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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Model study of the energy dependence of the correlation between anisotropic flow and the mean transverse momentum in Au + Au collisions

A hybrid model that employs the hadron-string transport model UrQMD and the (3+1)-dimensional relativistic viscous hydrodynamic code vHLLE, is used to investigate the beam energy dependence of the correlation coefficient ρ(v$^{2}_{2}$,[p T ]) between the average transverse momentum [p T ] of hadrons emitted in an event and the square of the anisotropic flow coefficient v$^{2}_{2}$. For Au+Au collisions, the model predicts characteristic patterns for the energy and event-shape dependence of the variances for [p T ] and v$^{2}_{n}$ [Var([p T ] and Var(v$^{2}_{2}$)], and the covariance of v$^{2}_{n}$ and [p T ][cov(v$^{2}_{2}$,[p T ])], consistent with the attenuation effects of the specific shear viscosity η/s. Here in contrast, ρ(v$^{2}_{2}$,[p T ]) is predicted to be insensitive to the beam energy but sensitive to the initial-state geometry of the collisions. These observations suggest that a precise set of measurements for Var([p T ]), Var(v$^{2}_{2}$), cov(v$^{2}_{2}$,[p T ]) and ρ(v$^{2}_{2}$,[p T ]) as a function of beam energy and event shape, could serve to constrain better the eccentricities and their fluctuations over the entire span of beam energies, and consequently aid precision extraction of the temperature and baryon chemical-potential dependence of η/s from the wealth of Au+Au data obtained in the RHIC beam energy scan.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Three-point energy correlators in hadronic Higgs boson decays

We present the analytic calculation of the leading-order three-point energy correlator (EEEC) in hadronic Higgs decays, including both the gluon-initiated channel H → g g + X and quark-initiated channel H → q q ¯ + X . The phase-space integration is evaluated directly using Mandelstam variables s i j = ( p i + p j ) 2 , and the appearing square roots can be rationalized by either conformal ratios or celestial coordinate variables. Throughout the calculation, we observe the same transcendental function space as in N = 4 super–Yang-Mills theory and e + e − → hadrons . Different infrared limits are also explored using the full analytic result, offering the fixed-order data for EEEC factorization and resummation. Given its nontrivial shape dependence, the EEEC presents an excellent opportunity to explore the dynamics of gluon jets originating from the H → g g decay channel at future lepton colliders. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

QCD axion: Some like it hot

We compare the quantum chromodynamics (QCD) axion phase-space distribution from unitarized next-to-leading order chiral perturbation theory with the one extracted from pion-scattering data. We derive a robust bound by confronting momentum-dependent Boltzmann equations against up-to-date observations of the cosmic microwave background, of the baryonic acoustic oscillations and of primordial abundances. These datasets imply 𝑚 𝑎 ≤ 0.16 eV for the 95% credible interval, i.e., ∼ 30% stronger bound than what previously found. We present forecasts using dedicated likelihoods for future cosmological surveys and the sphaleron rate from unquenched lattice QCD.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

From Hydrodynamics to Jet Quenching, Coalescence, and Hadron Cascade: A Coupled Approach to Solving the $R_{AA}Ⓧv_{2}$ Puzzle

Hydrodynamics and jet quenching are responsible for the elliptic flow $v_{2}$ and suppression of large transverse momentum ($p_{T}$) hadrons, respectively, two of the most important phenomena leading to the discovery of a strongly coupled quark-gluon plasma in high-energy heavy-ion collisions. A consistent description of the hadron suppression factor $R_{AA}$ and $v_{2}$, especially at intermediate $p_{T}$, however, remains a challenge. We solve this long-standing $R_{AA}Ⓧv_{2}$ puzzle by including quark coalescence for hadronization and final state hadron cascade in the coupled linear Boltzmann transport-hydro model that combines concurrent jet transport and hydrodynamic evolution of the bulk medium. We illustrate that quark coalescence and hadron cascade, two keys to solving the puzzle, also lead to a splitting of $v_{2}$ for pions, kaons, and protons in the intermediate $p_{T}$ region. We demonstrate for the first time that experimental data on $R_{AA}, v_{2}$, and their hadron flavor dependence from low to intermediate and high $p_{T}$ in high-energy heavy-ion collisions can be understood within this coupled framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Worldwide Physics-Based Lifetime Prediction of c-Si Modules Due to Solder-Bond Failure

