Search NASA⌕ Search

SEARCH · Search NASA

Results for “physical modification”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A parametric SPICE model for the simulation of spark gap switches

The use of SPICE-based software for the simulation of pulsed power systems—even large complex systems—has become commonplace in the pulsed power community. This is in contrast to earlier work in the field that relied on specially developed simulation codes such as Sandia’s Screamer or the Navy Research Lab’s Bertha, which natively incorporated models for common pulsed power components such as spark gap switches. Unlike these programs, SPICE programs provide a simple and familiar user interface and wide availability. However, SPICE programs do not include realistic models for key pulsed power circuit devices—including the spark gap switch. While simple switch models do exist in SPICE programs, these can only crudely approximate the behavior of a spark gap. This effort focuses on developing an SPICE circuit model for a gas-filled spark gap switch that is physically realistic while being simple enough to permit simulations to run in reasonable times on typical personal computers. Detailed information is provided for implementation in two common versions of SPICE: LTspice and Orcad PSPICE. Adaptation to other SPICE programs is possible with minimal modification. The model is intended as a design tool that uses physical parameters as inputs to connect it directly to the development of useable pulsed power systems. Data collected from the operation of a high-pressure pulsed-charged switch and a complete 12-stage Marx generator have been used to demonstrate the implementation and accuracy of the model over a wide range of parameters.

Pouncey, J. Cameron (ORCID:0000000153500816)↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Application of mesh refinement to relativistic magnetic reconnection

During relativistic magnetic reconnection, antiparallel magnetic fields undergo a rapid change in topology, releasing a large amount of energy in the form of non-thermal particle acceleration. This work explores the application of mesh refinement to 2D reconnection simulations to efficiently model the inherent disparity in length-scales. We have systematically investigated the effects of mesh refinement and determined necessary modifications to the algorithm required to mitigate non-physical artifacts at the coarse–fine interface. We have used the ultrahigh-order pseudo-spectral analytical time-domain Maxwell solver to analyze how its use can mitigate the numerical dispersion that occurs with the finite-difference time-domain (or “Yee”) method. Absorbing layers are introduced at the coarse–fine interface to eliminate spurious effects that occur with mesh refinement. We also study how damping the electromagnetic fields and current density in the absorbing layer can help prevent the non-physical accumulation of charge and current density at the coarse–fine interface. Using a mesh refinement ratio of 8 for two-dimensional magnetic reconnection simulations, we obtained good agreement with the high-resolution baseline simulation, using only 36% of the macroparticles and 71% of the node-hours needed for the baseline. The methods presented here are especially applicable to 3D systems where higher memory savings are expected than in 2D, enabling comprehensive, computationally efficient 3D reconnection studies in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1)

Abstract. The Community Atmosphere Model (CAM6.1), the atmospheric component of the Community Earth System Model (CESM; version 2.1), simulates the life cycle (emission, transport, and deposition) of mineral dust and its interactions with physio-chemical components to quantify the impacts of dust on climate and the Earth system. The accuracy of such quantifications relies on how well dust-related processes are represented in the model. Here we update the parameterizations for the dust module, including those on the dust emission scheme, the aerosol dry deposition scheme, the size distribution of transported dust, and the treatment of dust particle shape. Multiple simulations were undertaken to evaluate the model performance against diverse observations, and to understand how each update alters the modeled dust cycle and the simulated dust direct radiative effect. The model–observation comparisons suggest that substantially improved model representations of the dust cycle are achieved primarily through the new more physically-based dust emission scheme. In comparison, the other modifications induced small changes to the modeled dust cycle and model–observation comparisons, except the size distribution of dust in the coarse mode, which can be even more influential than that of replacing the dust emission scheme. We highlight which changes introduced here are important for which regions, shedding light on further dust model developments required for more accurately estimating interactions between dust and climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Downscaling atmospheric chemistry simulations with physically consistent deep learning

Abstract. Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrates the downscaling capabilities of modern CNN-based single image super resolution and video super-resolution schemes and develops modifications to these schemes to ensure they are appropriate for use with physical science data. The CNN-based video super-resolution schemes in particular incur only 39 % to 54 % of the grid-cell-level error of interpolation schemes and generate outputs with extremely realistic small-scale variability based on multiple perceptual quality metrics while performing a large (8×10) increase in resolution in the spatial dimensions. Methods are introduced to strictly enforce physical conservation laws within CNNs, perform large and asymmetric resolution changes between common model grid resolutions, account for non-uniform grid-cell areas, super-resolve lognormally distributed datasets, and leverage additional inputs such as high-resolution climatologies and model state variables. High-resolution chemistry simulations are critical for modeling regional air quality and for understanding future climate, and CNN-based downscaling has the potential to generate these high-resolution simulations and ensembles at a fraction of the computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Jacobian-scaled K-means clustering for physics-informed segmentation of reacting flows

