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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Heterometallic UO 2 2+ /Ag + Complexes: Structural Design and Luminescence Properties

Reported here are the synthesis, structural characterization, and luminescence properties of 11 novel UO 2 2+ /Ag + heterometallic complexes. Halogenated benzoic acids (2,6-dihalobenzoic acid (halo = F, Br), 3,5-dichlorobenzoic acid, and 3-halobenzoic acid (halo = Br, I)) and N-donor polycyclic ligands (2,2′-bipyridine, 2,2’;6′,2″-terpyridine, 1,10-phenanthroline, 2,2′-bipyrimidine) were employed to synthesize a set of compounds and induce structural diversity. The primary mode of coordination with the uranyl cation is hexagonal bipyramidal monomeric units with three halobenzoate ligands in the equatorial plane, though 1-D chains with pentagonal bipyramidal uranyl centers also form. The Ag + cations coordinate preferentially to the N-donor ligands and serve as counter-cations for the anionic uranyl motifs. The soft ligand character of the N-donor molecules is found to be a requirement for the inclusion of the Ag + cation into the structures. Anionic uranyl units and cationic silver units assemble via noncovalent interactions between π systems on adjacent rings and between halogens (when Br and I are present). Solid-state emission spectra display the usual uranyl band with superimposed vibronic fine structure, except for that of compound 1 , which shows emission from the 2,2′-bipyridine center. This family of compounds represents a substantial contribution to the already rich library of UO 2 2+ /Ag + compounds, and the synthetic parameters discussed within reveal a platform for the design of new heterometallic uranyl-containing materials.

anions↗
NASA NTRS2021

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high-biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height-normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Jonathan A. Walter↗
DOE OSTI2024

Deep Learning Prediction of Protein Complex Structures

Proteins interact to form protein complex to carry out biological functions such as catalytic chemical reaction. Therefore, it is important to develop computational methods to predict protein-protein interaction and the structures of protein complexes to study and enhance protein function. In this project, we successfully developed several deep learning methods to predict inter-protein contacts and the reinforcement learning and optimization methods to reconstruct protein complex structures from predicted inter-chain contacts. The methods were integrated with the MULTICOM protein complex structure prediction system and applied to predict the complex structures of biomass production-related proteins of green algae. During the two and a half years of research and development, all the specific milestones of the project were achieved successfully. 16 publications/manuscripts were produced. 10 software tools were developed. A patent application was submitted. Our MULTICOM predictors leveraging some tools developed in this project were ranked among the top predictors in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Active impedance matching of complex structural systems

Viewgraphs on active impedance matching of complex structural systems are presented. Topics covered include: traveling wave model; dereverberated mobility model; computation of dereverberated mobility; control problem: optimal impedance matching; H2 optimal solution; statistical energy analysis (SEA) solution; experimental transfer functions; interferometer actuator and sensor locations; active strut configurations; power dual variables; dereverberation of complex structure; dereverberated transfer function; compensators; and relative power flow.

Macmartin, Douglas G.↗
NASA NTRS1974

Application of ultrasonic signature analysis for fatigue detection in complex structures

Ultrasonic signature analysis shows promise of being a singularly well-suited method for detecting fatigue in structures as complex as aircraft. The method employs instrumentation centered about a Fourier analyzer system, which features analog-to-digital conversion, digital data processing, and digital display of cross-correlation functions and cross-spectra. These features are essential to the analysis of ultrasonic signatures according to the procedure described here. In order to establish the feasibility of the method, the initial experiments were confined to simple plates with simulated and fatigue-induced defects respectively. In the first test the signature proved sensitive to the size of a small hole drilled into the plate. In the second test, performed on a series of fatigue-loaded plates, the signature proved capable of indicating both the initial appearance and subsequent growth of a fatigue crack. In view of these encouraging results it is concluded that the method has reached a sufficiently advanced stage of development to warrant application to small-scale structures or even actual aircraft.

