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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Chaotic Dynamics Driven by Particle-Core Interactions

High-intensity beams in modern linacs are frequently encircled by diffuse halos, which drive sustained particle losses and result in gradual degradation of accelerating structures. In large part, the growth of halos is facilitated by internal space-charge forces within the beams, and detailed characterization of this process constitutes an active area of ongoing research. A partial understanding of dynamics that ensue within space-charge dominated beams is presented by the particle-core interaction paradigm – a mathematical model wherein single particle dynamics, subject to the collective potential of the core, are treated as a proxy for the broader behavior of the beam. In this work, we investigate the conditions for the onset of large-scale chaos within the framework of this model, and demonstrate that the propensity towards stochastic evolution is strongly dependent upon the charge distribution of the beam. In particular, we show that while particle motion within a uniformly charged beam is dominantly regular, rapid deterministic chaos readily arises within space-charge dominated Gaussian beams. Importantly, we find that for sufficiently high values of the beam’s space charge and beam pulsation amplitude, enhanced chaotic mixing between the core and the halo can lead to an enhanced radial diffusion of charged particles. We explain our results from analytic grounds by demonstrating that chaotic motion is driven by the intersection of two principal resonances of the system, and derive the relevant overlap conditions. Additionally, our analysis illuminates a close connection between the mathematical formulation of the particle-core interaction model and the Andoyer family of integrable Hamiltonians

43 PARTICLE ACCELERATORS↗
NASA NTRS2006

The Sugar Model: Autocatalytic Activity of the Triose-Ammonia Reaction

Reaction of triose sugars with ammonia under anaerobic conditions yielded autocatalytic products. The autocatalytic behavior of the products was examined by measuring the effect of the crude triose-ammonia reaction product on the kinetics of a second identical triose-ammonia reaction. The reaction product showed autocatalytic activity by increasing both the rate of disappearance of triose and the rate formation of pyruvaldehyde, the product of triose dehydration. This synthetic process is considered a reasonable model of origin-of-life chemistry because it uses plausible prebiotic substrates, and resembles modern biosynthesis by employing the energized carbon groups of sugars to drive the synthesis of autocatalytic molecules.

Weber, Arthur L.↗
NASA NTRS2016

Predictive Simulation of Gas Adsorption in Fixed-Beds and Limitations due to the Ill-Posed Danckwerts Boundary Condition

The 1-D axially dispersed plug flow model is a mathematical model widely used for the simulation of adsorption processes. Lumped mass transfer coefficients such as the Glueckauf linear driving force (LDF) term and the axial dispersion coefficient are generally obtained by fitting simulation results to the experimental breakthrough test data. An approach is introduced where these parameters, along with the only free parameter in the energy balance equations, are individually fit to specific test data that isolates the appropriate physics. It is shown that with this approach this model provides excellent simulation results for the C02 on zeolite SA sorbent/sorbate system; however, for the H20 on zeolite SA system, non-physical deviations from constant pattern behavior occur when fitting dispersive experimental results with a large axial dispersion coefficient. A method has also been developed that determines a priori what values of the LDF and axial dispersion terms will result in non-physical simulation results for a specific sorbent/sorbate system when using the one-dimensional axially dispersed plug flow model. A relationship between the steepness of the adsorption equilibrium isotherm as indicated by the distribution factor, the magnitude of the axial dispersion and mass transfer coefficient, and the resulting non-physical behavior is derived. This relationship is intended to provide a guide for avoiding non-physical behavior by limiting the magnitude of the axial dispersion term on the basis of the mass transfer coefficient and distribution factor.

Knox, James Clinton↗
DOE OSTI2019

Multicomponent and Multiphase Lipid Nanotubes Formed by Gliding Microtubule-Kinesin Motility and Phase-Separated Giant Unilamellar Vesicles

