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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Process Sensitivity, Performance, and Direct Verification Testing of Adhesive Locking Features

Phase I: The use of adhesive locking features or liquid locking compounds (LLCs) (e.g., Loctite) as a means of providing a secondary locking feature has been used on NASA programs since the Apollo program. In many cases Loctite was used as a last resort when (a) self-locking fasteners were no longer functioning per their respective drawing specification, (b) access was limited for removal & replacement, or (c) replacement could not be accomplished without severe impact to schedule. Long-term use of Loctite became inevitable in cases where removal and replacement of worn hardware was not cost effective and Loctite was assumed to be fully cured and working. The NASA Engineering & Safety Center (NESC) and United Space Alliance (USA) recognized the need for more extensive testing of Loctite grades to better understand their capabilities and limitations as a secondary locking feature. These tests, identified as Phase I, were designed to identify processing sensitivities, to determine proper cure time, the correct primer to use on aerospace nutplate, insert and bolt materials such as A286 and MP35N, and the minimum amount of Loctite that is required to achieve optimum breakaway torque values. The .1900-32 was the fastener size tested, due to wide usage in the aerospace industry. Three different grades of Loctite were tested. Results indicate that, with proper controls, adhesive locking features can be successfully used in the repair of locking features and should be considered for design. Phase II: Threaded fastening systems used in aerospace programs typically have a requirement for a redundant locking feature. The primary locking method is the fastener preload and the traditional redundant locking feature is a self-locking mechanical device that may include deformed threads, non-metallic inserts, split beam features, or other methods that impede movement between threaded members. The self-locking resistance of traditional locking features can be directly verified during assembly by measuring the dynamic prevailing torque. Adhesive locking features or LLCs are another method of providing redundant locking, but a direct verification method has not been used in aerospace applications to verify proper installation when using LLCs because of concern for damage to the adhesive bond. The reliability of LLCs has also been questioned due to failures observed during testing with coupons for process verification, although the coupon failures have often been attributed to a lack of proper procedures. It is highly desirable to have a direct method of verifying the LLC cure or bond integrity. The purpose of the Phase II test program was to determine if the torque applied during direct verification of an adhesive locking feature degrades that locking feature. This report documents the test program used to investigate the viability of such a direct verification method. Results of the Phase II testing were positive, and additional investigation of direct verification of adhesive locking features is merited.

Golden, Johnny L.↗
NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 1

A small, portable, relatively inexpensive computer system was developed for on-line use in clinical or laboratory situations. The system features an integrated hardware-software package that permits use of all peripherals, such as analog-to-digital converter, oscilloscope, plotter, digital bus, with an interpreter constructed around the BASIC programming language. The system is conceptually similar to the LINC system developed in 1962, but is more compact and powerful due to intervening advances in integrated circuit technology. A description of the hardware of the system was given. A reference manual, user manual, and programming guides were also presented. Finally, a stereo display system for vectorcardiograms was described.

Mark, R. G.↗
DOE OSTI2022

Geometric learning for computational mechanics Part II: Graph embedding for interpretable multiscale plasticity

The history-dependent behaviors of classical plasticity models are often driven by internal variables evolved according to phenomenological laws. The difficulty to interpret how these internal variables represent a history of deformation, the lack of direct measurement of these internal variables for calibration and validation, and the weak physical underpinning of those phenomenological laws have long been criticized as barriers to creating realistic models. In this work, geometric machine learning on graph data (e.g. finite element solutions) is used as a means to establish a connection between nonlinear dimensional reduction techniques and plasticity models. Geometric learning-based encoding on graphs allows the embedding of rich time-history data onto a low-dimensional Euclidean space such that the evolution of plastic deformation can be predicted in the embedded feature space. Finally, a corresponding decoder can then convert these low-dimensional internal variables back into a weighted graph such that the dominating topological features of plastic deformation can be observed and analyzed.

