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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Dynamic Networks Experiments: Virtual Experiments to Quantify Gains in Nuclear Explosion Monitoring

We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.

42 ENGINEERING↗
DOE OSTI2022

Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience

In this work, a post-disaster distribution system repair and restoration (DSRR) strategy is proposed to improve distribution system resilience. The DSRR strategy is formulated as a two-stage optimization. The first stage is a comprehensive co-optimization of repair crew scheduling, dynamic network reconfiguration, and distributed energy resource (DER) dispatch based on the forecast load profile. The goal is to minimize the accumulative operating cost caused by the load reduction payment as well as DER operating cost. In particular, since the number of available repair crews is usually smaller than the number of faulted lines after a disaster event, the DSRR strategy determines the optimal scheduling for repairing faulted lines. The second stage is a re-dispatch of the DER power output and load shedding based on the real-time load demand of each bus. The proposed algorithm is validated by case studies of the IEEE 33-bus and 123-bus test systems. We consider those scenarios in which faults occur in multiple heavy-loaded feeders. The simulation results demonstrate that the DSRR strategy effectively coordinate the repair scheduling, network reconfiguration and load shedding to minimize the operating cost.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks

An important task in network analysis is the detection of anomalous events in a network time series. These events could merely be times of interest in the network timeline or they could be examples of malicious activity or network malfunction. Hypothesis testing using network statistics to summarize the behavior of the network provides a robust framework for the anomaly detection decision process. Unfortunately, choosing network statistics that are dependent on confounding factors like the total number of nodes or edges can lead to incorrect conclusions (e.g., false positives and false negatives). In this article, we describe the challenges that face anomaly detection in dynamic network streams regarding confounding factors. We also provide two solutions to avoiding error due to confounding factors: the first is a randomization testing method that controls for confounding factors, and the second is a set of size-consistent network statistics that avoid confounding due to the most common factors, edge count and node count.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

DYNAMIC - The Nonlinear Dynamical Network Simulator v. 0.1

The purpose of the DYNAMIC software system is to perform simulations to validate a new research concept called “Chaotic Logic” which we recently published. The problem to be solved is to simulate certain networks of nonlinearly-interacting dynamical variables, and collect statistics on their behavior, to show that they can reliably perform useful computations. The dynamical trajectories for such networks are computed by time integration of their Hamilton’s equations.

Frank, MichaelP.↗
DOE OSTI2025

Viscosity-Controlled Thiol–Ene Reaction and Its Impact on Mechanical Response of Dynamic Networks

The impact of curing conditions on the final properties of thioester-thiol-based dynamic polymer networks was systematically investigated. Despite identical monomer and cross-linker compositions, networks synthesized in the absence of solvent exhibited significantly higher shear moduli and longer relaxation times compared to those cured in solvent. These differences arise from viscosity-controlled photoinitiated thiol–ene reactions, where reduced chain mobility under solvent-free conditions suppresses termination between two polymer radicals, leading to higher reaction conversion. Fourier Transform Infrared (FTIR) spectroscopy and solid-state NMR (ssNMR) spectroscopy confirmed a greater degree of “click” reaction completion in higher viscosity environments. Control experiments revealed that prolonged radical lifetimes and suppressed termination reactions under solvent-free curing conditions contribute to these variations. Here, this study highlights the crucial role of processing conditions in determining cross-link density and, consequently, the dynamic mechanical behavior of polymer networks. It demonstrates that, beyond polymer chemistry, dynamic cross-linker design, and phase separation, curing conditions serve as a key design parameter for tailoring material performance to specific applications.

polymers↗
DOE OSTI2023

Dynamic Network Analysis of Nuclear Science Literature for Research Influence Assessment

Analyzing nuclear science literature via data-driven methods is a critical step for assessing research influence and technology advancements. Indicators of scholarly activities may be buried in large volumes of nuclear research publications and collaboration networks over time. Mining for relevant scholarly influence trends in large volumes of text can be computationally challenging; however, open-source information on research collaborations over time can offer opportunities to extract meaningful insights. While network centrality analysis of scholarly research provides topology-based insights, additional emphasis on dynamics associated with the diffusion of information through these networks is important. Here this paper represents a step in that direction through the development of a novel dynamic network analysis framework and computational engine to identify key entities and capabilities over time within global scholarly nuclear science collaboration networks. Network theoretic, stochastic simulation, and optimization methods are leveraged to address variability in scholarly interactions, influence propagation, and collaboration patterns via network connections. A topic-aware influence maximization algorithm is developed to address the goal of identifying key influential authors in diverse research topics over time. Efficient parallelized implementation of the algorithm is applied to reduce computational costs. A proof-of-concept case study using open-source Scopus data with 33,517 published nuclear research papers from 2000-2019 is presented and representative analytic insights are generated. Broad implications of these insights are discussed and future research directions are also identified.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