This work introduces Jacobian-scaled K-means (JSK-means) clustering, which is a physicsinformed clustering strategy centered on the K-means framework. The method allows for the injection of underlying physical knowledge into the clustering procedure through a distance function modification: instead of leveraging conventional Euclidean distance vectors, the JSKmeans procedure operates on distance vectors scaled by matrices obtained from dynamical system Jacobians evaluated at the cluster centroids. The goal of this work is to show how the JSKmeans algorithm - without modifying the input dataset - produces clusters that capture regions of dynamical similarity, in that the clusters are redistributed towards high-sensitivity regions in phase space and are described by similarity in the source terms of samples instead of the samples themselves. The algorithm is demonstrated on a complex reacting flow simulation dataset (a channel detonation configuration), where the dynamics in the thermochemical composition space are known through the highly nonlinear and stiff Arrhenius-based chemical source terms. Interpretations of cluster partitions in both physical space and composition space reveal how JSK-means shifts clusters produced by standard K-means towards regions of high chemical sensitivity (e.g., towards regions of peak heat release rate near the detonation reaction zone). Furthermore, the findings presented here illustrate the benefits of utilizing Jacobian-scaled distances in clustering techniques, and the JSK-means method in particular displays promising potential for improving former partition-based modeling strategies in reacting flow (and other multi-physics) applications.

Clustering↗
DOE OSTI2026

A Material Frame: Hard Recoils from Slow Force Carriers

We modify the Standard Model by making the longitudinal component of the photon physical, propagating with small speed $c_L \ll 1$. This modification breaks gauge invariance and Lorentz symmetry, defining a preferred reference frame. No new fields or scales are introduced, and the photon mass is protected by a Galilean higher-form symmetry. The theory has a smooth $c_L\to0$ limit: the new modes decouple from standard matter and ordinary gauge theory predictions are recovered. Experimental constraints are severe. Charged particles Cherenkov-emit these slow modes, experiencing hard recoils against the preferred frame. The recoil rate decreases with $c_L$, but the momentum transfer remains of the order of the particle's momentum. Dark matter detectors, sensitive to keV-scale nuclear recoils, imply an order-of-magnitude bound $c_L \lesssim 10^{-60}$, tens of orders of magnitude stronger than speed-difference bounds. At such values, $c_L$ is better understood as a recoil-rate factor rather than a physically relevant speed. The slow modes, practically fixed in space, make the reference frame a material medium capable of absorbing momentum from charged particles.

Serra, Francesco [Johns Hopkins U.]↗
DOE OSTI2024

Respecting causality for training physics-informed neural networks

While the popularity of physics-informed neural networks (PINNs) is steadily rising, to this date PINNs have not been successful in simulating dynamical systems whose solution exhibits multi-scale, chaotic or turbulent behavior. In this work we attribute this shortcoming to the inability of existing PINNs formulations to respect the spatio-temporal causal structure that is inherent to the evolution of physical systems. We argue that this is a fundamental limitation and a key source of error that can ultimately steer PINN models to converge towards erroneous solutions. We address this pathology by proposing a simple re-formulation of PINNs loss functions that can explicitly account for physical causality during model training. We demonstrate that this simple modification alone is enough to introduce significant accuracy improvements, as well as a practical quantitative mechanism for assessing the convergence of a PINNs model. Here we provide state-of-the-art numerical results across a series of benchmarks for which existing PINNs formulations fail, including the chaotic Lorenz system, the Kuramoto–Sivashinsky equation in the chaotic regime, and the Navier–Stokes equations. To the best of our knowledge, this is the first time that PINNs have been successful in simulating such systems, introducing new opportunities for their applicability to problems of industrial complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Radius and equation of state constraints from massive neutron stars and GW190814

Motivated by the unknown nature of the 2.50–2.67M⊙ compact object in the binary merger event GW190814, we study the maximum neutron star mass based on constraints from low-energy nuclear physics, neutron star tidal deformabilities from GW170817, and simultaneous mass-radius measurements of PSR J0030+045 from NICER. Our prior distribution is based on a combination of nuclear modeling valid in the vicinity of normal nuclear densities together with the assumption of a maximally stiff equation of state at high densities, a choice that enables us to probe the connection between observed heavy neutron stars and the transition density at which conventional nuclear physics models must break down. Here we demonstrate that a modification of the highly uncertain suprasaturation density equation of state beyond 2.64 times normal nuclear density is required in order for chiral effective field theory models to be consistent with current neutron star observations and the existence of 2.6M⊙ neutron stars. We also show that the existence of very massive neutron stars strongly impacts the radii of ≈ 2.0M⊙ neutron stars (but not necessarily the radii of 1.4 M⊙ neutron stars), which further motivates future NICER radius measurements of PSR J1614 – 2230 and PSR J0740+6620.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Using Al 3+ to Tailor Graphene Oxide Nanochannels: Impact on Membrane Stability and Permeability