42 ENGINEERING↗
DOE OSTI2020

Degrees of Rate Control at Non(pseudo)steady-State Conditions

The degrees of rate control enable identification of rate-controlling transition states and species during (pseudo-)steady-state reaction. We demonstrate a method for identifying rate-controlling transition states and species at non-(pseudo-)steady-state conditions through modification of the definitions for degrees of rate control and sensitivities by superimposing the condition that time constants of the analytical rate function are kept constant when taking the partial derivatives of rate with respect to the rate constants/free energies. In conclusion, the utility of transient degrees of rate control is demonstrated for catalytic reaction networks to rationalize features of the transient rate including extrema and discontinuities.

42 ENGINEERING↗
DOE OSTI2021

Connectivity-informed drainage network generation using deep convolution generative adversarial networks

Abstract Stochastic network modeling is often limited by high computational costs to generate a large number of networks enough for meaningful statistical evaluation. In this study, Deep Convolutional Generative Adversarial Networks (DCGANs) were applied to quickly reproduce drainage networks from the already generated network samples without repetitive long modeling of the stochastic network model, Gibb’s model. In particular, we developed a novel connectivity-informed method that converts the drainage network images to the directional information of flow on each node of the drainage network, and then transforms it into multiple binary layers where the connectivity constraints between nodes in the drainage network are stored. DCGANs trained with three different types of training samples were compared; (1) original drainage network images, (2) their corresponding directional information only, and (3) the connectivity-informed directional information. A comparison of generated images demonstrated that the novel connectivity-informed method outperformed the other two methods by training DCGANs more effectively and better reproducing accurate drainage networks due to its compact representation of the network complexity and connectivity. This work highlights that DCGANs can be applicable for high contrast images common in earth and material sciences where the network, fractures, and other high contrast features are important.

42 ENGINEERING↗
DOE OSTI2021

AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning

Here we present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural network to perform multi-label partitioning based on local texture in the volume, and a second neural network to compress the information contained within each partition. We train both of these components simultaneously by optimizing a loss function that is designed to promote accurate reconstruction of each partition, while encouraging spatially smooth and contiguous partitioning, and discouraging relatively small partitions. We show that the partitions adapt to the subject specific structural variations of brain tissue while consistently appearing at similar spatial locations across subjects. AutoAtlas also produces very low dimensional features that represent local texture of each partition. We demonstrate prediction of metadata associated with each subject using the derived feature representations and compare the results to prediction using features derived from FreeSurfer anatomical parcellation. Since our features are intrinsically linked to distinct partitions, we can then map values of interest, such as partition-specific feature importance scores onto the brain for visualization.

42 ENGINEERING↗
DOE OSTI2021

A Projected Network Model of Online Disinformation Cascades

Within the past half-decade, it has become overwhelmingly clear that suppressing the spread of deliberate false and misleading information is of the utmost importance for protecting democratic institutions. Disinformation has been found to come from both foreign and domestic actors, but the effects from either can be disastrous. From the simple encouragement of unwarranted distrust to conspiracy theories promoting violence, the results of disinformation have put the functionality of American democracy under direct threat. Present scientific challenges posed by this problem include detecting disinformation, quantifying its potential impact, and preventing its amplification. We present a model on which we can experiment with possible strategies toward the third challenge: the prevention of amplification. This is a social contagion network model, which is decomposed into layers to represent physical, ''offline'', interactions as well as virtual interactions on a social media platform. Along with the topological modifications to the standard contagion model, we use state-transition rules designed specifically for disinformation, and distinguish between contagious and non-contagious infected nodes. We use this framework to explore the effect of grassroots social movements on the size of disinformation cascades by simulating these cascades in scenarios where a proportion of the agents remove themselves from the social platform. We also test the efficacy of strategies that could be implemented at the administrative level by the online platform to minimize such spread. These top-down strategies include banning agents who disseminate false information, or providing corrective information to individuals exposed to false information to decrease their probability of believing it. We find an abrupt transition to smaller cascades when a critical number of random agents are removed from the platform, as well as steady decreases in the size of cascades with increasingly more convincing corrective information. Finally, we compare simulated cascades on this framework with real cascades of disinformation recorded on Whatsapp surrounding the 2019 Indian election. We find a set of hyperparameter values that produces a distribution of cascades matching the scaling exponent of the distribution of actual cascades recorded in the dataset. We acknowledge the available future directions for improving the performance of the framework and validation methods, as well as ways to extend the model to capture additional features of social contagion.

