SEARCH · Engineering Papers

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.

SourceResearch connectionFrom yearThrough year

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

At least 1,585 records · Page 88

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Probing Ground-State Phase Transitions through Quench Dynamics

The study of quantum phase transitions requires the preparation of a many-body system near its ground state, a challenging task for many experimental systems. The measurement of quench dynamics, on the other hand, is now a routine practice in most cold atom platforms. Here we show that quintessential ingredients of quantum phase transitions can be probed directly with quench dynamics in integrable and nearly integrable systems. As a paradigmatic example, we study global quench dynamics in a transverse-field Ising model with either short-range or long-range interactions. When the model is integrable, we discover a new dynamical critical point with a nonanalytic signature in the short-range correlators. The location of the dynamical critical point matches that of the quantum critical point and can be identified using a finite-time scaling method. We extend this scaling picture to systems near integrability and demonstrate the continued existence of a dynamical critical point detectable at prethermal timescales. We quantify the difference in the locations of the dynamical and quantum critical points away from (but near) integrability. Thus, we demonstrate that this method can be used to approximately locate the quantum critical point near integrability. Furthermore, the scaling method is also relevant to experiments with finite time and system size, and our predictions are testable in near-term experiments with trapped ions and Rydberg atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Inverse transformation: unleashing spatially heterogeneous dynamics with an alternative approach to XPCS data analysis

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Dynamic Parameter Estimation with Physics-based Neural Ordinary Differential Equations

Accurate estimation of dynamic parameters of gen-erators is crucial to building a reliable model for dynamical studies and reliable operation of the power system. This paper develops a physics-based neural ordinary differential equations (ODE) approach to learn the parameters of generator dynamic model using phasor measurement units (PMU) data. We design a physics-based neural network to represent the swing equations of the power system dynamics. A loss function is defined as the difference between dynamic simulation results from the physics-based neural networks and pseudo PMU measurements. The parameters of generator dynamic model are iteratively updated using the neural ODEs and the adjoint method. By exploiting the mini-batch scheme in neural ODE training, the parameter estimation performance is significantly improved. Numerical study results on a 3-machine 9-bus system show that the proposed algorithm outperforms state-of-the-art baseline method in both computation time and dynamic parameter estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Dynamic-Feature Extraction, Attribution and Reconstruction (DEAR) Method for Power System Model Reduction

In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highest similarity, forming a suboptimal ‘basis’ of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.

Dynamic response, model reduction, orthogonal deco↗

DOE OSTI2015

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons

The formation of oscillating phase clusters in a network of identical Hodgkin–Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition—through (possibly perturbed) period-doubling and subsequent bifurcations—to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar “fine” states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron’s “identity” (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established “identity-state” correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Evaluating crown scorch predictions from a computational fluid dynamics wildland fire simulator

Abstract Background Crown scorch—the heating of live leaves, needles, and buds in the vegetative canopy to lethal temperatures without widespread combustion—is one of the most common fire effects shaping post-fire canopies. Despite the ability of computational fluid dynamic models to finely resolve fire activity and buoyant plume dynamics including heterogenous 3D distributions of forest canopy heating, these models have had only limited use in simulating fire effects and have not been used to evaluate crown scorch. Here, we demonstrate a method of evaluating crown scorch using a computational fluid dynamics model, FIRETEC, and validate this approach by simulating the experiments that were used to develop Van Wagner’s 1973 crown scorch model. Results The average scorch height prediction from FIRETEC compares well with the empirical model derived by Van Wagner, which is the most widely used empirical model for crown scorch. We further find that the 3D buoyant plume dynamics from a steady and homogeneous idealized heat source on the ground results in a spatially heterogenous crown scorch pattern reflecting complex heating dynamics that are best represented by percent scorch rather than height of scorch. Conclusions The ability of the computational fluid dynamics model to capture variation in crown scorch due to 3D buoyant plume dynamics provides direct links between forest structure, fire behavior, and fire effects that can be used by forest managers and researchers to better understand how fires result in crown damage under various environmental and management scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Fluctuations in the Dynamics of Glasses

