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Results for “Dynamic Timing Analysis”

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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Revealing spatially heterogeneous relaxation in a model nanocomposite

The detailed nature of spatially heterogeneous dynamics of glycerol-silica nanocomposites is unraveled by combining dielectric spectroscopy with atomistic simulation and statistical mechanical theory. Analysis of the spatial mobility gradient shows no “glassy” layer, but the α-relaxation time near the nanoparticle grows with cooling faster than the α-relaxation time in the bulk and is ∼20 times longer at low temperatures. The interfacial layer thickness increases from ∼1.8 nm at higher temperatures to ∼3.5 nm upon cooling to near bulk T{sub g}. A real space microscopic description of the mobility gradient is constructed by synergistically combining high temperature atomistic simulation with theory. Our analysis suggests that the interfacial slowing down arises mainly due to an increase of the local cage scale barrier for activated hopping induced by enhanced packing and densification near the nanoparticle surface. The theory is employed to predict how local surface densification can be manipulated to control layer dynamics and shear rigidity over a wide temperature range.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Analysis of cardiomyocyte movement in the developing murine heart

The precise assemblage of several types of cardiac precursors controls heart organogenesis. The cardiac precursors show dynamic movement during early development and then form the complicated heart structure. However, cardiomyocyte movements inside the newly organized mammalian heart remain unclear. We previously established the method of ex vivo time-lapse imaging of the murine heart to study cardiomyocyte behavior by using the Fucci (fluorescent ubiquitination-based cell cycle indicator) system, which can effectively label individual G1, S/G2/M, and G1/S-transition phase nuclei in living cardiomyocytes as red, green, and yellow, respectively. Global analysis of gene expression in Fucci green positive ventricular cardiomyocytes confirmed that cell cycle regulatory genes expressed in G1/S, S, G2/M, and M phase transitions were upregulated. Interestingly, pathway analysis revealed that many genes related to the cell cycle were significantly upregulated in the Fucci green positive ventricular cardiomyocytes, while only a small number of genes related to cell motility were upregulated. Time-lapse imaging showed that murine proliferating cardiomyocytes did not exhibit dynamic movement inside the heart, but stayed on site after entering the cell cycle. - Highlights: • We directly visualized cardiomyocyte movement inside the developing murine heart. • Cell cycle related genes were upregulated in the proliferating cardiomyocytes. • Time-lapse imaging revealed that proliferating murine cardiomyocytes stayed in place. • Murine ventricular cardiomyocytes proliferate on site during development.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Context-aided analysis of community evolution in networks

Here, we are interested in detecting and analyzing global changes in dynamic networks (networks that evolve with time). More precisely, we consider changes in the activity distribution within the network, in terms of density (ie, edge existence) and intensity (ie, edge weight). Detecting change in local properties, as well as individual measurements or metrics, has been well studied and often reduces to traditional statistical process control. In contrast, detecting change in larger scale structure of the network is more challenging and not as well understood. We address this problem by proposing a framework for detecting change in network structure based on separate pieces: a probabilistic model for partitioning nodes by their behavior, a label-unswitching heuristic, and an approach to change detection for sequences of complex objects. We examine the performance of one instantiation of such a framework using mostly previously available pieces. The dataset we use for these investigations is the publicly available New York City Taxi and Limousine Commission dataset covering all taxi trips in New York City since 2009. Using it, we investigate the evolution of an ensemble of networks under different spatiotemporal resolutions. We identify the community structure by fitting a weighted stochastic block model. In conclusion, we offer insights on different node ranking and clustering methods, their ability to capture the rhythm of life in the Big Apple, and their potential usefulness in highlighting changes in the underlying network structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Resolving nanoparticle growth mechanisms from size- and time-dependent growth rate analysis

