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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Full Gradient Solution to Adaptive Hybrid Control

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered-reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Bean, Jacob↗
NASA NTRS2017

Full Gradient Solution to Adaptive Hybrid Control

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Bean, Jacob↗
NASA NTRS2018

Verifying Implementation of the Dryden Turbulence Model and MIL-F-8785 Gust Gradient

Turbulence modeling in human-in-the-loop simulation is important to assessing aircraft handling qualities and pilot performance and to provide additional realism for pilot training. In the simulation community, the Dryden turbulence spectra is a popular choice for modeling the linear turbulent gusts because its rational form is efficiently reproduced by passing white noise through linear filters. The MIL-F-8785 gust gradients similarly use additional linear filters to model the gradient of the turbulent gust over the wing, and it represents the gust gradients as perturbations to the air-relative rotational rates. The Cockpit Motion Facility at NASA Langley Research Center (LaRC) models continuous random turbulence using the Dryden one-dimensional spectra and MIL-F-8785 gust gradient. The facility recently reviewed and updated its verification of these models as part of an initiative to improve motion cueing under turbulence. This exercise introduced improved methods for verifying the turbulence models and led to rediscovery of model assumptions that informed improvements to implementation.

Madden, Michael M.↗
NASA NTRS2020

Characterization of SiC/SiC Composites Subjected to Sequential Tensile Creep and Dwell Fatigue in Air under Thermal Gradient Conditions

Uncoated SiC/SiC composites, with 2D and 3D fiber architectures, were investigated under steady state thermal gradient conditions with sequential tensile creep and dwell fatigue. Melt infiltration (MI), chemical vapor infiltration (CVI), polymer impregnation and pyrolysis (PIP), and hybrid (CVI and PIP) techniques were used to fabricate ceramic matrix composites (CMCs) with a 2D balanced fiber architecture. CMCs with 3D fiber weaves were also fabricated using MI and hybrid methods. Steady state through the thickness thermal gradients were generated for the tensile specimens using laser heating on the front (hot side) and forced air cooling on the back (cold side). Hot side and cold side temperatures of 2400 and 2200 °F, respectively, were used for testing CMCs fabricated with the MI process, whereas hot side and cold side temperatures of 2700 and 2400 °F, respectively, were used for CMCs fabricated with CVI, PIP, and hybrid processes. Each CMC specimen was initially tested under tensile creep at 69 MPa (10 ksi) for 80 hours, which was then followed by tensile dwell fatigue testing at a maximum stress of 69 MPa (10 ksi) for another 80 hours for a total of 160 hours. This type of sequential tensile creep followed by tensile dwell fatigue testing was performed to ascertain the integrity of uncoated CMCs under steady state thermal gradient conditions. Tensile creep and dwell fatigue test results, generated under steady state thermal gradient conditions on different types of SiC/SiC composites, are compared with corresponding creep behaviors observed under isothermal conditions to determine the influence of both monotonic creep (static fatigue) and dwell fatigue on accumulated strains and deformation behaviors of the CMCs.

Kalluri, Sreeramesh↗
NASA NTRSDate not supplied

Investigation of Improved Wall Heat Flux Behavior Observed When Computing Hypersonic Flow Using a Face-averaged Nodal-gradient Approach On Tetrahedral Grids

We investigate the origin of a significant reduction in computed numerical “noise” in the spatial variation of computed wall heat flux observed when using a node-centered weighted least squares(WLSQ) gradient approach when solving the Reynolds-averaged Navier-Stokes (RANS) equations for hypersonic boundary layer flows on highly stretched tetrahedral grids. This investigation is conducted using a 2nd-order, cell-centered, finite-volume, discretization which we employ to contrast results obtained using two WLSQ gradient approaches: a conventional 3-D, cell-centered, node-neighbor, WLSQ gradient (NN-CCG) approach and a 3-D, face-averaged, node-centered gradient (F-ANG)approach. The F-ANG approach, is shown to produce significantly less “noise” in the spatial variation of wall heat flux, than the NN-CCG approach and we demonstrate the cause of this “noise” via a series of numerical experiments where we compute hypersonic laminar and turbulent boundary layer flows.We further investigate the level of grid resolution required for a tetrahedral grid to approach the fidelity of a grid resolved hexahedral grid solution obtained using an equivalent structured grid method.

