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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Parallel Methods on Large-Scale Structural Analysis and Physics Applications; Symposium, Hampton, VA, Feb. 5, 6, 1991, Selected Papers

Recent advances in parallel methods and algorithms integrated into large-scale codes are presented. Consideration is given to problem decomposition (substructuring), efficient matrix solution algorithms for shared memory architectures, dynamic and transient analysis algorithms for shared memory architectures, and algorithms for distributed and massively parallel architectures. Particular attention is given to partitioning of unstructured problems for parallel processing, parallel-vector computation for linear-structural analysis and nonlinear unconstraint optimization problems, a parallel-vector equation solver for unsymmetric matrices on supercomputers, parallel nonlinear finite element dynamic response, multigrid algorithms for solving structural mechanics problems on supercomputers, structural analysis on massively parallel computers, explicit finite element methods with contact-impact on SIMD computers, and the impact of mapping and sparsity on parallelized finite element method modules.

Storaasli, Olaf O.↗
NASA NTRS2003

Model-Data Assimilation of Internal Waves during ASIAEX-2001

In recent Asian Seas International Acoustics Experiment (ASIAEX), extensive moorings have been deployed around the continental shelf break area in the northeast of South China Sea in May 2001. Simultaneous RADARSAT SAR images have been collected during the field test to integrate with the in-situ measurements from moorings, ship-board sensors, and CTD casts. Besides it provides synoptic information, satellite imagery is very useful for tracking the internal waves, and locating surface fronts and mesoscale features. During ASIAEX in May 2001, many large internal waves were observed at the test area and were the major oceanic features for acoustic volume interaction. Based on the internal wave distribution maps compiled from satellite data, the wave crest can be as long as 200 km with amplitude of 100 m. Environmental parameters have been calculated based on extensive CTD casts data near the ASIAEX area. Nonlinear internal wave models have been applied to integrate and assimilate both SAR and mooring data. Using SAR data in deep water as an initial condition, numerical simulations produce the wave evolution on the continental shelf and compared reasonably well with the mooring measurements at the downstream station. The shoaling, turning, and dissipation of large internal waves on the shelf break, elevation solitons, and wave-wave interaction have been studied and are very important issues for acoustic propagation. The internal wave effects on acoustic modal coupling has been implicated and discussed.

Liu, Antony↗
NASA NTRS2016

Phase-Retrieval Uncertainty Estimation and Algorithm Comparison for the JWST-ISIM Test Campaign

Phase retrieval, the process of determining the exitpupil wavefront of an optical instrument from image-plane intensity measurements, is the baseline methodology for characterizing the wavefront for the suite of science instruments (SIs) in the Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST). JWST is a large, infrared space telescope with a 6.5-meter diameter primary mirror. JWST is currently NASA's flagship mission and will be the premier space observatory of the next decade. ISIM contains four optical benches with nine unique instruments, including redundancies. ISIM was characterized at the Goddard Space Flight Center (GSFC) in Greenbelt, MD in a series of cryogenic vacuum tests using a telescope simulator. During these tests, phase-retrieval algorithms were used to characterize the instruments. The objective of this paper is to describe the Monte-Carlo simulations that were used to establish uncertainties (i.e., error bars) for the wavefronts of the various instruments in ISIM. Multiple retrieval algorithms were used in the analysis of ISIM phase-retrieval focus-sweep data, including an iterativetransform algorithm and a nonlinear optimization algorithm. These algorithms emphasize the recovery of numerous optical parameters, including low-order wavefront composition described by Zernike polynomial terms and high-order wavefront described by a point-by-point map, location of instrument best focus, focal ratio, exit-pupil amplitude, the morphology of any extended object, and optical jitter. The secondary objective of this paper is to report on the relative accuracies of these algorithms for the ISIM instrument tests, and a comparison of their computational complexity and their performance on central and graphical processing unit clusters. From a phase-retrieval perspective, the ISIM test campaign includes a variety of source illumination bandwidths, various image-plane sampling criteria above and below the Nyquist- Shannon critical sampling value, various extended object sizes, and several other impactful effects.