Atmospheric new particle formation occurs frequently in the global atmosphere and may play a crucial role in climate by affecting cloud properties. The relevance of newly formed nanoparticles depends largely on the dynamics governing their initial formation and growth to sizes where they become important for cloud microphysics. One key to the proper understanding of nanoparticle effects on climate is therefore hidden in the growth mechanisms. In this study we have developed and successfully tested two independent methods based on the aerosol general dynamics equation, allowing detailed retrieval of time- and size-dependent nanoparticle growth rates. Both methods were used to analyze particle formation from two different biogenic precursor vapors in controlled chamber experiments. Our results suggest that growth rates below 10 nm show much more variation than is currently thought and pin down the decisive size range of growth at around 5 nm where in-depth studies of physical and chemical particle properties are needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Dynamical analysis of generalized Galileon cosmology

We perform a detailed dynamical analysis of generalized Galileon cosmology, incorporating also the requirements of ghost and instabilities absence. We find that there are not any new stable late-time solutions apart from those of standard quintessence. Furthermore, depending on the model parameters the Galileons may survive at late times or they may completely disappear by the dynamics, however the corresponding observables are always independent of the Galileon terms, determined only by the usual action terms. Thus, although the Galileons can play an important role at inflationary or at recent times, in the future, when the universe will asymptotically reach its stable state, they will not have any effect on its evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗
DOE OSTI2018

A Small Temperate Lake in the 21st Century: Dynamics of Water Temperature, Ice Phenology, Dissolved Oxygen, and Chlorophyll a

It is unclear how small temperate lakes will evolve physically and biologically in the whole water column under future climate because previous modeling studies usually focused on only one or two physical or biological state variables in the surface waters. To fill this gap, we used a well-validated lake biogeochemistry model driven with different climate scenarios to predict the dynamics of ice phenology, water temperature, dissolved oxygen (DO) and chlorophyll in a small Canadian temperate lake during the 21st century, considering the influence of catchment hydrology. We find that the ice season and ice thickness of the lake would shrink substantially, resulting in a positive energy feedback between climate and the lake. Due to the reduced heat diffusion and water mixing, the dynamics of water temperature in surface waters and deep waters are considerably different, with surface waters warmed dramatically but deep waters muted to warming. The lake DO concentrations would be depleted by warming in the whole column but the controlling processes are depth dependent. The chlorophyll concentration in the lake is inertia to climate change, mainly due to the mismatch of the timings of peak solar radiation and thermal and nutrient optima. Our analysis indicates that the influence of catchment hydrology is large on the dynamics of DO, but not on other state variables we have examined. Finally, this study suggests that small temperate lakes could be sensitive to climate change but their physical and biological responses could be diverse.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Approximate but accurate quantum dynamics from the Mori formalism: I. Nonequilibrium dynamics

We present a formalism that explicitly unifies the commonly used Nakajima-Zwanzig approach for reduced density matrix dynamics with the more versatile Mori theory in the context of nonequilibrium dynamics. Employing a Dyson-type expansion to circumvent the difficulty of projected dynamics, we obtain a self-consistent equation for the memory kernel which requires only knowledge of normally evolved auxiliary kernels. To illustrate the properties of the current approach, we focus on the spin-boson model and limit our attention to the use of a simple and inexpensive quasi-classical dynamics, given by the Ehrenfest method, for the calculation of the auxiliary kernels. For the first time, we provide a detailed analysis of the dependence of the properties of the memory kernels obtained via different projection operators, namely, the thermal (Redfield-type) and population based (NIBA-type) projection operators. We further elucidate the conditions that lead to short-lived memory kernels and the regions of parameter space to which this program is best suited. Via a thorough analysis of the different closures available for the auxiliary kernels and the convergence properties of the self-consistently extracted memory kernel, we identify the mechanisms whereby the current approach leads to a significant improvement over the direct usage of standard semi- and quasi-classical dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Simulation of injector dynamics during steady inductive helicity injection current drive in the HIT-SI experiment

We present simulations of inductive helicity injection in the Helicity Injected Torus with Steady Inductive helicity injection (HIT-SI) device that treats the entire plasma volume in a single dynamic MHD model. A new fully 3D numerical tool, the PSI-center TETrahedral mesh code, was developed that provides the geometric flexibility required for this investigation. Implementation of a zero-β Hall MHD model using PSI-TET will be presented including formulation of a new self-consistent magnetic boundary condition for the wall of the HIT-SI device. Results from simulations of HIT-SI are presented focusing on injector dynamics that are investigated numerically for the first time. Asymmetries in the plasma loading between the two helicity injectors and progression of field reversal in each injector are observed. Analysis indicates cross-coupling between injectors through confinement volume structures. Injector impedance is found to scale with toroidal current at fixed density, consistent with experimental observation. Comparison to experimental data with an injector drive frequency of 14.5 kHz shows good agreement with magnetic diagnostics. Global mode structures from Bi-Orthogonal decomposition agree well with experimental data for the first four modes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the data into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.