42 ENGINEERING↗
DOE OSTI2022

3D Printing at Los Alamos

At Los Alamos National Laboratory (LANL), their additive manufacturing division is seeking to answer the question whether it is possible to 3D print on a 5th axis. The end goal is to achieve true continuous fiber 3D printing. My goal on this project was to learn about additive manufacturing, and to learn how to operate the experimental 3D printer. Each print that was done demonstrated a different pattern that would change the strength and integrity of the print. Overall prints with minimal strand separation and featured weave-like patterns proved to have the best integrity.

42 ENGINEERING↗
NASA NTRS1993

Transient performance of fan engine with water ingestion

In a continuing investigation on developing and applying codes for prediction of performance of a turbine jet engine and its components with water ingestion during flight operation, including power settings, and flight altitudes and speed changes, an attempt was made to establish the effects of water ingestion through simulation of a generic high bypass ratio engine with a generic control. In view of the large effects arising in the air compression system and the prediffuser-combustor unit during water ingestion, attention was focused on those effects and the resulting changes in engine performance. Under all conditions of operation, whether ingestion is steady or not, it became evident that water ingestion causes a fan-compressor unit to operate in a time-dependent fashion with periodic features, particularly with respect to the state of water in the span and the film in the casing clearance space, at the exit of the machine. On the other hand, the aerodynamic performance of the unit may be considered as quasi-steady once the distribution of water has attained an equilibrium state with respect to its distribution and motion. For purposes of engine simulation, the performance maps for the generic fan-compressor unit were generated based on the attainment of a quasi-steady state (meaning steady except for long-period variations in performance) during ingestion and operation over a wide enough range of rotational speeds.

Murthy, S. N. B.↗
DOE OSTI2020

Spark-ignited direct-injection engine combustion systems

A direct-injection stratified charge internal combustion engine includes a combustion cylinder to receive an air-fuel mixture, and an air intake port to inlet air into the combustion cylinder. The direct-injection engine also includes a fuel injector configured to deliver fuel within the cylinder in a spray pattern substantially aligned to a cylinder central axis to create the air-fuel mixture. A spark igniter is located within a path of the spray pattern to ignite combustion of the air-fuel mixture. The direct-injection engine further includes a movable piston defining a lower boundary of the combustion cylinder to contain the combustion of the air-fuel mixture. The piston is configured to include a bowl portion having local geometric features located on an intake port side of the combustion cylinder to redirect fluid flow towards a vortex in fluid communication with a combustion location near the cylinder central axis.

42 ENGINEERING↗
NASA NTRSDate not supplied

Empowering Open Science with the Science Discovery Engine

: This presentation will describe the work to date in building the SDE as well as what the team has learned about the SMD ecosystem, information curation, and data governance. A short demonstration of the SDE will be presented, and an overview of near- and long-term goals for future development will be shared. Community feedback will be welcomed about the interface, content, and other features to help inform actions to maximize the SDE’s performance and usability. Whether users aim to discover Earth-like atmospheres on planets outside of our solar system or better understand the impacts of solar energy on our own planet, the Science Discovery Engine provides a means for scientists and all curious individuals to find content to further their understanding of science across all time and space scales.