This research program addressed the question of the presence of dynamical heterogeneities – strong spatial fluctuations in the dynamics – in glass forming liquids and jamming systems near dynamical arrest, with particular emphasis on aging systems, i.e. systems that are in the (non-equilibrium) glass regime. The main goals proposed for this research were: to perform numerical simulations of atomistic structural glass models to characterize dynamical heterogeneities in out of equilibrium (aging) glassy systems; to test the hypothesis that a certain symmetry (“time reparametrization symmetry”) is present in microscopic models of glassy systems and that this symmetry can explain the main features of dynamical heterogeneities; and to test to what extent these phenomena are universal across different glassy/jamming systems. It was found that: most of the important features of dynamical heterogeneities in the aging regime could be described in terms of simple scaling behaviors; that some of the most basic theoretical models of glassy systems indeed have time reparametrization symmetry; that all tests performed in numerical simulation data were consistent with the predictions from time reparametrization symmetry; and that to a large degree, the main features of dynamical heterogeneities were universal across different glassy systems. Most of the findings that came out of this research have been reported in detail in eight papers in high quality journals, two unpublished but publicly accessible manuscripts, and 27 invited and contributed talks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Modeling dynamic stall on wind turbine blades under rotationally augmented flow fields

It is well known that airfoils under unsteady flow conditions with a periodically varying angle of attack exhibit aerodynamic characteristics different from those under steady flow conditions, a phenomenon commonly known as dynamic stall. It is also well known that the steady aerodynamic characteristics of airfoils in the inboard region of a rotating blade differ from those under steady two-dimensional (2D) flow conditions, a phenomenon commonly known as rotational augmentation. This paper presents an investigation of these two phenomena together in the inboard parts of wind turbine blades. This analysis is carried out using data from three sources: (1) the National Renewable Energy Laboratory’s Unsteady Aerodynamics Experiment Phase VI experimental data, including constant as well as continuously pitching blade conditions during axial operation, (2) data from unsteady Delayed Detached Eddy Simulations (DDES) carried out using the Technical University of Denmark’s in-house flow solver Ellipsys3D, and (3) data from a simplified model based on the blade element momentum method with a dynamic stall subroutine that uses rotationally augmented steady-state polars obtained from steady Phase VI experimental sequences, instead of the traditional 2D nonrotating data. The aim of this work is twofold. First, the blade loads estimated by the DDES simulations are compared to three select cases of the N sequence experimental data, which serves as a validation of the DDES method. Results show reasonable agreement between the two data in two out of three cases studied. Second, the dynamic time series of the lift and the moment polars obtained from the experiments are compared to those from the dynamic stall subroutine that uses the rotationally augmented steady polars. This allowed the differences between the stall phenomenon on the inboard parts of harmonically pitching blades on a rotating wind turbine and the classic dynamic stall representation in 2D flow to be investigated. Results from the dynamic stall subroutine indicated a good qualitative agreement between the model and the experimental data in many cases, which suggests that the current 2D dynamic stall model as used in BEM-based aeroelastic codes may provide a reasonably accurate representation of three-dimensional rotor aerodynamics when used in combination with a robust rotational augmentation model.

17 WIND ENERGY↗

NASA NTRS2013

Session 6: Dynamic Modeling and Systems Analysis

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

control↗

NASA NTRS2015

Dynamic Characterization of Galfenol

A novel and precise characterization of the constitutive behavior of solid and laminated research-grade, polycrystalline Galfenol (Fe81:6Ga18:4) under under quasi-static (1 Hz) and dynamic (4 to 1000 Hz) stress loadings was recently conducted by the authors. This paper summarizes the characterization by focusing on the experimental design and the dynamic sensing response of the solid Galfenol specimen. Mechanical loads are applied using a high frequency load frame. The dynamic stress amplitude for minor and major loops is 2.88 and 31.4 MPa, respectively. Dynamic minor and major loops are measured for the bias condition resulting in maximum, quasi-static sensitivity. Three key sources of error in the dynamic measurements are accounted for: (1) electromagnetic noise in strain signals due to Galfenol's magnetic response, (2) error in load signals due to the inertial force of fixturing, and (3) time delays imposed by conditioning electronics. For dynamic characterization, strain error is kept below 1.2 % of full scale by wiring two collocated gauges in series (noise cancellation) and through lead wire weaving. Inertial force error is kept below 0.41 % by measuring the dynamic force in the specimen using a nearly collocated piezoelectric load washer. The phase response of all conditioning electronics is explicitly measured and corrected for. In general, as frequency increases, the sensing response becomes more linear due to an increase in eddy currents. The location of positive and negative saturation is the same at all frequencies. As frequency increases above about 100 Hz, the elbow in the strain versus stress response disappears as the active (soft) regime stiffens toward the passive (hard) regime.

