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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predictive Contaminant Transport Simulation with P2R Model for the Composite Analysis Limited Source Sensitivity Case.

The Plateau to River (P2R) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by the Central Plateau Cleanup Company at the Hanford Site in Washington State. Figure 1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model is utilized in the Composite Analysis (CA) for the Hanford Site as the computational engine for computing F&T predictions as described in CP-60406, Hanford Site Composite Analysis Technical Approach Description: Groundwater. The model simulates contaminants of concern within the saturated zone of the uppermost aquifer beneath the Central Plateau and downgradient to the Columbia River. CP-57037, Model Package Report for the Plateau to River Model Version 8.3 documents the current version of the P2R Model including a description of the conceptual site model, model development and calibration, and limitations to the model application. Simulations conducted to support the dose calculations required by the CA are documented in ECF-HANFORD-19-0119, Predictive Flow Simulation with the P2R Model for the Composite Analysis Base Case and ECF-HANFORD-19-0120, Contaminant Transport Simulation with the P2R Model for the Composite Analysis Base Case.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Evaluation of the rheological and electrical percolation of high‐density polyethylene/carbon black composites using mathematical models

Abstract In this work, conductive polymer composites (CPCs) of bio‐based polyethylene (BioPe) containing different concentrations of carbon black (CB) were developed. By using oscillatory rheology analysis, a Newtonian plateau was observed in BioPe, and all BioPe/CB composites had a behavior of a pseudo‐solid and that composites with volume fractions ranging from 0.24 to 0.56 presented higher viscosity, storage, and loss modulus. This suggests the formation of a percolated network and by using the power‐law models, it was observed that the electrical percolation threshold was higher than the rheological percolation threshold. The electrical conductivity was measured using the four‐point probe method and a sigmoid model was used to predict the CPCs' electrical conductivity percolation threshold. The results indicated that the four‐point probe method presented satisfactory results according to the calculated standard deviations and voltage–current characteristics for each round of measurements considering the same ranging as used in rheology analysis. The analytical model used showed a coefficient of determination ( R 2 ) higher than 95%, allowing the prediction of the electrical conductivity of the CPC and the percolation threshold as a function of the volumetric fraction of the CB.

da SiIva, Moacy P.↗
DOE OSTI2017

Development of models for predicting Torsade de Pointes cardiac arrhythmias using perceptron neural networks

Background: Blockage of some ion channels and in particular, the hERG (human Ether-a’-go-go-Related Gene) cardiac potassium channel delays cardiac repolarization and can induce arrhythmia. In some cases it leads to a potentially life-threatening arrhythmia known as Torsade de Pointes (TdP). Therefore recognizing drugs with TdP risk is essential. Candidate drugs that are determined not to cause cardiac ion channel blockage are more likely to pass successfully through clinical phases II and III trials (and preclinical work) and not be withdrawn even later from the marketplace due to cardiotoxic effects. The objective of the present study is to develop an SAR (Structure-Activity Relationship) model that can be used as an early screen for torsadogenic (causing TdP arrhythmias) potential in drug candidates. The method is performed using descriptors comprised of atomic NMR chemical shifts (13C and 15N NMR) and corresponding interatomic distances which are combined into a 3D abstract space matrix. The method is called 3D-SDAR (3-dimensional spectral data-activity relationship) and can be interrogated to identify molecular features responsible for the activity, which can in turn yield simplified hERG toxicophores. A dataset of 55 hERG potassium channel inhibitors collected from Kramer et al. consisting of 32 drugs with TdP risk and 23 with no TdP risk was used for training the 3D-SDAR model. Results: An artificial neural network (ANN) with multilayer perceptron was used to define collinearities among the independent 3D-SDAR features. A composite model from 200 random iterations with 25% of the molecules in each case yielded the following figures of merit: training, 99.2%; internal test sets, 66.7%; external (blind validation) test set, 68. 4%. In the external test set, 70.3% of positive TdP drugs were correctly predicted. Moreover, toxicophores were generated from TdP drugs. Conclusion: A 3D-SDAR was successfully used to build a predictive model for drug-induced torsadogenic and non-torsadogenic drugs based on 55 compounds. The model was tested in 38 external drugs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Evaluation of Spent Nuclear Fuel Disposition in Salt (FY18)

