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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the bulk rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number RE = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the polymer dynamics, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

Computer Science↗
DOE OSTI2023

Integration of discrete-event dynamics and machining dynamics for machine tool: Modeling, analysis and algorithms

Machining dynamics research lays a solid foundation for machining operations by providing stable combinations of spindle speed and depth of cut. Furthermore, machine learning has been applied to predict tool life as a function of cutting speed. However, the existing research does not consider the discrete-event dynamics in machine shop, i.e., the machine tool needs to process a series of parts in queue under various practical production requirements. This paper addresses the integration of discrete-event dynamics and machining dynamics to achieve cost savings in machining. A learning-based cost function is first proposed for the studied integrated optimization problem of machine tool. The proposed cost function utilizes the predicted tool life under different stable cutting speeds for further optimizing speed selection of machine tool to deal with the discrete-event dynamics in machine shop. Then, according to the practical production requirements, effective mathematical optimization models are developed for the related integrated optimization problems with the consideration of cost, makespan and due date, respectively. Numerical results show the effectiveness of our proposed methods and also the potential to be used in practice.

Ma, Mason↗
DOE OSTI2020

Extracting the Frequency-Dependent Dynamic Stokes Shift from Two-Dimensional Electronic Spectra with Prominent Vibrational Coherences

The dynamic Stokes shift is a common means for characterizing ultrafast solvation dynamics of electronically excited states. Here we extract the excitation frequency-dependent dynamic Stokes shift from two-dimensional electronic spectra (2DES) of cresyl violet, a molecule with a well-defined vibronic progression. The extracted dynamic Stokes shift function, S(t), exhibits oscillatory behavior, and the oscillatory components are assigned to intramolecular vibrational modes through DFT and TD-DFT calculations. Here, the well-characterized oscillations are incorporated into the fitting procedure of S(t). The excitation frequency dependence of the ultrafast response is examined through the analysis of S(t) obtained from slices taken at different excitation frequencies of the 2DES spectra. The extracted ultrafast timescales range from 36 to 98 fs, and we interpret the frequency dependence of the timescales in the context of other dynamic processes that also lead to lineshape changes in the 2DES spectrum, such as vibrational energy relaxation and spectral diffusion. Through comparison of the extracted timescales, we find that the fastest timescales are extracted over a range of excitation frequencies, where contributions from vibrational relaxation and spectral diffusion can be minimized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Solvation and Dynamics of Sodium and Potassium in Ethylene Carbonate from ab Initio Molecular Dynamics Simulations

The development of sodium and potassium batteries offers a promising way to meet the scaling and cost challenges of energy storage. However, compared to Li + , several intrinsic properties of Na + and K + , including their solvation and dynamics in typical organic electrolytes utilized in battery applications, are less well-understood. Here in this paper, we report a systematic investigation of Na + and K + in ethylene carbonate (EC) using first-principles molecular dynamics simulations. Our simulations reveal significant differences in the solvation structure and dynamical properties of Na + and K + compared to Li + . We find that, in contrast to Li + which exhibits a well-defined first solvation shell, the larger Na+ and K+ ions show more disordered and flexible solvation structures. These differences in solvation were found to significantly influence the ion dynamics, leading to larger diffusion coefficients of Na + and K + compared to Li + . Our simulations also reveal a clear and interesting analog in the behavior of the ions in EC and aqueous environments, particularly in the specific ion effects on the solvent dynamics. Lastly, this work provides fundamental understanding of the intrinsic properties of Na + and K + in organic electrolytes, which may ultimately influence the intercalation mechanism at the electrode–electrolyte interface and therefore battery performance, lifetime, and safety.

25 ENERGY STORAGE↗
DOE OSTI2017

Molecular Dynamics Study of CO 2 and H 2 O Intercalation in Smectite Clays: Effect of Temperature and Pressure on Interlayer Structure and Dynamics in Hectorite