algorithm analysis↗
DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2015

Modeling laser-driven electron acceleration using WARP with Fourier decomposition

WARP is used with the recent implementation of the Fourier decomposition algorithm to model laser-driven electron acceleration in plasmas. Simulations were carried out to analyze the experimental results obtained on ionization-induced injection in a gas cell. The simulated results are in good agreement with the experimental ones, confirming the ability of the code to take into account the physics of electron injection and reduce calculation time. We present a detailed analysis of the laser propagation, the plasma wave generation and the electron beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

5-Methoxyquinoline Photobasicity Is Mediated by Water Oxidation

A mechanism explaining the photobasicity of 5-methoxyquinoline (5-MeOQ) is proposed on the basis of nonadiabatic molecular dynamics simulations using time-dependent hybrid density functional theory (TDDFT) and fewest switches surface hopping (SH) and analysis of existing ultrafast spectroscopy experiments. According to the TDDFT-SH simulations, the rate-determining step is hole transfer from photoexcited 5-MeOQ to adjacent water molecules within ~5 ps followed by rapid electron-coupled proton transfer and deactivation to the ground state. This fast redox-catalyzed proton transfer mechanism is consistent with simple thermodynamic arguments, correlated wavefunction calculations, and recent isotope substitution time-resolved fluorescence experiments. Although energetically feasible, direct protonation of 5-MeOQ in the S 1 state appears to be too slow to contribute significantly to 5-MeOQ photobasicity in aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Coherent X-ray spectroscopy reveals the persistence of island arrangements during layer-by-layer growth

Understanding surface dynamics during epitaxial film growth is key to growing high-quality materials with controllable properties. X-ray photon correlation spectroscopy (XPCS) using coherent X-rays opens new opportunities for in situ observation of atomic-scale fluctuation dynamics during crystal growth. Here in this paper, we present XPCS measurements of two-dimensional island dynamics during homoepitaxial growth in the layer-by-layer mode. Analysis of the results using two-time correlations reveals a new phenomenon-a memory effect in the arrangement of islands formed on successive crystal layers. Simulations indicate that this persistence in the island arrangements arises from communication between islands on different layers via adatoms. With the worldwide advent of new coherent X-ray sources, the experimental and analysis methods pioneered here will enable broad application of XPCS to observe atomic-scale processes on surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Remote imaging of concealed objects

Optical detection of objects hidden behind opaque screening layers is a challenging problem. We demonstrate an optically detected echographic-like method that combines collimated acoustic and laser beams. The acoustic waves cross the screening layers and their back-reflection from the hidden objects is detected through the analysis of a dynamic laser speckle pattern created at the outer surface of the screening layer. Real-time remote detection of moving targets 15 meters away, with a few mm resolutions is demonstrated using a very sensitive camera detection scheme.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A Biosequence-based Approach to Software Characterization

For many applications, it is desirable to have some process for recognizing when software binaries are closely related without relying on them to be identical or have identical segments. Some examples include monitoring utilization of high performance computing centers or service clouds, detecting freeware in licensed code, and enforcing application whitelists. But doing so in a dynamic environment is a nontrivial task because most approaches to software similarity require extensive and time-consuming analysis of a binary, or they fail to recognize executables that are similar but nonidentical. Presented herein is a novel biosequence-based method for quantifying similarity of executable binaries. Using this method, it is shown in an example application on large-scale multi-author codes that 1) the biosequence-based method has a statistical performance in recognizing and distinguishing between a collection of real-world high performance computing applications better than 90% of ideal; and 2) an example of using family tree analysis to tune identification for a code subfamily can achieve better than 99% of ideal performance.

cyber security↗