Emily Foshee↗
NASA NTRS1999

A One Dimensional, Time Dependent Inlet/Engine Numerical Simulation for Aircraft Propulsion Systems

The NASA Lewis Research Center (LeRC) and the Arnold Engineering Development Center (AEDC) have developed a closely coupled computer simulation system that provides a one dimensional, high frequency inlet/engine numerical simulation for aircraft propulsion systems. The simulation system, operating under the LeRC-developed Application Portable Parallel Library (APPL), closely coupled a supersonic inlet with a gas turbine engine. The supersonic inlet was modeled using the Large Perturbation Inlet (LAPIN) computer code, and the gas turbine engine was modeled using the Aerodynamic Turbine Engine Code (ATEC). Both LAPIN and ATEC provide a one dimensional, compressible, time dependent flow solution by solving the one dimensional Euler equations for the conservation of mass, momentum, and energy. Source terms are used to model features such as bleed flows, turbomachinery component characteristics, and inlet subsonic spillage while unstarted. High frequency events, such as compressor surge and inlet unstart, can be simulated with a high degree of fidelity. The simulation system was exercised using a supersonic inlet with sixty percent of the supersonic area contraction occurring internally, and a GE J85-13 turbojet engine.

Doug Garrard↗
NASA NTRS2004

Advanced Manufacturing Techniques Demonstrated for Fabricating Developmental Hardware

NASA Glenn Research Center's Engineering Development Division has been working in support of innovative gas turbine engine systems under development by Glenn's Combustion Branch. These one-of-a-kind components require operation under extreme conditions. High-temperature ceramics were chosen for fabrication was because of the hostile operating environment. During the designing process, it became apparent that traditional machining techniques would not be adequate to produce the small, intricate features for the conceptual design, which was to be produced by stacking over a dozen thin layers with many small features that would then be aligned and bonded together into a one-piece unit. Instead of using traditional machining, we produced computer models in Pro/ENGINEER (Parametric Technology Corporation (PTC), Needham, MA) to the specifications of the research engineer. The computer models were exported in stereolithography standard (STL) format and used to produce full-size rapid prototype polymer models. These semi-opaque plastic models were used for visualization and design verification. The computer models also were exported in International Graphics Exchange Specification (IGES) format and sent to Glenn's Thermal/Fluids Design & Analysis Branch and Applied Structural Mechanics Branch for profiling heat transfer and mechanical strength analysis.

Redding, Chip↗
DOE OSTI2022

Investigation of the effects of passive pre-chamber nozzle pattern and ignition system on engine performance and emissions

The impact of passive pre-chamber (PC) internal volume, nozzle hole pattern (i.e. with and without a central axial nozzle), and PC igniter plug type on performance and emissions was investigated in an optically accessible, single-cylinder, gasoline research engine. The two PC igniter plugs investigated were a conventional inductive coil spark plug and a nanosecond repetitively pulsed (NRP) plasma discharge system previously demonstrated to accelerate early flame propagation. The baseline PC design featured a funnel shaped internal volume with a PC tip that contained six radial nozzles and a larger central axial nozzle. Two additional PC tip geometries were evaluated where either the baseline internal volume was increased or the axial nozzle was removed and the radial nozzle diameters were increased. A sweep of charge equivalence ratios ( ϕ) from nearly stoichiometric to the lean limit was performed for a fixed engine speed (1300 revolutions per minute), and engine load (3.5 bar gross indicated mean effective pressure). Time-resolved PC and main chamber (MC) pressure data as well as MC emissions data were collected to analyze engine performance and emissions characteristics. Combustion in the MC was further investigated using high-speed excited methylidyne radical (CH*) chemiluminescence imaging. Collected results highlighted that while all PC tips and ignition systems exhibited similar performance and emissions down to ϕ = 0.8, relevant differences in thermal efficiency and emissions for leaner charge mixtures were observed, with the results highly dependent on the nozzle pattern and ignition system. Major deviations were correlated to preferential de-pressurization of the PC through the axial nozzle for lean conditions that was not observed for mixture conditions closer to stoichiometric. Results show that a combination of radial and axial nozzle patterns in the PC extended lean-stability limits at the low-load condition evaluated. Further benefits were observed with the use of NRP ignition systems due to faster combustion within the PC volume provided that the volume was sufficiently large.