Cytoskeletal filaments and motor proteins are critical components in the transport and reorganization of membrane-based organelles in eukaryotic cells. Previous studies have recapitulated the microtubule-kinesin transport system in vitro to dynamically assemble large-scale nanotube networks from multilamellar liposomes and polymersomes. Moving toward more biologically relevant systems, this work examines whether lipid nanotube (LNT) networks can be generated from giant unilamellar vesicles (GUVs) and subsequently characterizes how the lipid composition may be tuned to alter the dynamics, structure, and fluidity of networks. Here, we describe a two-step process in which microtubule motility (i) drives the transport and aggregation of GUVs to form structures with a decreased energy barrier for LNT formation and (ii) extrudes LNTs without destroying parent GUVs, allowing for the formation of large LNT networks. We further show that the lipid composition of the GUV influences formation and morphology of the extruded LNTs and associated networks. For example, LNTs formed from phase-separated GUVs (e.g., liquid–solid phase-separated and coexisting liquid-ordered and liquid-disordered phase-separated) display morphologies related to the specific phase behavior reflective of the parent GUVs. Overall, the ability to form nanotubes from compositionally complex vesicles opens the door to generating lipid networks that more closely mimic the structure and function of those found in cellular systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Metastable phase transformation and hcp-ω transformation pathways in Ti and Zr under high hydrostatic pressures

The energy landscape of Zr at high hydrostatic pressure suggests that its transformation behavior is strongly pressure dependent. This is in contrast to the known transition mechanism in Ti, which is essentially independent of hydrostatic pressure. Generalized solid-state nudged elastic band calculations at constant pressure shows that α-Zr transforms like Ti only at the lowest pressure inside the stability field of ω-phase. Different pathways apply at higher pressures where the energy landscape contains several high barriers so that metastable states are expected, including the appearance of a transient bcc phase at ca. 23 GPa. The global driving force for the hcp-ω transition increases strongly with increasing pressure and reaches 23.7 meV/atom at 23 GPa. Much of this energy relates to the excess volume of the hcp phase compared with its ω phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Evaluate the System-Level Impact of Connected and Automated Vehicles Coupled with Shared Mobility: An Agent-based Simulation Approach

With the rapid growth of information and communication technologies, Connected and Automated Vehicles (CAVs) are deemed to be disruptive with the potential to significantly improve overall transportation system efficiency, however, may bring Vehicle Miles Traveled (VMT) increase or other issues. Further, shared mobility systems are another disruptive force that is reshaping our travel patterns. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance and energy efficiency, we develop a mesoscopic simulation-based framework for mobility and energy efficiency evaluation considering the disruptive transportation technologies. Under this framework, we develop novel models for energy intensity and modal activity, and evaluated a variety of energy scenarios for different combinations of CAV applications, various levels of automation, roadway characteristics, and traffic conditions, while also varying different vehicle types and fuel/powertrain technologies. Based applying this modeling suite to a calibrated BEAM simulation network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes.

42 ENGINEERING↗
NASA NTRS1988

Resonance absorption of compressible magnetohydrodynamic waves at thin 'surfaces'

The behavior of plasma and fields in the transition layer supporting MHD surface waves is analyzed, assuming that the total pressure fluctuations, delta-P(tot), can be taken to be nearly constant across this thin transition layer, with a value nearly the same as would be obtained if the MHD wave were supported by a truly discontinuous surface. Regarding therefore delta-P(tot) as known, the plasma and field equations in the transition layer were cast into a form in which delta-P(tot) appeared as a driving term. Among the two resonances that appear (the cusp resonance and the Alfven resonance) special attention is given to the Alfven resonance, which affects the velocity and magnetic field components normal to the background magnetic field. The effects of three types of viscosity on the Alfven resonance are considered, and it is shown that energy is pumped out of the surface wave into thin layers surrounding the resonant field lines.

Hollweg, Joseph V.↗
NASA NTRS1991

Unsteady surface pressure measurements on a slender delta wing undergoing limit cycle wing rock

An experimental investigation of slender wing limit cycle motion known as wing rock was investigated using two unique experimental systems. Dynamic roll moment measurements and visualization data on the leading edge vortices were obtained using a free to roll apparatus that incorporates an airbearing spindle. In addition, both static and unsteady surface pressure data was measured on the top and bottom surfaces of the model. To obtain the unsteady surface pressure data a new computer controller drive system was developed to accurately reproduce the free to roll time history motions. The data from these experiments include, roll angle time histories, vortex trajectory data on the position of the vortices relative to the model's surface, and surface pressure measurements as a function of roll angle when the model is stationary or undergoing a wing rock motion. The roll time history data was numerically differentiated to determine the dynamic roll moment coefficient. An analysis of these data revealed that the primary mechanism for the limit cycle behavior was a time lag in the position of the vortices normal to the wing surface.

