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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Elastic and Piezoelectric Properties of Boron Nitride Nanotube Composites: Finite Element Model - Part II

This paper is the second part of a two-part series where the first part presents a molecular dynamics model of a single Boron Nitride Nanotube (BNNT) and this paper scales up to multiple BNNTs in a polymer matrix. This paper presents finite element (FE) models to investigate the effective elastic and piezoelectric properties of (BNNT) nanocomposites. The nanocomposites studied in this paper are thin films of polymer matrix with aligned co-planar BNNTs. The FE modelling approach provides a computationally efficient way to gain an understanding of the material properties. We examine several FE models to identify the most suitable models and investigate the effective properties with respect to the BNNT volume fraction and the number of nanotube walls. The FE models are constructed to represent aligned and randomly distributed BNNTs in a matrix of resin using 2D and 3D hollow and 3D filled cylinders. The homogenisation approach is employed to determine the overall elastic and piezoelectric constants for a range of volume fractions. These models are compared with an analytical model based on Mori-Tanaka formulation suitable for finite length cylindrical inclusions. The model applies to primarily single-wall BNNTs but is also extended to multi-wall BNNTs, for which preliminary results will be presented. Results from the Part 1 of this series can help to establish a constitutive relationship for input into the finite element model to enable the modeling of multiple BNNTs in a polymer matrix.

Kim, H. Alicia↗
NASA NTRS2016

The Effects of Temporal and Topographic Decorrelation on Forest Height Retrieval Using Airborne Repeat-Pass L-Band Polarimetric SAR Interferometry

We have explored the effects of temporal baseline and terrain slope on forest height estimation using L-band repeat-pass polarimetric-interferometric synthetic aperture radar (PolIn-SAR). Data were collected using NASA’s Uninhabited Aerial Vehicle Synthetic Aperture Radar instrument over a study area exhibiting high slope topography in the Laurentides Wildlife Reserve of Quebec, Canada. We used lidar-derived canopy height and terrain slope maps to quantify the decorrelation effects, in both magnitude and phase, that distort the observed coherences compared to the random volume over ground forest model. We derived forest height maps for a number of different temporal baselines using both fixed model parameters and model parameters that varied with slope, and compared the results. Further work is necessary to develop improved slope correction methods, and to see if slope corrections derived from lidar data for this study area can be applied to other study areas, or generalized to a theoretical model.

polarimetric SAR interferometry↗
NASA NTRS2020

Genetic Algorithm for Optimization of Neural Networks for Bayesian Inference of Model Uncertainty

The objective of this work was to develop a genetic optimization algorithm that can design a neural network capable of producing uncertainty estimates along with predictions. This algorithm is necessary because the inclusion of uncertainty modeling in a neural network greatly complicates the network’s design space, making the development of a converging model extremely difficult and time consuming. The genetic algorithm presented in this work uses a number of value ranges for various configurable neural network parameters to create a randomly generated population of network architectures. The initially generated population is then evolved over the course of several generations, with the best performing models breeding to produce novel network configurations. Mutations are randomly applied to the network designs to facilitate the development of adaptations beneficial to the task being performed. An experiment was conducted to validate the proposed algorithm, in which the genetic optimizer was tasked with producing a neural network capable of predicting the sound pressure level (SPL) resulting from jet-surface interaction (JSI) noise. The data used for this task was generated at the NASA Glenn Research Center in the Aero-Acoustic Propulsion Laboratory. Starting with an initial population size of 35 randomly generated networks, and evolved over the course of 10 generations, the genetic algorithm produced a design able to predict SPL as a result of JSI noise within 0.272 dB, on average.