This report summarizes the 2018 fiscal year (FY18) field, laboratory, and modeling work funded by the US Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) campaign as part of the Sandia National Laboratories Salt Research and Development (R&D) and Salt International work packages. This report satisfies level-two milestone M2SF-18SNO10303031and comprises three related but stand-alone sections. The first section summarizes the programmatic progress made to date in the DOE-NE salt program and its goals going forward. The second section presents brine composition modeling and laboratory activities related to salt evaporation experiments, which will be used to interpret data collected during the heater test. The third section presents theoretical and numerical modeling work done to investigate the effects brine composition have on dihedral angle and the permeability of salt.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Defense waste processing facility (DWPF) liquids model: revisions for processing higher TIO 2 containing glasses

Radioactive high level waste (HLW) at the Savannah River Site (SRS) has successfully been vitrified into borosilicate glass in the Defense Waste Processing Facility (DWPF) since 1996. Vitrification requires stringent product/process (P/P) constraints since the glass cannot be reworked once it is poured into ten foot tall by two foot diameter canisters. A unique “feed forward” statistical process control (SPC) was developed for this control rather than statistical quality control (SQC). In SPC, the feed composition to the DWPF melter is controlled prior to vitrification. In SQC, the glass product would be sampled after it is vitrified. Individual glass property-composition models form the basis for the “feed forward” SPC. The models transform constraints on the melt and glass properties into constraints on the feed composition going to the melter in order to guarantee, at the 95% confidence level, that the feed will be processable and that the durability of the resulting waste form will be acceptable to a geologic repository. This report documents the development of revised TiO 2 , Na 2 O, Li 2 O and Fe 2 O 3 coefficients in the SWPF liquidus model and revised coefficients (a, b, c, and d).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy

NREL developed calibration models based on near-infrared (NIR) spectroscopy coupled with multivariate statistics to predict compositional properties relevant to cellulosic biofuels production for a variety of sorghum cultivars. A robust calibration population was developed in an iterative fashion. The quality of models developed using the same sample geometry on two different types of NIR spectrometers and two different sample geometries on the same spectrometer did not vary greatly.

09 BIOMASS FUELS↗
DOE OSTI2024

Physical origin of enhanced electrical conduction in aluminum-graphene composites

In this study, the electronic and transport properties of aluminum-graphene composite materials were investigated using the ab initio plane wave density functional theory. The interfacial structure is reported for several configurations. In some cases, the face-centered aluminum (111) surface relaxes in a nearly ideal registry with graphene, resulting in a remarkably continuous interface structure. The Kubo–Greenwood formula and space-projected conductivity were employed to study electronic conduction in aluminum single- and double-layer graphene-aluminum composite models. The electronic density of states at the Fermi level is enhanced by the graphene for certain aluminum–graphene interfaces, thus improving electronic conductivity. In double-layer graphene composites, conductivity varies non-monotonically with temperature, showing an increase between 300 and 400 K at short aluminum-graphene distances, unlike the consistent decrease in single-layer composites.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Search for new phenomena in high-mass final states with a photon and a jet from $pp$ collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search is performed for new phenomena in events having a photon with high transverse momentum and a jet collected in 36.7 fb -1 of proton–proton collisions at a centre-of-mass energy of s√ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The invariant mass distribution of the leading photon and jet is examined to look for the resonant production of new particles or the presence of new high-mass states beyond the Standard Model. No significant deviation from the background-only hypothesis is observed and cross-section limits for generic Gaussian-shaped resonances are extracted. Excited quarks hypothesized in quark compositeness models and high-mass states predicted in quantum black hole models with extra dimensions are also examined in the analysis. The observed data exclude, at 95% confidence level, the mass range below 5.3 TeV for excited quarks and 7.1 TeV (4.4 TeV) for quantum black holes in the Arkani-Hamed–Dimopoulos–Dvali (Randall–Sundrum) model with six (one) extra dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Glass Design Using Machine Learning Property Models with Prediction Uncertainties: Nuclear Waste Glass Formulation

The United States Department of Energy is responsible for managing the legacy nuclear waste stored in underground tanks at the Hanford Site. The waste will be separately vitrified as low-activity waste and high-level waste fractions. Waste glass formulation algorithms have been traditionally developed using partial quadratic mixture property-composition models. Recently, machine learning (ML) techniques have been used to predict glass properties and discover new glass materials for nuclear waste vitrification, and these advancements can be utilized to improve waste glass composition design. In this proof-of-principle study, ML algorithms such as Gaussian process regression (GPR) were used to interpolate glass properties (e.g., viscosity, electrical conductivity, chemical durability). After selecting appropriate sets of GPR hyper-parameters for each property, an optimization program was developed to formulate glass compositions to maximize waste loading while simultaneously satisfying property within constraints. The results of the ML-based waste loadings and glass compositions were compared to those obtained using the traditional methods. Comparing to the previous glass design framework, the ML-based optimization methods offer improved glass designs and a streamlined approach to generation of optimally designed data and near real-time updates.

