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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Closing the Gap Between Modeling and Experiments in the Self-assembly of Biomolecules at Interfaces and in Solution

Molecular self-assembly is a powerful tool in materials design, wherein non-covalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing self-assembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physics-based simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assembly - biomineralizing peptides, hierarchical peptoids, and large protein assemblies, and will aid in the development of a new synthesis science for achieving precise molecular control in materials design

Sampath, Janani↗
NASA NTRS2004

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

Patnaik, Surya N.↗
DOE OSTI2021

Self-organization of nanoparticles and molecules in periodic Liesegang-type structures

Chemical organization in reaction-diffusion systems offers a strategy for the generation of materials with ordered morphologies and structural hierarchy. Periodic structures are formed by either molecules or nanoparticles. On the premise of new directing factors and materials, an emerging frontier is the design of systems in which the precipitation partners are nanoparticles and molecules. We show that solvent evaporation from a suspension of cellulose nanocrystals (CNCs) and L -(+)-tartaric acid [ L -(+)-TA] causes phase separation and precipitation, which, being coupled with a reaction/diffusion, results in rhythmic alternation of CNC-rich and L -(+)-TA–rich rings. The CNC-rich regions have a cholesteric structure, while the L -(+)-TA–rich bands are formed by radially aligned elongated bundles. The moving edge of the pattern propagates with a finite constant velocity, which enables control of periodicity by varying film preparation conditions. This work expands knowledge about self-organizing reaction-diffusion systems and offers a strategy for the design of self-organizing materials.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Faster Antenna Noise Temperature Calculations Using a Novel Approximation Technique

In order to properly tradeoff the various antenna and feed configurations for the Square Kilometre Array (SKA) optical design it is necessary to evaluate the gain and noise temperature of each configuration over a wide range of frequencies. German Cortes describes the standard technique for computing antenna noise temperature. However, since the total antenna pattern needs to be calculated over the entire 4 pi steradians at a fine enough resolution to accurately include the main beam, the computer time required is enormous. Even at modest frequencies and reflector sizes (approximately 5 to 10 GHz for a 12 meter main reflector) the technique can take days on a single node of a supercomputer. Utilizing the standard technique to compute the noise temperature for all the cases required to properly characterize the SKA design is clearly not feasible. At least a 100 to 1000 speedup in the computation time is required. This paper describes an approximation technique that can accomplish this improvement with extremely small errors in noise temperature calculation of a few tenths of Kelvin.

Reflector Antennas↗
NASA NTRS1987

The first radio astronomy from space - RAE

The spacecraft design, instrumentation, and performance of the Radio Astronomy Explorer (RAE) satellites (RAE-1 launched to earth orbit in 1968 and RAE-2 launched to lunar orbit in 1972) are reviewed and illustrated with drawings, diagrams, and graphs of typical data. Consideration is given to the three pairs of antennas, the Ryle-Vonberg and burst radiometers, and problems encountered with antenna deployment and observing patterns. Results summarized include observations of type III solar bursts, the spectral distribution of cosmic noise in broad sky regions, Jupiter at low frequencies, and auroral kilometric radiation (AKR) from the earth. The importance of avoiding the AKR bands in designing future space observatories is stressed.

Kaiser, M. L.↗
DOE OSTI2023

Stabilizing Ni-rich layered cathode for high-voltage operation through hierarchically heterogeneous doping with concentration gradient

High-nickel LiNi x Mn y Co 1-x-y O 2 (NMC) cathodes have demonstrated superior energy density, yet their stability is compromised under high voltage conditions. To address this, here we propose a strategy of heterogeneous doping with a concentration gradient, specifically through Sr–Zr co-modification. We synthesized Ni-rich NMC particles featuring several micron-sized secondary particles composed of micron-sized primary grains. This design aims to harness the structural robustness of single-crystalline grains and the favorable diffusion kinetics of polycrystalline secondary particles. Systematic characterization using a combination of electrochemical measurements and synchrotron analytics reveals an intriguing pattern of hierarchically heterogeneous Sr–Zr co-doping. It demonstrates a depth-dependent concentration gradient at the secondary particle level and competing dopant segregation over the buried grain boundaries. This unique characteristic creates opportunities for enhancing battery performance, particularly by optimizing precursors and implementing advanced modulation techniques. We also investigate the dissolution and precipitation of the cathode's transition metal cations upon high-voltage cycling. These insights suggest that a tailored compositional variation can be a viable approach to effectively design the next-generation high-Ni NMC cathode materials for high-voltage lithium batteries.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Recent progress in the development of transition radiation detectors

