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Results for “Fuel property prediction”

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 271 records · Page 15

Investigation of spray characteristics for flashing injection of fuels containing dissolved air and superheated fuels

The flow, atomization and spreading of flashing injector flowing liquids containing dissolved gases (jet/air) as well as superheated liquids (Freon II) were considered. The use of a two stage expansion process separated by an expansion chamber, ws found to be beneficial for flashing injection particularly for dissolved gas systems. Both locally homogeneous and separated flow models provided good predictions of injector flow properties. Conventional correlations for drop sizes from pressure atomized and airblast injectors were successfully modified, using the separated flow model to prescribe injector exit conditions, to correlate drop size measurements. Additional experimental results are provided for spray angle and combustion properties of sprays from flashing injectors.

Solomon, A. S. P.↗

Impact of Precipitation Parameters on the Specific Surface Area of PuO 2

Controlling the properties of PuO 2 through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO 2 SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO 2 product properties in a production scale environment for key environmental and nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Computer program for prediction of fuel consumption statistical data for an upper stage three-axes stabilized on-off control system

A FORTRAN coded computer program and method to predict the reaction control fuel consumption statistics for a three axis stabilized rocket vehicle upper stage is described. A Monte Carlo approach is used which is more efficient by using closed form estimates of impulses. The effects of rocket motor thrust misalignment, static unbalance, aerodynamic disturbances, and deviations in trajectory, mass properties and control system characteristics are included. This routine can be applied to many types of on-off reaction controlled vehicles. The pseudorandom number generation and statistical analyses subroutines including the output histograms can be used for other Monte Carlo analyses problems.

Source record↗

First-principles free energies by hybrid thermodynamic integration for phase equilibria and fission product solubility in molten salts

The overarching goal of this research project is quantitative microscopic modeling of phase diagrams and solubility of actinides and lanthanide-fission products in molten salts for molten salt reactors. Application of molten salts as coolants and liquid fuels for next-generation reactors requires quantitative understanding of phase diagrams, equations of state and transport properties of binary and ternary molten salt mixtures, as well as solubility of fuel, fission products and reactor-wall corrosion products, but these remain beyond the reach of current first-principles computational techniques. We will address this fundamental capability gap using a novel hybrid framework for thermodynamic integration to directly predict absolute free energies of solid and molten salts at any specified conditions of composition, temperature and pressure. This framework will combine a hierarchy of first-principles, molecular dynamics and continuum techniques to deliver first-principles-level accuracy at a fraction of the computational cost of conventional ab initio molecular dynamics approaches. In particular, this technique is expected to provide first-principles accuracy, while off-loading most of the computational work on much less expensive classical molecular dynamics and continuum techniques.

36 MATERIALS SCIENCE↗

Predicted Impacts of Pt and Ionomer Distributions on Low-Pt-Loaded PEMFC Performance

Low-cost, high performance proton exchange membrane fuel cells (PEMFCs) have been difficult to develop due to limited understanding of coupled processes in the cathode catalyst layer (CCL). Low-Pt-loaded PEMFCs suffer losses beyond those predicted solely due to reduced catalyst area. Although consensus links these losses to thin ionomer films in the CCL, a precise mechanistic explanation remains elusive. In this publication, we present a physically based PEMFC model with novel structure-property relationships for thin-film Nafion, validated against PEMFC data with low Pt loading. Results suggest that flooding exacerbates kinetic limitations in low-loaded PEMFCs, shifting the Faradaic current distribution. As current density increases, protons travel further into the CCL, resulting in higher Ohmic overpotentials. We also present a parametric study of CCL design parameters. We find that graded Pt and ionomer loadings reduce Ohmic losses and flooding, but individually do not provide significant improvements. However, a dual-graded CCL (i.e., graded Pt and ionomer) is predicted to significantly improve the maximum power density and limiting current compared to uniformly loaded CCLs. This work highlights the importance of accurate transport parameters for thin-film Nafion and provides a pathway to low-cost PEMFCs via precise control of CCL microstructures.