Genetic algorithm↗
NASA NTRS2022

The Population of Galactic Centre Filaments – III. Candidate Radio and Stellar Sources

Recent MeerKAT radio continuum observations of the Galactic Centre at 20 cm show a large population of non-thermal radio filaments (NRFs) in the inner few hundred pc of the Galaxy. We have selected a sample of 57 radio sources, mainly compact objects, in the MeerKAT mosaic image that appear to be associated with NRFs. The selected sources are about four times the number of radio point sources associated with filaments than would be expected by random chance. Furthermore, an apparent correlation between bright IR stars and NRFs is inferred from their similar latitude distributions, suggesting that they both co-exist within the same region. To examine if compact radio sources are related to compact IR sources, we have used archival 2MASS, and Spitzer data to make spectral energy distribution of individual stellar sources coincident or close to radio sources. We provide a catalogue of radio and IR sources for future detailed observations to investigate a potential three-way physical association between NRFs, compact radio and IR stellar sources. This association is suggested by models in which NRFs are cometary tails produced by the interaction of a large-scale nuclear outflow with stellar wind bubbles in the Galactic Centre.

plasmas↗
DOE OSTI2026

Role of Chemical Disorder in High Temperature Dislocation Glide in Refractory Multi-principal Element Alloys

Refractory multi-principal element alloys (RMPEAs) combine a chemically disordered lattice with a structurally ordered, single‐phase body‐centered cubic (bcc) crystal structure. Chemical fluctuations in these alloys give rise to significant energy barriers that impede dislocation motion. In this study, we use phase field dislocation dynamics to examine how spatial temperature fluctuations compete with randomness in energy barriers to affect the motion of long screw dislocations in three equi-atomic MoNbTa‐based RMPEAs: MoNbTa, MoNbTaW, and MoNbTaVW. Over a wide range of homologous temperatures (T h ≈ 0–0.6), we determined a screw dislocation ‘flow stress’ as the minimum applied stress to sustain continuous motion over a long excursion distance within a fixed timeframe. All three RMPEAs exhibit temperature dependent flow stress with three characteristic glide regimes: at low homologous temperatures, flow stress drops sharply, and screw glide remains planar and rectilinear; at intermediate homologous temperatures, the flow stress levels off as glide becomes planar but wavy; and at high homologous temperatures, flow stress plateaus as screws exhibit nonplanar, three‐dimensional motion. Glide kinetics and transition temperatures are controlled by the chemically induced fluctuations in the energy landscape. The rectilinear to wavy transition temperature is controlled by statistically weakest local barriers in the glide plane, whereas the wavy to 3D transition temperature is governed by statistically strongest local barriers. At low and intermediate homologous temperatures, the relative spread in energy barriers governs glide behavior by controlling the local kinetics of kink pair formation and kink pinning. At high homologous temperatures, the average barrier height governs the glide behavior by controlling the number of out-of-plane excursions during 3D glide. These findings reveal how random chemical fluctuations determine screw‐driven plasticity in RMPEAs, providing critical insight for the design of high temperature structural alloys.

Defects↗
NASA NTRS1990

A fractal transition in the two dimensional shear layer

The dependence of product generation with the Peclet and Reynolds number in a numerically simulated, reacting, two dimensional, temporally growing mixing layer is used to compute the fractal dimension of passive scalar interfaces. A transition from a low dimension of 4/3 to a higher one of 5/3 is identified and shown to be associated to the kinematic distortion on the flow field during the first pairing interaction. It is suggested that the structures responsible for this transition are non-deterministic, non-random, inhomogeneous fractals. Only the large scales are involved. No further transition is found for Reynolds numbers up to 20,000.

Jimenez, Javier↗
NASA NTRS2024

Noise Reduction for Solar-Induced Fluorescence Retrievals Using Machine Learning and Principal Component Analysis: Simulations and Applications to GOME-2 Satellite Retrievals

