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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Diffusion kinetics of 3 He in pyroxene and plagioclase and applications to cosmogenic exposure dating and paleothermometry in mafic rocks

In this study, we investigate the diffusivity of cosmogenic 3 He in a variety of plagioclase and pyroxene compositions, and its application to paleothermometry and exposure dating in these minerals, through stepwise degassing experiments. While cosmogenic 3 He has been utilized for exposure dating in pyroxene for decades due to its retentivity, plagioclase, often found along with pyroxene in mafic rocks, is generally less retentive of cosmogenic noble gas. However, the diffusivity of 3 He in either plagioclase or pyroxene has not yet been measured quantitatively. A challenge in measuring diffusion kinetics by step-degassing experiments in poorly retentive minerals is the fact that significant amounts of He can be lost prior to the experiment. To address this issue, we apply a forward “multiple diffusion domain” (MDD) inversion model that includes model predictions of initial gas loss during irradiation and storage of the samples to account for this observation and add constraints to the diffusion parameters. We find that 3 He diffusivity in plagioclase appears to be highly variable. This variability can be explained by the MDD inversion models' inability to constrain the diffusion parameters when significant gas has been lost during irradiation and/or prolonged storage prior to experiment analysis, resulting in an overestimation of 3 He retentivity. Plagioclase samples that were kept frozen after irradiation, to limit this initial gas loss, yielded the most reliable estimate of diffusion kinetics. We find that 3 He in plagioclase is diffusively lost at Earth's surface temperatures on a timescale of 100 years and is therefore unsuitable for surface temperature paleothermometry. On the contrary, we find cosmogenic 3 He in pyroxene to be retentive at Earth's surface temperatures on a 1-million-year timescale.

Bergelin, Marie [Berkeley Geochronology Center (BG↗
DOE OSTI2017

A Non-Modeling Exploration of Residential Solar Photovoltaic (PV) Adoption and Non-Adoption

Although U.S. deployment of residential rooftop solar photovoltaic (PV) systems has accelerated in recent years, PV is still installed on less than 1 percent of single-family homes. Most research on household PV adoption focuses on scaling initial markets and modeling predicted growth rather than considering more broadly why adoption occurs. Among the studies that have investigated the characteristics of PV adoption, most collected data from adopters, sometimes with additional non-adopter data, and rarely from people who considered but did not adopt PV. Yet the vast majority of Americans are non-adopters, and they are a diverse group - understanding their ways of evaluating PV adoption is important. Similarly, PV is a unique consumer product, which makes it difficult to apply findings from studies of other technologies to PV. In addition, little research addresses the experience of households after they install PV. This report helps fill some of these gaps in the existing literature. The results inform a more detailed understanding of residential PV adoption, while helping ensure that adoption is sufficiently beneficial to adopters and even non-adopters.

14 SOLAR ENERGY↗
DOE OSTI2022

Plant-level performance and degradation of 31 GW DC of utility-scale PV in the United States

In this updated study, which samples 50% more capacity than the original and adds two additional years of operating history, we assess the performance of a fleet of 631 utility-scale PV plants totaling 31.0 GW DC (23.6 GW AC ) of capacity that achieved commercial operations in the United States from 2007-2018 and that have operated for at least two full calendar years. We use detailed information on individual plant characteristics, in conjunction with modeled irradiance data, to model expected or “ideal” capacity factors in each full calendar year of each plant’s operating history. A comparison of ideal versus actual first-year capacity factors finds that this fleet has modestly underperformed initial expectations (as modeled) on average, though perhaps due as much to modeling issues as to actual underperformance. We then analyze fleet-wide performance degradation in subsequent years by employing a “fixed effects” regression model to statistically isolate the impact of age on plant performance. The resulting average fleet-wide degradation rate of -1.2%/year (±0.1%) represents a slight improvement (seemingly driven by the oldest plants in our sample) over the -1.3%/year (±0.2%) found in our original study, yet is still of greater magnitude than is commonly found. We emphasize, however, that these fleet-wide estimates reflect both recoverable and unrecoverable degradation across the entire plant, and so will naturally be of greater magnitude than module- or cell-level studies, and/or studies that focus only on unrecoverable degradation. Moreover, when focusing on a sub-sample of newer and larger plants with higher DC:AC ratios—i.e., plants that more-closely resemble what is being built today—we find a more moderate sample-wide average performance decline of -0.7%/year (±0.4%), which is more in line with other estimates from the recent literature.