Design Analysis↗
DOE OSTI2024

Multi-objective Bayesian active learning for MeV-ultrafast electron diffraction

Ultrafast electron diffraction using MeV energy beams(MeV-UED) has enabled unprecedented scientific opportunities in the study of ultrafast structural dynamics in a variety of gas, liquid and solid state systems. Broad scientific applications usually pose different requirements for electron probe properties. Due to the complex, nonlinear and correlated nature of accelerator systems, electron beam property optimization is a time-taking process and often relies on extensive hand-tuning by experienced human operators. Algorithm based efficient online tuning strategies are highly desired. Here, we demonstrate multi-objective Bayesian active learning for speeding up online beam tuning at the SLAC MeV-UED facility. The multi-objective Bayesian optimization algorithm was used for efficiently searching the parameter space and mapping out the Pareto Fronts which give the trade-offs between key beam properties. Such scheme enables an unprecedented overview of the global behavior of the experimental system and takes a significantly smaller number of measurements compared with traditional methods such as a grid scan. This methodology can be applied in other experimental scenarios that require simultaneously optimizing multiple objectives by explorations in high dimensional, nonlinear and correlated systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Weak lensing trispectrum and Kurt-spectra

We introduce two kurt-spectra to probe fourth-order statistics of weak lensing convergence maps. Using state-of-the-art numerical simulations, we study the shapes of these kurt-spectra as a function of source redshifts and smoothing angular scales. We employ a pseudo-Cℓ approach to estimate the spectra from realistic convergence maps in the presence of an observational mask and noise for stage-IV large-scale structure surveys. We compare these results against theoretical predictions calculated using the FFTLog formalism, and find that a simple nonlinear clustering model — the hierarchical ansatz — can reproduce the numerical trends for the kurt-spectra in the nonlinear regime. In addition, we provide estimators for beyond fourth-order spectra where no definitive analytical results are available, and present corresponding results from numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory

The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R² from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.

Zeng, Yelu↗
DOE OSTI2023

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗
DOE OSTI2023

An Efficient Three-Dimensional CFD-Based Numerical Wave Tank for a Wave Energy Converter in Extreme Irregular Waves

A numerical wave tank approach for computational fluid dynamics (CFD) modelling of an extreme irregular seastate is presented. The technique couples a potential flow solution with a CFD solver for more efficient numerical predictions. This method has recently become attractive both for the research community and the industry working with offshore structures. The model is used to determine the response of a submerged pressure differential wave energy converter (WEC) in a fully nonlinear irregular wave condition using the high-fidelity CFD code, STAR-CCM+. Potential flow based numerical models are commonly used to predict motions and performance of wave energy converters. Wave kinematics can deviate from potential flow predictions for extreme wave conditions; the excitation loads on an absorber can also be increasingly influenced by viscous effects, not predicted by potential flow engineering level models. In these extreme conditions, a Reynolds-averaged Navier-Stokes CFD model can better predict motions and loads for a WEC. Long time series with varying random seed numbers can be used to identify singular extreme wave events from a stochastic irregular sea state. This approach simulates a more realistic wave series for a given sea state than a regular wave or a focused wave. However, it is computationally infeasible to run these long time series for three-dimensional (3D) CFD simulations. In this work, two-dimensional (2D) CFD simulations with a long domain allow the full development of an extreme nonlinear wave condition. The results are used to identify extreme events from a 50-year storm condition for the PacWave site off the coast of Oregon. A relatively short time window including this extreme event is then mapped to a 3D simulation using a user defined wave methodology. Convergence studies for domain length, wave forcing lengths, and time before the extreme event were conducted.

