Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic sampling”

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
DOE OSTI2021

Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo

As an important Markov chain Monte Carlo (MCMC) method, the stochastic gradient Langevin dynamics (SGLD) algorithm has achieved great success in Bayesian learning and posterior sampling. Furthermore, SGLD typically suffers from a slow convergence rate due to its large variance caused by the stochastic gradient. In order to alleviate these drawbacks, we leverage the recently developed Laplacian smoothing technique and propose a Laplacian smoothing stochastic gradient Langevin dynamics (LS-SGLD) algorithm. We prove that for sampling from both log-concave and non-log-concave densities, LS-SGLD achieves strictly smaller discretization error in 2-Wasserstein distance, although its mixing rate can be slightly slower. Experiments on both synthetic and real datasets verify our theoretical results and demonstrate the superior performance of LS-SGLD on different machine learning tasks including posterior sampling, Bayesian logistic regression, and training Bayesian convolutional neural networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Dynamic Mechanical Analysis of Post-Cured Bismaleimide Resins for Composite-Overwrapped Combustion Chambers Cycled From Cryogenic to High Temperatures

In support of the Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) project, samples made of polybismaleimide (BMI) resin were made and tested under cryogenic conditions. Neat resin samples were tested for multiple cycles, from high temperature (300°C) to cryogenic temperature (-150°C), to replicate the conditions a rocket engine assembly would experience in a test campaign and in operation. To increase the glass transition temperature (and thus mechanical stability), samples were exposed to different post-cure temperatures and were tested using a dynamic mechanical analysis (DMA) instrument. Consistent with expectations, the BMI samples post-cured at higher temperatures generally resulted in higher storage modulus under high temperature test conditions but at the expense of storage modulus values at low temperature test conditions.

Christopher Stelter↗
DOE OSTI2021

Highly Recyclable, Mechanically Isotropic and Healable 3D-Printed Elastomers via Polyurea Vitrimers

Delamination of three-dimensional (3D) printed polymer materials by fused deposition modeling (FDM) is a long-standing challenge in additive manufacturing (AM). With numerous efforts devoted to modification of commercially available thermoplastic FDM filaments, developing printing polymeric materials with new chemical design that could intrinsically improve interlayer adhesion, especially combined with other benefits, is in high demand. Herein, we developed a polyurea vitrimer with heat-driven malleability, which is printed to different 3D geometries using FDM. Significantly improved interlayer adhesion was observed by post-annealing the printed samples close to its topology-freezing transition temperature upon which fast associative dynamic covalent bonds exchange reaction occurs. Isotropic mechanical properties were achieved as demonstrated with printed tensile samples with different infill directions. Finally, the printed materials could be fully recycled for five generations with retained mechanical properties. Furthermore, the mechanical performance of the printed sample could also be repaired after damage.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Vibration-Based Sensor Design: A Grey-Box Approach

Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

In Situ Detection of Amino Acids from Bacterial Biofilms and Plant Root Exudates by Liquid Microjunction Surface-Sampling Probe Mass Spectrometry

The plant rhizosphere is a complex and dynamic chemical environment where the exchange of molecular signals between plants, microbes, and fungi drives the development of the entire biological system. Exogenous compounds in the rhizosphere are known to affect plant-microbe organization, interactions between organisms, and ultimately, growth and survivability. The function of exogenous compounds in the rhizosphere is still under much investigation, specifically with respect to their roles in plant growth and development, the assembly of the associated microbial community, and the spatiotemporal distribution of molecular components. A major challenge for spatiotemporal measurements is developing a nondisruptive and nondestructive technique capable of analyzing the exogenous compounds contained within the environment. A methodology using liquid microjunction-surface sampling probe-mass spectrometry (LMJ-SSP-MS) and microfluidic devices with attached microporous membranes was developed for in situ, spatiotemporal measurement of amino acids (AAs) from bacterial biofilms and plant roots. Exuded arginine was measured from a living Pantoea YR 343 biofilm, which resulted in a chemical image indicative of biofilm growth within the device. Spot sampling along the roots of Populus trichocarpa with the LMJ-SSP-MS resulted in the detection of 15 AAs. Of note, variation in AA concentrations across the root system was observed, indicating that exudation is not homogeneous and may be linked to local rhizosphere architecture and different biological processes along the root.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Investigation of dynamic fracture behavior of additively manufactured Al-10Si-Mg using high-speed synchrotron X-ray imaging