Jeffery A. White↗
NASA NTRS2021

CLEAR: The Gas-phase Metallicity Gradients of Star-forming Galaxies at 0.6<z<2.6

We report on the gas-phase metallicity gradients of a sample of 238 star-forming galaxies at 0.6 < z < 2.6, measured through deep near-infrared Hubble Space Telescope slitless spectroscopy. The observations include 12 orbit depth Hubble/WFC3 G102 grism spectra taken as a part of the CANDELS Lyα Emission at Reionization (CLEAR) survey, and archival WFC3 G102+G141 grism spectra overlapping the CLEAR footprint. The majority of galaxies in this sample are consistent with having a zero or slightly positive metallicity gradient ( dZ/dR ≥ 0, i.e., increasing with radius) across the full mass range probed (8.5 < log M * / M ⊙ < 10.5). We measure the intrinsic population scatter of the metallicity gradients, and show that it increases with decreasing stellar mass—consistent with previous reports in the literature, but confirmed here with a much larger sample. To understand the physical mechanisms governing this scatter, we search for correlations between the observed gradient and various stellar population properties at fixed mass. However, we find no evidence for a correlation with the galaxy properties we consider—including star formation rates, sizes, star formation rate surface densities, and star formation rates per gravitational potential energy. We use the observed weakness of these correlations to provide material constraints for predicted intrinsic correlations from theoretical models.

Raymond C. Simons↗
NASA NTRSDate not supplied

Aviary: An Open-Source Multidisciplinary Design, Analysis, and Optimization Tool for Modeling Aircraft with Analytic Gradients

In recent years demands on aircraft design methods have begun to require higher degrees of coupling between disciplines and optimization in order to satisfy competing objectives involving large numbers of design parameters that define unconventional configurations. These expanding requirements have amplified a need for new and improved aircraft design, analysis, and optimization codes that are capable of performing coupled design and exploiting analytic gradients to perform gradient-based optimization where possible. To address this need, a new multidisciplinary design optimization and analysis tool called Aviary is presented. This tool, built on OpenMDAO, allows for tightly coupled, simultaneous aircraft and subsystem design using analytic gradients. Aviary includes methods from two NASA developed legacy aircraft analysis tools and provides native analytically differentiated calculations for five different disciplines (weights and sizing, aerodynamics, geometry, propulsion, and mission analysis), while also allowing external discipline analysis tools to be coupled, regardless of whether those tools can provide analytic gradients. Verification and preliminary examples and modeling efforts show Aviary’s ability to effectively model novel concepts and explore large and non-intuitive design spaces. Additionally, a multi-level user interface in Aviary creates an easy entry point for users with any level of multidisciplinary design, analysis, and optimization experience.

optimization↗
DOE OSTI2022

Compact high gradient ion accelerating structure

A high gradient linear accelerating structure can propagate high frequency waves at a negative harmonic to accelerate low-energy ions. The linear accelerating structure can provide a gradient of 50 MV/m for particles at a β of between 0.3 and 0.4. The high gradient structure can be a part of a linear accelerator configured to provide an energy range from an ion source to 450 MeV/u for 12 C 6+ and 250 MeV for protons. The linear accelerator can include one or more of the following sections: a radiofrequency quadrupole (RFQ) accelerator operating at the sub-harmonic of the S-band frequency, a high gradient structure for the energy range from ˜45 MeV/u to ˜450 MeV/u.

Kutsaev, Sergey↗
DOE OSTI2022

Study of effect of PWR cold leg temperature gradient on reactor core condition

Effects of temperature and flow gradients in Westinghouse designed three-loop Pressurized Water Reactor (PWR) cold legs, the piping between the main coolant pump and the reactor vessel, were evaluated using Computational Fluid Dynamics (CFD) code STAR CCM+ and coupled neutronic and thermal-hydraulic (T/H) code system VERA. In the parametric study, several symmetric and asymmetric temperature gradients that were significantly larger than those observed from plant measurements were applied to the cold leg inlets for comparison with the base case without any temperature gradient. A CFD model using the STAR-CCM+ code was developed for a portion of the RCS region between the Reactor Coolant Pump (RCP) and the core inlet based on previously validated modeling approach. The CFD simulation results were processed for the temperature and flow rate distributions at the core inlet as input to the VERA calculations. The VERA code system consists of COBRA-TF (CTF) for thermal-hydraulics, MPACT for reactor physics and neutron transport, and ORIGEN for isotopic depletion. The VERA model was for depletion calculations of a high-burnup loading pattern with the reactor core in pin-by-pin and subchannel resolution. The results of the study indicate that the postulated temperature gradients within the PWR cold legs do not result in any significant changes in the core inlet temperature distributions and the core power distributions during the reactor operation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗
DOE OSTI2023