08 HYDROGEN↗

Study of Mechanical Properties, Microstructure, and Residual Stresses of AISI 304/304L Stainless Steel Submerged Arc Weld for Spent Fuel Dry Storage Systems

The confinement boundaries of spent nuclear fuel (SNF) canisters are typically fusion welded. Welded microstructures, strain hardening, and residual stresses combined with a chemically aggressive, chloride-rich environment led to concerns that the welded canister may be susceptible to chloride-induced stress corrosion cracking (CISCC). A comprehensive understanding of the modification of stainless steel (SS) metallurgical and mechanical properties by fusion welding could accelerate the predictive analysis of CISCC susceptibility. This paper describes a submerged arc welding (SAW) procedure that was developed and qualified on 12.7 mm (0.5 in.) thick AISI 304/304L SS to produce joints in a way similar to actual SNF canister manufacturing. This procedure has the potential to reduce the production cost and weld CISCC susceptibility by using fewer welding passes and lower heat input than current industrial applications. Global and local mechanical behaviors and properties, as well as residual stress distributions on the welded joint, were studied. The results indicate that hardness values in the fusion zone (FZ) and heat-affected zone (HAZ) are slightly higher than that of the base metal. Strain localization was presented in the HAZ before the tensile stress reached its maximum value, and then it shifted to the FZ. The specimen finally broke in the FZ. High tensile residual stresses exhibited in the FZ and the nearby HAZ suggest the highest CISCC-susceptible spots. The maximum tensile residual stresses were along the welding direction, indicating that if cracks occur, they would be perpendicular to the welding direction. This study involved developing and qualifying a SAW procedure for SNF canister production. The new procedure yielded cost savings (SAW working efficiency increased by about 80%), improved mechanical properties, and presented moderate residual stresses. Analysis revealed that the welded joint’s low-stress and high-stress damage assessments may be affected by shifts in the strain localization spot under loading.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Hurricanes↗

Multi-scale fission product release model with comparison to AGR data

TRistructural ISOtropic (TRISO) particle fuel is central to several advanced, high-temperature reactor designs. Each particle consists of a fuel kernel encapsulated by three layers of carbon and ceramics that prevent the release of fission products and ensure physical integrity. Despite outstanding retention properties, fission product release has been observed from intact particles. To better understand and quantify fission product release from TRISO particles, a multiscale, mechanistic model of fission product transport is being developed by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Previous work focused on silver (Ag) transport and improved Ag release predictions. The work described in this report builds on this experience to better understand cesium (Cs) transport in silicon carbide (SiC), the main barrier to the release of fission products. Atomistic simulations provide bulk and grain boundary (GB) Cs diffusivities in SiC, which are used by phase field simulations in the mesoscale code Marmot to determine the temperature, microstructure, and irradiation-dependent Cs diffusivity at the mesoscale in SiC. This approach attributes the different temperature regimes experimentally observed for Cs diffusivities in SiC to a transition from bulk-dominated diffusivity at high temperatures to a GB-dominated regime at low temperatures, providing new insight. The multiscale, mechanistic effective diffusivity is then implemented in the fuel performance code BISON and further validated by comparing Cs release predictions from Advanced Gas Reactor (AGR)-1 and AGR-2 post-irradiation measurements. The new model improves BISON’s predictability. This document also reports improvements made on Ag transport modeling by accounting for different GB types having different diffusivities. Moreover, this report details preliminary efforts to model palladium (Pd) attack of the SiC at the mesoscale using a phase field approach. Pd attack and its impact on accelerated Ag transport remains a misunderstood phenomenon, and we use the model to demonstrate that the formation of lamellae that has been observed in experiments can be explained by the reaction of Pd with SiC to form alternating layers of graphite and Pd 2 Si. This effort aims to improve our understanding of the reaction and eventually provide a model for BISON to account for Pd penetration and its effects on fission product release.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pressure modulated charge transfer and phonon interactions drive phase transitions in uranium–aluminum laves phases

Lanthanide AB 2 intermetallic compounds known as Laves phases have itinerant 3d and localized 4f electrons, which lead to interesting physical properties such as magnetic anisotropy and high Curie temperatures. Actinide Laves phases can display physical properties that are similarly intriguing. However, at reduced A–A spacing the C14 and C15 polytypes may exhibit larger wavefunction overlap for their 5f electron states and distinct characteristics for phases with more delocalized chemical bonding. The C36 polytype, on the other hand, is extraordinarily rare (<5% of known Laves phases). UAl 2 is the only known actinide Laves phase to show a pressure-controllable C15 → C36 transition. Here, we apply first principles calculations to determine the origin of the C15 → C36 phase transition and reveal the differences between the corresponding properties of each phase. Pressure increases lead to bond compression–induced electron transfer from Al to U, which drives dynamic instability in the C15 phonon modes because of the uniform U–U bonding environment. Further, the opposite phenomena is observed in C36: varied U–U bonding environments are vibronically more stable after charge transfer. We find that the interplay between charge transfer, chemical bonding, and phononic stability are central to predicting phase transitions and corresponding changes in physical properties for both C15 and C36 UAl 2 .