Grand Canonical Molecular Dynamics (GCMD) simulations were performed to investigate the intercalation of CO 2 and H 2 O molecules in the interlayers of the smectite clay, Na-hectorite, at temperatures and pressures relevant to petroleum reservoir and geological carbon sequestration conditions and in equilibrium with H 2 O-saturated CO 2 . The computed adsorption isotherms indicate that CO 2 molecules enter the interlayer space of Na-hectorite only when it is hydrated with approximately three H 2 O molecules per unit cell. The computed immersion energies show that the bilayer hydrate structure (2WL) contains less CO 2 than the monolayer structure (1WL) but that the 2WL hydrate is the most thermodynamically stable state, consistent with experimental results for a similar Na-montmorillonite smectite. Under all T and P conditions examined (323–368 K and 90–150 bar), the CO 2 molecules are adsorbed at the midplane of clay interlayers for the 1WL structure and closer to one of the basal surfaces for the 2WL structure. Interlayer CO 2 molecules are dynamically less restricted in the 2WL structures. The CO 2 molecules are preferentially located near basal surface oxygen atoms and H 2 O molecules rather than in coordination with Na+ ions. Accounting for the orientation and flexibility of the structural -OH groups of the clay layer has a significant effect on the details of the computed structure and dynamics of H 2 O and CO 2 molecules but does not affect the overall trends with changing basal spacing or the principal structural and dynamical conclusions. Temperature and pressure in the ranges examined have little effect on the principal structural and energetic conclusions, but the rates of dynamical processes increase with increasing temperature, as expected.

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

Impact of Solution Chemistry and Particle Anistropy on the Collective Dynamics of Oriented Aggregation

Although oriented aggregation of nanoparticles is a widely recognized mechanism of crystal growth, the impact of many fundamental parameters, such as crystallographically distinct interfacial structures, solution composition, and particle-shape-specific hydrodynamic characteristics, on the governing mechanisms and assembly kinetics are largely unexplored. In this context, we investigated the structure and dynamics of boehmite aggregation as a function of solution pH and ionic strength. Cryogenic transmission electron microscopy shows that boehmite platelets assemble by oriented attachment on (010) planes. The coagulation rate constants obtained from dynamic light scattering during the early stages of aggregation are found to span seven orders of magnitude and cross both the reaction-limited and diffusion-limited regimes. Combining a simple scaling with calculations for stability ratio and rotational/translational diffusivities of irregular particle shapes, the effects of orientation for irregular-shaped particles on the early stages of aggregation is understood via angular dependence of van der Waals, electrostatic, and hydrodynamic interactions. Using Monte Carlo simulations, we found that a simple geometric parameter, namely the contact area between two attaching platelets, provides physical insight into the unique structural characteristics of the larger aggregates of the irregular-shaped particles, explaining the unusually high fractal dimensions measured in the diffusion-limited aggregation regime.

oriented aggregation, boehmite, attachment, nanopl↗
DOE OSTI2016

Structure and dynamics of aqueous solutions from PBE-based first-principles molecular dynamics simulations

Establishing an accurate and predictive computational framework for the description of complex aqueous solutions is an ongoing challenge for density functional theory based first-principles molecular dynamics (FPMD) simulations. In this context, important advances have been made in recent years, including the development of sophisticated exchange-correlation functionals. On the other hand, simulations based on simple generalized gradient approximation (GGA) functionals remain an active field, particularly in the study of complex aqueous solutions due to a good balance between the accuracy, computational expense, and the applicability to a wide range of systems. In such simulations we often perform them at elevated temperatures to artificially “correct” for GGA inaccuracies in the description of liquid water; however, a detailed understanding of how the choice of temperature affects the structure and dynamics of other components, such as solvated ions, is largely unknown. In order to address this question, we carried out a series of FPMD simulations at temperatures ranging from 300 to 460 K for liquid water and three representative aqueous solutions containing solvated Na + , K + , and Cl - ions. We show that simulations at 390–400 K with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional yield water structure and dynamics in good agreement with experiments at ambient conditions. Simultaneously, this computational setup provides ion solvation structures and ion effects on water dynamics consistent with experiments. These results suggest that an elevated temperature around 390–400 K with the PBE functional can be used for the description of structural and dynamical properties of liquid water and complex solutions with solvated ions at ambient conditions.

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

Quantifying particle-scale 3D granular dynamics during rapid compaction from time-resolved in situ 2D x-ray images

Understanding the particle-scale dynamics of granular materials during rapid compaction and flow is of fundamental importance for manufacturing, planetary science, geology, and defense applications. Time-resolved 2D radiography and static 3D x-ray tomography are powerful in situ tools for studying particle-scale dynamics but provide detail only in 2D or with significant time-scale limitations, respectively. Here, we introduce a new method that uses 2D in situ x-ray imaging for determining time-resolved 3D particle-scale dynamics in rapidly compressed granular materials. The method employs initial particle packing structures obtained from x-ray tomography, a 2D x-ray image generation algorithm, and an optimization algorithm. We first describe and validate the method using finite element simulations. Furthermore, we then apply the technique to x-ray phase-contrast images obtained during rapid compaction of granular materials with varying particle morphology and sample thickness. The depth-resolved particle-scale dynamics reveal complex velocity and porosity fields evolving heterogeneously along and perpendicular to the compaction direction. We characterize these features, their fluctuations near the compaction front, and the compaction front thickness. Our technique can be applied to understanding granular dynamics during rapid compaction events, and rearrangements during slower, but non-quasi-static, flows.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamic and relativistic effects on Pt–Pt indirect spin–spin coupling in aqueous solution studied by ab initio molecular dynamics and two- vs four-component density functional NMR calculations