Dynamic sensing↗

NASA NTRSDate not supplied

Supersonic Free-Flight Dynamics Testing in the Stratosphere

A new technique for obtaining stratospheric free-flight dynamics data for atmospheric entry capsules is described. The Stratospheric Projectile Experiment of Entry Dynamics (SPEED) represents a new approach to characterizing the free-flight dynamics of vehicles in the supersonic and transonic regime of flight. The SPEED test architecture leverages a stratospheric balloon and 3D-printed flight system in a novel two-stage configuration to deliver test articles to supersonic conditions in the atmosphere which achieve dynamic similitude with a full-scale vehicle. Designed to address the limitations of existing test facilities, SPEED captures the complete time evolution of a vehicle’s dynamic state while producing a statistically significant number of observed flight trajectories to address the stochastic nature of the wake-driven dynamic stability phenomenon. SPEED was developed over two years at NASA Ames Research Center. The inaugural flight of the SPEED test platform was conducted in the summer of 2024 where scaled capsules of the Mars Sample Return Earth Entry System and Dragonfly entry vehicle were tested. This paper describes the motivation for a new test architecture, operational constraints and achievable flight test envelopes, the design and development of the SPEED concept, and results from the demonstration flight. Techniques for estimating the dynamic aerodynamic characteristics and atmospheric conditions for each test article individually and as a collective are also discussed.

Entry Vehicle↗

DOE OSTI2020

Multi-Timescale Integrated Dynamic and Scheduling Model (MIDAS-Solar)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power system operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power systems steady-state and dynamic performance. This project helps meet and exceed the Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for electric grid planning and operation. This will be accomplished by developing temporally comprehensive, closed-loop simulation models that seamlessly simulate power systems operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). Both a multi-timescale grid model and an integrated PV model will be developed in this project to accurately study the impacts of PV variability and uncertainty on system reliability at multiple timescales. Using quasi-dynamic simulation methods and data-driven security assessment (DSA) criteria will allow the dynamic characteristics of PV to be fed forward into longer-timescale scheduling models for a complete understanding of the effect of short-term PV dynamics on bulk systems operations (e.g., reserve scheduling and deployment). Upon completion of the proposed model, this project will help operators accurately assess system reliability by deploying energy and reserve scheduling under critical contingency conditions and studying interactions among all types of essential reliability services provided by modern PV power plants.

14 SOLAR ENERGY↗

DOE OSTI2024

DyG-DPCD: A Distributed Parallel Community Detection Algorithm for Large-Scale Dynamic Graphs

Dynamic (Temporal) graphs capture the valuable evolution of real-world systems, from the continuously evolving patterns of social interactions and genetic pathways to the dynamic fluctuations of economic forces. Detecting communities for such evolving networks poses unique challenges. Detecting and analyzing the evolution of communities within dynamic graphs unlocks valuable insights into the underlying structural and temporal patterns of real-world systems. However, the sheer volume of modern graph data and the inherent complexity of the temporal dimension pose significant challenges to scalable community detection algorithms. Addressing this gap, our work explores the limited landscape of scalable distributed-memory parallel methods specifically designed for dynamic network community detection. We propose a novel parallel algorithm, DyG-DPCD (Dynamic Graph Distributed Parallel Community Detection), to detect communities in dynamic networks using the Message Passing Interface (MPI) framework. We present a vertex-centric approach, allowing us to detect communities through local optimization. Furthermore, we enhance our baseline algorithm by incorporating three heuristics, which improve the algorithm’s performance significantly while maintaining the quality of the solutions. We demonstrate the efficiency of our algorithm by experimenting on several real-world large-scale networks with hundreds of millions of edges spanning diverse domains. Notably, DyG-DPCD achieves speedups between 25× and 30× for large networks that we experimented on using NERSC compute nodes. In conclusion, our algorithm outperforms the STINGER parallel re-agglomeration algorithm by 30×.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

The “High Fidelity, Faster than RealTime Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of largescale power system dynamics simulation, including (1) a validated faster than real time simulation of both stable and unstable transient dynamics in a largescale positive sequence transmission grid model, (2) a threephase unbalanced simulation platform for modeling new grid devices, such as independently controlled singlephase static var compensators (SVCs), (3) the world’s first high fidelity threephase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a firstofits kind implementation of a singlephase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the longterm, the simulator will form the backbone of the newly conceived hybrid realtime protection and control architecture that will coordinate local controls, widearea measurements, widearea controls and advanced realtime prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the fasterthanrealtime simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three phase unbalanced simulator’s ability to model threephase and single phase networks and devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2017