14 SOLAR ENERGY↗
DOE OSTI2024

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗
DOE OSTI2024

International fuel performance study of fresh fuel experiments for PCMI effects during RIA experiments

This paper presents the results of High-burnup Experiments for Reactivity-initiated Accident (HERA) Modeling & Simulation (M&S) exercise. The HERA project under the Nuclear Energy Agency (NEA) Second Framework for Irradiation Experiments (FIDES-II) program is focused on studying Light Water Reactor (LWR) fuel behavior during Reactivity-Initiated Accident (RIA) conditions. The Part I M&S cases are based on a series of tests in the Transient Reactor Test (TREAT) facility in the United States and the Nuclear Safety Research Reactor (NSRR) in Japan. The purpose of this work is to evaluate the test design to accomplish its goals in establishing clearer understanding of the effects of power pulse width during RIA conditions. Further, the blind predictions using various computational tools have been performed and compared amongst to interpret the behaviors of high burnup fuels during RIA. While many international participants evaluate the thermal–mechanical behavior of fuel rod under different conditions, a considerable scatter of outputs comes out for the cases due to the disparity between codes in predicting mechanical behaviors. In general, however, the results of thermal–mechanical analysis elaborate that nominal design conditions the shorter pulse width tests in NSRR should cause cladding failures while the TREAT tests appear to have more split prediction of failure or not. Furthermore, the sensitivity analysis varying key testing parameters reveals the considerable effect of power pulse width and total energy deposition on prediction of fuel rod failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Phase diagram of the triangular-lattice Potts antiferromagnet

Here, we study the phase diagram of the triangular-lattice Q-state Potts model in the real $(Q, v)$ -plane, where $v={\rm e}^J-1$ is the temperature variable. Our first goal is to provide an obviously missing feature of this diagram: the position of the antiferromagnetic critical curve. This curve turns out to possess a bifurcation point with two branches emerging from it, entailing important consequences for the global phase diagram. We have obtained accurate numerical estimates for the position of this curve by combining the transfer-matrix approach for strip graphs with toroidal boundary conditions and the recent method of critical polynomials. The second goal of this work is to study the corresponding $A_{p-1}$ RSOS model on the torus, for integer $p=4, 5, \ldots, 8$ . We clarify its relation to the corresponding Potts model, in particular concerning the role of boundary conditions. For certain values of p, we identify several new critical points and regimes for the RSOS model and we initiate the study of the flows between the corresponding field theories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Multi Resolution In-Situ Testing and Multiscale Simulation for Creep Fatigue Damage Analysis of Alloy 617

This report outlines the research activities that were carried out for the integrated experimental and simulation investigation of creep-fatigue damage mechanism and life prediction of Nickel-based alloy, Inconel 617 at high temperatures (950° and 850°). First, a novel experimental design using a hybrid control technique is proposed. The newly developed experimental technique can generate different combinations of creep and fatigue damage by changing the experimental design parameters. Next, detailed imaging analysis and statistical data analysis are performed to quantify the failure mechanisms of the creep fatigue of alloy 617 at high temperatures. It is observed that the creep damage is directly associated with the internal voids at the grain boundaries and the fatigue damage is directly related to the surface cracking. It is also observed that the classical time fraction approach does not has a good correlation with the experimental observed damage features. An effective time fraction parameter is seen to have an excellent correlation with the material microstructural damage. Thus, a new empirical damage interaction diagram is proposed based on the experimental observations. Following this, a macro level viscoplastic model coupled with damage is developed to simulate the stress/strain response under creep fatigue loadings. A damage rate function based on the hysteresis energy and creep energy is proposed to capture the softening behavior of the material and a good correlation with life prediction and material hysteresis behavior is observed. The simulation work is extended to include the microstructural heterogeneity. A crystal plasticity finite element model considering isothermal and large deformation conditions at the microstructural scale has been developed for fatigue, creep-fatigue as well as creep deformation and rupture at high temperature. The model considers collective dislocation glide and climb of the grains and progressive damage accumulation of the grain boundaries. The glide model incorporates a slip resistance evolution model that characterizes the solute-drag creep effects and can capture well the stress-strain and stress time response of fatigue and creep-fatigue tests at various strain ranges and hold times. In order to accurately capture the creep strains that accumulate particularly at relatively low stress levels, a dislocation climb model has been incorporated into the crystal plasticity modeling framework. The dislocation climb model parameters are calibrated and verified through experimental creep tests performed at 950°. In addition, a cohesive zone model has been fully implemented in the context of the crystal plasticity finite element model to capture the intergranular creep damage. The parameters of the cohesive zone model have been calibrated using available experimental data. The numerical simulations illustrate the capability of the proposed model in capturing damage initiation and growth under creep loads as compared to the experimental observations. The microscale analysis sheds light on the crack initiation sites and propagation patterns within the microstructure. The model is also utilized to investigate the hybrid-controlled creep-fatigue tests and has been found to capture reasonably well the stress-strain response with different hold times and hold stress magnitudes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Utilizing physics-based input features within a machine learning model to predict wind speed forecasting error