Arena, Andrew S., Jr.↗
NASA NTRS1993

A model for the hydrologic and climatic behavior of water on Mars

An analysis is carried out of the hydrologic response of a water-rich Mars to climate change and to the physical and thermal evolution of its crust, with particular attention given to the potential role of the subsurface transport, assuming that the current models of insolation-driven change describe reasonably the atmospheric leg of the planet's long-term hydrologic cycle. Among the items considered are the thermal and hydrologic properties of the crust, the potential distribution of ground ice and ground water, the stability and replenishment of equatorial ground ice, basal melting and the polar mass balance, the thermal evolution of the early cryosphere, the recharge of the valley networks and outflow, and several processes that are likely to drive the large-scale vertical and horizontal transport of H2O within the crust. The results lead to the conclusion that subsurface transport has likely played an important role in the geomorphic evolution of the Martian surface and the long-term cycling of H2O between the atmosphere, polar caps, and near-surface crust.

Clifford, Stephen M.↗
DOE OSTI2019

Synthesis and structure of Sr 14 Zn 1+ x As 11 and Eu 14 Zn 1+ x As 11 (x ≤ 0.5). New members of the family of pnictides isotypic with Ca 14 AlSb 11 , exhibiting a new type of structural disorder

Systematic investigation of the ternary systems A–Zn–As (A = Sr, Eu) led to the discovery of two new ternary phases, Sr 14 Zn 1+x As 11 and Eu 14 Zn 1+x As 11 (x ≤ 0.5). Both title compounds were structurally characterized by single-crystal X-ray diffraction. The basic structure of these new arsenides is akin to that of the numerous other pnictides adopting the tetragonal Ca 14 AlSb 11 structure type (space group I4 1 / acd (No. 142); Z = 8). The main difference is the presence of an interstitial Zn atom, located in a nearly trigonal-planar coordination environment of three As atoms. Four such fragments share common edges with the regular ZnAs 4 tetrahedron, to form an unusual new structural unit with the formula [Zn 1+x Sb 8] . The small uptake of additional zinc is needed to augment the overall valence electron count, thereby driving the system to an electronically charge-balanced state. Upon partial substitution of the nominally divalent Sr with a trivalent La, the equivalent of electron doping, the structure rids itself of the interstitial zinc, as demonstrated on the example of Sr 13.30(2) La 0.70 ZnAs 11 , which was also structurally characterized by single-crystal X-ray diffraction as part of this study. In conclusion, electronic structure calculations for the idealized composition Sr 14 ZnAs 11 confirm the speculated electron-deficient assignment, and suggest intrinsic semiconducting behavior for the one-electron richer Sr 14 Zn 1+x As 11 (x = 0.5) and Sr 13 LaZnAs 11 , respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Initially Disordered, Reflectin Assembly Tunably and Reversibly Drives Biophotonic Color

Reflectin proteins are found in the reflective Bragg lamellae in skin cells of certain squids, where they tunably control color for camouflage and communication. Initially disordered in the monomeric form, the reflectins have unusual amino acid compositions and are block copolymers consisting of polyampholytic canonical repeats interspersed with cationic linkers. In vivo, phosphorylation of the cationic linkers induces condensation, secondary folding and hierarchical assembly of the reflectins with concomitant emergence of tunable iridescence. We analyzed the folding and assembly of recombinant phospho‐mimetic and deletion mutants of reflectin, using pH titration as a surrogate for in vivo phosphorylation. Results of dynamic light scattering, transmission electron microscopy, fluorescence, circular dichroism and x‐ray scattering reveal that neutralization of the cationic linkers progressively and reversibly drives the reflectins to form monodisperse spherical assemblies of reproducible size. These analyses reveal a strongly predictive relationship between net charge density and size of the assembled reflectin multimers, with the switch appearing to be equally distributed across the spatially segregated linkers. Accompanying the progressive neutralization of Coulombic repulsion of the linkers, assembly appears to be driven by entropically driven folding of the canonical repeats into amphiphilic secondary structures that are likely to enable hierarchical assembly. These results suggest a model for tunable reflectin assembly and provide insight into the behavior of this unique, initially disordered protein. Support or Funding Information This research was supported by the U.S. Department of Energy, U.S. Army Research Office, and Institute of Collaborative Biotechnologies. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Levenson, Robert↗
DOE OSTI2014

