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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Atmospheric condition identification in multivariate data through a metric for total variation

Identification of atmospheric conditions within a multivariable atmospheric data set is a necessary step in the validation of emerging and existing high-fidelity models used to simulate wind plant flows and operation.Atmospheric conditions relevant for wind energy research include stationary conditions, given the need for well-converged statistics for model validation, as well as conditions observed less frequently, such as extreme atmospheric events, which are used in wind turbine and wind plant design.Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of atmospheric conditions.Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation set the stage for more advanced model validation and the development of real-time control and operational strategies.The current work explores a single metric for variation in a multivariate data sample that quantifies variability within each channel as well as covariance between channels.The total variation is used to identify conditions of interest that conform to desired objective functions, such as stationary conditions, ramps or waves of wind speed, and changes in wind direction.Total variation is somewhat sensitive to the presence of outliers in the input data, and the method is best complemented by quality-control procedures to ensure reliable results.The direct detection and classification of events or conditions of interest within atmospheric data sets is vital to developing our understanding of wind plant response and to the formulation of forecasting and control models.

17 WIND ENERGY↗
DOE OSTI2011

Nonlinear Dynamics of Single Bunch Instability

A nonlinear equation is derived that governs the evolution of the amplitude of unstable oscillations with account of quantum diffusion effects due to the synchrotron radiation. Numerical solutions to this equation predict a variety of possible scenarios of nonlinear evolution of the instability some of which are in good qualitative agreement with experimental observations. Microwave single bunch instability in circular accelerators has been observed in many machines. The instability usually arises when the number of particles in the bunch exceeds some critical value, Nc, which varies depending on the parameters of the accelerating regime. Recent observations on the SLC damping rings at SLAC with a new low-impedance vacuum chamber revealed new interesting features of the instability. In some cases, after initial exponential growth, the instability eventually saturated at a level that remained constant through the accumulation cycle. In other regimes, relaxation-type oscillations were measured in nonlinear phase of the instability. In many cases, the instability was characterized by a frequency close to the second harmonic of the synchrotron oscillations. Several attempts have been made to address the nonlinear stage of the instability based on either computer simulations or some specific assumptions regarding the structure of the unstable mode. An attempt of a more general consideration of the problem is carried out in this paper. We adopt an approach recently developed in plasma physics for analysis of nonlinear behavior of weakly unstable modes in dynamic systems. Assuming that the growth rate of the instability is much smaller than its frequency, we find a time dependent solution to Vlasov equation and derive an equation for the complex amplitude of the oscillations valid in the nonlinear regime. Numerical solutions to this equation predict a variety of possible scenarios of nonlinear evolution of the instability some of which are in good qualitative agreement with experimental observations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Core and Fuel Cycle Performance of a Molten Salt Fast Reactor

This paper discusses the reactor core design and modeling approaches for a specific molten salt fast reactor (MSFR) design that is started up with high-assay low-enriched uranium (HALEU) within a chloride fuel salt and focuses on the technical assumptions and design choices. These include the fuel salt properties, first core and make-up heavy metal requirements, fuel composition evolution, equilibrium fission product concentration, etc. This MSFR concept was developed as part of a wider study that sought to compare the fuel cycle performance tradeoffs between deploying a fleet of sodium-cooled fast reactors (SFRs) and deploying a fleet of MSFRs. MSFRs that use flowing liquid fuel salt and on-line salt processing are of particular interest because these technology characteristics are significantly different from those of SFRs and can lead to major differences in fuel cycle impacts. The goal of this study was not to draw general conclusions based on a direct comparison of two very specific point designs for an SFR and MSFR, but rather to use this example MSFR design and associated parametric studies to gain insight into the key technology characteristics that impact fuel cycle performance as it relates to resource utilization (i.e., uranium consumption). The MSFR reactor physics, fission product removal, and fuel salt mass flows were modeled using Argonne’s recently-developed molten salt reactor (MSR) analysis tools while the time-dependent fuel cycle performance of this specific reactor was compared to that of a representative SFR design using the fuel cycle system dynamics code DYMOND.