CFD↗
NASA NTRS1989

A dual-armed free flyer

This summary presents the main conclusions and results of the design studies conducted by a group of 13 students at the University of Maryland. The students, all participants in the spring 1989 course ENEE418 in the Electrical Engineering Department, met weekly in a two-hour class to discuss and evaluate design alternatives. The main problem considered was the design and control of a planar testbed simulating a free-flying space robot for applications in satellite servicing. This project grew out of the 1988 class where a dual-armed free flyer (DAFF) was designed and partially built. This year, a group of six students continued the development of the DAFF, achieving computer-controlled motion of the DAFF's arms. All fabrication and testing of the DAFF is being conducted in the Intelligent Servosystems Laboratory at the University of Maryland. While the work related to the design and development of the DAFF is the main subject of the report, it should be noted that other students in the ENEE418 class have investigated additional issues related to manipulation in space. For example, one group studied a new parallel linkage based manipulator for fine motion applications such as in assembly operations in space. They investigated the mechanism's kinematics, its reachable workspace, and precision of applying forces and torques. In yet another project, a student set out to measure and map the friction characteristics of the actuators used in the Modular Dextrous Hand, which has been recently developed in the Intelligent Servosystems Laboratory. The results are expected to help compensate for this friction, which is a highly nonlinear disturbance and presents significant problems in high-precision, low-speed operations. This summary continues with the discussion of the results obtained by the group of students who have been working on developing the DAFF testbed.

Beck, D.↗
NASA NTRS1994

Characteristics of finite amplitude stationary gravity waves in the atmosphere of Venus

This paper extends the study of stationary gravity waves generated near the surface of Venus reported previously by Young et al. to include finite amplitude effects associated with large amplitude waves. Waves are forced near the surface of Venus by periodic forcing. The height-dependent profiles of static stability and mean wind in the Venus atmosphere play a very important role in the evolution of the nonlinear behavior of the waves, just as they do in the linear wave solutions. Certain wave properties are qualitatively consistent with linear wave theory, such as wave trapping, resonance, and wave evanescence for short horizontal wavelenghts. However, the finite amplitude solutions also exhibit many other interesting features. In particular, for forcing amplitudes representative of those that could be expected in mountainous regions such as Aphrodite Terra, waves generated near the surface can reach large amplitudes at and above cloud levels, with clear signatures in the circulation pattern. At still higher levels, the waves can reach large enough amplitude to break, unless damping rates above the clouds are sufficient to limit wave amplitude growth. Well below cloud levels the waves develop complex flow patterns as the result of finite amplitude wave-wave interactions, and waves are generated having considerably shorter horizontal wavelenghts than that associated with the forcing near the surface. Nonlinear interactions can excite waves that are resonant with the background wind and static stability fields even when the primary surface forcing does not, and these waves can dominate the wave spectrum near cloud levels. A global map of Venus topographic slopes derived from Magellan altimetry data shows that slopes of magnitude comparable to or exceeding that used to force the model are ubiquitous over the surface.

Young, Richard E.↗
NASA NTRS1994

Dynamically consistent hydrography and absolute velocity in the eastern North Atlantic Ocean

The problem of mapping a dynamically consistent hydrographic field and associated absolute geostrophic flow in the eastern North Atlantic between 24 deg and 36 deg N is related directly to the solution of the so-called thermocline equations. A nonlinear optimization problem involving Needler's P equation is solved to find the hydrography and resulting flow that minimizes the vertical mixing above about 1500 m in the ocean and is simultaneously consistent with the observations. A sharp minimum (at least in some dimensions) is found, apparently corresponding to a solution nearly conserving potential vorticity and with vertical eddy coefficient less than about 10(exp -5) sq m/s. Estimates of `residual' quantities such as eddy coefficients are extremely sensitive to slight modifications to the observed fields. Boundary conditions, vertical velocities, etc., are a product of the optimization and produce estimates differing quantitatively from prior ones relying directly upon observed hydrography. The results are generally insensitive to particular elements of the solution methodology, but many questions remain concerning the extent to which different synoptic sections can be asserted to represent the same ocean. The method can be regarded as a practical generalization of the beta spiral and geostrophic balance inverses for the estimate of absolute geostrophic flows. Numerous improvements to the methodology used in this preliminary attempt are possible.

