and Behavior of Pan Wakes in Saturn's A Ring
Six previously unseen Pan wakes are found interior and exterior to the Encke gap in Saturn's A ring, one in the Voyager 2 photopolarimeter (PPS) stellar occultation data and five in the Voyager 1 radio science (RSS) Earth occultation data. Pan orbits at the center of the Encke gap and maintains it...The detection of Pan wakes at longitudes greater than 360(deg) demonstrates that wakes persist for much longer than originally hypothesized and may interact with one another.
planetary rings rings of saturn voyager spacecraft↗
A Transfer Learning Strategy for Improving the Data Efficiency of Deep Reinforcement Learning Control in Smart Buildings
Reinforcement learning (RL) is a powerful tool that has shown promising results in many domains such as robotics and game-playing. Because RL algorithms learn optimal control policies by continuously interacting with their environments, these algorithms require a lot of data to learn, which limits their application to a wide range of domains. For this reason, there is an immense need for improving the training and data efficiency of RL. Towards addressing this research gap, this paper proposes a transfer learning (TL) approach to improve the efficiency of the RL algorithms by reducing data need and, thus, reducing training time. To demonstrate the proposed approach, a knowledge transfer from a set of buildings to another building was conducted. The results show that the proposed TL approach is a promising method that can efficiently harness the information from similar RL tasks and reduce the data needs of RL algorithms.
Amasyali, Kadir↗
The water use of data center workloads: A review and assessment of key determinants
The global importance of data center water use is increasing with the rapid growth of digitalization and artificial intelligence. This study analyzes the factors influencing workload-level water use, measured in liters consumed per workload, to guide water-saving strategies in data centers. Our findings reveal workload-level water use variations exceeding 10,000-fold, driven by over 1000-fold differences in water consumption per kilowatt hour of server electricity consumed and approximately 10-fold differences in server workload efficiency. Key determinants are ranked as server efficiency, electrical grid water consumption factors, server utilization, cooling system type, infrastructure efficiency, climate zone, inactive server percentage, and server refresh cycle. Notably, there is no single recipe for minimizing water use; instead, optimal outcomes depend on tailored combinations of these factors. This analysis addresses critical knowledge gaps by identifying the determinants of data center water use and exploring their achievable minima under diverse site-specific constraints.
Data centers↗
Structural and thermal response of 30 cm diameter ion thruster optics
This paper presents tabular and graphical data intended for use in calibrating and validating structural and thermal models of ion thruster optics. A 30-cm-diameter, two electrode, mercury ion thruster was operated using two different electrode assembly designs. With no beam extraction, the transient and steady state temperature profiles and center electrode gaps were measured for three discharge powers. The data showed that the electrode mount design had little effect on the temperatures, but significantly impacted the motion of the electrode center. Equilibrium electrode gaps increased with one design and decreased with the other. Equilibrium displacements in excess of 0.5 mm and gap changes of 0.08 mm were measured at 450 W discharge power. Variations in equilibrium gaps were also found among assemblies of the same design. The presented data illustrate the necessity for high fidelity ion optics models and development of experimental techniques to allow their validation.
Macrae, G.↗
Domain Adaptation for Measurements of Strong Gravitational Lenses
Upcoming surveys are predicted to discover galaxy-scale strong lenses on the magnitude of 105, making deep learning methods necessary in lensing data analysis. Currently, there is insufficient real lensing data to train deep learning algorithms, but training only on simulated data results in poor performance on real data. Domain adaptation can bridge the gap between simulated and real datasets. We adopt domain adaptation on the estimation of Einstein radius in simulated galaxy-scale gravitational lensing images. We evaluate two domain adaptation techniques - domain adversarial neural networks (DANN) and maximum mean discrepancy (MMD). We train on a source domain of simulated lenses and apply it to a target domain with emulation of DES survey conditions. We show that both domain adaptation techniques can significantly improve the model performance on the more complex target domain datasets. Our results show the potential of using domain adaptation to perform analysis on future survey data with a deep neural network trained on simulated data.