Machine learning is quickly becoming a commonly used technique for wind speed and power forecasting. Many machine learning methods utilize exogenous variables as input features, but there remains the question of which atmospheric variables are most beneficial for forecasting, especially in handling non-linearities that lead to forecasting error. This question is addressed via creation of a hybrid model that utilizes an autoregressive integrated moving-average (ARIMA) model to make an initial wind speed forecast followed by a random forest model that attempts to predict the ARIMA forecasting error using knowledge of exogenous atmospheric variables. Variables conveying information about atmospheric stability and turbulence as well as inertial forcing are found to be useful in dealing with non-linear error prediction. Streamwise wind speed, time of day, turbulence intensity, turbulent heat flux, vertical velocity, and wind direction are found to be particularly useful when used in unison for hourly and 3 h timescales. The prediction accuracy of the developed ARIMA–random forest hybrid model is compared to that of the persistence and bias-corrected ARIMA models. The ARIMA–random forest model is shown to improve upon the latter commonly employed modeling methods, reducing hourly forecasting error by up to 5 % below that of the bias-corrected ARIMA model and achieving an R 2 value of 0.84 with true wind speed.

17 WIND ENERGY↗
DOE OSTI2017

Type Ib and IIb Supernova Progenitors in Interacting Binary Systems

We explore properties of Type Ib and IIb SN progenitors that are produced by stable mass transfer in binary systems using a new grid of stellar evolution models from an initial primary mass in the range of 10--18 M{sub ⊙} at solar and Large Magellanic Cloud metallicities. We find that blue and yellow supergiant SN IIb progenitors (e.g., of SN 2008ax, SN 2011dh, and SN 2016gkg) have a hydrogen envelope mass less than about 0.15 M{sub ⊙}, mostly resulting from early Case B mass transfer with relatively low initial masses and/or low metallicity. Red supergiant (RSG) SN IIb progenitors (e.g., of SN 1993J, SN 2013df) are produced via late Case B mass transfers and have a more massive hydrogen envelope (M{sub H,env}>0.15 M{sub ⊙}). SN Ib progenitors are predominantly produced by early Case B mass transfers. Our models predict that SN IIb progenitors are systematically more luminous in the optical (−8.0≲M{sub V}≲−5.0) than the majority of SN Ib progenitors (M{sub V}≳−5.0) for our considered initial mass range. However, the optically bright progenitor of SN Ib iPTF13bvn (i.e., M{sub V}≃−6.5) can be well explained by a relatively low-mass progenitor with a final mass of ∼3.0 M{sub ⊙}. The event rate of blue and yellow SN IIb progenitors would increase as metallicity decreases, while the event rate of SN Ib progenitors would decrease instead. By contrast, the population of RSG SN IIb progenitors would not be significantly affected by metallicity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Spectra and flow of light nuclei in relativistic heavy ion collisions at energies available at the BNL Relativistic Heavy Ion Collider and at the CERN Large Hadron Collider

Within the framework of the coalescence model based on the phase-space distributions of protons and neutrons generated from the iebe-vishnu hybrid model with ampt initial conditions, we study the spectra and elliptic flow of deuterons and helium-3 in relativistic heavy ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Larger Hadron Collider (LHC). Results from our model calculations for Au+Au collisions at √ s NN = 200 GeV at RHIC and Pb+Pb collisions at √ s NN = 2.76 TeV at the LHC are compared with available experimental data. Good agreements are generally seen between theoretical results and experimental data, except that the calculated yield of helium-3 in Pb+Pb collisions at √ s NN = 2.76 TeV underestimates the data by about a factor of 2. Possible reasons for these discrepancies are discussed. Here, we also make predictions on the spectra and elliptic flow of deuterons and helium-3 in Pb+Pb collisions at √ s NN = 5.02 TeV that are being studied at LHC.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Modeling of High-Temperature Corrosion of Zirconium Alloys Using the eXtended Finite Element Method (X-FEM)