Transition-radiation detectors have been used in several recent cosmic-ray experiments for particle identification at energies E/mc-squared of at least about 1000. In order to optimize the design of such detectors and to use them for energy measurements over a broad energy range, it is necessary to study the details of the transition-radiation process. Experimental results are presented which test the theoretical predictions more precisely and at higher energies than in previous experiments. The dependence of the interference pattern in the frequency spectrum on the radiator dimensions is studied, and the total transition-radiation yield generated by electrons in various radiators is measured over a very wide energy range, from 5 to 300 GeV. The significance of the individual experimental parameters in the design of transition radiation detectors is reviewed, and the characteristics of transition-radiation detectors capable of measuring particle energies over the range E/mc-squared from about 300 to 100,000 are discussed.

Cherry, M. L.↗
DOE OSTI2020

Organizing bacterial vortex lattices by periodic obstacle arrays

Recent experiments have shown that the complex spatio-temporal vortex structures emerging in active fluids are susceptible to weak geometrical constraints. This observation poses the fundamental question of how boundary effects stabilize a highly ordered pattern from seemingly turbulent motion. Here we show, by a combination of continuum theory and experiments on a bacterial suspension, how artificial obstacles guide the flow profile and reorganize topological defects, which enables the design of bacterial vortex lattices with tunable properties. To this end, the continuum model is extended by appropriate boundary conditions. Beyond the stabilization of square and hexagonal lattices, we also provide a striking example of a chiral, antiferromagnetic lattice exhibiting a net rotational flow, which is induced by arranging the obstacles in a Kagome-like array. Recent experiments showed that weak geometrical constraints can organize topological defects in turbulent bacterial suspensions. Here, the authors use a continuum model to study the connection between symmetry and stability of emergent vortex patterns and the geometry of constraining pillar arrays.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

Flow studies in close-coupled ventral nozzles for STOVL aircraft

Flow in a generic ventral nozzle system was studied experimentally and analytically with the PARC3D computational fluid dynamics program (a full Navier-Stokes equations solver) in order to evaluate the program's ability to predict system performance and internal flow patterns. A generic model of a tailpipe with a rectangular ventral nozzle, about one-third of full size, was tested with unheated air at steady-state pressure ratios up to 4.0. Measurements showed about 5.5 percent flow-turning loss and reasonable nozzle performance coefficients. The flow turned more than the designed 90 deg, causing an aftward axial component in the total thrust. Flow behavior into and through the ventral duct is discussed and illustrated with paint streak flow visualization photographs. PARC3D graphic images are shown for comparison with the experiment photographs. The program successfully predicted internal flow patterns; it also computed thrust and discharge coefficients within 1 percent of measured values.