We use a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network (NN) to substantially reduce noise and other artifacts in terrestrial chlorophyll solar-induced fluorescence (SIF) retrievals. SIF is a very small emission at red and far-red wavelengths that is difficult to measure and is highly sensitive to random errors and systematic artifacts. Our approach relies upon an assumption that a trained NN can effectively reconstruct the total SIF signal from a relatively small number of leading principal components of the satellite-observed far-red radiance spectra without using information from the trailing modes that contain most of the random errors. We test the approach with simulated reflectance spectra produced with a full atmospheric and surface radiative transfer model using different observing and geophysical parameters and various noise levels. Resulting noisy and noise-reduced retrieved SIF values are compared with true values to assess performance. We then apply our noise reduction approach to SIF derived from two different satellite spectrometers. For evaluation, since the truth in this case is unknown, we compare SIF retrievals from two independent sensors with each other. We also compare the noise-reduced SIF temporal variations with those from an independent gross primary product (GPP) product that should display similar variations. Results show that our noise reduction approach improves capture of SIF seasonal and inter-annual variability. Our approach should be applicable to many noisy data products derived from spectral measurements. Our methodology does not replace the original retrieval algorithms; rather the original noisy retrievals are needed as the target for the NN training process.

noise reduction, solar-induced fluorescence, SIF, ↗
NASA NTRS1992

Experimental Investigation of the Behavior of Sub-Grid Scale Motions in Turbulent Shear Flow

Experiments have been carried out on a vertical jet of helium issuing into a co-flow of air at a fixed exit velocity ratio of 2.0. At all the experimental conditions studied, the flow exhibits a strong self excited periodicity. The natural frequency behavior of the jet, the underlying fine-scale flow structure, and the transition to turbulence have been studied over a wide range of flow conditions. The experiments were conducted in a variable pressure facility which made it possible to vary the Reynolds number and Richardson number independently. A stroboscopic schlieren system was used for flow visualization and single-component Laser Doppler Anemometry was used to measure the axial component of velocity. The flow exhibits several interesting features. The presence of co-flow eliminates the random meandering typical of buoyant plumes in a quiescent environment and the periodicity of the helium jet under high Richardson number conditions is striking. Under these conditions transition to turbulence consists of a rapid but highly structured and repeatable breakdown and intermingling of jet and freestream fluid. At Ri = 1.6 the three-dimensional structure of the flow is seen to repeat from cycle to cycle. The point of transition moves closer to the jet exit as either the Reynolds number or the Richardson number increases. The wavelength of the longitudinal instability increases with Richardson number. At low Richardson numbers, the natural frequency scales on an inertial time scale. At high Richardson number the natural frequency scales on a buoyancy time scale. The transition from one flow regime to another occurs over a narrow range of Richardson numbers from 0.7 to 1. A buoyancy Strouhal number is used to correlate the high Richardson number frequency behavior.

Cantwell, Brian↗
DOE OSTI2025

Aided Active Learning (AAL) for Enhanced Critical Heat Flux Prediction

Accurate prediction of critical heat flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data, which are hard to obtain. This study introduces the Aided Active Learning (AAL) framework, which strategically minimizes data requirements without sacrificing model accuracy. Unlike conventional Active Learning (AL), AAL introduces an additional step of randomly selecting a subset from the sample pool before applying the query strategy. To evaluate the performance of AAL, two query strategies—uncertainty-based sampling and error-reduction sampling—were evaluated across the following models: random forest (RF), feedforward neural network (FNN), and variational feedforward neural network (vFNN). The proposed framework demonstrated that AAL effectively reduces the number of training samples needed to achieve comparable predictive accuracy. For the RF model, AL required only 710 samples to achieve an R2 score of 0.98, as compared to the 4,785 samples needed by random sampling. Similarly, the FNN model achieved the same R2 score with just 355 samples when using AL, a significant improvement over the 825 samples required by random sampling. In case of uncertainty-based sampling strategy, vFNN attained an R2 of 0.98 with 3,420 samples, reducing the sample requirement by 47% relative to the 6,440 samples needed for random sampling. Its performance suggests that larger training data are required to fully leverage its uncertainty quantification capabilities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2007