A Scale-Dynamic Network Abstraction Approach for Traffic Analysis

The necessary trade-off between accuracy and efficiency of various traffic simulation tools depends on the resolution of the roadway network. While a detailed high-resolution road network could better represent connectivity of real-world road network and ensure an accurate simulation result, a low-resolution network omitting trivial details could reduce computational burden and improve the computational efficiency of traffic simulation. This study focuses on dynamically adjusting the roadway network resolution during the process of simulation-based dynamic traffic assignment (SBDTA) with the objective to expedite both the simulation and the assignment within SBDTA. We propose to divide the whole time horizon into several periods dynamically and to Abstract the network for each period separately. The result showed that half of the CPU time for both the simulation and the assignment is saved, while the network performance remains consistent or near consistent compared with the scenario using the most detailed network.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Self-organization of network dynamics into local quantized states

Self-organization and pattern formation in network-organized systems emerges from the collective activation and interaction of many interconnected units. A striking feature of these non-equilibrium structures is that they are often localized and robust: only a small subset of the nodes, or cell assembly, is activated. Understanding the role of cell assemblies as basic functional units in neural networks and socio-technical systems emerges as a fundamental challenge in network theory. A key open question is how these elementary building blocks emerge, and how they operate, linking structure and function in complex networks. Here we show that a network analogue of the Swift-Hohenberg continuum model—a minimal-ingredients model of nodal activation and interaction within a complex network—is able to produce a complex suite of localized patterns. Thus, the spontaneous formation of robust operational cell assemblies in complex networks can be explained as the result of self-organization, even in the absence of synaptic reinforcements.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Spatiotemporal control of mitochondrial network dynamics in astroglial cells

Highlights: • Astrocytes display highly complex mitochondrial architectures in vivo. • Mitochondrial trafficking and dynamics in astrocytes are regulated. • Mitochondria critically contribute to astrocyte Ca{sup 2+} handling. • Astrocyte reacting to injury undergo marked changes in mitochondrial dynamics. Mitochondria are increasingly recognized for playing important roles in regulating the evolving metabolic state of mammalian cells. This is particularly true for nerve cells, as dysregulation of mitochondrial dynamics is invariably associated with a number of neuropathies. Accumulating evidence now reveals that changes in mitochondrial dynamics and structure may play equally important roles also in the cell biology of astroglial cells. Astroglial cells display significant heterogeneity in their morphology and specialized functions across different brain regions, however besides fundamental differences they seem to share a surprisingly complex meshwork of mitochondria, which is highly suggestive of tightly regulated mechanisms that contribute to maintain this unique architecture. Here, we summarize recent work performed in astrocytes in situ indicating that this may indeed be the case, with astrocytic mitochondrial networks shown to experience rapid dynamic changes in response to defined external cues. Although the mechanisms underlying this degree of mitochondrial re-shaping are far from being understood, recent data suggest that they may contribute to demarcate astrocyte territories undergoing key signalling and metabolic functions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Identification of Critical Switches for Integrating Renewable Distributed Generation by Dynamic Network Reconfiguration

With growing penetration of renewable distributed generations (DGs) in distribution systems, effective integration of DGs has become a major concern. Distribution system dynamic reconfiguration (DSDR), which relies on real-time operations of remote-controlled switches, is potentially an efficient strategy receiving inadequate attention. Moreover, in most DSDR-related publications, normally all switches are assumed remotely controllable, which is not practical. Here we borrow the concept of critical switches to denote the switches that are most effective in accommodating DGs by DSDR. In this regard, the problem of identifying critical switches is not well investigated, although in several related publications, selected switches are assumed remote-controlled based on experience. In this work, we study the application of DSDR for DG integration. Critical switches, which optimally enable intra-day DSDR to minimize DG curtailments, are identified by limiting the number of switches to be operated and the switch-type-dependent operation constraints. Considering uncertainties of loads and DGs, the problem is formulated as a two-stage robust optimization model solved by a nested column-and-constraint generation algorithm. Illustrative cases show that DG curtailments can be significantly reduced by a small number of critical switches that operate only several times in intra-day DSDR. The proposed method can be used to provide insights for switch allocation, maintenance, and operation