Mcardle, Jack G.↗
NASA NTRS2015

X-Band CubeSat Communication System Demonstration

Today's CubeSats mostly operate their communications at UHF- and S-band frequencies. UHF band is presently crowded, thus downlink communications are at lower data rates due to bandwidth limitations and are unreliable due to interference. This research presents an end-to-end robust, innovative, compact, efficient and low cost S-band uplink and X-band downlink CubeSat communication system demonstration between a balloon and a Near Earth Network (NEN) ground system. Since communication systems serve as umbilical cords for space missions, demonstration of this X-band communication system is critical for successfully supporting current and future CubeSat communication needs. This research has three main objectives. The first objective is to design, simulate, and test a CubeSat S- and X-band communication system. Satellite Tool Kit (STK) dynamic link budget calculations and HFSS Simulations and modeling results have been used to trade the merit of various designs for small satellite applications. S- and X-band antennas have been tested in the compact antenna test range at Goddard Space Flight Center (GSFC) to gather radiation pattern data. The second objective is simulate and test a CubeSat compatible X-band communication system at 12.5Mbps including S-band antennas, X-band antennas, Laboratory for Atmospheric and Space Physics (LASP) /GSFC transmitter and an S-band receiver from TRL-5 to TRL-8 by the end of this effort. Different X-band communication system components (antennas, diplexers, etc.) from GSFC, other NASA centers, universities, and private companies have been investigated and traded, and a complete component list for the communication system baseline has been developed by performing analytical and numerical analysis. This objective also includes running simulations and performing trades between different X-band antenna systems to optimize communication system performance. The final objective is to perform an end-to-end X-band CubeSat communication system demonstration between a balloon and/or a sounding rocket and a Near Earth Network (NEN) ground system. This paper presents CubeSat communication systems simulation results, analysis of X-band and S-band antennas and RF front-end components, transceiver design, analysis and optimization of space-to-ground communication performance, subsystem development, as well as the test results for an end-to-end X-band CubeSat communication system demonstration. The outcome of this work will be used to pave the way for next generation NEN-compatible X-band CubeSat communication systems to support higher data rates with more advanced modulation and forward error correction (FEC) coding schemes, and to support and attract new science missions at lower cost. It also includes an abbreviated concept of operations for CubeSat users to utilize the NEN, starting from first contact with NASA's communication network and continuing through on-orbit operations.

NEN↗
DOE OSTI2024

Catalytic Upgrading of Renewable Feedstock (Final Technical Report)

The goal of this DOE-funded project was to investigate the fundamental science related to the development of homogeneous (de)hydrogenation catalysts in order to enable energy-relevant transformations of bio-relevant chemical feedstocks including ethanol. The primary focus was to improve the activity of ethanol upgrading catalysts, specifically informed through mechanistic studies, in order to enable rational design optimization strategies. Following in depth mechanistic studies, targeted reaction optimization approaches included ligand redesign to improve catalyst stability, developing new carbon-carbon bond forming reactions using ethanol as a precursor, and examining photochemically-mediated reactions, ultimately to integrate within other reactor designs such as continuous flow reactors. The high modularity of the catalyst components (ligands) has enabled the preparation and analyses of multiple catalyst precursors. These studies uncovered an unexpectedly beneficial substitution pattern of the ligand structure that led to the development of new catalysts that are the best in class for upgrading ethanol to butanol with a turnover number of 155,890 and a turnover frequency of 12,690 h –1 . In addition to upgrading ethanol to butanol, cascade reaction sequences were developed to form new C-C bonds using ethanol as a bio-relevant feedstock, providing access to platform chemicals from renewable sources. As part of the reaction discovery process, new mechanistic details were uncovered that provided insights into: a) catalyst speciation, b) decomposition pathways, c) carbon monoxide releasing pathways, and d) carbon-carbon and carbon hydrogen bond breaking pathways. Most of these outcomes were previously not known; however, they provide important directions for new catalyst design strategies. Finally, use of high throughput and in situ photochemical reaction analyses enabled detailed studies into changes to the catalyst structure upon irradiation. Irradiation was found to improve hydrogen transfer catalysis, by promoting a ligand dissociation event.

09 BIOMASS FUELS↗
DOE OSTI2016

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this article, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Computational modeling and neutron imaging to understand interface shape and solute segregation during the vertical gradient freeze growth of BaBrCl:Eu

In this work we apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Aspen-based performance and energy modeling frameworks

Now with the anticipation of exascale architectures, energy consumption is becoming one of the critical design parameters, especially in light of the energy budget of 20-30 Megawatts set by the U.S. Department of Energy. Understanding an application’s execution pattern and its energy footprint is critical to improving application operation on a diverse heterogeneous architecture. Applying application-specific performance optimization can consequently improve energy consumption. However, this approach is only applicable to current systems. As we enter a new era of exascale architectures that is projected to contain more complex memory hierarchies, increased levels of parallelism, heterogeneity in hardware, and complex programming models and techniques, energy and performance management is getting more cumbersome. We therefore propose techniques that predict the energy consumption beforehand or at runtime to enable proactive tuning. Such energy prediction approaches must be generic and adapt themselves at runtime to changing application and hardware configurations. Most existing energy estimation and prediction approaches are empirical in nature and thus tied to current systems. To overcome this limitation, we propose two energy estimation techniques: ACEE (Algorithmic and Categorical Energy Estimation), which uses a combination of analytical and empirical modeling techniques; and AEEM (Aspen’s Embedded Energy Estimation), a system-level analytical energy estimation technique. Both of these models incorporate the Aspen domain specific language for performance modeling. We present the methodologies of these two models and test their accuracy using five proxy applications. We also describe three use cases.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteins in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Near-field Fourier ptychography: super-resolution phase retrieval via speckle illumination