Training material models using gradient descent algorithms

High temperature design requires accurate constitutive models to describe material inelastic deformation and failure behavior. Oftentimes, calibrating accurate models devolves into the problem of fitting the model parameters against experimental test data. Here, we present the pyopmat package, an open source framework for calibrating constitutive models against experiment data subjected to various loading conditions using machine learning techniques. The package calculates the exact gradient of the model response with respect to the parameters using a combination of automatic differentiation and the adjoint method. Given this exact gradient, we compare the performance of several gradient-based optimization techniques in fitting realistic constitutive models against data. Here, we demonstrate the efficiency and accuracy of our package through example problems using both synthetic data, generated using known parameter sets, under monotonic and cyclic loading conditions and also with an example applying the techniques developed here to actual high temperature creep-fatigue test data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A unified finite strain gradient-enhanced micropolar continuum approach for modeling quasi-brittle failure of cohesive-frictional materials

Here, in this work, a novel framework for modeling quasi-brittle crack propagation and shear band dominated failure of cohesive-frictional materials like concrete, mortar, rock, tough ceramics, energetic materials, but also granular materials like sands or powders in terms of a unified continuum approach is proposed. It is based on a combination of the gradient-enhanced continuum with gradients of internal variables for representing quasi-brittle cracking, and the micropolar continuum, accounting for the deformation of the microstructure. For developing the gradient-enhanced micropolar framework, the set of balance equations and the kinematic relations are derived, and the constitutive relations are established in a general manner. The framework is formulated in a geometrically exact setting, based on the thermodynamically sound theory of hyperelasto-plasticity, and the numerical implementation by means of the finite element method is discussed. For assessing the approach, realizations of this new approach in terms of constitutive models for particular materials are developed. They are applied to numerical benchmark examples, investigating various loading conditions, and the obtained results are validated by means of a comparison with experiments from the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An adaptive Hessian approximated stochastic gradient MCMC method

Bayesian approaches have been successfully integrated into training deep neural networks. One popular family is stochastic gradient Markov chain Monte Carlo methods (SG-MCMC), which have gained increasing interest due to their ability to handle large datasets and the potential to avoid overfitting. Although standard SG-MCMC methods have shown great performance in a variety of problems, they may be inefficient when the random variables in the target posterior densities have scale differences or are highly correlated. Here, we present an adaptive Hessian approximated stochastic gradient MCMC method to incorporate local geometric information while sampling from the posterior. The idea is to apply stochastic approximation (SA) to sequentially update a preconditioning matrix at each iteration. The preconditioner possesses second-order information and can guide the random walk of a sampler efficiently. Instead of computing and saving the full Hessian of the log posterior, we use limited memory of the samples and their stochastic gradients to approximate the inverse Hessian-vector multiplication in the updating formula. Moreover, by smoothly optimizing the preconditioning matrix via SA, our proposed algorithm can asymptotically converge to the target distribution with a controllable bias under mild conditions. To reduce the training and testing computational burden, we adopt a magnitude-based weight pruning method to enforce the sparsity of the network. Our method is user-friendly and demonstrates better learning results compared to standard SG-MCMC updating rules. The approximation of inverse Hessian alleviates storage and computational complexities for large dimensional models. Numerical experiments are performed on several problems, including sampling from 2D correlated distribution, synthetic regression problems, and learning the numerical solutions of heterogeneous elliptic PDE. The numerical results demonstrate great improvement in both the convergence rate and accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Radiation-induced bowing of SiC/SiC composites under neutron flux gradients—integral experimental data for model validation

Here, the radiation-induced swelling of SiC and its composites, including strong dependencies on temperature and dose, can drive significant lateral bowing in the presence of temperature and/or dose gradients. In recent years, simulations have been performed to assess the extent of bowing in SiC composite light-water reactor (LWR) fuel cladding and boiling water reactor (BWR) channel boxes. However, to date, no integral experimental data exist to validate these models. This work provides the first experimental bowing evaluation of three ∼380 mm long SiC composite specimens irradiated under varying neutron dose gradients (∼50°C–60°C, 0.03–0.06 dpa): two tubes (∼9.8 mm diameter) and a miniature BWR channel box (∼30 mm square). The measured radiation-induced length swelling (∼0.3%–0.7% linear) was consistently 10%–21% higher than values obtained from 3D finite element structural analyses with inputs from 3D radiation transport calculations. This discrepancy could be at least partially explained by differences in dose rate (∼10 -8 dpa/s) compared to the literature data (∼10-6 dpa/s) used to establish the dose-to-swelling correlations in the model. Nevertheless, the modeled bowing magnitudes (<2 mm) obtained from finite element analyses and simple analytical equations were within the bounds of the experimental measurements for all specimens. With improved confidence in the ability to predict the structural response and measure the macroscopic deformations, future experiments will target transient bowing under neutron flux gradients at representative LWR temperatures and assess whether grid spacers can mitigate the tens of millimeters of bowing that would otherwise be expected in ∼4 m long LWR components.