Lifetime prediction of the fielded c-Si solar modules due to location-specific weather conditions has been an important topic of photovoltaic research and the economic viability of solar energy. Data analytic techniques such as the performance ratio method, Statistical clear sky model, and Suns-Vmp methods quantify the degradation from measured data of a solar farm, however, the nonlinear time-dependence and correlated degradations make it difficult to use the empirical degradation rates for ultimate lifetime projection. In this article, we propose a complementary physics-based model to predict the solder bond failure caused by mechanical stress associated with the variations of the temperature. Integrating the worldwide weather information from NASA/NSRDB databases, the model predicts the location-specific output-power degradation and the lifetime of a module due to solder bond failure. The model parameters are calibrated against qualification tests involving thermal cycling of specific batches of modules from a specific technology/manufacturer. The results may be summarized as: 1) Modules installed at higher latitudes show a longer lifetime due to reduced damage accumulation. 2) The reduction of temperature fluctuation close to large bodies of water, such as seashores, increases solder bond lifetime significantly. 3) Relatively speaking, modules installed close to the Tropic of Cancer/Capricorn (23.5 degrees North/South) suffer from a higher solder bond damage and have a shorter lifetime, suggesting a conservative design. This model should serve as a building block of a comprehensive reliability framework that can predict the lifetime of a module that experiences simultaneous and correlated degradation mechanisms involving yellowing, corrosion, and potential-induced degradation.

14 SOLAR ENERGY↗
DOE OSTI2022

A Regime-Switching Spatio-Temporal GARCH Method for Short-Term Wind Forecasting

The growth of wind energy poses challenges to the integration of wind energy into the power grid. Within a wind farm, the conditions of local wind exhibit sizeable variations in very short term period and temporal wind speed patterns vary from turbine to turbine. Hence, short-term wind forecasting has been adopted to assist power system operations. In this work, we propose a wind plant-level short term wind speed and power forecasting methodology considering turbine contributions. The proposed model utilizes spatio-temporal dependencies and nonstationarity to accommodate the characteristics of wind farm data by using a novel regime-switching spatiotemporal generalized autoregressive conditional heteroscedasticity (RS-stGARCH) model. Case studies based on 2 years of data from a wind farm shows that the proposed RS-stGARCH method outperforms benchmark models by up to 21.10% for wind speed forecasting and up to 58.62% for the wind power forecasting.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Performance Testing and Assessment of Protection Scheme Using Real-Time Hardware-in-the-Loop and IEC 61850 Standard

The main challenge of the microgrid is to design a suitable protection scheme due to the complexity of the architecture of the microgrid. The importance of the proposed protection technique is threefold. First, it presents a co-simulation platform to integrate between a simulated model on power system computer aided design (PSCAD)/real time digital simulator computer aided design (RSCAD) software’s and physical devices schweitzer engineering laboratories (SEL) 421-7 relays to protect the microgrid that includes different resources connected based on inverter interface. Second, it presents a comprehensive hardware/software setup to test the protective relays in a closed loop system and shows how to configure the protective relay’s International Electrotechnical Commission 61850 communications. Third, IEEE 1588 standard is used to provide sub nanoseconds latency between the simulated model that emulated on real time digital simulator (RTDS) and the external devices. Also, the measurement signals are synchronized between RTDS and the external devices using giga-transceiver synchronization card (GTSYNC) interface card and SEL-2488 satellite-synchronized network clock. The results showed that the co-simulation infrastructure introduces a highly dependable design, analysis, and testing environment for cyber and physical data flow in the system. Besides that, the voltages at ac/dc sides and frequency at fault condition were maintained due to the energy storage device contributions at different modes of operation.

42 ENGINEERING↗
DOE OSTI2023

A General Framework for Human-in-the-Loop Cognitive Digital Twins

Modelling and analysis of systems that are equipped with sensors and connected to the Internet are becoming more automated and less human-dependent. However, bringing expert knowledge into the loop along with data obtained from Internet of Thing (IoT) devices minimizes the risk of making poor and unexplainable decisions and helps to assess the impact of different strategies before applying them in reality. While Digital Twins are more of a data-driven simulation of the physical system, Cognitive Digital Twins bring the human dimension into the modelling and simulation. In this paper, we aim to emphasize the crucial role of explainability and the underlying rationale behind automated or interactive decision-making processes. Furthermore, we propose an initial framework that delineates the specific points within the feedback loop of a cognitive digital twin where human involvement can be incorporated.

