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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Applications of Transient Grating Spectroscopy to Radiation Materials Science

Radiation damage is an inherently multi-scale phenomenon, with much of the key material evolution occurring at the mesoscale. Current techniques for the direct interrogation of material property changes due to irradiation either function with very small volumes, such as in-situ TEM, cannot cover the full range of defect populations produced, such as in positron annihilation spectroscopy, or requires destruction of the test material, such as in standard or micromechanical testing. In addition, the ultimate quantities of interest to radiation materials scientists are the changes in key material properties with irradiation. These include stiffness, ductility, and thermal conductivity for structural materials, and optical properties such as index of refraction or changes in transmittance spectra for optically active materials. The latter of these are often correlated directly to stress- or thermally-induced changes, themselves a function of the specific defect populations responsible for their change. The rapid study of such a mesoscale phenomenon requires an inherently mesoscale technique, where multiple quantities of interest can be accurately measured in very short times. Determining the sensitivity of any technique with known certainly is of critical importance to qualifying a new technique to measure in-situ material property changes during irradiation. In this paper, we present the new applicability of an existing technique, known as transient grating (TG) spectroscopy, to rapidly and accurately study key problems in radiation materials science. Results quantifying the absolute sensitivity of the technique are presented, alongside molecular dynamics (MD) simulations of the TG spectroscopy process to gauge direct agreement between theory, simulation, and experiment. An example problem of interest is demonstrated as an illustration of what is possible, showing elastic and thermal changes in irradiated silicon carbide (SiC) films. Finally, future work to quantify the effects of experimentally-simulated radiation defects is proposed, in support of building a database to use TG spectroscopy to deconvolve irradiated material property changes in-situ in terms of the defect populations responsible for their evolution. The application of the TG spectroscopy technique to in-situ radiation materials science has the potential to answer long-standing questions in the field, relating to ion beam rastering, the onset of void swelling, and direct measurement of radiation-created point defect concentrations. Before it can do so, the technique must carefully be analyzed and tuned to increase its sensitivity, the certainty of its results, and the ability to predict radiation-induced changes by simulations must be developed. Making such measurements in-situ with the aid of predictive MD simulations has the potential to elucidate mechanisms of radiation damage accumulation, as well as more rapidly qualify radiation-resistant alloys for service in nuclear systems. Work is underway to build this database of experimentally-simulated radiation-produced defects, which will be combined and compared with actual irradiated materials for eventual in-situ deconvolution of the TG signal into the defect populations responsible for irradiation-induced microstructural change. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2022

Modeling Dust Production, Growth, and Destruction in Reionization-era Galaxies with the CROC Simulations: Methods and Parameter Exploration

We introduce a model for the explicit evolution of interstellar dust in a cosmological galaxy formation simulation. We post-process a simulation from the Cosmic Reionization on Computers project, integrating an ordinary differential equation for the evolution of the dust-to-gas ratio along pathlines in the simulation sampled with a tracer particle technique. This model incorporates the effects of dust grain production in asymptotic giant branch star winds and supernovae, grain growth due to the accretion of heavy elements from the gas phase of the interstellar medium, and grain destruction due to thermal sputtering in the high-temperature gas of supernova remnants due to thermal sputtering. A main conclusion of our analysis is the importance of a carefully chosen dust destruction model, for which different reasonable parameterizations can predict very different values at the ∼100 pc resolution of the interstellar medium (ISM) in our simulations. We run this dust model on the single most massive galaxy in a 10 h$^{−1}$ comoving megaparsec box, which attains a stellar mass of ∼2 × 10$^{9}$ M $_{⊙}$ by z = 5. We find that the model is capable of reproducing dust masses and dust-sensitive observable quantities broadly consistent with existing data from high-redshift galaxies. The total dust mass in the simulated galaxy is somewhat sensitive to parameter choices for the dust model, especially the timescale for grain growth due to accretion in the ISM. Consequently, observable quantity observations that can constrain galaxy dust masses at these epochs are potentially useful for placing constraints on dust physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Ising meson spectroscopy on a noisy digital quantum simulator

Abstract Quantum simulation has the potential to be an indispensable technique for the investigation of non-perturbative phenomena in strongly-interacting quantum field theories (QFTs). In the modern quantum era, with Noisy Intermediate Scale Quantum (NISQ) simulators widely available and larger-scale quantum machines on the horizon, it is natural to ask: what non-perturbative QFT problems can be solved with the existing quantum hardware? We show that existing noisy quantum machines can be used to analyze the energy spectrum of several strongly-interacting 1+1D QFTs, which exhibit non-perturbative effects like ‘quark confinement’ and ‘false vacuum decay’. We perform quench experiments on IBM’s quantum simulators to compute the energy spectrum of 1+1D quantum Ising model with a longitudinal field. Our results demonstrate that digital quantum simulation in the NISQ era has the potential to be a viable alternative to numerical techniques such as density matrix renormalization group or the truncated conformal space methods for analyzing QFTs.

