Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamics”

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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Saether, Erik↗
NASA NTRS2021

Computational Fluid Dynamics Simulations of the Transonic Dynamics Tunnel Airstream Oscillator System

This paper presents computational fluid dynamics simulations of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with the airstream oscillator system (AOS) in operation. Test section flow angle can be modulated using sinusoidally oscillating vanes which are located in pairs within the contraction section of the tunnel circuit. A compilation of previously published experimental data for validation has been reviewed that contains hot-wire anemometer and fast-response probe data acquired in an empty test section with the vanes oscillating in-phase and out-of-phase. These experimental data have not previously been compared with computational results. The present results provide an opportunity for validation of the simulations of the sinusoidal AOS flow field in the TDT test section. Computed tunnel centerline, lateral and cross-section contour data of flow angle and vorticity show that resolving the vane tip vortex is critical to accurately predicting the test section center flow angle. The computed results show, as do the experimental data, what appears to be a resonance at higher frequencies. It is currently not known what is the cause of that resonance. Further refinement of the mesh is expected to improve the comparisons with experimental data

Robert E Bartels↗
NASA NTRSDate not supplied

Differential Dynamic Microscopy: A Novel Approach for Dynamics and Micro-rheology of Active Soft Matter

Differential dynamic microscopy (DDM) is a highly sensitive and cost-effective technique for studying the dynamics and micro-rheology of active soft matter in real time and at high resolution. In this work, we extend the capabilities of DDM, notably its size, to suit to space research and overcome challenges such as the environmental limited resources (e.g. Artemis, ISS, Cube sat, etc.).

Amine Missaoui↗
DOE OSTI2020

System and method for modeling and forecasting cyclical demand systems with dynamic controls and dynamic incentives

Systems and methods for modeling and forecasting cyclical demand systems in the presence of dynamic control or dynamic incentives. A method for modeling a cyclical demand system comprises obtaining historical data on one or more demand measurements over a plurality of demand cycles, obtaining historical data on incentive signals over the plurality of demand cycles, constructing a model using the obtained historical data on the one or more demand measurements and the incentive signals, wherein constructing the model comprises specifying a state-space model, specifying variance parameters in the model, and estimating unknown variance parameters.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Dynamic signature generation from keystroke dynamics

Described herein are various technologies pertaining to extracting cryptographic keys from user behavioral biometrics, specifically keystroke dynamics. Such cryptographic keys can be used for, among other things, user authentication throughout computer sessions. Keystroke dynamics are timing data indicating when keys were pressed and when they were released.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Modeling of threshold and dynamics behavior of organic nanostructured lasers

Organic dye molecules offer significant potential as gain media in the emerging field of optical amplification and lasing at subwavelength scales. In this article, we investigate the laser dynamics in systems comprising subwavelength-structured cavities that incorporate organic dyes. To this end, we have developed a comprehensive theoretical framework able to accurately describe the interaction of organic molecules with any arbitrary photonic structure to produce single-mode lasing. The model provides explicit analytic expressions of the threshold and slope efficiency that characterize this class of lasers, and also the duration over which lasing action can be sustained before the dye photobleaches. Both the physical properties of the dyes and the optical properties of the cavities are considered. We also systematically studied the feasibility of achieving lasing action under continuous-wave excitation in optically pumped monolithic organic dye lasers. This study suggests routes to realize an organic laser that can potentially lase with a threshold of only a few W cm -2 . In conclusion, our work puts forward a theoretical formalism that could enable the advancement of nanostructured organic-based light emitting and sensing devices.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Effects of boron-nitride substrates on Stone-Wales defect formation in graphene: An ab initio molecular dynamics study

Ab initio molecular dynamics simulations are performed to investigate the effects of a boron nitride (BN) substrate on Stone-Wales (SW) defect formation and recovery in graphene. It is found that SW defects can be created by an off-plane recoil atom that interacts with the BN substrate. A mechanism with complete bond breakage for formation of SW defects in suspended graphene is also revealed for recoils at large displacement angles. In addition, further irradiation can result in recovery of the SW defects through a bond rotation mechanism in both graphene and graphene/BN, and the substrate has little effect on the recovery process. This study indicates that the BN substrate enhances the irradiation resistance of graphene.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Thermal Interface Conductance Between Aluminum and Silicon by Molecular Dynamics Simulations