A Microfabricated Involute-Foil Regenerator for Stirling Engines

A segmented involute-foil regenerator has been designed, microfabricated and tested in an oscillating-flow rig with excellent results. During the Phase I effort, several approximations of parallel-plate regenerator geometry were chosen as potential candidates for a new microfabrication concept. Potential manufacturers and processes were surveyed. The selected concept consisted of stacked segmented-involute-foil disks (or annular portions of disks), originally to be microfabricated from stainless-steel via the LiGA (lithography, electroplating, and molding) process and EDM (electric discharge machining). During Phase II, re-planning of the effort led to test plans based on nickel disks, microfabricated via the LiGA process, only. A stack of nickel segmented-involute-foil disks was tested in an oscillating-flow test rig. These test results yielded a performance figure of merit (roughly the ratio of heat transfer to pressure drop) of about twice that of the 90% random fiber currently used in small ~ 100 W Stirling space-power convertors in the Reynolds Number range of interest (50-100). A Phase III effort is now underway to fabricate and test a segmented-involute-foil regenerator in a Stirling convertor. Though funding limitations prevent optimization of the Stirling engine geometry for use with this regenerator, the Sage computer code will be used to help evaluate the engine test results. Previous Sage Stirling model projections have indicated that a segmented-involute-foil regenerator is capable of improving the performance of an optimized involute-foil engine by 6-9%; it is also anticipated that such involute-foil geometries will be more reliable and easier to manufacture with tight-tolerance characteristics, than random-fiber or wire-screen regenerators. Beyond the near-term Phase III regenerator fabrication and engine testing, other goals are (1) fabrication from a material suitable for high temperature Stirling operation (up to 850 C for current engines; up to 1200 C for a potential engine-cooler for a Venus mission), and (2) reduction of the cost of the fabrication process to make it more suitable for terrestrial applications of segmented involute foils. Past attempts have been made to use wrapped foils to approximate the large theoretical figures of merit projected for parallel plates. Such metal wrapped foils have never proved very successful, apparently due to the difficulties of fabricating wrapped-foils with uniform gaps and maintaining the gaps under the stress of time-varying temperature gradients during start-up and shut-down, and relatively-steady temperature gradients during normal operation. In contrast, stacks of involute-foil disks, with each disk consisting of multiple involute-foil segments held between concentric circular ribs, have relatively robust structures. The oscillating-flow rig tests of the segmented-involute-foil regenerator have demonstrated a shift in regenerator performance strongly in the direction of the theoretical performance of ideal parallel-plate regenerators.

Tew, Roy↗
NASA NTRS1985

A multiple scattering theory for EM wave propagation in a dense random medium

For a dense medium of randomly distributed scatterers an integral formulation for the total coherent field has been developed. This formulation accounts for the multiple scattering of electromagnetic waves including both the twoand three-particle terms. It is shown that under the Markovian assumption the total coherent field and the effective field have the same effective wave number. As an illustration of this theory, the effective wave number and the extinction coefficient are derived in terms of the polarizability tensor and the pair distribution function for randomly distributed small spherical scatterers. It is found that the contribution of the three-particle term increases with the particle size, the volume fraction, the frequency and the permittivity of the particle. This increase is more significant with frequency and particle size than with other parameters.

Karam, M. A.↗
DOE OSTI2025

Quantum entanglement in nuclear fission

Nuclear fission presents a unique example of quantum entanglement in strongly interacting many-body systems. A heavy nucleus can split into hundreds of combinations of two complementary fragments in the fission process. The entanglement of fragment wave functions is persistent even after separation and impacts the partition of particles and energies between fragments. Based on microscopic dynamical calculations of the fission of 240 Pu, this work finds that dynamical quantum entanglement is indispensable in the appearance of sawtooth distributions of average excitation energies of fragments and thus neutron multiplicities, but not in average neutron excess of fragments. Both sawtooth slopes from particle-number projections are found to be steep – a feature which can be alleviated by random fluctuations. The persistent entanglement is mainly due to non-adiabatic dynamics since the final splitting is so fast that the non-localization of wave functions is kept during the separation. These findings may impact the understanding of quantum entanglement more broadly in mesoscopic systems

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles

Iron carbide (Fe x C y ) nanoparticles (NPs) are promising candidates for replacing platinum group metals in industrial applications, such as high-temperature Fischer–Tropsch synthesis. However, due to their amorphous nature, characterization of the active sites has been challenging experimentally and computationally. Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe 182 C 88 NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). Once generated, the Fe 182 C 88 NP active sites and particle morphology are thoroughly characterized before the effects of syngas adsorbate interactions are explored by using DFT and molecular dynamics simulations. Lastly, we explore correlations between geometric and electronic features of the active sites and the adsorption of H (H ads ), using a regularized random forest machine learning algorithm. In doing so, we identified the Fe–C coordination number and p orbital occupancy as the most important descriptors affecting H ads . Furthermore, using a combined ML and quantum chemistry approach, our work demonstrates a general and efficient procedure for generating and probing complex surface phenomena on binary nanoparticles.

