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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 721 records · Page 40
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 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 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 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 OSTI2024

Ultrafast Exciton Dynamics of CH 3 NH 3 PbBr 3 Perovskite Nanoclusters

Exciton dynamics of perovskite nanoclusters has been investigated for the first time using femtosecond transient absorption (TA) and time-resolved photoluminescence (TRPL) spectroscopy. The TA results show two photoinduced absorption signals at 420 and 461 nm and a photoinduced bleach (PB) signal at 448 nm. The analysis of the PB recovery kinetic decay and kinetic model uncovered multiple processes contributing to electron-hole recombination. The fast component (~8 ps) is attributed to vibrational relaxation within the initial excited state, and the medium component (~60 ps) is attributed to shallow carrier trapping. The slow component is attributed to deep carrier trapping from the initial conduction band edge (~666 ps) and the shallow trap state (~40 ps). The TRPL reveals longer time dynamics, with modeled lifetimes of 6.6 and 93 ns attributed to recombination through the deep trap state and direct band edge recombination, respectively. In conclusion, the significant role of exciton trapping processes in the dynamics indicates that these highly confined nanoclusters have defect-rich surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Determination of a Generic Human Error Probability Distribution, Part 2: A Dynamic SPAR-H Example Application

Humans are an integral part of a nuclear power plant (NPP) from its construction, to its everyday maintenance and operation. In the nuclear industry there are many approaches to quantifying component reliability, which is called probability risk assessment (PRA). In PRA there are two considerations given to the quantification, static and dynamic. Static is quantified before or after an operation; and dynamic is time dependent, in that the probability changes as real time data are provided. In PRA, the importance of the components is calculated, but what of the importance of the human component? There are several methods for human reliability analysis (HRA), which include but are not limited to: THERP, ATHEANA, CREAM, SPAR-H, ASEP, and SLIM. Each of these methods aims to provide a more accurate and objective human error probability (HEP) quantification. Of the methods listed above, ASEP, THERP, and SPAR-H are all inextricably linked. The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method was generated to better generalize the Technique for Human Error Rate Prediction (THERP) and Accident Sequence Precursor (ASEP). THERP is mapped to specific scenario templates, and ASEP is a simplified screening method, while SPAR-H employs generalizations to describe the spectrum of human behavior while maintaining the same theoretical underpinnings. SPAR-H is a well-known and accepted HRA method that uses performance shaping factors (PSFs) to classify inputs to the human component. PSFs capture a wide variety of input data, including plant status, crew dynamics, task description, and psychological aspects of the human operator. Current efforts have been focused to further generalize SPAR-H in to a dynamic framework. These methods can fit into dynamic NPP simulations such as RAVEN / RELAP-7. In order to do this, a dynamic methodology is applied to model the human as would be applied to the components. This method is applied in part one in the accompanying paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Insights into distorted lamellar phases with small-angle scattering and machine learning

Lamellar phases are essential in various soft matter systems, with topological defects significantly influencing their mechanical properties. In this report, we present a machine-learning approach for quantitatively analyzing the structure and dynamics of distorted lamellar phases using scattering techniques. By leveraging the mathematical framework of Kolmogorov–Arnold networks, we demonstrate that the conformations of these distorted phases – expressed as superpositions of complex waves – can be reconstructed from small-angle scattering intensities. Through the contour analysis of wave field phase singularities, we obtain the statistics of the spatial distribution of topological defects. Furthermore, we establish that the temporal evolution of these defects can be derived from the time-dependent traveling wave field, informed by the dispersion relation of spectral components. This method opens new avenues for investigating the dynamics of distorted lamellar phases using various dynamic scattering techniques such as neutron spin echo and X-ray photon correlation spectroscopy. These findings enhance our microscopic understanding of how defects influence the physical properties of lamellar materials, with implications for both equilibrium and non-equilibrium states in general lamellar systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

rmap: An R package to plot and compare tabular data on customizable maps across scenarios and time

`rmap` is an R package that allows users to easily plot tabular data (CSV or R data frames) on maps without any Geographic Information Systems (GIS) knowledge. Maps produced by `rmap` are `ggplot` objects and thus capitalize on the flexibility and advancements of the `ggplot2` package and all elements of each map are thus fully customizable. Additionally `rmap` automatically detects and produces comparison maps if the data has multiple scenarios or time periods as well as animations for time series data. Advanced users can load their own shapefiles if desired. `rmap` comes with a range of pre-built color palettes but users can also provide any `R` color palette or create their own as needed. Four different legend types are available to highlight different kinds of data distributions. The input spatial data can be both gridded or polygon data. `rmap` is desgined in particular for comparing spatial data across scenarios and time periods and comes preloaded with standard country, state, and basin maps as well as custom maps compatible with the Global Change Analysis Model (GCAM) spatial boundaries. `rmap` has a growing number of users and its products have been used in multiple multisector dynamics publications as well as a required dependency in other R packages such as `rfasst` and `metis`. `rmap's` automatic processing of tabular data using pre-built map selection, difference map calculations, faceting, and animations offers unique functionality which makes it a powerful and yet simple tool for users looking to explore multi-sector, multi-scenario data across space and time.

58 GEOSCIENCES↗
DOE OSTI2025

Quasinormal Coupled-Mode Analysis of Dynamic Gain in Exceptional-Point Lasers

One of the key features of lasers operating near exceptional points (EPs) is that the gain medium can support an oscillating population inversion above a pump threshold, leading to self-modulated laser dynamics. This unusual behavior opens up new possibilities for frequency comb generation and temporal modulation. However, the dynamic population inversion couples signals with different frequencies and is difficult to capture using conventional temporal coupled-mode theory (TCMT) based on stationary saturable gain. In this paper, we develop a perturbative coupled-mode analysis framework to capture the spatial-temporal dynamics of near-EP lasers. By decomposing discrete frequency generation into multiple excitations of resonant modes, our analysis establishes a minimal physical model that translates the local distribution of dynamic population-inversion into a resonant modal interpretation of laser gain. Furthermore, this work enables the exploration of unique properties in this self-time-modulated systems, such as time-varying scattering and nonreciprocal transmission.

Absorption↗
DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗
DOE OSTI2020

Evolution of Metastable Structures at Bimetallic Surfaces from Microscopy and Machine-Learning Molecular Dynamics

The restructuring of interfaces plays a crucial role in materials science and heterogeneous catalysis. Bimetallic systems, in particular, often adopt very different compositions and morphologies at surfaces compared to the bulk. For the first time, we reveal a detailed atomistic picture of long-time scale restructuring of Pd deposited on Ag using microscopy, spectroscopy, and novel simulation methods. By developing and performing accelerated machine-learning molecular dynamics followed by an automated analysis method, we discover and characterize previously unidentified surface restructuring mechanisms in an unbiased fashion, including Pd-Ag place exchange and Ag pop-out as well as step ascent and descent. Remarkably, layer-by-layer dissolution of Pd into Ag is always preceded by an encapsulation of Pd islands by Ag, resulting in a significant migration of Ag out of the surface and a formation of extensive vacancy pits within a period of microseconds. These metastable structures are of vital catalytic importance, as Ag-encapsulated Pd remains much more accessible to reactants than bulk-dissolved Pd. We report our approach is broadly applicable to complex multimetallic systems and enables the previously intractable mechanistic investigation of restructuring dynamics at atomic resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