The thermal interface conductance between Al and Si was simulated by a non-equilibrium molecular dynamics method. In the simulations, the coupling between electrons and phonons in Al are considered by using a stochastic force. The findings demonstrate the size dependence of the interface thermal conductance and the effect of electron–phonon coupling on the interface thermal conductance. To understand the mechanism of interface resistance, the vibration power spectra are calculated. We postulate that the atomic level disorder near the interface is an important aspect of interfacial phonon transport, which leads to a modification of the phonon states near the interface. There, the vibrational spectrum near the interface greatly differs from the bulk. This change in the vibrational spectrum affects the results predicted by AMM and DMM theories and indicates new physics is involved with phonon transport across interfaces.

42 ENGINEERING↗
DOE OSTI2015

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models. Current status and future directions

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and loss from soil accounts for a large pro portion of land-atmosphere C exchange. Due to large pool size and variable residence time from years to millennia, even small changes in soil organic C(SOC) have substantial effects on the terrestrial C budget, thereby affecting atmospheric carbon dioxide (CO2)concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain and identifying major driving forces controlling soil C storage and fluxes remains a key research challenge his study has compiled century-long (1901-2010)estimates of SOC storage and heterotrophic respiration (Rh) from ten terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) and two observation based datasets. The ten-TBM ensemble shows that global SOC estimate range from 4 to 2111 Pg C (1 Pg = 10 15 g) with a median value of 1158 Pg C33 in 2010. Modeling approach estimates a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51Pg C yr -1 during 200–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude band while Rh differences are the largest in the tropics. All the models agreed that climate and land use changes have decreased SOC stocks while elevated CO 2 and atmospheric nitrogen deposition have increased SOC stocks though the response varied significantly among models. Model representations of temperature and moisture sensitivity,nutrient limitation and land use partially explain the divergent estimates of global SOC stocks and soil fluxes in this study. In addition, major sources of uncertainty from model estimation include exclusion of SOC storage in wetlands and peatlands as well as C storage in deep soil layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Intramolecular Hydrogen Bonding Restricts Gd-Aqua-Ligand Dynamics [The Day the Water Stood Still: Intramolecular Hydrogen Bonding to Restrict Gd-Aqua Ligand Dynamics]

Aqua ligands can undergo rapid internal rotation about the M-O bond. For magnetic resonance contrast agents, this rotation results in diminished relaxivity. Herein, we show that an intramolecular hydrogen bond to the aqua ligand can reduce this internal rotation and increase relaxivity. Molecular modeling was used to design a series of four Gd complexes capable of forming an intramolecular H-bond to the coordinated water ligand, and these complexes had anomalously high relaxivities compared to similar complexes lacking a H-bond acceptor. Molecular dynamics simulations supported the formation of a stable intramolecular H-bond, while alternative hypotheses that could explain the higher relaxivity were systematically ruled out. Finally, intramolecular H-bonding represents a useful strategy to limit internal water rotational motion and increase relaxivity of Gd complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Interface and embedded joint methods for modeling dynamic fracture opening by explosive products [Two methods for modeling dynamic fracture opening by explosive products]

Two computational approaches are proposed in the paper to model dynamic fracture opening by explosive products. The first method assumes that the fractures may be modeled using flow elements embedded along the mesh lines. This method models crack opening in a straightforward way by splitting the nodes of the computational grid. It can account for crack branching; however, the crack directions are constrained by existing mesh faces, which may lead to mesh dependence. Also, the stress in flow elements is calculated explicitly separate from the surrounding solid elements that can impose additional limits on the time step stability condition for explicit integration. The second approach uses embedded flow elements to model the cracks. Typical thickness of the cracks is much smaller than the element size. Therefore, gas pressure in the cracks is assumed to be in stress equilibrium with the element stress. To achieve this, the crack thickness and the state of the gas is updated simultaneously with the state of the solid element which contains the crack. Therefore, the time step is controlled by the explicit solver applied for the solid and does not depend on the thickness of the crack. In conclusion, the main disadvantage of the second approach is due to the complexity of modeling multiple intersecting cracks, which go through the same element. We discuss the areas of possible applications of these 2 methods and the ways to improve and enhance them for future practical applications.

58 GEOSCIENCES↗
DOE OSTI2017

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed by simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.

97 MATHEMATICS AND COMPUTING↗