chloride salt↗
DOE OSTI2020

Microscale mechanical modeling of deformable geomaterials with dynamic contacts based on the numerical manifold method

Abstract Micromechanical modeling of geomaterials is challenging because of the complex geometry of discontinuities and potentially large number of deformable material bodies that contact each other dynamically. In this study, we have developed a numerical approach for micromechanical analysis of deformable geomaterials with dynamic contacts. In our approach, we detect contacts among multiple blocks with arbitrary shapes, enforce different contact constraints for three different contact states of separated, bonded, and sliding, and iterate within each time step to ensure convergence of contact states. With these features, we are able to simulate the dynamic contact evolution at the microscale for realistic geomaterials having arbitrary shapes of grains and interfaces. We demonstrate the capability with several examples, including a rough fracture with different geometric surface asperity characteristics, settling of clay aggregates, compaction of a loosely packed sand, and failure of an intact marble sample. With our model, we are able to accurately analyze (1) large displacements and/or deformation, (2) the process of high stress accumulated at contact areas, (3) the failure of a mineral cemented rock samples under high stress, and (4) post-failure fragmentation. The analysis highlights the importance of accurately capturing (1) the sequential evolution of geomaterials responding to stress as motion, deformation, and high stress; (2) large geometric features outside the norms (such as large asperities and sharp corners) as such features can dominate the micromechanical behavior; and (3) different mechanical behavior between loosely packed and tightly packed granular systems.

58 GEOSCIENCES↗
DOE OSTI2015

Measurement of planet masses with transit timing variations due to synodic “chopping” effects

Gravitational interactions between planets in transiting exoplanetary systems lead to variations in the times of transit that are diagnostic of the planetary masses and the dynamical state of the system. Here we show that synodic “chopping” contributions to these transit timing variations (TTVs) can be used to uniquely measure the masses of planets without full dynamical analyses involving direct integration of the equations of motion. We present simple analytic formulae for the chopping signal, which are valid (generally <10% error) for modest eccentricities e≲0.1. Importantly, these formulae primarily depend on the mass of the perturbing planet, and therefore the chopping signal can be used to break the mass/free-eccentricity degeneracy, which can appear for systems near first-order mean motion resonances. Using a harmonic analysis, we apply these TTV formulae to a number of Kepler systems, which had been previously modeled with full dynamical analyses. We show that when chopping is measured, the masses of both planets can be determined uniquely, in agreement with previous results, but without the need for numerical orbit integrations. This demonstrates how mass measurements from TTVs may primarily arise from an observable chopping signal. The formula for chopping can also be used to predict the number of transits and timing precision required for future observations, such as those made by TESS or PLATO, in order to infer planetary masses through analysis of TTVs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Analysis of electron dynamics in non-ideal Penning traps

Penning traps that are used for particular applications, such as in ion pump technology, Larmor, bouncing, and diocotron frequencies, can be of the same order of magnitude. The paper deals with the dynamics of electrons confined in such devices starting from the study of the properties of the trajectories. In cases of interest, in which electron-neutral collision frequency is much smaller with respect to the characteristic frequencies of the motion, suitable time averages of the trajectories are introduced in order to simplify the analysis of the problem. In the work, time averages have been calculated in a simple way by using an approximate r-z decoupling of the effective potential. Results obtained with the method are presented and discussed in both linear and nonlinear regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Case studies of the time-dependent potential energy surface for dynamics in cavities

Here, the exact time-dependent potential energy surface driving the nuclear dynamics was recently shown to be a useful tool to understand and interpret the coupling of nuclei, electrons, and photons in cavity settings. Here, we provide a detailed analysis of its structure for exactly solvable systems that model two phenomena: cavity-induced suppression of proton-coupled electron-transfer and its dependence on the initial state, and cavity-induced electronic excitation. We demonstrate the inadequacy of simply using a weighted average of polaritonic surfaces to determine the dynamics. Such a weighted average misses a crucial term that redistributes energy between the nuclear and the polaritonic systems, and this term can in fact become a predominant term in determining the nuclear dynamics when several polaritonic surfaces are involved. Evolving an ensemble of classical trajectories on the exact potential energy surface reproduces the nuclear wavepacket quite accurately, while evolving on the weighted polaritonic surface fails after a short period of time. The implications and prospects for application of mixed quantum-classical methods based on this surface are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Eliminating Signal Bias Caused by Vacuum System Backstreaming in the Diagnostic Residual Gas Analyzer of ITER

