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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Entangled Photon Correlations Allow a Continuous-Wave Laser Diode to Measure Single-Photon, Time-Resolved Fluorescence

Fluorescence lifetime experiments are a standard approach for measuring excited state dynamics and local environment effects. Here, we show that entangled photon pairs produced from a continuous-wave (CW) laser diode can replicate pulsed laser experiments without phase modulation. As a proof of principle, picosecond fluorescence lifetimes of indocyanine green are measured in multiple environments. Here, the use of entangled photons has three unique advantages. First, low power CW laser diodes and entangled photon source design lead to straightforward on-chip integration for a direct path to distributable fluorescence lifetime measurements. Second, the entangled pair wavelength is easily tuned by temperature or electric field, allowing a single source to cover octave bandwidths. Third, femtosecond temporal resolutions can be reached without requiring major advances in source technology or external phase modulation. Entangled photons could therefore provide increased accessibility to time-resolved fluorescence while also opening new scientific avenues in photosensitive and inherently quantum systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

ZnO-Au x Cu 1-x Alloy and ZnO-Au x Al 1-x Alloy Vertically Aligned Nanocomposites for Low-Loss Plasmonic Metamaterials

Hyperbolic metamaterials are a class of materials exhibiting anisotropic dielectric function owing to the morphology of the nanostructures. In these structures, one direction behaves as a metal, and the orthogonal direction behaves as a dielectric material. Applications include subdiffraction imaging and hyperlenses. However, key limiting factors include energy losses of noble metals and challenging fabrication methods. In this work, self-assembled plasmonic metamaterials consisting of anisotropic nanoalloy pillars embedded into the ZnO matrix are developed using a seed-layer approach. Alloys of Au x Al 1-x or Au x Cu 1-x are explored due to their lower losses and higher stability. Optical and microstructural properties were explored. The ZnO-Au x Cu 1-x system demonstrated excellent epitaxial quality and optical properties compared with the ZnO-Au x Al 1-x system. Both nanocomposite systems demonstrate plasmonic resonance, hyperbolic dispersion, low losses, and epsilon-near-zero permittivity, making them promising candidates towards direct photonic integration.

36 MATERIALS SCIENCE↗
NASA NTRS1978

Measurements of mixed-mode crack surface displacements and comparison with theory

A theoretical and an experimental technique is used to determine crack surface displacements under mixed-mode conditions. Crack surface displacements proved to be quite useful in mode 1 fracture analysis in that they are directly related to strain energy release rate and stress intensity factor. It is felt that similar relationships can be developed for the mixed-mode case. A boundary-integral method was developed for application to two-dimensional fracture mechanics problems. This technique was applied to the mixed-mode problem. A laser interferometry technique, for measurement of crack surface displacements under mixed-mode conditions, is presented. The experimental measurements are reported and the results of the two approaches are compared and discussed.

Altiero, N. J., Jr.↗
NASA NTRS1990

Smart built-in test

The work which built-in test (BIT) is asked to perform in today's electronic systems increases with every insertion of new technology or introduction of tighter performance criteria. Yet the basic purpose remains unchanged -- to determine with high confidence the operational capability of that equipment. Achievement of this level of BIT performance requires the management and assimilation of a large amount of data, both realtime and historical. Smart BIT has taken advantage of advanced techniques from the field of artificial intelligence (AI) in order to meet these demands. The Smart BIT approach enhances traditional functional BIT by utilizing AI techniques to incorporate environmental stress data, temporal BIT information and maintenance data, and realtime BIT reports into an integrated test methodology for increased BIT effectiveness and confidence levels. Future research in this area will incorporate onboard fault-logging of BIT output, stress data and Smart BIT decision criteria in support of a singular, integrated and complete test and maintenance capability. The state of this research is described along with a discussion of directions for future development.

Richards, Dale W.↗
NASA NTRS1995

Novel Techniques for Millimeter-Wave Packages

A new millimeter-wave package architecture with supporting electrical, mechanical and material science experiment and analysis is presented. This package is well suited for discrete devices, monolithic microwave integrated circuits (MMIC's) and multichip module (MCM) applications. It has low-loss wide-band RF transitions which are necessary to overcome manufacturing tolerances leading to lower per unit cost Potential applications of this new packaging architecture which go beyond the standard requirements of device protection include integration of antennas, compatibility to photonic networks and direct transitions to waveguide systems. Techniques for electromagnetic analysis, thermal control and hermetic sealing were explored. Three dimensional electromagnetic analysis was performed using a finite difference time-domain (FDTD) algorithm and experimentally verified for millimeter-wave package input and output transitions. New multi-material system concepts (AlN, Cu, and diamond thin films) which allow excellent surface finishes to be achieved with enhanced thermal management have been investigated. A new approach utilizing block copolymer coatings was employed to hermetically seal packages which met MIL STD-883.