The dynamic tensile properties of additively manufactured (AM) and cast Al-10Si-Mg alloy were disccused using high-speed synchrotron X-ray imaging coupled with a modified Kolsky bar apparatus. A controlled tensile loading (strain rate ≈ 750 s -1 ) was applied using the Kolsky bar apparatus and the deformation and fracture behavior were recorded using the high-speed X-ray imaging setup. The CT and high-speed imaging results worked together to identify the location of the critical flaw and to capture the dynamics of crack propagation. In all experiments, the critical flaw was located on the surface of each specimen. The AM specimens displayed significantly higher crack propagation speed, yield strength, ultimate tensile strength, strain hardening coefficient, and yet lower ductility compared to the cast specimens under dynamic tension. Although the strength values were higher for the AM specimens, the critical mode I stress intensity factors were comparable for both specimens. The microstructures of the samples were characterized by synchrotron X-ray computed tomography (CT) and scanning electron microcopy. The correlation between the dynamic fracture behavior of the samples and the microstructure of the samples is analyzed and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Neural network representation of electronic structure from ab initio molecular dynamics

Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. Here we introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When it is applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born–Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving the way to previously inaccessible or challenging avenues in materials modeling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An Integrated Study on a Novel High Temperature High Entropy Alloy

This report summarizes our recent works of theoretical modeling, simulation, and experimental validation of the simulation results on the new refractory high entropy alloy (HEA) design and oxide doped refractory HEA research. The simulation of the stability and thermal dynamics simulation on potential thermal stable candidates were performed and related HEA with oxide doped samples were synthesized and characterized. The HEA ab initio density functional theory and molecular dynamics physical property simulation methods and experimental texture validation techniques development, achievements already reached, course work development, students and postdoc training, and future improvement research directions are briefly introduced.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ultra-high temperature testing and performance of L-PBF C103

Additive Manufacturing (AM) of refractory alloys is gaining traction as a materials processing route for components subject to extreme temperature environments. Due to the low oxidation resistance of refractory alloys, novel methods for evaluating their elevated temperature performance must be developed. In this work, a Gleeble® 3800 thermomechanical load frame was modified to evaluate the mechanical properties of laser powder bed fusion (L-PBF) consolidated niobium alloy C103 ranging from room temperature (RT) to 1400 °C. The fixturing and sample geometry were designed to accommodate Joule heating and prevent damage to the test chamber. Oxidation of the samples was minimized via testing in vacuum level of 1E-5 Torr. Ultimate tensile strength (UTS), yield strength (YS), elongation, and strain-hardening behavior were determined as a function of temperature. L-PBF C103 presented an average UTS of ∼650 MPa and over 25 % elongation at RT. Above RT, the UTS and YS dropped then leveled off from 500 °C to 1000 °C with values ranging from ∼400 MPa to ∼460 MPa, which is consistent with dynamic strain aging observed in this class of alloys. The strength rapidly declined after 1200 °C to ∼150 MPa at 1400 °C. Fractography indicated ductile fractures for the C103 at all test temperatures, and Electron Backscatter Diffraction (EBSD) analysis revealed a textured microstructure and the presence of dynamic recrystallization within the necked region of the sample tested at 1400 °C.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

The structural and dynamical role of water in natural organic matter: A 2H NMR and XRD study