Oxidation modeling in modern nuclear fuel performance codes is currently limited by the lack of coupling with mechanics, thus preventing proper description of how high-temperature oxidation impacts mechanical properties. This is mostly due to the fact that the finite difference formalism adopted in corrosion models is incompatible with the direct coupling with mechanics in the finite element modeling employed in modern nuclear fuel performance codes. In this study, a physically based zirconium alloy corrosion model called the Coupled-Current Charge Compensation (C4) model, which was initially developed for operating temperature conditions, has been updated to include high-temperature corrosion in order to provide additional critical information (e.g., oxygen concentration profile) under loss-of-coolant accident (LOCA) conditions—information lacking in existing empirical models. The C4 model was implemented in the MOOSE finite-element framework developed at Idaho National Laboratory, enabling it to be used in the BISON nuclear fuel performance code based on the MOOSE framework. To precisely track the different interfaces at a relatively low computational cost, the eXtended Finite Element Method (X-FEM) was applied in MOOSE. The model’s results were compared to those of existing empirical models as well as metallographic analysis of high-temperature oxidized Zircaloy-4 coupons. Oxygen diffusivities in the a and ß phases resulting from this comparison closely agree with those found in the literature. The C4 model implemented with X-FEM in MOOSE now has the capability to accurately predict oxide, oxygen-stabilized a, and prior ß phase layer growth kinetics under isothermal exposure at high temperature (1000–1500°C). Furthermore, in contrast with the empirical models, the C4 model accounts for the finite thickness of the fuel cladding. It can predict the oxygen concentration profile evolution through the whole cladding, enabling evaluation of the remaining ductile thickness—a crucial variable for modeling the mechanical behavior of the fuel cladding under LOCA. Furthermore, this implementation allows direct coupling with mechanics, at a low computing cost, using finite-element-based nuclear fuel performance codes such as BISON.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Experiments and simulations of isochorically heated warm dense carbon foam at the Texas Petawatt Laser

An experimental and simulation study of warm dense carbon foams at ambient density (n e ~10 21 cm –3 ) is presented. This study of isochorically heated foams is motivated by their potential application in carbon-atmosphere white-dwarf envelopes, where there are modeling uncertainties due to the equation of state. The foams are heated on an approximately picosecond time scale with a laser-accelerated proton beam. The cooling and expansion of the heated foams can be modeled with appropriately initialized radiation-hydrodynamics codes; xRAGE code is used in this work. The primary experimental diagnostic is the streaked optical pyrometer, which images a narrow band of radiation from the rear surface of the heated material. Presented are xRAGE modeling results for both solid aluminum targets and carbonized resorcinol-formaldehyde foam targets, showing that the foam appears to cool slowly on the pyrometer because of partial transparency. So that simulations of cooling foam are processed properly, it is necessary to account for finite optical depth in the photosphere calculation, and the methods for performing that calculation are presented in depth.

36 MATERIALS SCIENCE↗
DOE OSTI2022

1D Modeling for the Development of a Digital Twin for Hydropower Systems with Applications for a Testing Rig

Modeling and simulation constitute two important parts in constructing a sensible digital twin to mimic the dynamics of hydropower systems. Because of the physical nature of a hydropower system, the basic modeling should cover the water flow systems from the reservoir to the penstock (inlet water pipes), penstock to hydro turbine, and hydro turbine to generator and from the linkage of the hydropower systems to the grid. This report describes initial attempts to model these dynamic components, including the formulation of the linearized state space model for hydro turbine systems using the well-known six-coefficients linearization method and the formulation of the voltage and power dynamical models of a synchronous generator. To validate the accuracy of the proposed model, data collected from Norwegian University of Science and Technology were used to obtain relevant parameters for the model, and the desired simulation results were obtained. Additionally, neural network modeling and learning were also developed and applied to model the generation torque and water flow rate subsystems to demonstrate a potential learning scheme, which can be used in the development of a digital twin.