36 MATERIALS SCIENCE↗

Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives

Abstract Discovering renewable fuels and fuel additives is paramount in reducing carbon emissions from internal combustion engines. Terpenes, a group of compounds that can be synthesized from plant matter and microorganisms, have gained significant interest in recent years as promising candidates for fuels/additives. Terpenes are a diverse class of compounds that contain rings and methyl branches, resulting in high energy densities and optimal cold weather behavior. Their variation in bond order, carbon chains, and functional groups lead to varying degrees of soot formation and performance in existing engines. The present work leverages predictive models, namely artificial neural networks, to predict the cetane number (CN), sooting tendency (quantified with yield sooting index, YSI), and energy density (quantified with lower heating value, LHV) of terpenes and hydrogenated terpenes whose sooting propensities were previously determined through experimental means. Predicted sooting propensities of these terpenes are compared with experimental values, and predicted cetane numbers and energy densities are used to comment on the compounds’ ability to act as fuels/additives. Expected prediction errors for CN, YSI, and LHV, defined by blind test set median absolute error, are within 5.56 cetane units, 3.63 yield sooting index units, and 0.77 MJ/kg respectively. Additionally, the present work investigates a variety of correlation/dependence metrics for property-property relationships, furthering our understanding of how combustion-relevant properties are related.

09 BIOMASS FUELS↗

Comparison between PARFUME and Bison Using the AGR-2 Irradiation Experiment

This report documents comparisons between Fuel Model (PARFUME) model predictions versus Bison for selected compacts from the second irradiation test of the Advanced Gas Reactor (AGR) program that occurred from June 2010 to October 2013 in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). PARFUME is a fuel performance analysis and modeling code, used for evaluating gas-reactor tristructural isotropic (TRISO) coated particle fuel for prismatic, pebble bed, plate, and cylindrical type fuel geometries. PARFUME is an integrated mechanistic computer code that evaluates the thermal, mechanical, and physico-chemical behavior of TRISO coated-fuel particles and the probability for fuel failure given the particle-to-particle statistical variations in physical dimensions and material properties that arise during the fuel fabrication process. Bison is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library (Permann 2020). Bison is capable of modeling multiple fuel forms in a wide variety of dimensions and geometries. It solves coupled nonlinear partial differential equations, including heat conduction, mechanics, fission product species transport etc., in a fully implicit manner. Comparisons between PARFUME and Bison were performed using four compacts from the AGR-2 experiment. Selected outputs were chosen based on their impact on the probability of the SiC layer failing. In general there was good agreement between PARFUME and Bison with the exception of predicting the gap formed between the buffer and IPyC. Further comparisons between PARFUME and Bison are planned to further develop Bison’s capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Predicting thermodynamic and thermophysical properties of molten chloride salts from ab-initio and classical molecular dynamics simulations

Molten salt reactors (MSRs) are among the advanced concepts pursued under the generation IV nuclear energy technology umbrella. However, the basic concept is not new and was first developed as part of the effort to power aircrafts with nuclear energy in the 1950’s. Later in the 1960’s, Oak Ridge National Laboratory (ORNL) built and operated the Molten-Salt Reactor Experiment (MSRE). This reactor used a fluoride salt with uranium as fuel. Fluorides salts are still highly relevant and proposed in several designs. In addition, chloride salts are being considered for MSRs operating in the fast neutron spectrum. This report focuses on chloride salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Material Ignition and Suppression Test (MIST) in Space Exploration Atmospheres, Summary of Research