Natural organic matter (NOM) is an important component in many near-surface geochemical environments, and its properties are greatly affected by the incorporation of water. Because of its importance, the macroscopic behavior and effects of water in NOM and soil organic matter (SOM) have been extensively studied using a wide range of experimental and computational methods. The molecular scale structural and dynamical behavior of water in these materials, however, is less well understood. This paper presents a variable temperature 2 H NMR and XRD study of water in Suwannee River NOM and its fulvic acid (FA) and humic acid (HA) fractions that provides new insight into the dynamical behavior of structurally different types of water and exchangeable hydrogen environments in NOM. The results provide a basis for future studies of more complex natural organic materials and the interaction of organic materials with mineral surfaces. Room temperature 2 H NMR spectra of samples hydrated in 2 H 2 O and then dehydrated, distinguish 2 H 2 O molecules that are in rapid reorientational motion (correlation times, ν c, > 10 5 Hz), 2 H exchanged onto carboxylic sites of the NOM that do not undergo rapid reorientation at frequencies >~10 3 Hz, and 2 H exchanged onto phenolic and possibly other alcohol sites of the NOM that undergoes rapid, but anisotropic, dynamical reorientation. For samples exposed to water and not dried, the XRD results collected at temperatures from 173 to 298 K show the formation of ice-1h in samples exposed to 100% relative humidity (R.H.) but not in samples exposed to 43% R.H. 2 H NMR of those samples collected at temperatures from 313 K to 173 K show the presence of multiple sites. Near room temperature, the spectra contain a narrow resonance for mobile water undergoing rapid isotropic motion, and a broader symmetrical resonance probably due to a combination of more dynamically restricted water molecules and 2 H exchanged onto phenolic and alcohol functional groups undergoing rapid anisotropic motion. The 43% R.H. samples also yield a broader, quadrupole-dominated, resonance for 2 H exchanged onto functional groups of the NOM. With decreasing temperature the resonances for dynamically restricted water molecules and 2 H exchanged onto phenolic and alcohol functional groups become broader, reflecting a decreasing rate of exchange between the water molecules and functional groups and a decreasing rate of reorientation of the 2 H 2 O molecules. The formation of ice-1h is directly reflected in the 2 H spectra of the 100% R.H. samples as a resonance with a quadrupole coupling constant (QCC) of ~180 kHz. For the 43% R.H. samples, there is also a broad, poorly resolved resonance with typical QCCs of ~180 kHz for which the relative signal intensity increases with decreasing temperature. This signal represents 2 H 2 O molecules that are not crystallized in ice-1h but have greatly reduced reorientation frequencies at low temperature and a hydrogen bonding network with hydrogen bond strengths similar to, but somewhat weaker than, ice-1h. Such molecules are also likely to be present in the 100% R.H. samples. At both R.H.s, some of the 2 H 2 O molecules do not freeze and retain their isotropic motion down to 173 K, the lowest temperature investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗
DOE OSTI2017

Material property analytical relations for the case of an AFM probe tapping a viscoelastic surface containing multiple characteristic times

We explore the contact problem of a flat-end indenter penetrating intermittently a generalized viscoelastic surface, containing multiple characteristic times. This problem is especially relevant for nanoprobing of viscoelastic surfaces with the highly popular tapping-mode AFM imaging technique. By focusing on the material perspective and employing a rigorous rheological approach, we deliver analytical closed-form solutions that provide physical insight into the viscoelastic sources of repulsive forces, tip-sample dissipation and virial of the interaction. We also offer a systematic comparison to the well-established standard harmonic excitation, which is the case relevant for dynamic mechanical analysis (DMA) and for AFM techniques where tip–sample sinusoidal interaction is permanent. This comparison highlights the substantial complexity added by the intermittent-contact nature of the interaction, which precludes the derivation of straightforward equations as is the case for the well-known harmonic excitations. The derivations offered have been thoroughly validated through numerical simulations. Despite the complexities inherent to the intermittent-con-tact nature of the technique, the analytical findings highlight the potential feasibility of extracting meaningful viscoelastic properties with this imaging method.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning

