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Results for “dynamic characterization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Cell-machine interfaces for characterizing gene regulatory network dynamics

Gene regulatory networks and the dynamic responses theyproduce offer a wealth of information about how biologicalsystems process information about their environment.Recently, researchers interested in dissecting these networkshave been outsourcing various parts of their experimentalworkflow to computers. Here we review how, using microfluidicor optogenetic tools coupled with fluorescence imaging, it isnow possible to interface cells and computers. These platformsenable scientists to perform informative dynamic stimulationsof genetic pathways and monitor their reaction. It is alsopossible to close the loop and regulate genes in real time,providing an unprecedented view of how signals propagatethrough the network. Finally, we outline new tools that can beused within the framework of cell–machine interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Characterization of plasma expansion dynamics in a high power diode with a carbon-fiber-aluminum cathode

Thermal plasma expansion is characterised during the operation of a high power diode with an explosive emission carbon-fiber-aluminum cathode driven by a 250 kV, 150 ns accelerating pulse. It is found that a quasi-stationary state of plasma expansion is obtained during the main part of the accelerating pulse and the whole plasma expansion exhibits an “U”-shape velocity evolution. A theoretical model describing the dynamics of plasma expansion is developed, which indicates that the plasma expansion velocity is determined by equilibrium between the diode current density and plasma thermal electron current density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Characterizing magnetized plasmas with dynamic mode decomposition

Accurate and efficient plasma models are essential to understand and control experimental devices. Existing magnetohydrodynamic or kinetic models are nonlinear and computationally intensive and can be difficult to interpret, while often only approximating the true dynamics. In this work, data-driven techniques recently developed in the field of fluid dynamics are leveraged to develop interpretable reduced-order models of plasmas that strike a balance between accuracy and efficiency. In particular, dynamic mode decomposition (DMD) is used to extract spatio-temporal magnetic coherent structures from the experimental and simulation datasets of the helicity injected torus with steady inductive (HIT-SI) experiment. Three-dimensional magnetic surface probes from the HIT-SI experiment are analyzed, along with companion simulations with synthetic internal magnetic probes. A number of leading variants of the DMD algorithm are compared, including the sparsity-promoting and optimized DMD. Optimized DMD results in the highest overall prediction accuracy, while sparsity-promoting DMD yields physically interpretable models that avoid overfitting. These DMD algorithms uncover several coherent magnetic modes that provide new physical insights into the inner plasma structure. These modes were subsequently used to discover a previously unobserved three-dimensional structure in the simulation, rotating at the second injector harmonic. Finally, using data from probes at experimentally accessible locations, DMD identifies a resistive kink mode, a ubiquitous instability seen in magnetized plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Experimental characterization of discharge plasma dynamics in a square capillary for prospective applications in laser wakefield acceleration

Research on plasma generated by electrical discharge in gas-filled capillaries plays an important role in advancing laser wakefield accelerators. We present a comprehensive study of the temporal and spatial distribution of plasma density within a short, 1 cm long, square-shaped capillary filled with hydrogen gas. Two transverse capillary sizes, 500 μm and 300 μm, were investigated achieving peak plasma densities of 0.9 × 10 18 cm −3 and 2.5 × 10 18 cm −3 , respectively, at the capillary center. In addition, we explore how these distributions depend on discharge parameters, specifically discharge current and gas flow through the capillary. Plasma density was determined by analyzing the Stark broadening of the hydrogen Balmer-alpha line. The results obtained were compared with the theoretical models and simulations. The comparison between the model predictions and the experimental data at the transient ionization stage of the discharge reveals a discrepancy of a factor of ∼1.3–2.1, depending on the capillary size, which is thoroughly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

