Hydration Control of the Mechanical and Dynamical Properties of Cellulose
Explore the source record for details and available documents.
biofuels (including algae and biomass), bio-inspir↗
SEARCH · Search NASA
Results for “dynamic”
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.
Approximate but accurate quantum dynamics from the Mori formalism: I. Nonequilibrium dynamics
We present a formalism that explicitly unifies the commonly used Nakajima-Zwanzig approach for reduced density matrix dynamics with the more versatile Mori theory in the context of nonequilibrium dynamics. Employing a Dyson-type expansion to circumvent the difficulty of projected dynamics, we obtain a self-consistent equation for the memory kernel which requires only knowledge of normally evolved auxiliary kernels. To illustrate the properties of the current approach, we focus on the spin-boson model and limit our attention to the use of a simple and inexpensive quasi-classical dynamics, given by the Ehrenfest method, for the calculation of the auxiliary kernels. For the first time, we provide a detailed analysis of the dependence of the properties of the memory kernels obtained via different projection operators, namely, the thermal (Redfield-type) and population based (NIBA-type) projection operators. We further elucidate the conditions that lead to short-lived memory kernels and the regions of parameter space to which this program is best suited. Via a thorough analysis of the different closures available for the auxiliary kernels and the convergence properties of the self-consistently extracted memory kernel, we identify the mechanisms whereby the current approach leads to a significant improvement over the direct usage of standard semi- and quasi-classical dynamics.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
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↗
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↗
The interaction of an atmospheric pressure plasma jet with liquid water: dimple dynamics and its impact on crystal violet decomposition
Not Available
Kondeti, V. S. Santosh K. (ORCID:000000018825845X)↗
Co-GISAXS technique for investigating surface growth dynamics
Detailed quantitative measurement of surface dynamics during thin film growth is a major experimental challenge. Here X-ray Photon Correlation Spectroscopy with coherent hard X-rays is used in a Grazing-Incidence Small-Angle X-ray Scattering (i.e. Co-GISAXS) geometry as a new tool to investigate nanoscale surface dynamics during sputter deposition of a-Si and a-WSi2 thin films. For both films, kinetic roughening during surface growth reaches a dynamic steady state at late times in which the intensity autocorrelation function g2(q,t) becomes stationary. The g2(q,t) functions exhibit compressed exponential behavior at all wavenumbers studied. The overall dynamics are complex, but the most surface sensitive sections of the structure factor and correlation time exhibit power law behaviors consistent with dynamical scaling.
Rainville, Meliha G.↗
Resolving Dynamic Properties of Polymers through Coarse-Grained Computational Studies
Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly modeled. In this paper, we probe the degree of coarse graining required to simultaneously retain significant atomistic details and access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using linear polyethylene as a model system, we probe how the coarse-graining scale affects the measured dynamics. Iterative Boltzmann inversion is used to derive coarse-grained potentials with 2–6 methylene groups per coarse-grained bead from a fully atomistic melt simulation. We show that atomistic detail is critical to capturing large-scale dynamics. Finally, using these models we simulate polyethylene melts for times over 500 μs to study the viscoelastic properties of well-entangled polymer melts.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗
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.↗
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↗
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.↗
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.↗
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.↗
Dynamics of Nanoscale Grain-Boundary Decohesion in Aluminum by Molecular-Dynamics Simulation
The dynamics and energetics of intergranular crack growth along a flat grain boundary in aluminum is studied by a molecular-dynamics simulation model for crack propagation under steady-state conditions. Using the ability of the molecular-dynamics simulation to identify atoms involved in different atomistic mechanisms, it was possible to identify the energy contribution of different processes taking place during crack growth. The energy contributions were divided as: elastic energy, defined as the potential energy of the atoms in fcc crystallographic state; and plastically stored energy, the energy of stacking faults and twin boundaries; grain-boundary and surface energy. In addition, monitoring the amount of heat exchange with the molecular-dynamics thermostat gives the energy dissipated as heat in the system. The energetic analysis indicates that the majority of energy in a fast growing crack is dissipated as heat. This dissipation increases linearly at low speed, and faster than linear at speeds approaching 1/3 the Rayleigh wave speed when the crack tip becomes dynamically unstable producing periodic dislocation bursts until the crack is blunted.
Yamakov, V.↗
Pruning of Discrete Dynamic Event Trees Using Density Peaks and Dynamic Time Warping
Discrete Dynamic Event Trees (DDETs) are used in probabilistic risk assessment (PRA) to determine the risk associated with complex systems, such as nuclear power plants, where accident scenarios need to be realistically modeled. One of the most challenging aspects of the DDET method is that a large number of branches are produced for each initiating event. This can result in data that is difficult to organize and time consuming to analyze. As the number of uncertain parameters increases, so does the complexity of the event tree. An event tree often has nodes that do not contribute to the overall results and predictive capabilities; therefore, we suggest a pre-pruning algorithm that can work to remove these nodes, and consequently, reduce the complexity of the tree. Sandia National Laboratories (SNL) is currently working on a two year dynamic cyber-risk informed project to assess cyber failure in a nuclear power plant. This will be achieved by coupling SNL's dynamic scheduler known as Analysis of Dynamic Accident Progression Trees (ADAPT) with MELCOR, a reactor accident simulator, and a System for Circuit Evaluation and Prediction of Transient Radiation Effects (SCEPTRE), a cyber Emulytics code. This paper will discuss the preliminary results of a feasibility study for using density peaks (DP) clustering with dynamic time warping (DTW) to prune branches that are formed from large DDETs, like the ones that will be produced throughout SNL's project. Papers from the project that are submitted to this conference discuss the following: - The MELCOR model for a Pressurized Water Reactor that uses a digital instrumentation and control system. - Proposed generic cyber exploits for the above reactor. - Modifications to ADAPT to extend the framework for multiple simulators, incorporate importance measures into DDET analysis, as well as sort and reduce DDETs based on inputs to or outputs from the tree. (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Analysis of Dynamical Peculiarities in Nanoalloys at Subsystems Level: Dynamical Degrees of Freedom, Temperature Differences, and the Chameleon Effect
Abstract A novel analysis of the dynamical behavior of nanoalloy systems, as represented by model Ni/Al 13‐atom clusters, over a broad range of energies that cover the stage‐wise transition of the systems from their solid‐like to liquid‐like state is presented. Conceptually, the analysis is rooted in partitioning the systems into judiciously chosen subsystems and characterizing the latter in terms of subsystem‐specific dynamical descriptors that include dynamical degrees of freedom , root‐mean‐square bond‐length fluctuation , and element‐specific subsystem temperature . The analysis reveals a host of intriguing new peculiarities in the dynamical behavior of the Ni/Al 13‐mers, among which are what we call the chameleon effect and the difference in the temperatures of the Ni and Al subsystems at high energies, a difference that strongly depends on the cluster composition and also changes with energy. These do not have an analog in pure Ni 13 and Al 13 and are explained in terms of the coupled effects of the difference between the masses of the Ni and Al atoms (the mass effect) and of the difference in the anharmonicity of the overall interaction potential as experienced by the Ni and Al subsystems of the clusters (the potential effect).
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