glass formulation, machine learning, constraints, ↗
DOE OSTI2020

Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016

The southeast Atlantic is home to well-defined smoke outflow from Africa coinciding vertically with extensive marine boundary-layer cloud decks, both reaching their climatological maxima in spatial extent around September. A framework is put forth for evaluating the performance of a range of global and regional aerosol models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. The sparse airborne observations are first aggregated into 2o grid boxes and into three vertical layers: the cloud-topped marine boundary layer (MBL), the layer from cloud top to 3 km, and the 3-6 km layer. Aerosol extensive properties simulated for the entire study region for all September suggest that the 2016 ORACLES observations are reasonably representative of the regional monthly average, with systematic deviations of 30% or less. All six models typically place the bottom of the smoke layer at lower altitudes than do the airborne lidar observations by 300-1400 m, whereas model aerosol top heights are within 0-500 m of the observations. All but one of the models that report carbonaceous aerosol masses underestimate the ratio of particulate extinction to the masses, a proxy for mass extinction efficiency, in 3-6 km. Notable findings on individual models include that WRF-CAM5 predicts the mass of black carbon and organic aerosols with minor (~10% or less) biases. GEOS-5 overestimates the carbonaceous particle masses in the MBL by a factor of 3-6. Extinction coefficients in the free troposphere (FT) and above-cloud aerosol optical depth (ACAOD) are 10-30% lower in WRF-CAM5, 30-50% lower in GEOS-5, 10-40% higher in GEOS-Chem, 10-20% higher in EAM-E3SM except for the practically unbiased 3-6 km extinction, and 20-70% lower in the Unified Model, than the airborne in situ, lidar and sunphotometer measurements. ALADIN-Climate also underestimates the ACAOD, by 30%. GEOS-5 and GEOS-Chem predict carbon monoxide in the MBL with small (10% or less) negative biases, despite their overestimates of carbonaceous aerosol masses. Overall, this study highlights a new approach to utilizing airborne aerosol measurements for model diagnosis.

Shinozuka, Yohei↗
DOE OSTI2017

Search for new phenomena in high-mass final states with a photon and a jet from p p collisions at s = 13 TeV with the ATLAS detector

A search is performed for new phenomena in events with a high-transverse momentum photon and jets collected in 36.7/fb of pp collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The invariant mass distribution of the leading photon and jet is examined to look for a resonant production of new particles or the presence of new high-mass states beyond the Standard Model. No significant deviation is observed in the mass distribution from the background-only hypothesis and cross section limits for generic Gaussian-shaped resonances are extracted. Excited quarks hypothesized in the quark compositeness model and high-mass states predicted in the quantum black hole models with extra dimensions are also examined in the analysis. The observed data exclude, at 95% confidence level, mass range below 5.3 TeV for the excited quarks and 7.1 TeV (4.4 TeV) for the quantum black holes with six (one) extra dimensions in the Arkani-Hamed-Dimopoulos-Dvali (Randall-Sundrum) model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

A comparison of molecular dynamics and diffuse interface model predictions of Lennard-Jones fluid evaporation

The unsteady evaporation of a thin planar liquid film is studied by molecular dynamics simulations of Lennard-Jones fluid. The obtained results are compared with the predictions of a diffuse interface model in which capillary Korteweg contributions are added to hydrodynamic equations, in order to obtain a unified description of the liquid bulk, liquid-vapor interface and vapor region. Particular care has been taken in constructing a diffuse interface model matching the thermodynamic and transport properties of the Lennard-Jones fluid. The comparison of diffuse interface model and molecular dynamics results shows that, although good agreement is obtained in equilibrium conditions, remarkable deviations of diffuse interface model predictions from the reference molecular dynamics results are observed in the simulation of liquid film evaporation. It is also observed that molecular dynamics results are in good agreement with preliminary results obtained from a composite model which describes the liquid film by a standard hydrodynamic model and the vapor by the Boltzmann equation. The two mathematical model models are connected by kinetic boundary conditions assuming unit evaporation coefficient.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Modeling and design of a separate effects irradiation test targeting fission gas release from Cr-doped UO 2

