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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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System for computer construction, enumeration and notation of organic molecules as tree structures and cyclic graphs
Ground and aerial imaging techniques to detect tree damage caused by bark beetles in forested areas
Relation between solar activity and tree ring growth in western North America
Review of proceedings from seminar on solar dendroclimatic relationships and discussion of predictions of sunspot activity on basis of tree ring variance
This paper talks about the Mars Odyssey's risk assessment process and its use of fault trees as an enabling tool.
The use of software fault trees for requirements identification and analysis in an Intrusion Detection System (IDS) is described.
A novel method for combining decision trees and kernel density estimators is proposed. Standard.
Tree fruit, although desirable from a crew nutrition and menu diversity perspective, have long been dismissed as candidate crops based on their long juvenile phase, large architecture, low short-term harvest index, and dormancy requirements. Recent developments in Rapid Cycle Crop Breeding (RCCB) have overcome these historical limitations, opening the door to a new era in candidate crop research. Researchers at the United States Department of Agriculture (USDA) have developed FT-construct (Flowering Locus T) dwarf plum lines that have a very short juvenile phase, vine-like architecture, and no obligate dormancy period. In a collaborative research effort, NASA and the USDA are evaluating the performance of these FT-lines under controlled environment conditions relevant to spaceflight.
Canopy light interception is a main driver of water use and crop yield in almond and walnut production. Fractional green canopy cover (Fc) is a good indicator of light interception and can be estimated remotely from satellite using the normalized difference vegetation index (NDVI) data. Satellite-based Fc estimates could be used to inform crop evapotranspiration models, and hence support improvements in irrigation evaluation and management capabilities. Satellite estimates of Fc in almond and walnut orchards, however, need to be verified before incorporating them into irrigation scheduling or other crop water management programs. In this study, Landsat-based NDVI and Fc from NASA's Satellite Irrigation Management Support (SIMS) were compared with four estimates of canopy cover: 1. light bar measurement, 2. in-situ and image-based dimensional tree-crown analyses, 3. high-resolution NDVI data from low flying aircraft, and 4. orchard photos obtained via Google Earth and processed by an Image J thresholding routine. Correlations between the various estimates are discussed.
(1) Temperate forests are shaped by late spring freezes after budburst—false springs—which may shift with climate change. Research to date has generated conflicting results, potentially because few studies focus on the multiple underlying drivers of false spring risk. (2) Here, we assessed the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six tree species across 11648 sites in Europe, to determine which were the strongest predictors of false spring risk and how these predictors shifted with climate change. (3) All predictors influenced false spring risk before recent warming, but their effects have shifted in both magnitude and direction with warming. These shifts have potentially magnified the variation in false spring risk among species with an increase in risk for early‐leafout species (i.e., Aesculus hippocastanum , Alnus glutinosa , Betula pendula ) versus a decline or no change in risk among late‐leafout species (i.e., Fagus sylvatica , Fraxinus excelsior , Quercus robur ). (4) Our results show how climate change has reshaped the drivers of false spring risk, complicating forecasts of future false springs, and potentially reshaping plant community dynamics given uneven shifts in risk across species.
Temperate and boreal forests are shaped by late spring freezing events after budburst, which are also known as false springs. Research has generated conflicting results on whether or not these events will change with climate change, potentially because---to date---no study has compared the myriad climatic and geographic factors that contribute to a plant's risk of a false spring. We assessed and compared the strength of the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six temperate, decidious tree species across 11,648 sites in Central Europe and how these predictors shifted with climate change. Across species before recent warming, mean spring temperature and distance from the coast were the strongest predictors, with higher mean spring temperatures associated with decreased risk in false springs (–7.64% per 2°C increase) and sites further from the coast experiencing an increased risk (5.32% per 150km from the coast). Elevation (2.23% per 200m increase in elevation) and NAO index (1.91% per 0.3 increase) also increased false spring risk. With climate change, elevation and distance from coast---i.e., the geographic factors---remain relatively stable, while climatic factors shifted in magnitude for mean spring temperature (down to -2.84% in risk per 2°C), and in direction, with positive NAO phases leading to lower risk (-9.15% per 0.3). The residual effects of climate change---unexplained by the climatic and geographic factors already included in the model---magnified the species-level variation in risk, with risk increasing among early-leafout species (i.e., Aesculus hippocastanum, Alnus glutinosa and Betula pendula) but a decline or no change in risk among late-leafout species (i.e., Fagus sylvatica, Fraxinus excelsior and Quercus robur). Our results show that climate change has reshaped the major drivers of false spring risk and highlight how considering multiple factors can yield a better understanding of the complexities of climate change.
Rapid drought intensification, or flash droughts, is often driven by anomalous atmospheric ridging and can cause severe and complex impacts on water availability and agriculture, but the full range of variability of such events in terms of intensity and frequency is unknown. New tree-ring reconstructions of May–July mid-tropospheric ridging and soil moisture anomalies back to 1500 CE in the central United States — a hotspot for flash drought — suggest that over the last five centuries, anomalies in these two variables combined to indicate flash-drought conditions in ~17% of years and exceptionally severe flash drought in ~4% of years, similar to frequencies in recent decades. However, over one-third of all inferred exceptional flash droughts occurred since 1900, suggesting the 20th century was highly flash-drought prone. These results may guide future work to diagnose the roles of external, oceanic, and land-surface forcing of warm-season atmospheric circulation and hydroclimate over North America.
We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.
Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.
Historians and paleoclimatologists have both identified the decades spanning the late-18th and early-19th centuries in many East African regions as a period of prolonged and severe drought. A challenge that emerges from both the historical evidence and the paleolimnological data that have been primarily used to characterize this drought period, however, concerns the dating of events and the characterization of their spatial character; both oral traditions and lake-core proxies cannot typically offer hydroclimate estimates with seasonal or annual resolution, nor can they provide gridded reconstructions on the order of 1° latitude and longitude. The new East African Drought Atlas (EADA) incorporates far-field dendroclimatic records and several local East African tree-ring chronologies to provide estimates of the self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5° latitude-longitude grid. We present the Point-by-Point Regression technique that was used to create the EADA, the rationale for the employed input data network, and the calibration and validation skill of the derived hydroclimatic field reconstruction. We use the EADA to characterize the timing of two decadal-scale droughts, centered over the Uganda and Kenya regions, which occurred in the late 18th century and early in the 19th century and were separated by a shorter, but pronounced wet period. We characterize the spatial patterns of the associated events and the dynamical causes that that the patterns imply. The reconstructed droughts are also compared to historical and paleolimnological data to evaluate the robustness of the reconstruction and the degree of agreement across the different sources of information.
We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.
Algorithm for synthesis of switching circuit in generaized tree circuit form
Convolutional encoder for orthogonal tree codes in presence of white Gaussian noise