Wunsch, Carl↗
DOE OSTI2023

An Efficient Three-Dimensional CFD-Based Numerical Wave Tank for a Wave Energy Converter in Extreme Irregular Waves: Preprint

A numerical wave tank approach for computational fluid dynamics (CFD) modelling of an extreme irregular seastate is presented. The technique couples a potential flow solution with a CFD solver for more efficient numerical predictions. This method has recently become attractive both for the research community and the industry working with offshore structures. The model is used to determine the response of a submerged pressure differential wave energy converter (WEC) in a fully nonlinear irregular wave condition using the high fidelity CFD code, STAR-CCM+. Potential flow based numerical models are commonly used to predict motions and performance of wave energy converters. Wave kinematics can deviate from potential flow predictions for extreme wave conditions; the excitation loads on an absorber can also be increasingly influenced by viscous effects, not captured in engineering level models. In these extreme conditions, a Reynolds-averaged Navier-Stokes CFD model can better predict motions and loads for a WEC. Long time series with varying random seed numbers can be used to identify singular extreme wave events from a stochastic irregular sea state. This approach simulates a more realistic wave series for a given sea state than a regular wave or a focused wave. However, it is computationally infeasible to run these long time series for three-dimensional (3D) CFD simulations. In this work, two-dimensional (2D) CFD simulations with a long domain allow the full development of an extreme nonlinear wave condition. The results are used to identify extreme events from a 50-year storm condition for the PacWave site off the coast of Oregon. A relatively short time window including this extreme event is then mapped to a 3D simulation using a user defined wave methodology. Convergence studies for domain length, wave forcing lengths, and time before the extreme event were conducted.

cfd↗
NASA NTRS1991

Neuromorphic learning of continuous-valued mappings from noise-corrupted data

The effect of noise on the learning performance of the backpropagation algorithm is analyzed. A selective sampling of the training set is proposed to maximize the learning of control laws by backpropagation, when the data have been corrupted by noise. The training scheme is applied to the nonlinear control of a cart-pole system in the presence of noise. The neural computation provides the neurocontroller with good noise-filtering properties. In the presence of plant noise, the neurocontroller is found to be more stable than the teacher. A novel perspective on the application of neural network technology to control engineering is presented.

Troudet, T.↗
DOE OSTI2020

Anharmonic Eigenvectors and Acoustic Phonon Disappearance in Quantum Paraelectric SrTiO 3

Pronounced anomalies in the SrTiO 3 dynamical structure factor, S(Q,E), including the disappearance of acoustic phonon branches at low temperatures, were uncovered with inelastic neutron scattering (INS) and simulations. The striking effect reflects anharmonic couplings between acoustic and optic phonons and the incipient ferroelectric instability near the quantum critical point. It is rationalized using a first-principles renormalized anharmonic phonon approach, pointing to nonlinear Ti-O hybridization causing unusual changes in real-space phonon eigenvectors, frequencies, group velocities, and scattering phase space. Lastly, our method is general and establishes how T dependences beyond the harmonic regime, assessed by INS mapping of large reciprocal-space volumes, provide real-space insights into anharmonic atomic dynamics near phase transitions.

36 MATERIALS SCIENCE↗
NASA NTRS1990

On three dimensional object recognition and pose-determination: An abstraction based approach

A method of computing reliable Gaussian and mean curvature sign-map descriptors from the polynomial approximation of surfaces was demonstrated. Such descriptors which are invariant under perspective variation are suitable for hypothesis generation. A means for determining the pose of constructed geometric forms whose algebraic surface descriptors are nonlinear in terms of their orienting parameters was developed. This was done by means of linear functions which are capable of approximating nonlinear forms and determining their parameters. It was shown that biquadratic surfaces are suitable companion linear forms for cylindrical approximation and parameter estimation. The estimates provided the initial parametric approximations necessary for a nonlinear regression stage to fine tune the estimates by fitting the actual nonlinear form to the data. A hypothesis-based split-merge algorithm for extraction and pose determination of cylinders and planes which merge smoothly into other surfaces was developed. It was shown that all split-merge algorithms are hypothesis-based. A finite-state algorithm for the extraction of the boundaries of run-length regions was developed. The computation takes advantage of the run list topology and boundary direction constraints implicit in the run-length encoding.