Science & Technology - Other Topics↗
DOE OSTI2018

A processing diagram for high-density Ti-6Al-4V by selective laser melting

Density optimization is the first critical step in building additively manufactured parts with highquality and good mechanical properties. In earlier work, we developed an approach that combines simulations and experiments to identify processing parameters for high-density parts. Here we present the results for Ti-6Al-4V using the laser powder-bed-fusion technique. We show how simple, but approximate, simulations are used to design parameters for a limited set of single track experiments. The resulting melt-pool characteristics are then used to identify processing parameters for high-density pillars. From these experimental data, a processing diagram based on the normalized energy density concept is constructed, illustrating an optimized processing window for high- or low-density samples. Excellent mechanical properties are obtained for Ti-6Al-4V samples built from the optimized window. We discuss the limitations and implications of the processing diagram on the microstructure and mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A coupled, multiphase heat flux boundary condition for the discrete element method

Similar to single-phase flows, multiphase systems with a constant heat flux at the wall are common in practice. Unlike single-phase flows, however, the numerical implementation of a constant boundary flux is non-trivial due to the coupling between phases – i.e., the partition of the total flux between the phases can vary in space and time. A numerical technique for modeling such a boundary condition is proposed here and verified via simulations of gas-solid flows. While discrete-particle simulations of monodisperse particles are considered in this report, the technique can be extended to include radiation, polydisperse systems, and/or a continuum representation of the solids phase.

42 ENGINEERING↗
DOE OSTI2021

Supporting Co-Design of Extreme-Scale Systems with In Situ Visual Analysis of Event-Driven Simulations (Final Report)

Extreme-scale systems for compute- and data-centric science are pushing the boundaries of system architectures in order to achieve ambitious goals in terms of computing capability, resilience, and power efficiency. Future systems necessitate emerging designs that incorporate new technologies, system organizations, and computer science techniques, and these changes are not yet well understood. Discrete-event-driven simulation of computing system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential designs, along with capabilities for executing these simulations of extreme-scale systems. However, techniques for analyzing the behavior of these simulations have not kept pace with our ability to perform the simulations, preventing us from extracting the most value from this promising approach. The objective of this project is to support the codesign of extreme-scale system architectures for compute and data-centric science through research and development of novel methods for analysis and visualization of large-scale event-driven simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surroundings have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part I of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using the System for Atmospheric Modeling (SAM) with bin microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method: Preprint

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power, and they are currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

17 WIND ENERGY↗
DOE OSTI2024

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

In the past decade, dynamical downscaling using “pseudo-global-warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)-simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic-scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large-scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic-scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

17 WIND ENERGY↗
DOE OSTI2019

Assessment of geophysical monitoring methods for detection of brine and CO 2 leakage in drinking water aquifers

Here, we evaluated and compared the effectiveness of four surface-based geophysical monitoring methods to downhole pressure and chemical methods to detect brine and CO 2 leakage in underground sources of drinking water overlying a CO 2 storage reservoir. This assessment uses synthetic monitoring data generated from 400 simulated aquifer impact data sets. Here, the six monitoring techniques can detect impacted groundwater once 20,000 tonnes of CO 2 have leaked into the drinking water resource. Geophysical methods are most effective at detecting shallow plumes. Although downhole monitoring methods outperform geophysical methods in detecting deep plumes, geophysical methods may help reduce the false negative during the post injection site care because they detect impacted groundwater where downhole sensors may be absent.

58 GEOSCIENCES↗
DOE OSTI2020

Hierarchical Phenomena in Multicomponent Liquids: Simulation Methods, Analysis, Chemistry

Complex, multicomponent, solutions have often been studied solely through the lens of specific applications of interest. Yet advances to both simulation methodologies (enhanced sampling, etc.) and analysis techniques (network analysis algorithms and others), are creating a trove of data that reveal transcending characteristics across vast compositional phase space. This perspective discusses technical considerations of the reliable and accurate simulations of complex solutions, followed by the advances to analysis algorithms that elucidate coupling of different length and timescale behavior (hierarchical phenomena). The different manifestations of hierarchical phenomena are presented across an array of solution environments, emphasizing fundamental and ongoing science questions. With a more advanced molecular understanding in hand, a quintessential application (solvent extraction) is discussed, where significant opportunities exist to re-imagine the technical scope of an established technology.

