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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Viscosity of transient glass-forming melt and its relation to foaming during batch-to-glass conversion

Primary foam, which affects the heat transfer into the glass batch and the final glass quality, occurs when a sufficient quantity of transient glass-forming melt evolves with viscosity low enough to close the open porosity of the reacting glass batch. To better understand how the fraction of transient melt and its viscosity affect the primary foam temperature range, we determined, with x-ray diffraction, the fraction and composition of the transient glass-forming melt in a heated waste glass melter feed as a function of temperature. Then we prepared a set of transient melts that occurred within the foaming temperature interval and measured their viscosities with spindle and falling sphere viscometers. Further, the results agree with the Adam-Gibbs and VFT viscosity-composition models, even for transient melt compositions outside of the models compositional validity range. As silica and other refractory particles dissolved in the predominantly borate transient melt while temperature increased, viscosity increased from the initial value of ~500 Pa s at the onset of foaming (~650°C) to a maximum of ~770 Pa s when silica dissolution was almost complete (~700°C). As temperature increased further, transient melt viscosity decreased to ~220 Pa s (~850°C) when the primary foam collapsed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Constraining Aging Processes of Black Carbon in the Community Atmosphere Model Using Environmental Chamber Measurements

Abstract The direct radiative forcing of black carbon aerosol (BC) on the Earth system remains unsettled, largely due to the uncertainty with physical properties of BC throughout their lifecycle. Here we show that ambient chamber measurements of BC properties provide a novel constraint on the crude BC aging representation in climate models. Observational evidence for significant absorption enhancement of BC can be reproduced when the aging processes in the four‐mode version of the Modal Aerosol Module (MAM4) aerosol scheme in the Community Atmosphere Model version 5 are calibrated by the recent in situ chamber measurements. An observation‐based scaling method is developed in the aging timescale calculation to alleviate the influence of biases in the simulated model chemical composition. Model sensitivity simulations suggest that the different monolayer settings in the BC aging parameterization of MAM4 can cause as large as 26% and 24% differences in BC burden and radiative forcing, respectively. We also find that an increase in coating materials (e.g., sulfate and secondary organic aerosols) reduces BC lifetime by increasing the hygroscopicity of the mixture but enhances its absorption, resulting in a net increase in BC direct radiative forcing. Our results suggest that accurate simulations of BC aging processes as well as other aerosol species are equally important in reducing the uncertainty of BC forcing estimation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Cross-Categorical Transfer Learning based Composite Load Protection Modeling

Protection equipment is used to prevent damage to induction motor loads by isolating them from power systems in the event of severe faults. Modeling the response of induction motor loads and their protection is vital for power system planning and operation, especially in understanding system's dynamic performance and stability after a fault occurs. Induction motors are usually equipped with several types of protection with different operation mechanisms, making it challenging to develop adequate yet not overly complex protection models and determine their parameters for aggregate induction motor models. This paper proposes a novel cross-categorical transfer learning based framework to determine protection model parameters for aggregate induction motor loads in commercial buildings. Introducing a mathematical abstraction, the task of determining a suitable set of parameters for the protection model in composite load models is formulated as a combination of feature extraction using transferable layers, followed by affine operations through non-transferable layers applied on the previous extracted features. Numerical results are provided to illustrate the application of the framework.

transfer learning, Stacked Autoencoder, Composite ↗
DOE OSTI2021

$S$ parameter from a prototype composite-Higgs model

We have calculated the low-energy constant $L_{10}$ in a prototype composite Higgs model with dynamical fermions in two different representations of the gauge group. The resulting contribution of the new strong sector to the $S$ parameter is consistent with current bounds on the vacuum misalignment parameter. We end with a brief discussion of future directions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A layered solid finite element formulation with interlaminar enhanced displacements for the modeling of laminated composite structures

Accurate modeling of layered composite structures often requires the use of detailed finite element models which can sufficiently resolve the kinematics and material behavior within each layer of the composite. However, individually discretizing each material layer into finite elements presents a prohibitive computational expensive given the large number of thin layers comprising some laminated composites. To address these challenges, an 8-node layered solid hexahedral finite element is formulated with the aim of striking an appropriate balance between efficiency and fidelity. The element is discretized into an arbitrary number of distinct material layers, and employs reduced in-plane integration within each layer. The chosen reduced integration scheme is supplemented by a novel physical stabilization approach which includes layerwise enhancements to mitigate various forms of locking phenomena. The proposed framework additionally supports the inclusion of interlaminar enhanced displacements to better represent the kinematics of general layered composite materials. Finally, the described element formulation has been implemented in the ParaDyn finite element code, and its efficacy for modeling laminated composite structures is demonstrated on a variety of verification problems.