Zuckerwar, A. J.↗
DOE OSTI2025

Electronic structure complexity and extremely large magnetoresistance in antiferromagnetic semimetal SmAgSb 2

SmAgSb 2 , a layered magnetic semimetal in the tetragonal 𝑅⁢𝑇⁢ Sb 2 family (𝑅 = Y, Sc, rare earth; 𝑇 = transition metal), is known to exhibit extremely large magnetoresistance (XMR) below its antiferromagnetic (AFM) transition temperature. Here, in this work, we present a comprehensive investigation combining magnetotransport measurements, density functional theory calculations accounting for electron correlation, and angle-resolved photoemission spectroscopy. Our results reveal a complex electronic structure characterized by a multiband Fermi surface and intricate magnetic ground states. We demonstrate that simple two-band models, previously employed in the literature, fail to consistently describe the observed transport phenomena. Notably, we report an XMR of approximately 25200% at 2 K under a 14 T magnetic field, significantly exceeding earlier reports for this material family and rivaling the performance of prominent nonmagnetic XMR systems. This pronounced enhancement below 𝑇 𝑁 suggests that the XMR originates from a combination of multiband electron-hole compensation and enhanced magnetic scattering in this correlated AFM semimetal.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2023

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗
NASA NTRS1990

Developing a framework for qualitative engineering: Research in design and analysis of complex structural systems

The research is focused on automating the evaluation of complex structural systems, whether for the design of a new system or the analysis of an existing one, by developing new structural analysis techniques based on qualitative reasoning. The problem is to identify and better understand: (1) the requirements for the automation of design, and (2) the qualitative reasoning associated with the conceptual development of a complex system. The long-term objective is to develop an integrated design-risk assessment environment for the evaluation of complex structural systems. The scope of this short presentation is to describe the design and cognition components of the research. Design has received special attention in cognitive science because it is now identified as a problem solving activity that is different from other information processing tasks (1). Before an attempt can be made to automate design, a thorough understanding of the underlying design theory and methodology is needed, since the design process is, in many cases, multi-disciplinary, complex in size and motivation, and uses various reasoning processes involving different kinds of knowledge in ways which vary from one context to another. The objective is to unify all the various types of knowledge under one framework of cognition. This presentation focuses on the cognitive science framework that we are using to represent the knowledge aspects associated with the human mind's abstraction abilities and how we apply it to the engineering knowledge and engineering reasoning in design.

Franck, Bruno M.↗
NASA NTRS2008

Evaluation of Lightning Incidence to Elements of a Complex Structure: A Monte Carlo Approach

There are complex structures for which the installation and positioning of the lightning protection system (LPS) cannot be done using the lightning protection standard guidelines. As a result, there are some "unprotected" or "exposed" areas. In an effort to quantify the lightning threat to these areas, a Monte Carlo statistical tool has been developed. This statistical tool uses two random number generators: a uniform distribution to generate origins of downward propagating leaders and a lognormal distribution to generate returns stroke peak currents. Downward leaders propagate vertically downward and their striking distances are defined by the polarity and peak current. Following the electrogeometrical concept, we assume that the leader attaches to the closest object within its striking distance. The statistical analysis is run for 10,000 years with an assumed ground flash density and peak current distributions, and the output of the program is the probability of direct attachment to objects of interest with its corresponding peak current distribution.

Mata, Carlos T.↗
NASA NTRS2008

Evaluation of Lightning Incidence to Elements of a Complex Structure: A Monte Carlo Approach

There are complex structures for which the installation and positioning of the lightning protection system (LPS) cannot be done using the lightning protection standard guidelines. As a result, there are some "unprotected" or "exposed" areas. In an effort to quantify the lightning threat to these areas, a Monte Carlo statistical tool has been developed. This statistical tool uses two random number generators: a uniform distribution to generate the origin of downward propagating leaders and a lognormal distribution to generate the corresponding returns stroke peak currents. Downward leaders propagate vertically downward and their striking distances are defined by the polarity and peak current. Following the electrogeometrical concept, we assume that the leader attaches to the closest object within its striking distance. The statistical analysis is run for N number of years with an assumed ground flash density and the output of the program is the probability of direct attachment to objects of interest with its corresponding peak current distribution.