Servis, Michael J.↗
DOE OSTI2015

Development of a novel neutron detection technique by using a boron layer coating a Charge Coupled Device

This article describes the design features and the first test measurements obtained during the installation of a novel high resolution 2D neutron detection technique. The technique proposed in this work consists of a boron layer (enriched in ${^{10}}$B) placed on a scientific Charge Coupled Device (CCD). After the nuclear reaction ${^{10}}$B(n,$\alpha$)${^{7}}$Li, the CCD detects the emitted charge particles thus obtaining information on the neutron absorption position. The above mentioned ionizing particles, with energies in the range 0.5-5.5 MeV, produce a plasma effect in the CCD which is recorded as a circular spot. This characteristic circular shape, as well as the relationship observed between the spot diameter and the charge collected, is used for the event recognition, allowing the discrimination of undesirable gamma events. We present the first results recently obtained with this technique, which has the potential to perform neutron tomography investigations with a spatial resolution better than that previously achieved. Numerical simulations indicate that the spatial resolution of this technique will be about 15 $\mu$m, and the intrinsic detection efficiency for thermal neutrons will be about 3 %. We compare the proposed technique with other neutron detection techniques and analyze its advantages and disadvantages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data

Abstract Recent advances in machine learning, specifically transformer architecture, have led to significant advancements in commercial domains. These powerful models have demonstrated superior capability to learn complex relationships and often generalize better to new data and problems. This paper presents a novel transformer-powered approach for enhancing prediction accuracy in multi-modal output scenarios, where sparse experimental data is supplemented with simulation data. The proposed approach integrates transformer-based architecture with a novel graph-based hyper-parameter optimization technique. The resulting system not only effectively reduces simulation bias, but also achieves superior prediction accuracy compared to the prior method. We demonstrate the efficacy of our approach on inertial confinement fusion experiments, where only 10 shots of real-world data are available, as well as synthetic versions of these experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

An Easy Algorithm to Generate Colored Noise Sequences

The need for accurate and efficient simulation of the noise background arises in statistical significance tests for periodic signals buried in colored noise. This paper discusses techniques for generating colored-noise sequences which simulate processes with a given spectral density. Matlab routines based on the fast fractional difference algorithm are presented. These routines can create various stochastic models (e.g., first-order autoregressive (AR(1)), power law (PL), autoregressive fractionally integrated moving average ((1, d, 0)), and generalized Gauss Markov (GGM)) that serve as possible candidate null hypotheses to test against in various scenarios. Allan variance and power spectral density (PSD) show that our algorithms are accurate and efficient, and can be easily implemented for stationary noise models and non-stationary PLs with spectral indices up to 2. Our algorithms can also be extended to produce a non-stationary PL with a range-limited steeper PSD (spectral indices up to about 4) using a GGM approximation with a proper break frequency. The red-noise leakage effect on the periodogram is further discussed. The result shows that our GGM approximation has a potential for alleviating the red-noise leakage in the PSD estimates. The Timmer and Koenig procedure is also included for comparison.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Investigation of the Effect of Chrome and Nickel Concentrations During Two-Piston Splat Quenching of Austenitic Stainless Steels

For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Measurement of the sound speed in dense fluid deuterium along the cryogenic liquid Hugoniot

Many experimental studies, spanning several decades of research and using various dynamic compression schemes, have been conducted to investigate cryogenic liquid deuterium under strong shock compression. The consensus emerging from these studies is that of a progressive dissociation of the D 2 molecules into an electrically conducting, atomic plasma, when subjected to shock pressures exceeding ~50 GPa. While state-of-the-art numerical simulations based on density-functional-theory or quantum Monte-Carlo techniques capture this behavior quite well, subtle differences subsist between these simulations and the available experimental data regarding the pressure-density compressibility. Here, leveraging a recently developed analysis method for high-resolution Doppler interferometric velocity data, we present Eulerian sound speed measurements in compressed deuterium to shock pressures between 50 and 200 GPa. These results, extracted from laser-driven shockwave experiments, are found to agree with several of the most accurate equation of state models for deuterium at those conditions up to ~150 GPa. However, the data indicate that these models fail to reproduce the experimentally observed sound speed at higher pressures, approaching 200 GPa. In particular, we unveil a discrepancy between the experimental results and the equation of state model that is most commonly used in inertial confinement fusion at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Design and Analysis of the Staggered Double Grating Slow Wave Circuit for 263 GHz Sheet Beam TWT

The complete design process of a high-frequency circuit for a 263 GHz staggered double grating, sheet beam traveling wave tube is presented in this article. Here, this device, for use in a pulsed electron paramagnetic resonance spectrometer instrument, requires >30 dB gain and a 20 GHz bandwidth centered at 263 GHz. In addition to the standard Pierce gain analysis and point by point particle in cell (PIC) simulation, a novel fast pulse response analysis technique was utilized to determine the accurate synchronization voltage and test the ``hot” feature of the high-frequency circuit. Since this new method can evaluate the entire bandwidth in a single simulation, it can significantly reduce the computational resources normally required for the conventional PIC analysis while also illustrating the potential instabilities near the band edge. Good agreement between the fast pulse response and PIC simulation results validate the accuracy of this novel method. According to the analysis results and given the manufacturing limits of nano/micro-computer numerical control (CNC) machining, an appropriate SWS, coupler, and sever designs were chosen to complement the simulated design. Finally, a prototype circuit was manufactured and cold tested to verify the design and inspect the machining tolerances.

42 ENGINEERING↗