Herman, Martin I.↗
NASA NTRS2008

NASA Tech Briefs, March 2008

Topics covered include: WRATS Integrated Data Acquisition System; Breadboard Signal Processor for Arraying DSN Antennas; Digital Receiver Phase Meter; Split-Block Waveguide Polarization Twist for 220 to 325 GHz; Nano-Multiplication-Region Avalanche Photodiodes and Arrays; Tailored Asymmetry for Enhanced Coupling to WGM Resonators; Disabling CNT Electronic Devices by Use of Electron Beams; Conical Bearingless Motor/Generators; Integrated Force Method for Indeterminate Structures; Carbon-Nanotube-Based Electrodes for Biomedical Applications; Compact Directional Microwave Antenna for Localized Heating; Using Hyperspectral Imagery to Identify Turfgrass Stresses; Shaping Diffraction-Grating Grooves to Optimize Efficiency; Low-Light-Shift Cesium Fountain without Mechanical Shutters; Magnetic Compensation for Second-Order Doppler Shift in LITS; Nanostructures Exploit Hybrid-Polariton Resonances; Microfluidics, Chromatography, and Atomic-Force Microscopy; Model of Image Artifacts from Dust Particles; Pattern-Recognition System for Approaching a Known Target; Orchestrator Telemetry Processing Pipeline; Scheme for Quantum Computing Immune to Decoherence; Spin-Stabilized Microsatellites with Solar Concentrators; Phase Calibration of Antenna Arrays Aimed at Spacecraft; Ring Bus Architecture for a Solid-State Recorder; and Image Compression Algorithm Altered to Improve Stereo Ranging.

Source record↗
NASA NTRSDate not supplied

Testing of Mars Retropropulsion Concepts in the Langley Unitary Plan Wind Tunnel

Future Mars human lander missions will require using retrorockets beginning at supersonic conditions, something which has never been done before at Mars. Significant aerosciences challenges exist due to interactions between the retrorocket exhaust plumes, the freestream flow, and the vehicle that alter the aerodynamic behavior. Historical retropropulsion ground and flight data do not provide a basis for calibrating the computational uncertainties for aerodynamic interference forces and moments on proposed Mars descent vehicles, either because of insufficient data or dissimilar vehicles geometries and/or conditions. A new retropropulsion wind tunnel test was conducted in the NASA Langley Unitary Plan Wind Tunnel in order to address some of the deficiencies of previous tests and to provide a basis for computational model comparisons on relevant geometries. The test included improvements in model design and measured data. Two sub-scale model geometries derived from full-scale vehicle concepts were tested: a blunt low lift-to-drag vehicle and a more slender geometry. The first model includes variations in nozzle parameters that were estimated to have first-order effects on the measurements: location, pointing direction, size, and exit-to-throat area ratio. Both models were instrumented with discrete steady and unsteady pressure sensors on the aerodynamic and interior flow path surfaces. The heats shields of both models also were covered with pressure sensitive paint that effectively measures a steady pressure distribution in an otherwise unsteady flow field. This pressure distribution was integrated over the surface geometry in order to estimate the steady aerodynamic force and moment coefficient contribution from the painted surfaces; this approach was used as a replacement for using a flow-through balance. This paper will cover the test objectives, model design, test matrix, and available test results for each model configuration at different freestream Mach numbers, model attitude, and non-dimensional thrust magnitude. A subsequent publication will cover uncertainty quantification of the test data and comparisons to computational fluid dynamics model results.