Adsorption↗
DOE OSTI2025

Towards Scalable 3D Integration of 2T-nC FeRAM with Hundreds of Layer Stacking

In this article, we study the limits of the number of capacitors and read history dependence in a 2T-nC ferroelectric random-access memory (FeRAM) cell, paving the way for its high-density integration toward hundreds of stacked layers. Through a comprehensive experimental and simulation study on the scaling behavior of the 2T-nC FeRAM architecture, we demonstrate: (i) successful fabrication of 2T-64C cells with robust memory operation and clearly distinguishable ‘0’ and ‘1’ states, even in 64- capacitor configurations; (ii) that the parasitic capacitance of the floating node originates predominantly from the linear component of the ferroelectric capacitor, and its impact on n-scaling—due to degraded sense margin—can be mitigated by floating unselected capacitors with enough TΩ isolation; (iii) that sharing write and read transistors among n capacitors introduces a read history dependence issue due to fluctuating floating node voltage (VFN); and (iv) that a proposed FN discharge scheme can effectively eliminate read-sequence dependence, at the cost of reduced read endurance.

36 MATERIALS SCIENCE↗
NASA NTRS1976

The computer for design and optimization

Computerized design using numerical optimization techniques is discussed and guidelines for writing analysis computer codes that can be readily coupled to optimization codes are presented. The following numerical optimization techniques are examined: random search, sequential unconstrained minimization, direct constrained optimization, and one-dimensional search. A number of design applications are considered including high speed airfoil lift maximization, the preliminary design of a wing, design of a planar tower for optimal geometry, and the conceptual design of a tactical fighter aircraft.

Vanderplaats, G. N.↗
NASA NTRS1980

Socio-psychological airplane noise investigation in the districts of three Swiss airports: Zurich, Geneva and Basel

The results of noise measurements and calculations are available in the form of noise maps for each of the three areas. To measure the stress due to airplane noise the Noise and Number Index (NNI) was applied. In the vicinities of the airports, 400 households were randomly selected in each of the three noise zones (of 10 NNI intervals each). A total of 3939 questionnaires could be evaluated, one quarter of which came from areas without airplane noise. Concurrently, traffic noise was measured in areas of Basel and expressed in sum total levels L sub 50 and the reaction of 944 persons was elicited by interrogation.

Graf, R.↗
NASA NTRS1981

Computational methods of robust controller design for aerodynamic flutter suppression

The development of Riccati iteration, a tool for the design and analysis of linear control systems is examined. First, Riccati iteration is applied to the problem of pole placement and order reduction in two-time scale control systems. Order reduction, yielding a good approximation to the original system, is demonstrated using a 16th order linear model of a turbofan engine. Next, a numerical method for solving the Riccati equation is presented and demonstrated for a set of eighth order random examples. A literature review of robust controller design methods follows which includes a number of methods for reducing the trajectory and performance index sensitivity in linear regulators. Lastly, robust controller design for large parameter variations is discussed.

Anderson, L. R.↗
NASA NTRS1988

Multiple input/output random vibration control system

A multi-input/output random vibration control algorithm was developed based on system identification concepts derived from random vibration spectral analysis theory. The unique features of the algorithm are: (1) the number of input excitors and the number of output control responses need not be identical; (2) the system inverse response matrix is obtained directly from the input/output spectral matrix; and (3) the system inverse response matrix is updated every control loop cycle to accommodate system amplitude nonlinearities. A laboratory demonstration case of two imputs with three outputs is presented to demonstrate the system capabilities.

Unruh, James F.↗