79 ASTRONOMY AND ASTROPHYSICS↗
Highlights of the Version 8 SBUV and TOMS Datasets Released at this Symposium
Last October was the 25th anniversary of the launch of the SBUV and TOMS instruments on NASA's Nimbus-7 satellite. Total Ozone and ozone profile datasets produced by these and following instruments have produced a quarter century long record. Over time we have released several versions of these datasets to incorporate advances in UV radiative transfer, inverse modeling, and instrument characterization. In this meeting we are releasing datasets produced from the version 8 algorithms. They replace the previous versions (V6 SBUV, and V7 TOMS) released about a decade ago. About a dozen companion papers in this meeting provide details of the new algorithms and intercomparison of the new data with external data. In this paper we present key features of the new algorithm, and discuss how the new results differ from those released previously. We show that the new datasets have better internal consistency and also agree better with external datasets. A key feature of the V8 SBUV algorithm is that the climatology has no influence on inter-annual variability and trends; it only affects the mean values and, to a limited extent, the seasonal dependence. By contrast, climatology does have some influence on TOMS total O3 trends, particularly at large solar zenith angles. For this reason, and also because TOMS record has gaps, md EP/TOMS is suffering from data quality problems, we recommend using SBUV total ozone data for applications where the high spatial resolution of TOMS is not essential.
Bhartia, Pawan K.↗
Structural and thermal response of 30 cm diameter ion thruster optics
Tabular and graphical data are presented which are intended for use in calibrating and validating structural and thermal models of ion thruster optics. A 30 cm diameter, two electrode, mercury ion thruster was operated using two different electrode assembly designs. With no beam extraction, the transient and steady state temperature profiles and center electrode gaps were measured for three discharge powers. The data showed that the electrode mount design had little effect on the temperatures, but significantly impacted the motion of the electrode center. Equilibrium electrode gaps increased with one design and decreased with the other. Equilibrium displacements in excess of 0.5 mm and gap changes of 0.08 mm were measured at 450 W discharge power. Variations in equilibrium gaps were also found among assemblies of the same design. The presented data illustrate the necessity for high fidelity ion optics models and development of experimental techniques to allow their validation.
Macrae, G. S.↗
New approaches to an old problem: addressing spatial gaps in the World Stress Map
Abstract A well-recognized characteristic of the World Stress Map (WSM) database is the continued presence of large spatial gaps in the distribution of the data records despite the more than 40-year development history of the database. The current release has more than 30 000 high-quality (A–C) data records (often referred to as ‘stress indicators’), but while some continental areas (such as Australia) have seen a significant increase in spatial converge with the latest release, other continental regions (Africa, central Asia, most of South America) remain markedly sparse. In this contribution we (1) review the current state of the spatial distribution of stress indicators in the continental regions (above sea-level); (2) quantify the clustering of the stress indicators in the latest WSM release using the Hopkins statistic as a way to explore the current spatial distribution of the indicators and assess future WSM releases; and (3) present three approaches (joint inversion, seismic anisotropy and InSAR) that provide a way to fill in the gaps (both in the S Hmax orientation and principal stress magnitudes) in regions that lack active seismicity and where borehole drilling is cost prohibitive. These three approaches have the potential to guide procedures for improving a priori estimates of the ambient stress field in the Earth's crust and reduce the uncertainty in predicting both the magnitude and orientation of the principal tectonic stresses.
58 GEOSCIENCES↗
Game Based Learning For Earth Science Applications Training
Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.
Human centered design↗
Data-driven discovery of dynamics from time-resolved coherent scattering
Coherent X-ray scattering (CXS) techniques are capable of interrogating dynamics of nano- to mesoscale materials systems at time scales spanning several orders of magnitude. However, obtaining accurate theoretical descriptions of complex dynamics is often limited by one or more factors—the ability to visualize dynamics in real space, computational cost of high-fidelity simulations, and effectiveness of approximate or phenomenological models. In this work, we develop a data-driven framework to uncover mechanistic models of dynamics directly from time-resolved CXS measurements without solving the phase reconstruction problem for the entire time series of diffraction patterns. Our approach uses neural differential equations to parameterize unknown real-space dynamics and implements a computational scattering forward model to relate real-space predictions to reciprocal-space observations. This method is shown to recover the dynamics of several computational model systems under various simulated conditions of measurement resolution and noise. Moreover, the trained model enables estimation of long-term dynamics well beyond the maximum observation time, which can be used to inform and refine experimental parameters in practice. Finally, we demonstrate an experimental proof-of-concept by applying our framework to recover the probe trajectory from a ptychographic scan. Our proposed framework bridges the wide existing gap between approximate models and complex data.