Powered Descent↗
NASA NTRS2010

A Framework for Integrated Component and System Analyses of Instabilities

Instabilities associated with fluid handling and operation in liquid rocket propulsion systems and test facilities usually manifest themselves as structural vibrations or some form of structural damage. While the source of the instability is directly related to the performance of a component such as a turbopump, valve or a flow control element, the associated pressure fluctuations as they propagate through the system have the potential to amplify and resonate with natural modes of the structural elements and components of the system. In this paper, the authors have developed an innovative multi-level approach that involves analysis at the component and systems level. The primary source of the unsteadiness is modeled with a high-fidelity hybrid RANS/LES based CFD methodology that has been previously used to study instabilities in feed systems. This high fidelity approach is used to quantify the instability and understand the physics associated with the instability. System response to the driving instability is determined through a transfer matrix approach wherein the incoming and outgoing pressure and velocity fluctuations are related through a transfer (or transmission) matrix. The coefficients of the transfer matrix for each component (i.e. valve, pipe, orifice etc.) are individually derived from the flow physics associated with the component. A demonstration case representing a test loop/test facility comprised of a network of elements is constructed with the transfer matrix approach and the amplification of modes analyzed as the instability propagates through the test loop.

Ahuja, Vineet↗
NASA NTRS2012

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

imon, Donald L.↗
DOE OSTI2024

Analysis of heat transfer and AuNPs-mediated photo-thermal inactivation of E. coli at varying laser powers using single-phase CFD modeling

In the wake of the COVID-19 pandemics, the demand for innovative and effective methods of bacterial inactivation has become a critical area of research, providing the impetus for this study. The purpose of this research is to analyze the AuNPs-mediated photothermal inactivation of E. coli. Gold nanoparticles irradiated by laser represent a promising technique for combating bacterial infection that combines high-tech and scientific progress. The intermediate aim of the work was to present the calibration of the model with respect to the gold nanorods experiment. The purpose of this work is to study the effect of initial concentration of E. coli bacteria, the design of the chamber and the laser power on heat transfer and inactivation of E. coli bacteria. Using the CFD simulation, the work combines three main concepts. 1. The conversion of laser light to heat has been described by a combination of three distinctive approximations: a- Discrete particle integration to take into account every nanoparticle within the system, b- Rayleigh-Drude approximation to determine the scattering and extinction coefficients and c- Lambert–Beer–Bourger law to describe the decrease in laser intensity across the AuNPs. 2. The contribution of the presence of E. coli bacteria to the thermal and fluid-dynamic fields in the microdevice was modeled by single-phase approach by determining the effective thermophysical properties of the water-bacteria mixture. 3. An approach based on a temperature threshold attained at which bacteria will be inactivated, has been used to predict bacterial response to temperature increases. The comparison of the thermal fields and temporal temperature changes obtained by the CFD simulation with those obtained experimentally confirms the accuracy of the light-heat conversion model derived from the aforementioned approximations. The results show a linear relationship between maximum temperature and variation in laser power over the range studied, which is in line with previous experimental results. It was also found that the temperature inside the microchamber can exceed 55 °C only when a laser power higher than 0.8 W is used, so bacterial inactivation begins. The experimental data allows to determinate the concentration of nanoparticles. This parameter is introduced into the mathematical model obtaining the same number of AuNPs. However, this assumption introduces a certain simplification, as in the mathematical model the distribution of nanoparticles is uniform. This work is directly connected to the use of gold nanoparticles for energy conversion, as well as the field of bacterial inactivation in microfluidic systems such as lab-on-a-chip. Presented mathematical and numerical models can be extended to the entire spectrum of wavelengths with particular use of white light in the inactivation of bacteria. This work represents a significant advancement in the field, as to the best of the authors’ knowledge, it is the first to employ a single-phase computational fluid dynamics (CFD) approach specifically combined with the thermal inactivation of bacteria. Moreover, this research pioneers the use of a numerical simulation to analyze the temperature threshold of photothermal inactivation of E. coli mediated by gold nanorods (AuNRs). The integration of these methodologies offers a new perspective on optimizing bacterial inactivation techniques, making this study a valuable contribution to both computational modeling and biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale CFD simulation of biomass fast pyrolysis with a machine learning derived intra-particle model and detailed pyrolysis kinetics

Coupling particle and reactor scale models is as essential as reactor fluid dynamics and particle motion for accurate Computational Fluid Dynamic (CFD) simulations of biomass fast pyrolysis reactors due to intraparticle heat transfer and chemical reactions controlling conversion time and product distributions. Direct online coupling of a particle model with a reactor model is computationally expensive, while offline coupling is case-dependent. In this research, solutions from a series of particle pyrolysis simulations were regressed with Artificial Neural Network (ANN). Furthermoer, this machine learning-derived model predicted the same temperature and conversion profiles compared with particle resolved simulation while the isothermal approach overpredicted the temperature by 130 K and underpredicted the conversion time by 30 s. The ANN model was then integrated into CFD simulations of fluidized bed biomass fast pyrolysis with varied feedstocks via coupling PyTorch and MFiX. The averaged error of simulation predicted bio-oil yields with four feedstocks is 6.4%. This multi-scale approach provides an efficient tool for the coupled particle and reactor scale simulations of biomass pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2024