In fusion neutral gas analysis, such as with the Diagnostic Residual Gas Analyzer (DRGA) for ITER, the primary measurement range of interest comprises the low-amu species (1 to 6), especially deuterium and helium. The challenge in successfully obtaining accurate measurements is two-fold. First, the sensitivity of the method must be sufficient to resolve trace amounts accurately; typically, one percent or less. Second, the gas signal from the fusion processes must be free of bias caused by the latent presence (from system outgassing and/or vacuum backstreaming) of these gases to enable accurate interpretation of the measured signal. This latter criterion can be problematic for the lightest gases since there is a propensity for some fraction of the pumped gas load to undergo a phenomenon known as backstreaming. This behavior is manifested in pumping systems for gas properties related to relative atomic weight (lightest) and size (smallest). Backstreaming results in a significant amount of the pumped gas undertaking a reverse flow and re-entering the measurement region; thus, contaminating the forward, real-time measurement. To fully eliminate this adverse effect, a conductance-limiting device – or orifice – has been installed in the high-vacuum pumping system of the present ITER DRGA prototype. The system was already equipped with a secondary turbomolecular pump (TMP), but with limited effectiveness against backstreaming in the inter-pump volume (IPV). This orifice is placed within the suction inlet coupling of the secondary TMP, which is downstream of the IPV. Its objective is to eliminate the backstreaming phenomenon by increasing the back pressure in the IPV. However, the orifice sizing must take into consideration other factors, such as the diagnostic measurement objectives. For example, in the ITER DRGA, one of the measurement requirements is a dynamic response time of ~1s. Fortunately, an added benefit of the pumping restriction created by the orifice is that the upstream pressure increase is beneficial for the DRGA’s optical gas analysis (OGA) sensors. These sensors are attached to the IPV in the present design. The glow discharges, when used as an OGA light source, will typically have a brighter light emission with increasing plasma cell pressure. In addition to the fusion machine research sector, there are other potential applications of this pumping technique where the monitoring of lighter gas concentrations is essential, such as the photolithography process for the semiconductor fabrication of integrated circuits. This presentation will describe the vacuum system used to demonstrate a process to eliminate backstreaming as well as show test results to verify the accomplishment of this critical objective.

Marcus, Chris↗
DOE OSTI2023

Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects

We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [1]. We focus here on test cases of physical interest where the dynamics of the system is modelled by the Langevin equation and is simulated using the molecular dynamics software LAMMPS. In this work, the parareal algorithm uses a family of machine-learning spectral neighbor analysis potentials (SNAP) as fine, reference, potentials and embedded-atom method potentials (EAM) as coarse potentials. We consider a self-interstitial atom in a tungsten lattice and compute the average residence time of the system in metastable states. Our numerical results demonstrate significant computational gains using the adaptive parareal algorithm in comparison to a sequential integration of the Langevin dynamics. We also identify a large regime of numerical parameters for which statistical accuracy is reached without being a consequence of trajectorial accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Understanding the breakdown of classic two-phase theory and spray atomization at engine-relevant conditions