42 ENGINEERING↗
DOE OSTI2016

B-decay anomalies in a composite leptoquark model

Here, the collection of a few anomalies in semileptonic B-decays, especially in b → cτ$\overline{v}$, invites speculation about the emergence of some striking new phenomena, perhaps interpretable in terms of a weakly broken U(2) n flavor symmetry and of leptoquark mediators. We aim at a partial UV completion of this interpretation by generalizing the minimal composite Higgs model to include a composite vector leptoquark as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Mass–radius relation for rocky planets based on PREM

Several small dense exoplanets are now known, inviting comparisons to Earth and Venus. Such comparisons require translating their masses and sizes to composition models of evolved multi-layer interior planets. Such theoretical models rely on our understanding of the Earth’s interior, as well as independently derived equations of state, but so far have not involved direct extrapolations from Earth’s seismic model: the Preliminary Reference Earth Model (PREM). To facilitate more detailed compositional comparisons between small exoplanets and the Earth, we derive here a semi-empirical mass–radius relation for two-layer rocky planets based on PREM, (R/(R{sub ⊕}))=(1.07−0.21⋅CMF)⋅((M/(M{sub ⊕}))){sup 1/3.7}, where CMF stands for core mass fraction. It is applicable to 1 ∼ 8 M{sub ⊕} and a CMF of 0.0 ∼ 0.4. Applying this formula to Earth and Venus and several known small exoplanets with radii and masses measured to better than ∼30% precision gives a CMF fit of 0.26 ± 0.07.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Robust Time-Varying Parameter Identification for Composite Load Modeling

With the increasing integration of uncertain resources, e.g., renewables, electric vehicles, and demand responses, it is imperative to understand the characteristics of loads for power system analysis and control. Challenges of load modeling come from a variety of load components and time-varying compositions. In addition, the existence of outliers in measurements further complicates the problem. This paper proposes a robust time-varying parameter identification technique for composite ZIP and induction motor load models. A batch-model regression form, including time-varying parameters, is established based on state transition models and observation models with current observations and previous predictions to guarantee data redundancy. To deal with outliers, down-weighting coefficients of measurements are calculated with a projection statistics approach. Based on the batch-model regression and the down-weighting coefficients, parameter identification at each sample time is formulated as a weighted least squares optimization, which is solved by the Newton-Raphson approach with the previous estimated parameters as the initial iteration values. In addition, parameters' sensitivities to different outliers in measurements are analyzed. Results on the IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm can robustly identify time-varying parameters for the composite load models.

Composite load model↗
DOE OSTI2020

Open-Source High-Fidelity Aggregate Composite Load Models of Emerging Load Behaviors for Large-Sale Analysis

The goal of this project is to accurately model the dynamic loads for power system planning and operation and to address the challenges inherent in such modeling. Existing load models are inadequate to handle the increasing proliferation of residential air conditioner loads and distributed energy resources, the emerging trends of price-responsive demand, and the growing importance of protective devices in equipment and buildings. A need has emerged to develop a fundamentally new class of load models and next-generation data tools. This work proposes to develop a set of regional–level, scalable open source load models and tools, including large-scale aggregate load protection, concept of price responsive demand, advanced load composition data, next-generation load model data tools, and advanced composite load model calibration and validation frameworks to address new challenges in the representation of next-generation load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Chemical durability assessment of enhanced low-activity waste glasses through EPA method 1313

In this work, we report the progress of the Glass Leaching Assessment for Durability (GLAD) program on the implementation of the United States Environmental Protection Agency (EPA) Leaching Environmental Assessment Framework pH-dependent leach test (EPA Method 1313) to low-activity nuclear waste (LAW) glasses. The GLAD program seeks to develop new strategies to understand the chemical durability of nuclear waste glasses for the disposal in near-surface conditions. A series of 16 high-waste loading LAW glasses, currently under development, were selected using machine learning methods to study the corrosion behavior using EPA Method 1313. Reacted glass powders were examined using scanning electron microscopy and the eluate compositions were examined using inductively coupled plasma-optical emission spectroscopy. Compositional modeling was used to fit the measured elemental releases from EPA Method 1313. The compositional models demonstrated that elements such as Si reduce elemental release while B can increase elemental release (consistent with elemental modeling of the Product Consistency Test and Vapor Hydration Test) while other elements, such as Fe, exhibit pH-dependent behavior. The amount of acid added during the EPA testing was found to significantly impact the observed result, which was only apparent after preforming the present matrix study. The overall titration curves were able to be compositionally modeled for future process optimization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Model Package Report: Composite Analysis Solid Waste Release Model (CASWR Model)