CHARACTERIZING THE ORBITAL AND DYNAMICAL STATE OF THE HD 82943 PLANETARY SYSTEM WITH KECK RADIAL VELOCITY DATA

We present an updated analysis of radial velocity data of the HD 82943 planetary system based on 10 yr of measurements obtained with the Keck telescope. Previous studies have shown that the HD 82943 system has two planets that are likely in 2:1 mean-motion resonance (MMR), with orbital periods about 220 and 440 days. However, alternative fits that are qualitatively different have also been suggested, with two planets in a 1:1 resonance or three planets in a Laplace 4:2:1 resonance. Here we use χ{sup 2} minimization combined with a parameter grid search to investigate the orbital parameters and dynamical states of the qualitatively different types of fits, and we compare the results to those obtained with the differential evolution Markov chain Monte Carlo method. Our results support the coplanar 2:1 MMR configuration for the HD 82943 system, and show no evidence for either the 1:1 or three-planet Laplace resonance fits. The inclination of the system with respect to the sky plane is well constrained at 20{sup +4.9}{sub -5.5} degrees, and the system contains two planets with masses of about 4.78 M{sub J} and 4.80 M{sub J} (where M{sub J} is the mass of Jupiter) and orbital periods of about 219 and 442 days for the inner and outer planet, respectively. The best fit is dynamically stable with both eccentricity-type resonant angles θ{sub 1} and θ{sub 2} librating around 0°.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Automated characterization of spatial and dynamical heterogeneity in supercooled liquids via implementation of machine learning

Abstract A computational approach by an implementation of the principle component analysis (PCA) with K -means and Gaussian mixture (GM) clustering methods from machine learning algorithms to identify structural and dynamical heterogeneities of supercooled liquids is developed. In this method, a collection of the average weighted coordination numbers ( W C N s ‾ ) of particles calculated from particles’ positions are used as an order parameter to build a low-dimensional representation of feature (structural) space for K -means clustering to sort the particles in the system into few meso-states using PCA. Nano-domains or aggregated clusters are also formed in configurational (real) space from a direct mapping using associated meso-states’ particle identities with some misclassified interfacial particles. These classification uncertainties can be improved by a co-learning strategy which utilizes the probabilistic GM clustering and the information transfer between the structural space and configurational space iteratively until convergence. A final classification of meso-states in structural space and domains in configurational space are stable over long times and measured to have dynamical heterogeneities. Armed with such a classification protocol, various studies over the thermodynamic and dynamical properties of these domains indicate that the observed heterogeneity is the result of liquid–liquid phase separation after quenching to a supercooled state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2011

Experimental characterization of energetic material dynamics for multiphase blast simulation.

Currently there is a substantial lack of data for interactions of shock waves with particle fields having volume fractions residing between the dilute and granular regimes, which creates one of the largest sources of uncertainty in the simulation of energetic material detonation. To close this gap, a novel Multiphase Shock Tube has been constructed to drive a planar shock wave into a dense gas-solid field of particles. A nearly spatially isotropic field of particles is generated in the test section by a gravity-fed method that results in a spanwise curtain of spherical 100-micron particles having a volume fraction of about 19%. Interactions with incident shock Mach numbers of 1.66, 1.92, and 2.02 were achieved. High-speed schlieren imaging simultaneous with high-frequency wall pressure measurements are used to reveal the complex wave structure associated with the interaction. Following incident shock impingement, transmitted and reflected shocks are observed, which lead to differences in particle drag across the streamwise dimension of the curtain. Shortly thereafter, the particle field begins to propagate downstream and spread. For all three Mach numbers tested, the energy and momentum fluxes in the induced flow far downstream are reduced about 30-40% by the presence of the particle field. X-Ray diagnostics have been developed to penetrate the opacity of the flow, revealing the concentrations throughout the particle field as it expands and spreads downstream with time. Furthermore, an X-Ray particle tracking velocimetry diagnostic has been demonstrated to be feasible for this flow, which can be used to follow the trajectory of tracer particles seeded into the curtain. Additional experiments on single spherical particles accelerated behind an incident shock wave have shown that elevated particle drag coefficients can be attributed to increased compressibility rather than flow unsteadiness, clarifying confusing results from the historical database of shock tube experiments. The development of the Multiphase Shock Tube and associated diagnostic capabilities offers experimental capability to a previously inaccessible regime, which can provide unprecedented data concerning particle dynamics of dense gas-solid flows.