Graphene oxide (GO) membranes, which form from the lamination of GO sheets, attract much attention due to their unique nanochannels. There is much interest in controlling the nanochannel structures and improving the aqueous stability of GO membranes so they can be effectively used in separation and filtration applications. This study employed a simple yet effective method of introducing trivalent aluminum cations to a GO sheet solution through the oxidation of aluminum foil, which modifies the nanochannels in the self-assembled GO membrane by increasing the inter-sheet distance while decreasing intra-sheet spacing. The Al 3+ modification resulted in an increase in membrane stability in water, methanol, ethanol, and propanol, yet decreased membrane permeability to water and propanol. These changes were attributed to strong interactions between Al 3+ and the membrane oxygenated functional groups, which resulted in an increase in membrane hydrophobicity and a decrease in the intra-sheet spacing as supported by surface tension, contact angle, atomic force microscopy, and X-ray photoelectron spectroscopy measurements. Our approach for forming Al 3+ modified GO membranes provides a method for improving the aqueous stability and tailoring the permeation selectivity of GO membranes, which have the potential to be implemented in vapor separation and fuel purification applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Organic Modifiers Promote Furfuryl Alcohol Ring Hydrogenation via Surface Hydrogen-Bonding Interactions

Interactions between surface adsorbed species can affect catalyst reactivity, and thus, the ability to tune these interactions is of considerable importance. Deposition of organic modifiers provides one method of intentionally introducing controllable surface interactions onto catalyst surfaces. In this study, Pd/Al2O 3 catalysts were modified with either thiol or phosphonic acid (PA) ligands and tested in the hydrogenation of furanic species. The thiol modifiers were found to inhibit ring hydrogenation (RH) activity, with the degree of inhibition trending with the thiol surface coverage. This suggests that thiols do not strongly interact with the reactants and simply serve to block active sites on the Pd surface. PAs, on the other hand, were found to enhance RH when furfuryl alcohol (FA) was used as the reactant. Density functional theory calculations suggested that this enhancement was due to hydrogen-bonding interactions between FA-derived surface intermediates and PA modifiers. Here, installation of hydrogen-bonding groups on the Pd surface served to preferentially stabilize RH product states. Furthermore, the promotional effect on the RH of FA was observed to be greater when a higher-coverage PA was used, providing a rate more than twice that of the unmodified Pd/Al2O 3 . The results of this work suggest that organic ligands can be designed to impart tunable surface interactions on heterogeneous catalysts, providing an additional method of controlling catalytic performance.

09 BIOMASS FUELS↗
DOE OSTI2024

Transverse energy-energy correlators in the color-glass condensate at the electron-ion collider

We investigate the transverse energy-energy correlators (TEEC) in the small- x regime at the upcoming Electron-Ion Collider (EIC). Focusing on the back-to-back production of electron-hadron pairs in both e p and e A collisions, we establish a factorization formula given in terms of the hard function, quark distributions, soft functions, and TEEC jet functions, where the gluon saturation effect is incorporated. Numerical results for TEEC in both e p and e A collisions are presented, together with the nuclear modification factor R A . Our analysis reveals that TEEC observables in deep inelastic scattering provide a valuable approach for probing gluon saturation phenomena. Our findings underscore the significance of measuring TEEC at the EIC, emphasizing its efficacy in advancing our understanding of gluon saturation and nuclear modifications in high-energy collisions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2022

Modeling electrokinetic flows with the discrete ion stochastic continuum overdamped solvent algorithm

In this article we develop an algorithm for the efficient simulation of electrolytes in the presence of physical boundaries. In previous work the discrete ion stochastic continuum overdamped solvent (DISCOS) algorithm was derived for triply periodic domains, and was validated through ion-ion pair correlation functions and Debye-Hückel-Onsager theory for conductivity, including the Wien effect for strong electric fields. In extending this approach to include an accurate treatment of physical boundaries we must address several important issues. First, the modifications to the spreading and interpolation operators necessary to incorporate interactions of the ions with the boundary are described. Next we discuss the modifications to the electrostatic solver to handle the influence of charges near either a fixed potential or dielectric boundary. An additional short-ranged potential is also introduced to represent interaction of the ions with a solid wall. Finally, the dry diffusion term is modified to account for the reduced mobility of ions near a boundary, which introduces an additional stochastic drift correction. Herein, several validation tests are presented confirming the correct equilibrium distribution of ions in a channel. Additionally, the methodology is demonstrated using electro-osmosis and induced-charge electro-osmosis, with comparison made to theory and other numerical methods. Notably, the DISCOS approach achieves greater accuracy than a continuum electrostatic simulation method. We also examine the effect of under-resolving hydrodynamic effects using a “dry diffusion” approach, and find that considerable computational speedup can be achieved with a negligible impact on accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Solar Modeling and Opacities