We present a generalized framework for multi-component liquid injections to understand and predict the breakdown of classic two-phase theory and spray atomization at engine-relevant conditions. The analysis focuses on the thermodynamic structure and the immiscibility state of representative gas-liquid interfaces. The most modern form of Helmholtz energy mixture state equation is utilized which exhibits a unique and physically-consistent behavior over the entire two-phase regime of fluid densities. It is combined with generalized models for non-linear Gradient Theory and for liquid injections to quantify multi-component two-phase interface structures in global thermal equilibrium. Then, the Helmholtz free energy is minimized which determines the interfacial species distribution as a consequence. This minimal free energy state is demonstrated to validate the underlying assumptions of classic two-phase theory and spray atomization. However, under certain engine-relevant conditions for which corroborating experimental data is presented, this requirement for interfacial thermal equilibrium becomes unsustainable. A rigorously derived probability density function quantifies the ability of the interface to develop internal spatial temperature gradients in the presence of significant temperature differences between injected liquid and ambient gas. Then, the interface can no longer be viewed as an isolated system at minimal free energy. Instead, the interfacial dynamics become intimately connected to those of the separated homogeneous phases. Hence, the interface transitions toward a state in local equilibrium whereupon it becomes a dense-fluid mixing layer. A new conceptual view of a transitional liquid injection process emerges from a transition time scale analysis. Close to the nozzle exit, the two-phase interface still remains largely intact and more classic two-phase processes prevail as a consequence. Further downstream, however, the transition to dense- fluid mixing generally occurs before the liquid length is reached. The significance of the presented modeling expressions is established by a direct comparison to a reduced model, which utilizes widely-applied approximations but fundamentally fails to capture the physical complexity discussed in this paper.

42 ENGINEERING↗
DOE OSTI2016

Application of periodic perturbations to a RELAP5 hydraulic simulation to determine frequency response

Time series analysis requires a collection of data taken sequentially in time to apply techniques for identification, modeling, prediction or control purposes. Some systems operating at steady state are perturbed with white noise to extract system information using autoregressive models or spectral analysis, and then the dynamic response is used to assess system properties. If it is not possible to perturb the physical system, a mathematical model can be used to work with and study the perturbation effect. In this work, the system object of perturbation study is a RELAP5 hydraulic model, and since the excitation with a white noise sequence is not readily implementable, an alternative is proposed to apply a series of periodic steps in a square wave pattern. With this periodic excitation, the output of a RELAP5 model for a hydraulic piping system can be analyzed with frequency domain tools. The piping systems can be found in the balance of plant of a steam power plant, and the aim of this work is to explore the capability of RELAP5 to determine system frequency characteristics linked to mechanical vibration in operating lines of a power plant. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Odor mitigation and bacterial community dynamics in on-site biocovers at a sanitary landfill in South Korea

Highlights: • On-site biocovers were evaluated to mitigate odors at a Korean sanitary landfill. • The biocover systems achieved above 80% removal of complex odor. • Removal efficiency of sulfur odor as significant contributor was greater than 90%. • The most abundant bacteria had little correlation with odor removability. • Bacteria increased in relative abundance contributed highly to odor removal. Unpleasant odors emitted from landfills have been caused environmental and societal problems. For odor abatement, two pilot-scale biocovers were installed at a sanitary landfill site in South Korea. Biocovers PBC1 and PBC2 comprised a soil mixture with different ratios of earthworm casts as an inoculum source and were operated for 240 days. Their odor removal efficiencies were evaluated, and their bacterial community structures were characterized using pyrosequencing. In addition, the correlation between odor removability and bacterial community dynamics was assessed using network analysis. The removal efficiency of complex odor intensity in the two biocovers ranged from 81.1% to 97.8%. Removal efficiencies of sulfur-containing odors (hydrogen sulfide, methanethiol, dimethyl sulfide, and dimethyl disulfide), which contributed most to complex odor intensity, were greater than 91% in both biocovers. Despite the fluctuations in ambient temperature (−8.2 to 31.3 °C) and inlet complex odor intensity (10,000–42,748 of odor dilution ratio), biocovers PBC1 and PBC2 displayed stable deodorizing performance. A high ratio of earthworm casts as an inoculum source led to high odor removability during the first 25 days of operation, but different mixing ratios of earthworm casts did not significantly affect overall odor removability. A bacterial community analysis showed that Methylobacter, Arthrobacter, Acinetobacter, Rhodanobacter, and Pedobacter were the dominant genera in both biocovers. Network analysis results indicated that Steroidobacter, Cystobacter, Methylosarcina, Solirubrobacter, and Pseudoxanthomonas increased in relative abundance with time and were major contributors to odor removal, although these bacteria had a relatively low abundance compared to the overall bacterial community. These data contribute to a more comprehensive understanding of the relationship between bacterial community dynamics and deodorizing performance in biocovers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Exploration of High-Dimensional Scalar Function for Nuclear Reactor Safety Analysis and Visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Exploration of high-dimensional scalar function for nuclear reactor safety analysis and visualization