36 MATERIALS SCIENCE↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence Q - Raw Data

Sequence Q: Dynamic Inflow (P) This sequence was designed to characterize the dynamic inflow variation using the five-hole probes that extend upwind of the leading edge of the blade. This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speeds ranged from 5 m/s to 15 m/s, and data were collected at a 0° yaw angle. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to -99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. The blade pitch angle was changed from the initial tip pitch angle to the final tip pitch angle at the maximum rate of 67°/s. This angle was maintained for the specified delay time duration. Then the blade was pitched back to the initial pitch angle and held for the specified hold time. This was repeated 20 times. The campaign at 15 m/s was aborted early due to excessive low-speed shaft torque loads. The file length varied depending on the time required to obtain 20 pitch cycles for the specified range of angles. The name convention was the standard format, except for the short campaigns collected to ascertain the functionality of the instrumentation. These points were collected at a 3° pitch angle and use the characters REF in the four digits that normally represent yaw angle.

17 WIND ENERGY↗
DOE OSTI2014

Characterization of protein redox dynamics induced during light-to-dark transitions and nutrient limitation in cyanobacteria

Protein redox chemistry constitutes a major void in knowledge pertaining to photoautotrophic system regulation and signaling processes. We have employed a chemical biology approach to analyze redox sensitive proteins in live Synechococcus sp. PCC 7002 cells in both light and dark periods, and to understand how cellular redox balance is disrupted during nutrient perturbation. The present work identified several novel putative redox-sensitive proteins that are involved in the generation of reductant, macromolecule synthesis, and carbon flux through central metabolic pathways, and may be involved in cell signaling and response mechanisms. Furthermore, our research suggests that dynamic redox changes in response to specific nutrient limitations contribute to the regulatory changes driven by a shift from light to dark. Taken together, these results contribute to the high-level understanding of post-translational mechanisms regulating flux distributions and therefore present potential metabolic engineering targets for redirecting carbon towards biofuel precursors.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2021

In-Situ Characterization of Pore Formation Dynamics in Pulsed Wave Laser Powder Bed Fusion

Laser powder bed fusion (LPBF) is an additive manufacturing technology with the capability of printing complex metal parts directly from digital models. Between two available emission modes employed in LPBF printing systems, pulsed wave (PW) emission provides more control over the heat input compared to continuous wave (CW) emission, which is highly beneficial for printing parts with intricate features. However, parts printed with pulsed wave LPBF (PW-LPBF) commonly contain pores, which degrade their mechanical properties. In this study, we reveal pore formation mechanisms during PW-LPBF in real time by using an in-situ high-speed synchrotron x-ray imaging technique. We found that vapor depression collapse proceeds when the laser irradiation stops within one pulse, resulting in occasional pore formation during PW-LPBF. We also revealed that the melt ejection and rapid melt pool solidification during pulsed-wave laser melting resulted in cavity formation and subsequent formation of a pore pattern in the melted track. The pore formation dynamics revealed here may provide guidance on developing pore elimination approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bayesian chain graph models to characterize microbe-environment dynamics

Microbiome data require statistical models that can simultaneously decode microbes' reaction to the environment and interactions among microbes. While a multiresponse linear regression model seems like a straight-forward solution, we argue that treating it as a graphical model is problematic given that the regression coefficient matrix does not encode the conditional dependence structure between response and predictor nodes. This observation is especially important in biological settings when we have prior knowledge on the edges from specific experimental interventions that can only be properly encoded under a conditional dependence model. Here, we propose a chain graph model with two sets of nodes (predictors and responses) whose solution yields a graph with edges that indeed represent conditional dependence, thus agreeing with the experimenter's intuition on the average behavior of nodes under treatment. The solution to our model is sparse via the Bayesian linear regression (LASSO). In addition, we propose an adaptive extension so that different shrinkages can be applied to different edges to incorporate edge-specific prior knowledge. Our model is computationally inexpensive through an efficient Gibbs sampling algorithm and can account for binary, counting, and compositional responses via an appropriate hierarchical structure. We test the performance of our model in a variety of simulated datasets, thereby showing superior performance to state-of-the-art approaches. We further apply our model to human gut and soil microbial compositional datasets, and we highlight that CG-LASSO can estimate biologically meaningful network structures in the data.

compositional data↗
NASA NTRS2011

Characterization of Terrestrial Water Dynamics in the Congo Basin Using GRACE and Satellite Radar Altimetry

The Congo Basin is the world's third largest in size (approx.3.7 million sq km), and second only to the Amazon River in discharge (approx.40,200 cu m/s annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3deg 3deg regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 cu km, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.

Lee, Hyongki↗