Fission gas release (FGR) from nuclear fuel during operation can diminish heat transfer properties across the pellet-cladding gap and increase the fuel rod internal pressure, thereby posing a concern to fuel reliability and safety during an accident. Enlarging the fuel grain size, which has been shown to improve fission gas retention, can be achieved by doping the fuel feedstock prior to sintering. In this work, the BISON fuel performance code was used to predict FGR from undoped and chromia-doped UO 2 (referred to as Cr-doped UO 2 ) fuel specimens with different grain sizes and across various temperatures. The BISON models identified the irradiation conditions for which FGR is most significant, and a separate effects irradiation experiment in the High Flux Isotope Reactor (HFIR) was then developed targeting those conditions. Further, the experiment leveraged the MiniFuel irradiation capability at Oak Ridge National Laboratory and consisted of 12 fuel specimens of varying grain size and Cr content. A coupling scheme between BISON FGR results and the ANSYS finite element thermal model used for experiment design was formulated to predict cumulative FGR from each fuel specimen based on expected irradiation temperature histories. The fuel samples were fabricated and characterized as a part of this work, and the fuel compositions modeled in BISON were representative of the specimens used in the experiment. This combined modeling and experimental effort aims to study the effect of fuel grain size and Cr content on FGR and to provide simulated BISON FGR results that can be used for future model validation activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

IHLW PCT, Spinel T1%, Electrical Conductivity, and Viscosity Model Development (Final Report)

This report is the last in a series of currently scheduled reports that presents the results from the High Level Waste (HLW) glass formulation development and testing work performed at the Vitreous State Laboratory (VSL) of the Catholic University of America (CUA) and the development of IHLW property-composition models performed jointly by Pacific Northwest National Laboratory (PNNL) and VSL for the River Protection Project-Waste Treatment and Immobilization Plant (RPP-WTP). Specifically, this report presents results of glass testing at VSL and model development at PNNL for Product Consistency Test (PCT), one-percent crystal fraction temperature (T1%), electrical conductivity (EC), and viscosity of HLW glasses. The models presented in this report may be augmented and additional validation work performed during any future immobilized HLW (IHLW) model development work. Completion of the test objectives is addressed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Composition-Based Density Model for High Level Waste Glasses

In this report, the Savannah River National Laboratory (SRNL) provides a first-principles model capable of predicting the density of high-level waste (HLW) glass based on the glass composition. The model relies on the additivity of the specific volume of bound glass oxides to obtain a quantitative evaluation of the approximate glass density. A database of glass densities and compositions was compiled from various sources including previous Defense Waste Processing Facility (DWPF) variability study glasses, HLW studies from other institutions, and literature references. There are a total of 1104 glass compositions in the database with densities ranging from 2.224 g/cm 3 to 3.997 g/cm 3 . The breadth of the compositional coverage space is reported as well. A predictive method was investigated in which the glass density was calculated as a function of the weighted partial molar volumes of the individual glass oxides and the molar mass of the glass. This method yielded a high correlation between the predicted density and the measured density. In addition, a linear regression of these predictions indicated that the predicted value was equal to the measured within the bounds of analytical uncertainty. The following conclusions were drawn from the results of these analyses: 1. Measured glass density is highly correlated with glass composition (R 2 ≈ 0.95). 2. The correlation between glass density and glass composition can be expressed as either: a. A weighted sum of the individual oxide glass-component densities, or b. A weighted sum of the individual oxide glass-component partial molar volumes. 3. A linear regression of the predicted density via partial molar volume method to the measured density yields a slope of 0.9975 and an intercept of -0.0007 – the uncertainty interval associated with these coefficients contain one and zero, respectively. 4. The fitted coefficients and associated uncertainty intervals of the linear regression of the predicted density via the partial molar volume method to the measured density suggest that the predicted theoretical density is, within analysis uncertainty, equal to the measured density of the glass. It is recommended that glass density measurements included with the variability study for each sludge batch be discontinued. In their place, SRNL will calculate a bounding glass density value for the frit/sludge system using the model. It is also recommended that DWPF implement the density model as part of the fissile loading determination portion of the SME acceptability process. Details for implementation are provided in this report.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Analysis of Nonclassical Fracture Problems for Prestressed Bodies with Interacting Cracks