This document describes the implementation of a solid waste form release model in GoldSim for the Hanford Site Composite Analysis (CA) Update. This Composite Analysis Solid Waste Release model (CASWR model) was designed to generate deterministic radionuclide release rates for Hanford’s Central Plateau solid waste disposal sites using single realizations of release model coefficients. Five generalized waste form types are used for the conceptual model of waste release: surplus reactor block, cement, soil-debris, grouted residual waste, and ancillary equipment. The surplus reactor block waste form consists of radionuclide leaching from surplus production graphite reactor core blocks via unspecified processes (White et al., 1984 as cited in PNNL-15965). The cement waste form represents solidified wastes whose permeability is much lower than that of the surrounding soil. The soil-debris waste form type is defined as unconsolidated waste mixed with soil material. Tanks and canyon complexes comprise the grouted residual waste form such that their solid waste will be grouted and capped with a surface barrier at the completion of their cleanup. Finally, the ancillary equipment waste form constitutes contaminant releases from ancillary and auxiliary waste form residues associated with tank farms at closure. Individual sub-models are implemented to numerically represent a respective waste form within the CASWR Model: Surplus Reactor Block Sub-model, Cement Sub-model, SoilDebris Sub-model, Grouted Residual Waste Sub-model, and Ancillary Equipment Submodel. Advection is assumed to be the primary transport process governing the release of radionuclides in the Ancillary Equipment and Soil-Debris Sub-models. Diffusion is assumed to be the primary release process in the Grouted Residual Waste and Cement Sub-models. An unspecified zero-order release process is considered in the Surplus Reactor Block Sub-model due to the lack of information regarding actual processes involved in irradiated graphite leaching. The Surplus Reactor Block, Cement, and SoilDebris Sub-models were compared against analytical solutions (PNNL-11800, Composite Analysis for Low-Level Waste Disposal in the 200 Area Plateau of the Hanford Site). The agreement between results of these analytical solutions and the corresponding waste form models verified their correct implementation in GoldSim. A 1-D modeling abstraction approach for the Grouted Residual Waste and Ancillary Equipment Sub-models was adopted from existing Performance Assessment (PA) models. Despite the simplifications made in these sub-models, they were found to be appropriate representations of the waste forms, similar to what was used in the Waste Management Area C PA model (RPP-ENV-58782, Performance Assessment of Waste Management Area C, Hanford Site, Washington, Rev. 0). A sensitivity analysis was conducted to identify the most influential parameters in each waste form sub-model. Suggestions for considering pH-dependent and redox-dependent release mechanisms are formulated through the development of a conditional constant approach in GoldSim.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Model-based compositional predictions for a differential scanning calorimetry/thermogravimetric analysis-mass spectrometry system used for heat of vaporization measurements

A Differential Scanning Calorimetry/Thermogravimetric Analysis (DSC/TGA) procedure for determination of Heat of Vaporization (HOV) of fuel and surrogate fuel mixtures has been previously utilized for evaluation of oxygenate impacts on spark ignition fuels. This analysis has been further leveraged with mass spectrometry (MS) to elucidate vapor phase compositional changes during evaporation. In this study we focus on a simple system of three compounds (ethanol, n-hexane, and n-octane) to provide a model-based understanding of the evaporation process under these experimental conditions. An Aspen Plus model was set up to provide liquid and vapor phase concentration predictions during mixture evaporation using the initial mixture composition, and measured temperature and mass loss profiles from DSC/TGA experiments. Agreements between the trends of the MS ion count profiles and model composition predictions provide a degree of validation of this modeling approach that can allow the interpretation and extrapolation of DSC/TGA measurements for more complex fuel mixtures.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