Niloofar, Parisa↗
DOE OSTI2022

Effective mass of α-cluster in 12C nucleus

Based on the effective-mass concept, we perform the Faddeev calculations for a low-lying spectrum of 3[Formula: see text] states in [Formula: see text]C nucleus. A three-body potential is used to describe the known breaking of the 3[Formula: see text]-cluster structure in the nucleus. We show that the contribution of the three-body potential to the Hamiltonian can be compensated by increasing/decreasing the [Formula: see text]-particle free mass. The effective-mass values are adjusted to reproduce the experimental data for the [Formula: see text]C nucleus. The energy dependence of the effective mass and the correlation to a three-body potential are discussed. We show that the coupling between the [Formula: see text] ([Formula: see text]) levels forms a specific picture of anti-crossing on the energy/effective-mass plane.

Physics↗
DOE OSTI2020

Computational study of TATB

We have performed a computational study of TATB. The study is composed of two parts, one where we perform static T = 0 K calculations with several different DFT functionals, to investigate structural properties and obtain a cold curve. Even though the functionals used in this study give poor results at ambient pressure, they perform much better at compression, when the dominance of the van der Waals’ forces in the binding is replaced by more normal interactions. In particular AM05 gives good results, mainly because it doesn’t include any “faulty” van der Waals’. Indeed the van der Waals’ corrected functional (PBE+D2) results shows the worst performance on structural properties. For the cold curve the PBE+D2 functional gives the best results compared to experiments (room temperature) but since the structural properties were bad with this functional we cannot for sure say that this is in any way a validation. It is shown that scaling the AM05 results with a common factor reproduces the experimental data. We leave the question on why to a follow up study but speculate that maybe the experiment and our calculations do not represent the same system set-up. From the structural properties we identify a site in the TATB lattice that contains a high concentration of oxygen and hydrogen. The consequences of this finding, if any, are left to a future project. In the second part of the study we perform extensive high-quality DFT-MD (molecular dynamics with DFT forces) calculations to obtain points on the Hugoniot. This part of the study did not get finished within this project and a more extensive summary of this part will be given in a follow up report at a future date. However, we show that obtaining calculated data is essential for equations of state development since the existing experimental Hugoniot data barely deviates from room temperature isotherm data and thus give no information of the high temperature dependency of materials properties. Our conclusion so far in the project is that being able to calculate materials properties is essential for high explosives since experiments are unable to give information in the high temperature part of phase space. While blind use of DFT cannot (yet) give unambiguous answers, we can still explore qualitatively and use such information to guide us in EOS development. However, the main conclusion is that we need better functionals in DFT to easily extract needed properties from calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fast Emulation of Expensive Simulations using Approximate Gaussian Processes [Slides]

Nuclear Computational Low-Energy Initiative (NUCLEI) collaboration uses Density Functional Theory (DFT) simulations to predict the structure and binding energies of nuclei over a wide range of proton (Z) and neutron (N) numbers. The DFT simulations utilize a particular parameterization of a Skyrme energy density functional called UNEDF1 which depends on 12 free parameters that must be fit to data (M Kortelainen et al 2014). Fitting involves comparing (e.g.) predicted binding energies of nuclei to experimentally measured values. We use only binding energies as observables, but DFT with UNEDF1 will predict structure (shape) observables as well. In this work, assessing the capability of approximate GP emulators to balance emulator accuracy with computational speed to facilitate improved UNEDF1 calibration. Sparse GPs are straightforward to train and accurate. Calibration is not straightforward with MCMC (using MH or HMC/NUTS). We produced reusable software for continuing and building on this work as well as accessing and using Darwin cluster compute resources

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Exploring Si Heterojunction Solar Cell Degradation: Bulk and Interface Processes Analyzed by Simulations and Experiments in Order to Develop Mitigation Strategies

The Si technology with the highest conversion efficiency is a-Si/c-Si heterojunction (HJ) PV. Its market penetration, however, is slowed by reports that fielded HJ modules degraded at twice the rate of regular c-Si modules. Our very recent work confirmed this degradation and attributed it to enhanced recombination at the a-Si/c-Si interface, caused by the slow, order-of-magnitude increase of the defect density. We propose to comprehensively explore degradation mechanisms in Si HJ cells by combining simulations and experiments. Theoretically, we will: (1) simulate structure of a-Si and a-Si/c-Si interfaces, identify defects; (2) determine statistics of energy barriers that control defect formation; (3) compute growth of defect density from the barrier distribution, and the resulting degradation of Voc. Experimentally, we will: (1) create a series of HJ-cell-representative stacks with varying layer thicknesses and deposition conditions by using PECVD tools; (2) use temperature and injection-dependent lifetime spectroscopy to determine effective lifetimes; (3) deconvolve the data to separate bulk and interface effects, and the effects of charge density and interface defects to analyze long time degradation. The goal is to identify material and device degradation mechanisms, to develop mitigation strategies for improved stability, such as the introduction of capping layers and hydrogen diffusion control.