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

Contact dynamics↗

DOE OSTI2015

Impact of the dynamical core on the direct simulation of tropical cyclones in a high-resolution global model

Our paper examines the impact of the dynamical core on the simulation of tropical cyclone (TC) frequency, distribution, and intensity. The dynamical core, the central fluid flow component of any general circulation model (GCM), is often overlooked in the analysis of a model's ability to simulate TCs compared to the impact of more commonly documented components (e.g., physical parameterizations). The Community Atmosphere Model version 5 is configured with multiple dynamics packages. This analysis demonstrates that the dynamical core has a significant impact on storm intensity and frequency, even in the presence of similar large-scale environments. In particular, the spectral element core produces stronger TCs and more hurricanes than the finite-volume core using very similar parameterization packages despite the latter having a slightly more favorable TC environment. Furthermore, these results suggest that more detailed investigations into the impact of the GCM dynamical core on TC climatology are needed to fully understand these uncertainties. Key Points The impact of the GCM dynamical core is often overlooked in TC assessments The CAM5 dynamical core has a significant impact on TC frequency and intensity A larger effort is needed to better understand this uncertainty

58 GEOSCIENCES↗

DOE OSTI2016

Estimating groundwater dynamics at a Colorado River floodplain site using historical hydrological data and climate information

Long-term prediction of groundwater dynamics is important for assessing water resources and their impacts on biogeochemical cycling. However, estimating future groundwater dynamics is challenging due to the wide range of spatiotemporal scales in hydrological processes and uncertainty in future climate conditions. In this study, we develop a Bayesian model to combine small-scale historical hydrological data with large-scale climate information to estimate groundwater dynamics at a floodplain site in Rifle, Colorado. Although we have only a few years of groundwater elevation measurements, we have 47 years of streamflow data from a gaging station approximately 43 km upstream and long-term climate prediction on the Upper Colorado River Basin. To estimate future daily groundwater dynamics, we first develop a time series model to downscale the monthly streamflow derived from climate information to daily streamflow, and then transform the daily streamflow to groundwater dynamics at the downstream floodplain site. We use Monte Carlo methods to estimate future groundwater dynamics at the site through sampling from the joint posterior probability distribution. The results suggest that although future groundwater levels are expected to be similar to the current levels, the timing of the high groundwater levels is predicted to occur about 1 month earlier. The developed framework is extendable to other sites to estimate future groundwater dynamics given disparate data sets and climate projections. Additionally, the obtained estimates are being used as input to a site-specific watershed reactive transport models to predict how climate-induced changes will influence future biogeochemical cycling relevant to a variety of ecosystem services.

58 GEOSCIENCES↗

DOE OSTI2025

An Internal Digital Image Correlation Technique for High-Strain Rate Dynamic Experiments

Full-field, quantitative visualization techniques, such as digital image correlation (DIC), have unlocked vast opportunities for experimental mechanics. However, DIC has traditionally been a surface measurement technique, and has not been extended to perform measurements on the interior of specimens for dynamic, full-scale laboratory experiments. This limitation restricts the scope of physics which can be investigated through DIC measurements, especially in the context of heterogeneous materials. The focus of this study is to develop a method for performing internal DIC measurements in dynamic experiments. The aim is to demonstrate its feasibility and accuracy across a range of stresses (up to 650 MPa), strain rates (10 3 - 10 6 s -1 ), and high-strain rate loading conditions (e.g., ramped and shock wave loading). Internal DIC is developed based on the concept of applying a speckle pattern at an inner-plane of a transparent specimen. The high-speed imaging configuration is coupled to the traditional dynamic experimental setups, and is focused on the internal speckle pattern. During the experiment, while the sample deforms dynamically, in-plane, two-dimensional deformations are measured via correlation of the internal speckle pattern. In this study, the viability and accuracy of the internal DIC technique is demonstrated for split-Hopkinson (Kolsky) pressure bar (SHPB) and plate impact experiments. The internal DIC experimental technique is successfully demonstrated in both the SHPB and plate impact experiments. In the SHPB setting, the accuracy of the technique is excellent throughout the deformation regime, with measurement noise of approximately 0.2% strain. In the case of plate impact experiments, the technique performs well, with error and measurement noise of 1% strain. The internal DIC technique has been developed and demonstrated to work well for full-scale dynamic high-strain rate and shock laboratory experiments, and the accuracy is quantified. Here, the technique can aid in investigating the physics and mechanics of the dynamic behavior of materials, including local deformation fields around dynamically loaded material heterogeneities.

36 MATERIALS SCIENCE↗