Treating 195Pt nuclear magnetic resonance parameters in solution remains a considerable challenge from a quantum chemistry point of view, requiring a high level of theory that simultaneously takes into account the relativistic effects, the dynamic treatment of the solvent–solute system, and the dynamic electron correlation. A combination of Car-Parrinello molecular dynamics (CPMD) and relativistic calculations based on two-component zeroth order regular approximation spin–orbit Kohn–Sham (2c-ZKS) and four-component Dirac–Kohn–Sham (4c-DKS) Hamiltonians is performed to address the solvent effect (water) on the conformational changes and JPtPt1 coupling. A series of bridged PtIII dinuclear complexes [L1–Pt2(NH3)4(Am)2–L2]n+ (Am = α–pyrrolidonate and pivalamidate; L = H2O, Cl−, and Br−) are studied. The computed Pt–Pt coupling is strongly dependent on the conformational dynamics of the complexes, which, in turn, is correlated with the trans influence among axial ligands and with the angle N–C–O from the bridging ligands. The J-coupling is decomposed in terms of dynamic contributions. The decomposition reveals that the vibrational and explicit solvation contributions reduce JPtPt1 of diaquo complexes (L1 = L2 = H2O) in comparison to the static gas-phase magnitude, whereas the implicit solvation and bulk contributions correspond to an increase in JPtPt1 in dihalo (L1 = L2 = X−) and aquahalo (L1 = H2O; L2 = X−) complexes. Relativistic treatment combined with CPMD shows that the 2c-ZKS Hamiltonian performs as well as 4c-DKS for the JPtPt1 coupling.

Chemistry↗
DOE OSTI2021

A Secure Learning Control Strategy via Dynamic Camouflaging for Unknown Dynamical Systems under Attacks

This paper presents a secure reinforcement learning (RL) based control method for unknown linear time-invariant cyber-physical systems (CPSs) that are subjected to compositional attacks such as eavesdropping and covert attack. We consider the attack scenario where the attacker learns about the dynamic model during the exploration phase of the learning conducted by the designer to learn a linear quadratic regulator (LQR), and thereafter, use such information to conduct a covert attack on the dynamic system, which we refer to as doubly learning-based control and attack (DLCA) framework. We propose a dynamic camouflaging based attack-resilient reinforcement learning (ARRL) algorithm which can learn the desired optimal controller for the dynamic system, and at the same time, can inject sufficient misinformation in the estimation of system dynamics by the attacker. The algorithm is accompanied by theoretical guarantees and extensive numerical experiments on a consensus multi-agent system and on a benchmark power grid model.

Mukherjee, Sayak↗
DOE OSTI2018

Dynamic, Intermediate Soil Carbon Pools May Drive Future Responsiveness to Environmental Change

Accurately capturing dynamic soil response to disturbance effects in agroecosystem models remains elusive, thereby limiting projections of climate change mitigation potential. Perennial grasses cultivated in zero‐tillage management systems hold promise as sustainable agroecosystems. High‐yielding tropical C 4 grasses often have extensive rooting systems, and the belowground processes of root turnover, aggregate formation, and mineral stabilization drove rapid C accumulation after cultivation in a recent study. We sought (i) to understand and constrain the size and responsiveness of dynamic, intermediate‐cycling C pools contributing to the observed C accrual rates, and (ii) to simulate C stocks over time under the disturbance of elevated temperature using soil incubation at multiple temperatures and physical fractionation via density and sonication. Three‐pool transfer modeling of soil incubations revealed small pools of readily available (i.e., days to months) microbial substrate that were responsive to temperature, time since cultivation, and inputs. Larger, kinetically slow‐cycling pools were more indicative of long‐term (i.e., years to decades) changes in C stock and strongly connected to measured changes in physical fractions. Combining the sensitivity of readily available microbial substrate with three‐pool transfer modeling of the physical fractions over time since cultivation revealed that dynamic transfers of inputs occurred between the free organic and aggregate‐protected fractions, and from these fractions to the mineral‐associated dense fraction. Under 5°C temperature elevation, increased transfer rates outweighed elevated decomposition losses to sustain soil C accrual into the future. To effectively plan managed landscapes and monitor sustainable agroecosystems for climate change mitigation, tools must incorporate the complexity of soil response to change. Core Ideas Dynamic aspects of soil C are inadequately represented in most models. Intermediate‐cycling pools are more responsive to disturbances than thought. Root inputs are rapidly moved from particulate debris to mineral‐bound stable pools. Temperature increased the transfer rate to stable pools and sustained C accumulation Climate change mitigation projections must capture dynamic responses in agroecosystems.