Mata, Carlos T.↗
NASA NTRS1993

The complex structured singular value

A tutorial introduction to the complex structured singular value (mu) is presented, with an emphasis on the mathematical aspects of mu. The mu-based methods discussed here have been useful for analyzing the performance and robustness properties of linear feedback systems. Several tests for robust stability and performance with computable bounds for transfer functions and their state space realizations are compared, and a simple synthesis problem is studied. Uncertain systems are represented using linear fractional transformations which naturally unify the frequency-domain and state space methods.

Packard, A.↗
DOE OSTI2024

Forest structural complexity and ignition pattern influence simulated prescribed fire effects

Background: Forest structural characteristics, the burning environment, and the choice of ignition pattern each influence prescribed fire behaviors and resulting fire effects; however, few studies examine the influences and interactions of these factors. Understanding how interactions among these drivers can influence prescribed fire behavior and effects is crucial for executing prescribed fires that can safely and effectively meet management objectives. To analyze the interactions between the fuels complex and ignition patterns, we used FIRETEC, a three-dimensional computational fluid dynamics fire behavior model, to simulate fire behavior and effects across a range of horizontal and vertical forest structural complexities. For each forest structure, we then simulated three different prescribed fires each with a unique ignition pattern: strip-head, dot, and alternating dot. Results: Forest structural complexity and ignition pattern affected the proportions of simulated crown scorch, consumption, and damage for prescribed fires in a dry, fire-prone ecosystem. Prescribed fires in forests with complex canopy structures resulted in increased crown consumption, scorch, and damage compared to less spatially complex forests. The choice of using a strip-head ignition pattern over either a dot or alternating-dot pattern increased the degree of crown foliage scorched and damaged, though did not affect the proportion of crown consumed. We found no evidence of an interaction between forest structural complexity and ignition pattern on canopy fuel consumption, scorch, or damage. Conclusions: We found that forest structure and ignition pattern, two powerful drivers of fire behavior that forest managers can readily account for or even manipulate, can be leveraged to influence fire behavior and the resultant fire effects of prescribed fire. These simulation findings have critical implications for how managers can plan and perform forest thinning and prescribed burn treatments to meet risk management or ecological objectives.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Mathematical synthesization of complex structures

A mathematical synthesization approach for rapidly modeling and analyzing complex structures comprised of hundreds or thousands of repeating individual structural members, interconnecting hardware, and other components was described. The techniques are applicable to any structure with repeating structural members. The capabilities are embodied within the Interactive Design and Evaluation of Advanced Spacecraft (IDEAS) computer-aided design system. IDEAS has a full range of integrated spacecraft modeling, design, analysis, performance, and cost estimating capabilities which include about 40 technical program and executive, data base, and file management systems. With IDEAS, a single user at an interactive terminal can create, design, analyze, and conduct parametric studies of Earth orbiting spacecraft in a timely, cost-efficient manner. The system is particularly useful in the conceptual design phases of advanced space missions when a multiplicity of concepts must be evaluated. The IDEAS interactive finite-element modeling capabilities are discussed. The mathematical synthesization programs were structured not only to provide a detailed finite-element model of the structure but also to automatically perform the many auxiliary computations needed to analyze the spacecraft in its orbital operational environment.

Garrett, L. B.↗
NASA NTRS1974

On the recognition of complex structures: Computer software using artificial intelligence applied to pattern recognition

An approach to simultaneous interpretation of objects in complex structures so as to maximize a combined utility function is presented. Results of the application of a computer software system to assign meaning to regions in a segmented image based on the principles described in this paper and on a special interactive sequential classification learning system, which is referenced, are demonstrated.

Yakimovsky, Y.↗