Controlled ambient and temperature treatment of InGaZnO thin film transistors for improved bias-illumination stress reliability

The failure mechanisms arising from the instability in operation of indium gallium zinc oxide based thin film transistors (TFTs) upon prolonged real application stresses (bias and illumination) have been extensively studied and reported. Positive and negative gate bias conditions, along with high photonic energy wavelengths within visible light spectrum are used as stress conditions. The increased carrier concentration due to photonic excitation of defects within bandgap and ionization of deep level vacancies is compensated by the reduction in off currents under illumination due to the trapping of carriers in the intermetal dielectric. Band lowering at the source-channel junction due to accumulation of negative carriers repelled due to negative gate bias stress further causes high carrier flow into the channel and drives the devices into failure. The defect identification during failure and degradation assisted in proposing suitable low temperature post processing in specific ambients. Reliability tests after specific anneals in oxygen, vacuum, and forming gas ambients confirm the correlation of the defect type with anneal ambient. Annealed TFTs demonstrate high stabilities under illumination stresses and do not fail when subjected to combined stresses that cause failure in as-fabricated TFTs. Oxygen and forming gas anneals are impactful on the reliability and opens an area of study on donor and vacancy behavior in amorphous mixed oxide based TFTs. The subthreshold swing, field-effect mobilities, and off currents provide knowledge on best anneal practices by understanding role of hydrogen and oxygen in vacancy annihilation and transistor switching properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Elucidating Abnormal Grain Growth in Thermomagnetic Processed Materials with Transfer Learning and Reinforcement Learning

The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring Object Detection and Image Classification Tasks for Niche Use Case in Naturalistic Driving Studies

Naturalistic driving studies consist of drivers using their personal vehicles and provide valuable real-world data, but privacy issues must be handled very carefully. Drivers sign a consent form when they elect to participate, but passengers do not for a variety of practical reasons. However, their privacy must still be protected. One large study includes a blurred image of the entire cabin which allows reviewers to find passengers in the vehicle; this protects the privacy but still allows a means of answering questions regarding the impact of passengers on driver behavior. A method for automatically counting the passengers would have scientific value for transportation researchers. We investigated different image analysis methods for automatically locating and counting the non-drivers including simple face detection and fine-tuned methods for image classification and a published object detection method. We also compared the image classification using convolutional neural network and vision transformer backbones. Our studies show the image classification method appears to work the best in terms of absolute performance, although we note the closed nature of our dataset and nature of the imagery makes the application somewhat niche and object detection methods also have advantages. We perform some analysis to support our conclusion.

Peruski, Ryan↗
DOE OSTI2016

SHEAR-DRIVEN DYNAMO WAVES IN THE FULLY NONLINEAR REGIME

Large-scale dynamo action is well understood when the magnetic Reynolds number ( Rm ) is small, but becomes problematic in the astrophysically relevant large Rm limit since the fluctuations may control the operation of the dynamo, obscuring the large-scale behavior. Recent works by Tobias and Cattaneo demonstrated numerically the existence of large-scale dynamo action in the form of dynamo waves driven by strongly helical turbulence and shear. Their calculations were carried out in the kinematic regime in which the back-reaction of the Lorentz force on the flow is neglected. Here, we have undertaken a systematic extension of their work to the fully nonlinear regime. Helical turbulence and large-scale shear are produced self-consistently by prescribing body forces that, in the kinematic regime, drive flows that resemble the original velocity used by Tobias and Cattaneo. We have found four different solution types in the nonlinear regime for various ratios of the fluctuating velocity to the shear and Reynolds numbers. Some of the solutions are in the form of propagating waves. Some solutions show large-scale helical magnetic structure. Both waves and structures are permanent only when the kinetic helicity is non-zero on average.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Investigation of particle and vapor wall-loss effects on controlled wood-smoke smog-chamber experiments