Lithium diffusion at Si-C interfaces in silicon-graphene composites

Models of intercalated Li and its diffusion in Si-Graphene interfaces are investigated using density functional theory. Results suggest that the presence of interfaces alters the energetics of Li binding and diffusion significantly compared to bare Si or Graphene surfaces. Our results show that cavities along reconstructed Si surface provide diffusion paths for Li. Diffusion barriers calculated along these cavities are significantly lower than penetration barriers to bulk Si. Interaction with Si surface results in graphene defects, creating Li diffusion paths that are confined along the cavities but have still lower barrier than in bulk Si.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Temperature and Composition Dependence Modeling of Viscosity and Electrical Conductivity of Low-Activity Waste Glass Melts

The development of models that accurately relate the properties of a glass melt to its temperature and composition is important for glass formulation, melter control, and modeling the melt flow, refractory corrosion, and production rate. Using a database consisting of more than 4,000 data points measured between 900 °C and 1250 °C for over 600 unique low-activity waste glass compositions, we developed models for the melt viscosity and electrical conductivity. Models based on the Gaussian process regression approach outperformed models based on the Vogel–Fulcher–Tammann equation according to four standard metrics and yielded reliable prediction intervals. The models found primarily linear effects between properties and individual components, except for the effect of the Na 2 O mass fraction on the electrical conductivity. The effects were found to be consistent with current theories on physical processes involved with those properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Pseudoscalar pair production via off-shell Higgs in composite Higgs models

We propose a new type of search for a pseudoscalar particle $\eta$ pair produced via an off-shell Higgs, $pp$ → $h*$ → $\eta\eta$. The search is motivated by a composite Higgs model in which the $\eta$ is extremely narrow and decays almost exclusively into Z in the mass range 65 $\lesssim$ GeV $m_{\eta}$ $\lesssim$ 160 GeV. We devise an analysis strategy to observe the novel Zγ Zγ channel and estimate potential bounds on the Higgs-$\eta$ coupling. The experimental sensitivity to the signatures depends on the power to identify fake photons and on the ability to predict large photon multiplicities. This search allows us to exclude large values of the compositeness scale $f$, being thus complementary to other typical processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Biaxial steel plated concrete constitutive models for composite structures: Implementation and validation

The Steel-plated Concrete (SC) technique is an alternative construction technique with faster onsite construction speed, reduced construction time, and increased structural performance. Aiming to predict the force transfer mechanism of SC elements, an innovative constitutive model package is proposed by implementing experimental-based biaxial steel plate concrete models into the nonlinear finite element (FE) model “Membrane Model of SC (MM-CS).” First, the formulation and implementation of the MM-SC is illustrated in detail, including the equilibrium and compatibility equations and the implementation of constitutive models. Next, various experimental data of SC members are selected and simulated using the proposed MM-SC model. In this research, two types of structures, SC panels and framed SC shear walls, and three types of loading conditions, including uniaxial compression, pure shear, and combined axial-flexural-shear tests, are analyzed respectively. Good agreements were obtained between the reported results and the FE simulation results in terms of yield capacity and ultimate capacity, proving the reliability of the implemented analytical constitutive material models and the biaxial membrane model formulations.

42 ENGINEERING↗
DOE OSTI2017

Flexible, cluster-based analysis of the electronic medical record of sepsis with composite mixture models

The widespread adoption of electronic medical records (EMRs) in healthcare has provided vast new amounts of data for statistical machine learning researchers in their efforts to model and predict patient health status, potentially enabling novel advances in treatment. In the case of sepsis, a debilitating, dysregulated host response to infection, extracting subtle, uncataloged clinical phenotypes from the EMR with statistical machine learning methods has the potential to impact patient diagnosis and treatment early in the course of their hospitalization. However, there are significant barriers that must be overcome to extract these insights from EMR data. First, EMR datasets consist of both static and dynamic observations of discrete and continuous-valued variables, many of which may be missing, precluding the application of standard multivariate analysis techniques. Second, clinical populations observed via EMRs and relevant to the study and management of conditions like sepsis are often heterogeneous; properly accounting for this heterogeneity is critical. Here, we describe an unsupervised, probabilistic framework called a composite mixture model that can simultaneously accommodate the wide variety of observations frequently observed in EMR datasets, characterize heterogeneous clinical populations, and handle missing observations. In conclusion, we demonstrate the efficacy of our approach on a large-scale sepsis cohort, developing novel techniques built on our model-based clusters to track patient mortality risk over time and identify physiological trends and distinct subgroups of the dataset associated with elevated risk of mortality during hospitalization.

59 BASIC BIOLOGICAL SCIENCES↗