Lei, Shunbo (ORCID:0000000181690821)↗
DOE OSTI2023

Simulation study of the effects of polymer network dynamics and mesh confinement on the diffusion and structural relaxation of penetrants

The diffusion of small molecular penetrants through polymeric materials represents an important fundamental problem, relevant to the design of materials for applications such as coatings and membranes. Polymer networks hold promise in these applications because dramatic differences in molecular diffusion can result from subtle changes in the network structure. In this paper, we use molecular simulation to understand the role that cross-linked network polymers have in governing the molecular motion of penetrants. By considering the local, activated alpha relaxation time of the penetrant and its long-time diffusive dynamics, we can determine the relative importance of activated glassy dynamics on penetrants at the segmental scale vs entropic mesh confinement on penetrant diffusion. We vary several parameters, such as the cross-linking density, temperature, and penetrant size, to show that cross-links primarily affect molecular diffusion through the modification of the matrix glass transition, with local penetrant hopping at least partially coupled to the segmental relaxation of the polymer network. This coupling is very sensitive to the local activated segmental dynamics of the surrounding matrix, and we also show that penetrant transport is affected by dynamic heterogeneity at low temperatures. To contrast, only at high temperatures and for large penetrants or when the dynamic heterogeneity effect is weak, does the effect of mesh confinement become significant, even though penetrant diffusion more broadly empirically follows similar trends as established models of mesh confinement-based transport.

Chemistry↗
DOE OSTI2019

Water Network Dynamics Next to the Oxygen-Evolving Complex of Photosystem II

The influence of the environment on the functionality of the oxygen-evolving complex (OEC) of photosystem II has long been a subject of great interest. In particular, various water channels, which could serve as pathways for substrate water diffusion, or proton translocation, are thought to be critical to catalytic performance of the OEC. Here, we address the dynamical nature of hydrogen bonding along the water channels by performing molecular dynamics (MD) simulations of the OEC and its surrounding protein environment in the S1 and S2 states. Through the eigenvector centrality (EC) analysis, we are able to determine the characteristics of the water network and assign potential functions to the major channels, namely that the narrow and broad channels are likely candidates for proton/water transport, while the large channel may serve as a path for larger ions such as chloride and manganese thought to be essential during PSII assembly.

Reiss, Krystle (ORCID:0000000309977953)↗
DOE OSTI2019

Biophysical Characterization of a Disabled Double Mutant of Soybean Lipoxygenase: The “Undoing” of Precise Substrate Positioning Relative to Metal Cofactor and an Identified Dynamical Network

Soybean lipoxygenase (SLO) has served as a prototype for understanding the molecular origin of enzymatic rate accelerations. The double mutant (DM) L546A/L754A is considered a dramatic outlier, due to the unprecedented size and near temperature-independence of its primary kinetic isotope effect, low catalytic efficiency, and elevated enthalpy of activation. To uncover the physical basis of these features, we herein apply three structural probes: hydrogen–deuterium exchange mass spectrometry, room-temperature X-ray crystallography and EPR spectroscopy on four SLO variants (wild-type (WT) enzyme, DM, and the two parental single mutants, L546A and L754A). DM is found to incorporate features of each parent, with the perturbation at position 546 predominantly influencing thermally activated motions that connect the active site to a protein–solvent interface, while mutation at position 754 disrupts the ligand field and solvation near the cofactor iron. However, the expanded active site in DM leads to more active site water molecules and their associated hydrogen bond network, and the individual features from L546A and L754A alone cannot explain the aggregate kinetic properties for DM. Lastly, using recently published QM/MM-derived ground-state SLO-substrate complexes for WT and DM, together with the thorough structural analyses presented herein, we propose that the impairment of DM is the combined result of a repositioning of the reactive carbon of linoleic acid substrate with regard to both the iron cofactor and a catalytically linked dynamic region of protein.

59 BASIC BIOLOGICAL SCIENCES↗