High spatial resolution is the goal of many imaging systems. While designing a high-resolution lens with diffraction-limited performance over a large field of view remains a difficult task, creating a complex speckle pattern with wavelength-limited spatial features is easily accomplished with a simple random diffuser. With this observation and the concept of near-field ptychography, we report a new imaging modality, termed near-field Fourier ptychography, which is to be used for high-resolution imaging challenges in both microscopic and macroscopic imaging settings. 'Near-field' refers to placing the object at a short defocus distance with a large Fresnel number. We predict a speckle pattern with fine spatial features on the object instead of directly resolving the spatial features via a high-resolution lens. We then translate the object (or speckle) to different positions and acquire the corresponding images by using a low-resolution lens. A ptychographic phase retrieval process is used to recover the complex object, the unknown speckle pattern, and the coherent transfer function at the same time. In a microscopic imaging setup, we use a 0.12 numerical aperture (NA) lens to achieve an NA of 0.85 in the reconstruction process. In a macroscale photographic imaging setup, we achieve similar to 7-fold resolution gain by using a photographic lens. The collection optics do not determine the final achievable resolution; rather, the speckle pattern's feature size does. This is similar to our recent demonstration in fluorescence imaging settings (Guo et al., Biomed. Opt. Express , 9(1), 2018). The reported imaging modality can be utilized in light, coherent X-ray, and transmission electron imaging systems to increase resolution and provide quantitative absorption and object phase contrast.

42 ENGINEERING↗
DOE OSTI2021

PIP-II 800 MeV Proton Linac Beam Pattern Generator

The PIP2 IT Beam Pattern Generator is the system that synchronizes beam injection and the RF systems between the PIP2 LINAC to the Booster. The RF frequencies of these two accelerator systems are not harmonically related. Synchronization is accomplished by controlling two MEBT Beam Choppers, which select 162.5MHz beam bunches from the LEBT and RFQ to produce an appropriate reduced beam bunch pattern that enables bucket-to-bucket transfer to the Booster RF at 46.46MHz (84th harmonic). This chopping pattern also reduces the beam current to an average of 2mA over the Booster injection, matching the Linac nominal beam current. The BPG also generates the RF frequency/phase reference which the Booster will phase lock to during injection. The BPG is fully programmable, allowing for arbitrary beam patterns with adjustable timing parameters, having a fine adjustment resolution of 38ps. The latter is accomplished using digital signal processing techniques. This paper discusses the design of the BPG, its construction, test results, and operational experience after being integrated into the PIP2 IT test accelerator and concludes with a discussion of the system’s performance and future plans.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

“Shoulda, Coulda, Woulda”: Conceptualizing the Differences in Trust Between Human-Human Teaming and Human-Machine Teaming

Intelligent decision support systems (IDSSs) are machine teammates designed to facilitate better human decision-making in high-consequence domains such as health care, power grid operations, and fraud detection. IDSSs identify patterns in datasets and provide intelligent decision-making recommendations to human teammates. However, previous research indicates that humans often trust IDSS recommendations less than the recommendations from their human teammates, even when the machine teammate is more accurate. To conceptualize why trust differs, we review the literature surrounding trust, error, and predictability. Then, we compile and compare participant trust ratings and decision-making in an abridged systematic review of previous studies manipulating teammate type, error rate, and error type. Finally, we conduct a content analysis of participants’ qualitative responses to trust queries from a survey on generative language models. Results suggest that humans may trust IDSS teammates less than other human teammates because of differences in (1) interaction complexity, (2) blame attribution, and (3) swift trust. We conclude that human factors practitioners should collaborate with data scientists and domain experts to build and maintain trust in IDSSs by anthropomorphizing algorithms, matching mental models, and considering individual differences.

97 MATHEMATICS AND COMPUTING↗