Unmanned aerial vehicles (UAV) carrying multispectral cameras are increasingly being used for high-throughput phenotyping (HTP) of above-ground traits of crops to study genetic diversity, resource use efficiency and responses to abiotic or biotic stresses. There is significant unexplored potential for repeated data collection through a field season to reveal information on the rates of growth and provide predictions of the final yield. Generating such information early in the season would create opportunities for more efficient in-depth phenotyping and germplasm selection. This study tested the use of high-resolution time-series imagery (5 or 10 sampling dates) to understand the relationships between growth dynamics, temporal resolution and end-of-season above-ground biomass (AGB) in 869 diverse accessions of highly productive (mean AGB = 23.4 Mg/Ha), photoperiod sensitive sorghum. Canopy surface height (CSM), ground cover (GC), and five common spectral indices were considered as features of the crop phenotype. Spline curve fitting was used to integrate data from single flights into continuous time courses. Random Forest was used to predict end-of-season AGB from aerial imagery, and to identify the most informative variables driving predictions. Improved prediction of end-of-season AGB (RMSE reduction of 0.24 Mg/Ha) was achieved earlier in the growing season (10 to 20 days) by leveraging early- and mid-season measurement of the rate of change of geometric and spectral features. Early in the season, dynamic traits describing the rates of change of CSM and GC predicted end-of-season AGB best. Late in the season, CSM on a given date was the most influential predictor of end-of-season AGB. The power to predict end-of-season AGB was greatest at 50 days after planting, accounting for 63% of variance across this very diverse germplasm collection with modest error (RMSE 1.8 Mg/ha). End-of-season AGB could be predicted equally well when spline fitting was performed on data collected from five flights versus 10 flights over the growing season. This demonstrates a more valuable and efficient approach to using UAVs for HTP, while also proposing strategies to add further value.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Synoptic NO3 in Slate River Watershed, Colorado (2022)

The synoptic nitrate (NO3) dataset in the Slate River Watershed, Colorado consists of NO3 data collected at 19 locations three times during the summer of 2022. Stream samples were collected in early summer (early July), mid summer (late August), and late summer (late September). The samples include mainstem, tributary, and point source input water samples. These data were collected to evaluate spatiotemporal variability in stream NO3 during the summer, and evaluate anthropogenic controls on stream NO3 dynamics. This data package contains: (1) a csv of all NO3 samples and (2) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATE↗
DOE OSTI2023

A hybrid machine-learning approach for analysis of methane hydrate formation dynamics in porous media with synchrotron CT imaging

Fast multi-phase processes in methane hydrate bearing samples pose a challenge for quantitative micro-computed tomography study and experiment steering due to complex tomographic data analysis involving time-consuming segmentation procedures. This is because of the sample's multi-scale structure, which changes over time, low contrast between solid and fluid materials, and the large amount of data acquired during dynamic processes. Here, a hybrid approach is proposed for the automatic segmentation of tomographic data from time-resolved imaging of methane gas-hydrate formation in sandy granular media, which includes a deep-learning 3D U-Net model. To prepare a training dataset for the 3D U-Net, a technique to automate data labeling based on sample-specific information about the mineral matrix immobility and occasional fluid movement in pores is proposed. Automatic segmentation allowed for studying properties of the hydrate growth in pores, as well as dynamic processes such as incremental flow and redistribution of pore brine. Results of the quantitative analysis showed that for typical gas-hydrate stability parameters (100 bar methane pressure, 7°C temperature) the rate of formation is slow (less than 1% per hour), after which the surface area of contact between brine and gas increases, resulting in faster formation (2.5% per hour). Hydrate growth reaches the saturation point after 11 h of the experiment. Finally, the efficacy of the proposed segmentation scheme in on-the-fly automatic data analysis and experiment steering with zooming to regions of interest is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Flux line relaxation kinetics following current quenches in disordered type-II superconductors

We investigate the relaxation dynamics of magnetic vortex lines in type-II superconductors following rapid changes of the external driving current by means of an elastic line model simulated with Langevin molecular dynamics. A system of flux vortices in a sample with randomly distributed point-like defects is subjected to an external current of appropriate strength for a sufficient period of time so as to be in a moving non-equilibrium steady state. Here, the current is then instantaneously lowered to a value that pertains to either the moving or pinned regime. The ensuing relaxation of the flux lines is studied via one-time observables such as their mean velocity and radius of gyration. We have in addition measured the two-time flux line height autocorrelation function to investigate dynamical scaling and aging behavior in the system, which in particular emerge after quenches into the glassy pinned state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