Di Sabatino, Francesco↗
DOE OSTI2023

Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis

Accurate cloud type identification and coverage analysis are crucial in understanding the Earth’s radiative budget. Traditional computer vision methods rely on low-level visual features of clouds for estimating cloud coverage or sky conditions. Several handcrafted approaches have been proposed; however, scope for improvement still exists. Newer deep neural networks (DNNs) have demonstrated superior performance for cloud segmentation and categorization. These methods, however, need expert engineering intervention in the preprocessing steps—in the traditional methods—or human assistance in assigning cloud or clear sky labels to a pixel for training DNNs. Such human mediation imposes considerable time and labor costs. We present the application of a new self-supervised learning approach to autonomously extract relevant features from sky images captured by ground-based cameras, for the classification and segmentation of clouds. We evaluate a joint embedding architecture that uses self-knowledge distillation plus regularization. We use two datasets to demonstrate the network’s ability to classify and segment sky images—one with ~85,000 images collected from our ground-based camera and another with 400 labeled images from the WSISEG database. We find that this approach can discriminate full-sky images based on cloud coverage, diurnal variation, and cloud base height. Additionally, it semantically segments the cloud areas without labels. The approach shows competitive performance in all tested tasks, suggesting a new alternative for cloud characterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Engineering of flat bands and Dirac bands in two-dimensional covalent organic frameworks (COFs): relationships among molecular orbital symmetry, lattice symmetry, and electronic-structure characteristics

Two-dimensional covalent organic frameworks (2D-COFs), also referred to as 2D polymer networks, display unusual electronic-structure characteristics, which can significantly enrich and broaden the fields of electronics and spintronics. In this Focus article, the objective of this report is to lay the groundwork for the conceptual description of the fundamental relationships among the COF electronic structures, the symmetries of their 2D lattices, and the frontier molecular orbitals (MOs) of their core and linker components. We focus on monolayers of hexagonal COFs and use tight-binding model analyses to highlight the critical role of the frontier-MO symmetry, in addition to lattice symmetry, in determining the nature of the electronic bands near the Fermi level. We rationalize the intriguing feature that, when the core unit has degenerate highest occupied MOs [or lowest unoccupied MOs], the COF highest valence band [or lowest conduction band] is flat but degenerate with a dispersive band at a high-symmetry point of the Brillouin zone; the consequences of having such band characteristics are briefly described. Multi-layer and bulk 2D COFs are found to maintain the salient features of the monolayer electronic structures albeit with a reduced bandgap due to the interlayer coupling. This Focus article is thus meant to provide an effective framework for the engineering of flat and Dirac bands in 2D polymer networks.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High frequency lithium niobate film-thickness-mode optomechanical resonator

High-frequency optomechanical resonators are in demand as transduction devices to bridge microwave and optical fields. Thin-film lithium niobate is a promising platform for implementing high-frequency optomechanics for its low optical loss and strong piezoelectric coefficients. However, its strong piezoelectricity is also known to introduce excess phonon loss. Here, we present lithium niobate optomechanical resonators with film-thickness-mode mechanical resonances up to 5.2 GHz, reaching the operating frequency regime of superconducting qubits. By engineering the mechanical anchor to minimize the phonon loss, we achieve a high quality factor up to 12 500 at cryogenic temperatures and, hence, a frequency-quality factor product of 6.6 × 10 13 . Our system also features interference between piezo-optomechanical and electro-optic modulation. A theoretical model is derived to analyze these two effects and their interference.

42 ENGINEERING↗
NASA NTRS1983

Digital computer program for generating dynamic turbofan engine models (DIGTEM)

This report describes DIGTEM, a digital computer program that simulates two spool, two-stream turbofan engines. The turbofan engine model in DIGTEM contains steady-state performance maps for all of the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. Altogether there are 16 state variables and state equations. DIGTEM features a backward-differnce integration scheme for integrating stiff systems. It trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off-design points and iterates to a balanced engine condition. Transients can also be run. They are generated by defining controls as a function of time (open-loop control) in a user-written subroutine (TMRSP). DIGTEM has run on the IBM 370/3033 computer using implicit integration with time steps ranging from 1.0 msec to 1.0 sec. DIGTEM is generalized in the aerothermodynamic treatment of components.

Daniele, C. J.↗