Here, smog chambers are extensively used to study processes that drive gas and particle evolution in the atmosphere. A limitation of these experiments is that particles and gas-phase species may be lost to chamber walls on shorter timescales than the timescales of the atmospheric processes being studied in the chamber experiments. These particle and vapor wall losses have been investigated in recent studies of secondary organic aerosol (SOA) formation, but they have not been systematically investigated in experiments of primary emissions from combustion. The semi-volatile nature of combustion emissions (e.g. from wood smoke) may complicate the behavior of particle and vapor wall deposition in the chamber over the course of the experiments due to the competition between gas/particle and gas/wall partitioning. Losses of vapors to the walls may impact particle evaporation in these experiments, and potential precursors for SOA formation from combustion may be lost to the walls, causing underestimations of aerosol yields. Here, we conduct simulations to determine how particle and gas-phase wall losses contributed to the observed evolution of the aerosol during experiments in the third Fire Lab At Missoula Experiment (FLAME III). We use the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm coupled with the organic volatility basis set (VBS) and wall-loss formulations to examine the predicted extent of particle and vapor wall losses. We limit the scope of our study to the dark periods in the chamber before photo-oxidation to simplify the aerosol system for this initial study. Our model simulations suggest that over one-third of the initial particle-phase organic mass (41 %) was lost during the experiments, and over half of this particle-organic mass loss was from direct particle wall loss (65 % of the loss) with the remainder from evaporation of the particles driven by vapor losses to the walls (35 % of the loss). We perform a series of sensitivity tests to understand uncertainties in our simulations. Uncertainty in the initial wood-smoke volatility distribution contributes 18 % uncertainty to the final particle-organic mass remaining in the chamber (relative to base-assumption simulation). We show that the total mass loss may depend on the effective saturation concentration of vapor with respect to the walls as these values currently vary widely in the literature. The details of smoke dilution during the filling of smog chambers may influence the mass loss to the walls, and a dilution of ~ 25:1 during the experiments increased particle-organic mass loss by 33 % compared to a simulation where we assume the particles and vapors are initially in equilibrium in the chamber. Finally, we discuss how our findings may influence interpretations of emission factors and SOA production in wood-smoke smog-chamber experiments.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗
NASA NTRS1998

GPS Monitoring of Surface Change During and Following the Fortuitous Occurrence of the M(sub w) = 7.3 Landers Earthquake in our Network

Accomplishments: (1) Continues GPS monitoring of surface change during and following the fortuitous occurrence of the M(sub w) = 7.3 Landers earthquake in our network, in order to characterize earthquake dynamics and accelerated activity of related faults as far as 100's of kilometers along strike. (2) Integrates the geodetic constraints into consistent kinematic descriptions of the deformation field that can in turn be used to characterize the processes that drive geodynamics, including seismic cycle dynamics. In 1991, we installed and occupied a high precision GPS geodetic network to measure transform-related deformation that is partitioned from the Pacific - North America plate boundary northeastward through the Mojave Desert, via the Eastern California shear zone to the Walker Lane. The onset of the M(sub w) = 7.3 June 28, 1992, Landers, California, earthquake sequence within this network poses unique opportunities for continued monitoring of regional surface deformation related to the culmination of a major seismic cycle, characterization of the dynamic behavior of continental lithosphere during the seismic sequence, and post-seismic transient deformation. During the last year, we have reprocessed all three previous epochs for which JPL fiducial free point positioning products available and are queued for the remaining needed products, completed two field campaigns monitoring approx. 20 sites (October 1995 and September 1996), begun modeling by development of a finite element mesh based on network station locations, and developed manuscripts dealing with both the Landers-related transient deformation at the latitude of Lone Pine and the velocity field of the whole experiment. We are currently deploying a 1997 observation campaign (June 1997). We use GPS geodetic studies to characterize deformation in the Mojave Desert region and related structural domains to the north, and geophysical modeling of lithospheric behavior. The modeling is constrained by our existing and continued GPS measurements, which will provide much needed data on far-field strain accumulation across the region and on the deformational response of continental lithosphere during and following a large earthquake, forming the basis for kinematic and dynamic modeling of secular and seismic-cycle deformation. GPS geodesy affords both regional coverage and high precision that uniquely bear on these problems.

Miller, M. Meghan↗