36 MATERIALS SCIENCE↗
SATS Transient Fission Gas Release Test with Irradiated Fuel under Loss of Coolant Accident Conditions
The transient fission gas release (tFGR) during the temperature ramp associated with a loss-of-coolant accident (LOCA) in light-water reactors (LWRs) is likely a significant contribution to the total pressure in a fuel rod and may cause an unexpected rod burst. The lack of data related to tFGR continues to be a key gap in understanding LWR cladding burst behavior under LOCA conditions. To fully characterize this behavior, tFGR data must be collected from several different systems that can capture all relevant testing conditions. Oak Ridge National Laboratory (ORNL) has developed a system to measure the integral tFGR from irradiated fuel segments. This system was designed to integrate with the existing Severe Accident Test Station (SATS) and to build upon decades of experience capturing fission gas to characterize fuel behavior. The tFGR system consists of a sweep gas system to transport gases from the in-cell SATS apparatus to an out-of-cell fission gas detection system composed of a series of cold traps to capture the off-gas from the heating tests and a gamma spectrometry system to detect and measure 85 Kr. Initial system testing operations were completed during which 85 Kr collection and measurement were verified along with the ability to detect stable inert gases. A tFGR test with a high-burnup fuel specimen was successfully conducted by the in-cell SATS-tFGR system at ORNL. The posttest examination is under way, the result of which will be reported in FY24.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.
42 ENGINEERING↗
Landscape-scale characterization of Arctic tundra vegetation composition, structure, and function with a multi-sensor unoccupied aerial system
The Arctic is experiencing some of the most rapid climate change on Earth, with strong impacts on tundra ecosystems that are characterized by high land-surface and vegetation heterogeneity. Previous studies have explored this complexity using satellite remote sensing, however these typically coarse spatial resolution data have generally missed sub-pixel heterogeneity, leaving critical gaps in our understanding of tundra vegetation dynamics from the community to landscape scales. To address these gaps, we collected very high-resolution (1-5 cm) optical, structural, and thermal data at three low-Arctic tundra sites on the Seward Peninsula, Alaska, using a multi-sensor unoccupied aerial system (UAS). We examined the application of these data to studying tundra vegetation dynamics, by quantifying (1) canopy height and thermoregulation (leaf-air temperature) of representative plant functional types (PFTs), (2) fine-scale patterns of vegetation composition across landscapes, and (3) impacts of fine-scale vegetation composition on landscape-scale variation of canopy height and thermoregulation. Our results show that deciduous tall shrubs (those that can potentially grow >2 m) had a strong cooling effect, with canopy temperatures significantly lower than local air temperatures and other PFTs. Increased cover of tall shrubs also had the potential to reduce the cover of low-stature PFTs across the landscape, potentially associated with their closed canopy (i.e., increased light competition) and strong thermoregulation. To understand the connections between fine-scale vegetation composition and large-scale ecosystem processes, we produced a random forest model which showed that fine-scale PFT composition accounted for 86.8% and 74.2% of the landscape-scale variation in canopy height and thermoregulation, respectively. These findings highlight the importance of spatially detailed characterization of tundra PFTs to improve our ecological understanding and model representation of tundra vegetation, also transcend our study to show the need for continued collection of similar datasets to better understand the impacts of surface heterogeneity on the mapping and modeling of tundra ecosystem dynamics, as well as assist with conservation management and biodiversity monitoring strategies.
54 ENVIRONMENTAL SCIENCES↗
Spectral Signatures of a Negative Polaron in a Doped Polymer Semiconductor: Energy Levels and Hubbard U Interactions
The modern picture of negative charge carriers on conjugated polymers invokes the formation of a singly occupied (spin-up/spin-down) level within the polymer gap and a corresponding unoccupied level above the polymer conduction band edge. The energy splitting between these sublevels is related to on-site Coulomb interactions between electrons, commonly termed Hubbard U. However, spectral evidence for both sublevels and experimental access to the U value is still missing. Here, in this work, we provide evidence by n-doping the polymer P(NDI 2 OD-T 2 ) with [RhCp*Cp] 2 , [N-DMBI] 2 , and cesium. Changes in the electronic structure after doping are studied with ultraviolet photoelectron and low-energy inverse photoemission spectroscopies (UPS, LEIPES). UPS data show an additional density of states (DOS) in the former empty polymer gap while LEIPES data show an additional DOS above the conduction band edge. These DOS are assigned to the singly occupied and unoccupied sublevels, allowing determination of a U value of ~1 eV.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