Crow, Susan E.↗
DOE OSTI2023

Advanced monitoring of soil-vegetation co-dynamics reveals the successive controls of snowmelt on soil moisture and on plant seasonal dynamics in a mountainous watershed

Evaluating the interactions between above- and below-ground processes is important to understand and quantify how ecosystems respond differently to atmospheric forcings and/or perturbations and how this depends on their intrinsic characteristics and heterogeneity. Improving such understanding is particularly needed in snow-impacted mountainous systems where the complexity in water and carbon storage and release arises from strong heterogeneity in meteorological forcing and terrain, vegetation and soil characteristics. This study investigates spatial and temporal interactions between terrain, soil moisture, and plant seasonal dynamics at the intra- and inter-annual scale along a 160 m long mountainous, non-forested hillslope-to-floodplain system in the upper East River Watershed in the upper Colorado River Basin. To this end, repeated UAV-based multi-spectral aerial imaging, ground-based soil electrical resistivity imaging, and soil moisture sensors were used to quantify the interactions between above and below-ground compartments. Results reveal significant soil-plant co-dynamics. The spatial variation and dynamics of soil water content and electrical conductivity, driven by topographic and soil intrinsic characteristics, correspond to distinct plant types, with highest plant productivity in convergent areas. Plant productivity in heavy snow years benefited from more water infiltration as well as a shallow groundwater table depth. In comparison, low snowpack years with an early first bare-ground date, which are linked to an early increase in plant greenness, imply a short period of saturated conditions that leads to lower average and maximum greenness values during the growing season. Overall, these results emphasize the strong impact of snowpack dynamics, and terrain and subsurface characteristics on the heterogeneity in plant type and seasonal dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

Thermosphere dynamics - Contributions from the first 5 years of the Dynamics Explorer program

Instrumentation flown on the Dynamics Explorer 2 (DE-2) spacecraft enabled the dynamics of both the neutral and the ionized components of the earth's upper atmosphere to be monitored over the lifetime of the spacecraft, from August 1981 to February 1983. The direct measurements of global thermospheric vector neutral winds and ion drifts were supplemented by observations of neutral and ionic constituent abundances and temperatures, precipitating particle fluxes and pitch angle distributions, electric and magnetic fields, and global-scale auroral luminosity distributions. Analysis of this unique and comprehensive global data base has led to advances in our understanding of the manner in which the earth's thermosphere responds dynamically to the insertion of energy and momentum. We review the scientific progress achieved over the past 5 years through the efforts of members of the Dynamics Explorer science team and the other interested scientists who have used the DE data base to investigate the dynamical response of the thermosphere.

Killeen, T. L.↗
NASA NTRS2004

Linear State-Space Representation of the Dynamics of Relative Motion, Based on Restricted Three Body Dynamics

Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM) , the associated MAXIM pathfinder mission, Stellar Imager (SI) and the Terrestrial Planet Finder (TPF). An essential element of the technology is the control algorithm, requiring a clear understanding of the dynamics of relative motion. This paper examines the dynamics of relative motion in the context of the Restricted Three Body Problem (RTBP). The natural dynamics of relative motion are presented in their full nonlinear form. Motivated by the desire to apply linear control methods, the dynamics equations are linearized and presented in state-space form. The stability properties are explored for regions in proximity to each of the libration points in the Earth/Moon - Sun rotating frame. The dynamics of relative motion are presented in both the inertial and rotating coordinate frames.

Luquette,Richard J.↗
NASA NTRS2004

Linear State-Space Representation of the Dynamics of Relative Motion, Based on Restricted Three Body Dynamics

Precision Formation Flying is an enabling technology for a variety of proposed space- based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), Stellar Imager (SI) and the Terrestrial Planet Finder (TPF). An essential element of the technology is the control algorithm, requiring a clear understanding of the dynamics of relative motion. This paper examines the dynamics of relative motion in the context of the Restricted Three Body Problem (RTBP). The natural dynamics of relative motion are presented in their full nonlinear form. Motivated by the desire to apply linear control methods, the dynamics equations are linearized and presented in state-space form. The stability properties are explored for regions in proximity to each of the libration points in the Earth/Moon - Sun rotating frame. The dynamics of relative motion are presented in both the inertial and rotating coordinate frames.

Luquette, Richard J.↗