13 HYDRO ENERGY↗
DOE OSTI2023

Predicting encapsulant delamination in photovoltaic modules bridging photochemical reaction kinetics and fracture mechanics

Abstract Photovoltaic (PV) modules are subjected to environmental stressors (UV exposure, temperature, and humidity) that cause degradation within the encapsulant and its interfaces with adjacent glass and cell substrates. To save experimental time and to enable long‐term assessment with intensive degradation only taking place after many years, the development of predictive models is indispensable. Previous works have modeled the delamination of the ethylene vinyl acetate (EVA) encapsulant/glass and encapsulant/cell interfaces under field aging conditions with fundamental photochemical degradation reactions that lead to molecular scission and loss of interfacial adhesion, characterized by the fracture resistance, G c . However, these models were fundamentally limited in that the following aspects were not incorporated: (i) molecular crosslinking in the field, (ii) synergistic autocatalytic interactions of degradation mechanisms, (iii) connection between degraded encapsulant structure and its mechanical properties, and (iv) rigorous treatment of the plasticity contribution to G c with finite element models. Here, we present a time‐dependent multiscale model that addresses these limitations and is applicable to a wide range of encapsulants and interfaces. For the reference EVA encapsulant and its interfaces with the glass and cell, the presented model predicts an initial rise in G c in the first 3 years of field aging from crosslinking, then a subsequent sharp decline from degradation mechanisms. We used nanoindentation to measure the changes in EVA mechanical properties over exposure time to tune the model parameters. The model predictions of G c and mechanical properties match with experimental data and show an improvement compared to previous models. The model can even predict switches in failure interfaces, such as the observed EVA/cell to EVA/glass transition. We also conducted a sensitivity analysis study by varying the degradation and crosslinking kinetic parameters to demonstrate their effects on G c . Model extensions to polyolefin elastomer‐ and silicone‐encapsulants and their interfaces are also demonstrated.

Liu, Kuan↗
DOE OSTI2020

An overview of the Energy Modeling Forum 33rd study: Assessing large-scale global bioenergy deployment for managing climate change

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2°C or 1.5°C. However, with significant variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University’s Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run, biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research.

Rose, Steven K.↗
DOE OSTI2020

Adult weight change and premenopausal breast cancer risk: A prospective pooled analysis of data from 628,463 women

Early-adulthood body size is strongly inversely associated with risk of premenopausal breast cancer. It is unclear whether subsequent changes in weight affect risk. We pooled individual-level data from 17 prospective studies to investigate the association of weight change with premenopausal breast cancer risk, considering strata of initial weight, timing of weight change, other breast cancer risk factors and breast cancer subtype. Hazard ratios (HR) and 95% confidence intervals (CI) were obtained using Cox regression. Among 628,463 women, 10,886 were diagnosed with breast cancer before menopause. Models adjusted for initial weight at ages 18–24 years and other breast cancer risk factors showed that weight gain from ages 18–24 to 35–44 or to 45–54 years was inversely associated with breast cancer overall (e.g., HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.95–0.98) and with oestrogen-receptor(ER)-positive breast cancer (HR per 5 kg to ages 45–54: 0.96, 95% CI: 0.94–0.98). Weight gain from ages 25–34 was inversely associated with ER-positive breast cancer only and weight gain from ages 35–44 was not associated with risk. None of these weight gains were associated with ER-negative breast cancer. Weight loss was not consistently associated with overall or ER-specific risk after adjusting for initial weight. Weight increase from early-adulthood to ages 45–54 years is associated with a reduced premenopausal breast cancer risk independently of early-adulthood weight. Biological explanations are needed to account for these two separate factors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Finite-Time Universality in Nonequilibrium CFT

Recently, remarkably simple exact results were presented about the dynamics of heat transport in the local Luttinger model for nonequilibrium initial states defined by position-dependent temperature profiles. We present mathematical details on how these results were obtained. We also give an alternative derivation using only algebraic relations involving the energy-momentum tensor which hold true in any unitary conformal field theory (CFT). This establishes a simple universal correspondence between initial temperature profiles and the resulting heat-wave propagation in CFT. We extend these results to larger classes of nonequilibrium states. It is proposed that such universal CFT relations provide benchmarks to identify nonuniversal properties of nonequilibrium dynamics in other models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