14 SOLAR ENERGY↗
DOE OSTI2022

Changes to the morphology and coefficient of thermal expansion in HDPE and UHMWPE following irradiation-based crosslinking

This work describes recent findings of the Los Alamos National Laboratory concerning the alterations to polyethylene’s (PE’s) mechanical and chemical properties after crosslinking via gamma irradiation. Three materials were examined as part of this study, including one HDPE and two UHMWPE specimens. Changes to degree of crystallinity (X C ) were qualitatively determined via measurements of density, and results suggest that X C is not necessarily correlated to crosslink density, depending on polymer manufacturing process and treatment following irradiation. TMA data suggests an anisotropic response in linear thermal expansion, and that the response may be more correlated to X C than crosslink density. Finally, FTIR analysis has led to the conclusion that oxidation occurs as a result of irradiation in open air, the degree of oxidation is proportional to the maximum radiation dose received, and that oxidation is largely a surface effect, penetrating no deeper than 1.5 mm. Due to time constraints, a full dataset could not be generated for changes in creep and thermal properties as a result of irradiation, and TMA analysis is only complete for one material tested in this study. These measurements are ongoing and will provide more context to the hypotheses drawn in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-Temperature Mobility of Tungsten Grain Boundaries

The objective of this study is to assess the effect of hydrogen isotopes on mechanical properties of tungsten relevant to first-wall applications in a tokamak. We report progress on calculation of the mobility of tungsten grain boundaries at high temperature, a key property in the process of recrystallization. In prior work we studied tungsten grain boundary properties such as the energies of boundaries with various orientations and misorientations, including energies of grain boundary phases that differ in structure from those at low temperature. We have calculated properties associated with the grain boundary mobility including the response of grain boundaries to applied shear stress. Here we report direct calculation of the motion of curved grain boundaries at high temperature using molecular dynamics. We compute how the mobility increases with temperature and how the mobility depends on the grain boundary misorientation. These calculations form baseline data to calculate the change when hydrogen or other defects are present.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigation of Methane Generation Rates from Simulated and Radioactive Waste at Evaporator Conditions

Savannah River National Laboratory researchers have performed 9 experiments with simulated waste and 13 experiments with radioactive waste to determine methane generation rates (MGR) applicable to Savannah River Site waste at temperatures greater than or equal to 100 °C. Data from these experiments was used to generate temperature-dependent expressions to conservatively account for methane generation at elevated temperatures. Measured MGRs and the derived expressions are reported in units of standard cubic feet per hour per gallon of solution, where standard conditions are 25 °C and 1 atm.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2022

Device Classification for Industrial Control Systems Using Predicted Traffic Features

To achieve a secure interconnected Industrial Control System (ICS) architecture, security practitioners depend on accurate identification of network host behavior. However, accurate machine learning based host identification methods depends on the availability of significant quantities of network traffic data, which can be difficult to obtain due to system constraints such as network security, data confidentiality, and physical location. In this work, we propose a network traffic feature prediction method based on a generative model, which achieves high host identification accuracy. Furthermore, we develop a joint training algorithm to improve host identification performance compared to separate training of the generative model and the classifier responsible for host identification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data throughput and reduced energy consumption. Two popular techniques for reducing computation in neural networks are pruning, removing insignificant synapses, and quantization, reducing the precision of the calculations. In this work, we explore the interplay between pruning and quantization during the training of neural networks for ultra low latency applications targeting high energy physics use cases. Techniques developed for this study have potential applications across many other domains. We study various configurations of pruning during quantization-aware training, which we term quantization-aware pruning, and the effect of techniques like regularization, batch normalization, and different pruning schemes on performance, computational complexity, and information content metrics. We find that quantization-aware pruning yields more computationally efficient models than either pruning or quantization alone for our task. Further, quantization-aware pruning typically performs similar to or better in terms of computational efficiency compared to other neural architecture search techniques like Bayesian optimization. Surprisingly, while networks with different training configurations can have similar performance for the benchmark application, the information content in the network can vary significantly, affecting its generalizability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