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A machine learning-based fast frequency response control for a VSC-HVDC system

An HVDC system can realize a very fast frequency response to the disturbed system under a contingency because its active power control is decoupled from the frequency deviation. However, most of existing HVDC frequency control strategies are coupled with system primary frequency control and secondary frequency control. Since the traditional system frequency control is dominated by the thermal generators, the advantage of the fast response of the HVDC system is not made fully used. The development of a frequency response estimation based on a machine learning algorithm provides another approach to improve the frequency response capability of the HVDC system. Different from other frequency deviation tracking strategies, a machine learning based HVDC frequency response control can directly increase the power flow of a HVDC system by estimation of the system generator or load lost. In this paper, a fast frequency response control using a HVDC system for a large power system disturbance based on the multivariate random forest regression (MRFR) algorithm is proposed. The simulation is carried out with an integrated power system model based on the North American interconnections. The simulation results indicate that the proposed MRFR based frequency response control can significantly improve the frequency low point during an event, while stabilizing the frequency in advance.

42 ENGINEERING↗
NASA NTRS1990

Structures and materials technology for hypersonic aerospacecraft

Major considerations in structural design of a transatmospheric aerospacecraft are discussed. The general direction of progress in structures and materials technology is indicated, and technical areas in structures and materials where further research and development is necessary are indicated. Various structural concepts under study and materials which appear to be most applicable are discussed. Structural design criteria are discussed with particular attention to the factor-of-safety approach and the probabilistic approach. Structural certification requirements for the aerospacecraft are discussed. The kinds of analyses and tests which would be required to certify the structural integrity, safety, and durability of the aerospacecraft are discussed, and the type of test facility needed to perform structural certification tests is identified.

Mccomb, Harvey G., Jr.↗
NASA NTRS1990

A computational procedure for multibody systems including flexible beam dynamics

A computational procedure suitable for the solution of equations of motions for flexible multibody systems has been developed. A fully nonlinear continuum approach capable of accounting for both finite rotations and large deformations has been used to model a flexible beam component. The beam kinematics are referred directly to an inertial reference frame such that the degrees of freedom embody both the rigid and flexible deformation motions. As such, the beam inertia expression is identical to that of rigid body dynamics. The nonlinear coupling between gross body motion and elastic deformation is contained in the internal force expression. Numerical solution procedures for the integration of spatial kinematic systems can be directily applied to the generalized coordinates of both the rigid and flexible components. An accurate computation of the internal force term which is invariant to rigid motions is incorporated into the general solution procedure.

Downer, J. D.↗
NASA NTRS2002

Integrating Analysis Goals for EOP, CRF and TRF

In a simplified, idealized way the TRF (Terrestrial Reference Frame) can be considered a set of positions at epoch and corresponding linear rates of change while the CRF (Celestial Reference Frame) is a set of fixed directions in space. VLBI analysis can be optimized for CRF and TRF separately while handling some of the complexity of geodetic and astrometric reality. For EOP (Earth Orientation Parameter) time series both CRF and TRF should be accurate at the epoch of interest and well defined over time. The optimal integration of EOP, TRF and CRF in a single VLBI solution configuration requires a detailed consideration of the data set and the possibly conflicting nature of the reference frames. A possible approach for an integrated analysis is described.

Ma, Chopo↗
NASA NTRS2004

Probability Distribution Estimated From the Minimum, Maximum, and Most Likely Values: Applied to Turbine Inlet Temperature Uncertainty

Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal distribution (ref.1). This new approach allows for a very simple and direct algebraic solution without restricting the standard deviation. The beta parameters obtained by the new method are comparable to the conventional method (and identical when the distribution is symmetrical). However, the proposed method generally produces a less peaked distribution with a slightly larger standard deviation (up to 7 percent) than the conventional method in cases where the distribution is asymmetric or skewed. The beta distribution model has now been implemented into the Fast Probability Integration (FPI) module used in the NESSUS computer code for probabilistic analyses of structures (ref. 2).

Holland, Frederic A., Jr.↗