The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user's guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving data from a nuclear reactor safety simulation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2012

AUTOMATICALLY DETECTING AND TRACKING CORONAL MASS EJECTIONS. I. SEPARATION OF DYNAMIC AND QUIESCENT COMPONENTS IN CORONAGRAPH IMAGES

Automated techniques for detecting and tracking coronal mass ejections (CMEs) in coronagraph data are of ever increasing importance for space weather monitoring and forecasting. They serve to remove the biases and tedium of human interpretation, and provide the robust analysis necessary for statistical studies across large numbers of observations. An important requirement in their operation is that they satisfactorily distinguish the CME structure from the background quiescent coronal structure (streamers, coronal holes). Many studies resort to some form of time differencing to achieve this, despite the errors inherent in such an approach-notably spatiotemporal crosstalk. This article describes a new deconvolution technique that separates coronagraph images into quiescent and dynamic components. A set of synthetic observations made from a sophisticated model corona and CME demonstrates the validity and effectiveness of the technique in isolating the CME signal. Applied to observations by the LASCO C2 and C3 coronagraphs, the structure of a faint CME is revealed in detail despite the presence of background streamers that are several times brighter than the CME. The technique is also demonstrated to work on SECCHI/COR2 data, and new possibilities for estimating the three-dimensional structure of CMEs using the multiple viewing angles are discussed. Although quiescent coronal structures and CMEs are intrinsically linked, and although their interaction is an unavoidable source of error in any separation process, we show in a companion paper that the deconvolution approach outlined here is a robust and accurate method for rigorous CME analysis. Such an approach is a prerequisite to the higher-level detection and classification of CME structure and kinematics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Continuous and discrete modeling of HIV-1 decline on therapy

Mathematical models have shed light on the dynamics of HIV- 1 infection in vivo. In this paper, we generalize continuous mathematical models of drug therapy for HIV-1 by Perelson et al. (Science 271:1582–1586, 1996) and Perelson and Nelson (SIAM Rev 41:3–44, 1999) on time scales, i.e., a nonempty closed subset of real numbers in order to derive new discrete models that predict the total concentration of plasma virus as a function of time. Here, one of our main goals is to compare discrete mathematical models with the continuous model in Perelson et al. (1996) where HIV infected patients were given protease inhibitors and sampled frequently thereafter. For the comparison, we use experimental data collected in Perelson et al. (1996) and estimate the parameters such as the virion clearance rate and the rate of loss of infected cells by fitting the total concentration of plasma virus to this data set. Our results show that discrete systems describe the best fit. In the previous models of this study, the efficacy of protease inhibitor is assumed to be perfect. Motivated by Perelson and Nelson (1999), we end the paper with a mathematical model of imperfect protease inhibitor and reverse transcriptase (RT) inhibitor combination therapy of HIV-1 infection on time scales with its stability analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Linearized spectrum correlation analysis for line emission measurements

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100–200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Partial synchronization in networks of non-linearly coupled oscillators: The Deserter Hubs Model

We study the Deserter Hubs Model: a Kuramoto-like model of coupled identical phase oscillators on a network, where attractive and repulsive couplings are balanced dynamically due to nonlinearity of interactions. Under weak force, an oscillator tends to follow the phase of its neighbors, but if an oscillator is compelled to follow its peers by a sufficient large number of cohesive neighbors, then it actually starts to act in the opposite manner, i.e., in anti-phase with the majority. Analytic results yield that if the repulsion parameter is small enough in comparison with the degree of the maximum hub, then the full synchronization state is locally stable. Numerical experiments are performed to explore the model beyond this threshold, where the overall cohesion is lost. We report in detail partially synchronous dynamical regimes, like stationary phase-locking, multistability, periodic and chaotic states. Via statistical analysis of different network organizations like tree, scale-free, and random ones, we found a measure allowing one to predict relative abundance of partially synchronous stationary states in comparison to time-dependent ones.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