We consider two types of nonclassical fracture mechanisms, namely, the fracture of cracked bodies with initial (residual) stresses acting along the crack planes and the fracture of solids under compression along parallel cracks. To investigate nonaxisymmetric and axisymmetric problems for infinite solids containing two parallel coaxial cracks or a periodic set of coaxial parallel cracks, we use a combined analytic-numerical method within the framework of the three-dimensional linearized mechanics of solids. The analysis involves the representation of stresses and displacements in the linearized theory via harmonic potential functions. With the use of the integral Fourier–Hankel transformations, the problems are reduced to the solution of Fredholm integral equations of the second kind. This approach allows us to investigate problems in a unified general form for compressible and noncompressible homogeneous isotropic or transversely isotropic elastic bodies with an arbitrary structure of the elastic potential, and the material specification of the model is carried out only in the stage of numerical analysis of the resolving equations obtained in the general form. The effects of initial stresses on the stress intensity factors are analyzed for highly elastic materials and layered composites (modeled as transversely isotropic elastic bodies). The “resonance-like” effects are revealed when compressive initial stresses reach the values corresponding to the local loss of stability of the material in the vicinity of cracks, which, according to the indicated combined method, allows one to determine the critical (limiting) load parameters under the conditions of compression of the body along the cracks. The conclusions concerning the dependences of the stress intensity factors and critical (limiting) parameters of compression on the geometric parameters of the problems are formulated as well as concerning the dependences on physical and mechanical characteristics of the materials.

42 ENGINEERING↗
DOE OSTI2015

Analysis of material recovery facilities for use in life-cycle assessment

Highlights: • Life-cycle assessment of solid waste management relies on accurate process models. • Material recovery facility (MRF) processes were modeled with new primary data. • Single stream, dual stream, pre-sorted, and mixed waste MRFs were considered. • MRF electricity consumption ranges from 4.7 to 7.8 kW h per Mg input. • Total cost ranges from $19.8 to $24.9 per Mg input. - Abstract: Insights derived from life-cycle assessment of solid waste management strategies depend critically on assumptions, data, and modeling at the unit process level. Based on new primary data, a process model was developed to estimate the cost and energy use associated with material recovery facilities (MRFs), which are responsible for sorting recyclables into saleable streams and as such represent a key piece of recycling infrastructure. The model includes four modules, each with a different process flow, for separation of single-stream, dual-stream, pre-sorted recyclables, and mixed-waste. Each MRF type has a distinct combination of equipment and default input waste composition. Model results for total amortized costs from each MRF type ranged from $19.8 to $24.9 per Mg (1 Mg = 1 metric ton) of waste input. Electricity use ranged from 4.7 to 7.8 kW h per Mg of waste input. In a single-stream MRF, equipment required for glass separation consumes 28% of total facility electricity consumption, while all other pieces of material recovery equipment consume less than 10% of total electricity. The dual-stream and mixed-waste MRFs have similar electricity consumption to a single-stream MRF. Glass separation contributes a much larger fraction of electricity consumption in a pre-sorted MRF, due to lower overall facility electricity consumption. Parametric analysis revealed that reducing separation efficiency for each piece of equipment by 25% altered total facility electricity consumption by less than 4% in each case. When model results were compared with actual data for an existing single-stream MRF, the model estimated the facility’s electricity consumption within 2%. The results from this study can be integrated into LCAs of solid waste management with system boundaries that extend from the curb through final disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Physically-based control-oriented modeling for turbocharged stoichiometric spark-ignited engine with cooled EGR and flexible VVT systems

Accurate estimation and prediction of engine gas exchange system and in-cylinder conditions are critical for spark-ignited engine control and diagnostic algorithm development. In this paper, a physically-based, control-oriented model for a 2.8 l turbocharged, variable valve timing (VVT) and low pressure (LP) exhaust gas recirculation (EGR)-utilizing SI engine was developed. The model includes the impact of modulation to any combination of 10 actuators, including the throttle valve, compressor bypass valve, fueling rate, waste-gate, LP EGR valve, number of deactivated cylinders, intake valve open (IVO) timing, intake valve close (IVC) timing, exhaust valve open (EVO) timing and exhaust valve close (EVC) timing. The accuracy of the model in capturing engine dynamics was demonstrated by validating it against high-fidelity engine GT-Power simulation results for various drive cycles, particularly emphasizing elevated loads. In comparison to the open literature, novel contributions of the effort described in this paper includes in-cylinder gas composition modeling and turbine-out pressure estimation.

Zhang, Xu↗