bowing↗
DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗
DOE OSTI2022

Low-Tortuosity Thick Electrodes with Active Materials Gradient Design for Enhanced Energy Storage

The ever-growing energy demand of modern society calls for the development of high-loading and high-energy-density batteries, and substantial research efforts are required to optimize electrode microstructures for improved energy storage. Low-tortuosity architecture proves effective in promoting charge transport kinetics in thick electrodes; however, heterogeneous electrochemical mass transport along the depth direction is inevitable, especially at high C-rates. In this work, we create an active material gradient in low-tortuosity electrodes along ion-transport direction to compensate for uneven reaction kinetics and the nonuniform lithiation/delithiation process in thick electrodes. The gradual decrease of active material concentration from the separator to the current collector reduces the integrated ion diffusion distance and accelerates the electrochemical reaction kinetics, leading to improved rate capabilities. Further, the structure advantages combining low-tortuosity pores and active material gradient offer high mass loading (60 mg cm –2 ) and enhanced performance. Comprehensive understanding of the effect of active material gradient architecture on electrode kinetics has been elucidated by electrochemical characterization and simulations, which can be useful for development of batteries with high-energy/power densities.

25 ENERGY STORAGE↗
DOE OSTI2022

20%-efficient polycrystalline Cd(Se,Te) thin-film solar cells with compositional gradient near the front junction

Bandgap gradient is a proven approach for improving the open-circuit voltages (V OC s) in Cu(In,Ga)Se 2 and Cu(Zn,Sn)Se 2 thin-film solar cells, but has not been realized in Cd(Se,Te) thin-film solar cells, a leading thin-film solar cell technology in the photovoltaic market. Here, we demonstrate the realization of a bandgap gradient in Cd(Se,Te) thin-film solar cells by introducing a Cd(O,S,Se,Te) region with the same crystal structure of the absorber near the front junction. The formation of such a region is enabled by incorporating oxygenated CdS and CdSe layers. We show that the introduction of the bandgap gradient reduces the hole density in the front junction region and introduces a small spike in the band alignment between this and the absorber regions, effectively suppressing the nonradiative recombination therein and leading to improved VOCs in Cd(Se,Te) solar cells using commercial SnO 2 buffers. A champion device achieves an efficiency of 20.03% with a V OC of 0.863 V.

14 SOLAR ENERGY↗
DOE OSTI2021

New understanding of inter-ELM pedestal turbulence, transport, and gradient behavior in the DIII-D tokamak

New observations of pedestal localized turbulence in the inter-ELM period of H-mode plasmas in DIII-D show that ion temperature gradient mode scale (ITG-scale) density fluctuation (ñ) increases immediately after each ELM crash and is quickly suppressed during the increase in local E × B shear. This excitation and subsequent suppression of ITG-scale ñ can explain the previously reported anomalous ion heat flux, Qi during the ELM (Viezzer et al 2017 Nucl. Fusion 57 022020). Shorter wavelength trapped electron mode scale (TEM-scale) ñ starts to increase at a critical pedestal temperature gradient (∇Te,ped) and saturates as local E × B shear, ${T}_{\mathrm{i}}^{\mathrm{C}\mathrm{6}+}/{T}_{\mathrm{e}}$ ratio, and ∇Te,ped saturate. This TEM-scale ñ, which has the potential to cause electron (and also ion) heat transport, is consistent with driving an anomalous electron heat flux Qe, where Qe is estimated between ELMs using experimental profiles and power balance. Both ITG- and TEM-scale ñ amplitude variations with background Ti/Te and ∇ne,ped are found to be consistent with theoretical predictions of these measured density fluctuations being ITG and TEM instabilities respectively. Furthermore, these new and unique observations on the nature of turbulence and their potential contributions to electron and ion heat fluxes at different ELM periods (i.e. collapse, recovery, and saturation phases of pedestal gradients) can significantly test and improve our pedestal predictive capabilities for ITER and other future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