In 2004, improved analyses of solar spectra resulted in a downward revision of the abundances of elements heavier than hydrogen and helium, in particular, the elements C, N, and O. Solar models evolved using these lower abundances showed discrepancies with inferences from solar oscillation observations (helioseismology). This problem has not been solved satisfactorily in the intervening 16 years. How serious/important is this problem? This talk will give an overview of how standard solar models are calculated and of the constraints from helioseismology. The talk will also present results of some attempts to change input physics or assumptions in the standard solar model, including opacity modifications, to try to resolve the discrepancies. I would like to have a discussion with the participants after the talk about which directions appear most promising to resolve the problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Design Enhancements for the SNS RFQ Coaxial Coupler

The H⁻ ion linear accelerator at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory operates with reliability that routinely surpasses 90% during scheduled beam operation. With the ambitious goal of eventually achieving at least 95% availability, several upgrade and improvement projects are ongoing. One such project is the modification of the coaxial couplers that transfer radio frequency (RF) power to the accelerator’s Radio Frequency Quadrupole (RFQ). The proposed modification utilizes stub sections and capacitive coupling to construct a physically separable assembly with DC isolation. With a separated coupler assembly, the section that includes the magnetic coupling loop can be permanently mounted to the RFQ which would eliminate the need to re-adjust the couplers after maintenance activities, upgrades, and repairs. Additionally, the modified design would provide increased multipaction suppression with DC biasing and potentially lower thermal gradients across the device. This paper presents the design and simulation results of the project.

Toby, George↗
DOE OSTI2022

OC6 phase I: Improvements to the OpenFAST predictions of nonlinear, low-frequency responses of a floating offshore wind turbine platform

We report in the OC5 and OC6 projects, the authors observed a persistent underprediction of the nonlinear, low-frequency responses of an offshore wind semisubmersible with many mid-fidelity engineering models, including the OpenFAST tool developed by the National Renewable Energy Laboratory. Both the low-frequency wave excitation in surge and pitch and the resulting resonance motions were severely underpredicted. In response, we developed several modifications to the OpenFAST model from the OC5/6 projects to improve the predictions of the low-frequency wave loads and responses. All modifications are in the modeling of the viscous drag forces. Efforts were made to provide physical justifications to the changes and to limit the number of additional parameters requiring tuning, so that the modified model can be applied to other floating wind systems. With the proposed modifications, the predictions of the low-frequency surge and pitch wave loads on a fixed floater and the resonance responses of a floating structure are both significantly improved with a single set of model coefficients, which leads to good agreement with the measurements from the OC6 wave-basin experimental campaign.

17 WIND ENERGY↗
DOE OSTI2022

Biochar Nanocomposite as an Inexpensive and Highly Efficient Carbonaceous Adsorbent for Hexavalent Chromium Removal

Biochar is commonly used for soil amendment, due to its excellent water-holding capacity. The Cr(VI) contamination of water is a current environmental issue in industrial regions. Here, we evaluated the effects of two-step modifications on boosting biochar’s performance in terms of the removal of aqueous hexavalent chromium (Cr(VI)), along with investigating the alterations to its surface properties. The first modification step was heat treatment under air at 300 °C, producing hydrophilic biochar (HBC). The resulting HBC was then impregnated with zero-valent iron nanoparticles (nZVI), creating an HBC/nZVI composite, adding a chemical reduction capability to the physical sorption mechanism. Unmodified biochar (BC), HBC, and HBC/nZVI were characterized for their physicochemical properties, including surface morphology and elemental composition, by SEM/EDS, while functional groups were ascertained by FTIR and surface charge by zeta potential. Cr(VI) removal kinetic studies revealed the four-time greater sorption capacity of HBC than BC. Although unmodified BC showed faster initial Cr(VI) uptake, it rapidly worsened and started desorption. After nZVI impregnation, the Cr(VI) removal rate of HBC increased by a factor of 10. FTIR analysis of biochars after Cr(VI) adsorption showed the presence of Cr(III) oxide only on the used HBC/nZVI and demonstrated that the carbonyl and carboxyl groups were the main groups involved in Cr(VI) sorption. Modified biochars could be considered an economical substitute for conventional methods.

36 MATERIALS SCIENCE↗