Quek, Kok How Francis↗
NASA NTRS2002

Spectral Re-Growth Reduction for CCSDS 8-D 8-PSK TCM

This report presents a study on the CCSDS recommended 8-dimensional 8 PSK Trellis Coded Modulation (TCM) scheme. The important steps of the CCSDS scheme include: conversion of serial data into parallel form, differential encoding, convolutional encoding, constellation mapping, and filtering the 8-PSK symbols using the square root raised cosine (SRRC) pulses. The last step, namely the filtering of the 8 PSK symbols using SRRC pulses, significantly affects the bandwidth of the signal. If a nonlinear power amplifier is used, the SRRC filtered signal creates spectral regrowth. The purpose of this report is to investigate a technique, called the smooth phase interpolated keying (SPIK), that can provide an alternative to SRRC filtering so that good spectral as well as power efficiencies can be obtained with the CCSDS encoder. The results of this study show that the CCSDS encoder does not affect the spectral shape of the SRRC filtered signal or the SPIK signal. When a nonlinear traveling wave tube amplifier (TWTA) is used, the spectral performance of the SRRC signal degrades significantly while the spectral performance of SPIK remains unaffected. The degrading effect of a nonlinear solid state power amplifier (SSPA) on SRRC is found to be less than that due to a nonlinear TWTA. However, in both cases, the spectral performance of the SRRC modulated signal is worse than that of the SPIK signal. The bit error rate (BER) performance of the SRRC signal in a linear amplifier environment is about 2.5 dB better than that of the SPIK signal when both the receivers use algorithms of similar complexity. In a nonlinear TWTA environment, the SRRC signal requires accurate phase tracking since the TWTA introduces additional phase distortion. This problem does not arise with SPIK signal due to its constant envelope property. When a nonlinear amplifier is used, the SRRC method loses nearly 1 dB in the bit error rate performance. The SPIK signal does not lose any performance. Thus the performance gap between SRRC and SPIK reduces. The BER performance of SPIK can be improved even further by using a more optimal receiver. A similar optimal receiver for SRRC is quite complex since the amplifier distorts the pulse shape. However, this requires further investigation and is not covered in this report.

Borah, Deva K.↗
NASA NTRS2005

Integrated Microphotonic Receiver for Ka-Band

This report consists of four main sections. Part I: LiNbO3 microdisk resonant optical modulator. Brief review of microdisk optical resonator and RF ring resonator. Microwave and photonic design challenges for achieving simultaneous RF-optical resonance are addressed followed by our solutions. Part II: Experimental demonstration of LiNbO3 microdisk modulator performance in wired and wireless RF-optical links. Part III: Microphotonic RF receiver architecture that exploits the nonlinear modulation in the LiNbO3 microdisk modulator to achieve direct photonic down-conversion from RF carrier without using any high-speed electronic elements. Part IV: Ultimate sensitivity of the microdisk photonic receiver and the future road map toward a practical device.

Levi, A. F. J.↗
DOE OSTI2025

Reduced Order Modeling conditioned on monitored features for response and error bounds estimation in engineered systems

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM construction, schemes that allow to retain a portion of the physics tend to enhance the interpretability and generalization of ROMs. However, physics-based techniques can adversely scale when dealing with nonlinear systems that feature parametric dependencies. This study introduces a generative physics-based ROM that is suited for nonlinear systems with parametric dependencies and is additionally able to provide numerical error bounds associated with the respective estimates. A main contribution of this work is the conditioning of these parametric ROMs to features that can be derived from monitoring measurements, feasibly in an online fashion. This is contrary to most existing ROM schemes, which remain restricted to the prescription of the physics-based, and usually a priori unknown, system parameters. Our work utilizes conditional Variational Autoencoders to continuously map the required reduction bases to a feature vector extracted from limited output measurements, while additionally allowing for a probabilistic assessment of the ROM-estimated Quantities of Interest. An auxiliary task using a neural network-based parametrization of suitable probability distributions is introduced to re-establish the link with physical model parameters. We verify the proposed scheme on a series of simulated case studies incorporating effects of geometric and material nonlinearity under parametric dependencies related to system properties and input load characteristics.

Conditional VAEs↗