The Material Ignition and Suppression Test (MIST) project has had the objective of evaluating the ease of ignition and the fire suppression of materials used in spacecraft under environmental condition expected in a spacecraft. For this purpose, an experimental and theoretical research program is being conducted on the effect of space exploration atmospheres (SEA) on the piloted ignition of representative combustible materials, and on their fire suppression characteristics. The experimental apparatus and test methodology is derived from the Forced Ignition and Flame Spread Test (FIST), a well-developed bench scale test designed to extract material properties relevant to prediction of material flammability. In the FIST test, materials are exposed to an external radiant flux and the ignition delay and critical mass flux at ignition are determined as a function of the type of material and environmental conditions. In the original MIST design, a small-scale cylindrical flow duct with fuel samples attached to its inside wall was heated by a cylindrical heater located at the central axis of the cylinder. However, as the project evolved it was decided by NASA that it would be better to produce an experimental design that could accommodate other experiments with different experimental concepts. Based on those instructions and input from the requirements of other researchers that may share the hardware in an ISS/CIR experiment, a cylindrical design based on placing the sample at the center of an optically transparent tube with heaters equally spaced along the exterior of the cylinder was developed. Piloted ignition is attained by a hot wire igniter downstream of the fuel sample. Environment variables that can be studied via this experimental apparatus include: external radiant flux, oxidizer oxygen concentration, flow velocity, ambient pressure, and gravity level (if flown in the ISS/CIR). This constitutes the current experimental design, which maintains fairly good consistency with Dr Tien's and Dr Olson's project approaches. A further goal of the project has been to develop a combined solid/gas phase numerical model based on the MIST test methodology to predict the flammability behavior of practical materials in spacecraft.

flammability↗

Toward an In-Depth Material Model for Cermet Nuclear Thermal Rocket Fuel Elements

The development and qualification of nuclear thermal propulsion (NTP) fuel element technologies would be aided by an in-depth model of material response and failure modes at operating conditions. Integrated computational materials engineering techniques have the potential to provide such a model, as demonstrated here through three case studies focused on a tungsten-uranium mononitride cermet fuel. The first case focuses on the erosion of tungsten (W, also named wolfram), a nominal coating/cladding material, in hot hydrogen. Ab initio techniques are used to calculate erosion rates and thermal expansion at NTP operating conditions. The second focuses on the stability of uranium mononitride (UN) fuels at high temperature and in the presence of hydrogen. Phase diagram techniques reveal potential instabilities and decomposition pathways at high hydrogen concentrations. The third focuses on using microstructure information to predict high temperature mechanical response and failure of tungsten, used in refractory cermet materials. Combined finite element and discrete dislocation dynamics techniques provide mechanical properties in agreement with experimental methods. The integration of these techniques for an all-encompassing material model is discussed.

cermet↗

Effect of Cyclo-Pentane Impurities on the Autoignition Reactivity and Properties of a Gasoline Surrogate Fuel

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. Here, in the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied. Chemical kinetic simulations were performed to predict the effects of cyclo-pentane impurities on the properties, octane rating, and autoignition reactivity under homogeneous charge compression-ignition conditions of PACE-20. From the numerical results, cyclo-pentane with 85% purity or higher is required to reasonably match both the research octane number and motor octane number of the target gasoline. Finally, homogeneous charge compression-ignition engine simulations show that impurities have only a modest effect on reactivity at naturally aspirated conditions, but cyclo-pentane purity is critical to properly replicate the pressure dependency of the reactivity.

33 ADVANCED PROPULSION SYSTEMS↗

Analysis of Real-World Preignition Data Using Neural Networks

Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure. Further, this indicates that the alternating pattern of preignition cycles within clusters is influenced by the thermodynamic state as reflected in the pressure, but that the trigger for the initial preignition cycle is not thermodynamic in nature, but more likely tied to a critical threshold in the chemistry of the fuel/lubricant mixture in the upper crevice or other factors related to the presence of an ignition source.

33 ADVANCED PROPULSION SYSTEMS↗

Utilizing the deuterium-tritium fusion resonance to diagnose thermal runaway in igniting plasmas

For high-efficiency inertial confinement fusion implosions, it is predicted that a burning hot spot will successfully encompass all surrounding fuel and then transition into a thermal runaway where the internal energy increase from fusion occurs on a timescale faster than the expansion of the fuel is able to quench the fusion chain reaction after ignition occurs. Observation of this dynamic phase transition would indicate distinct burn properties and indicate an implosion's robustness. A technique for diagnosing the presence of thermal runaway from measurements of nuclear reaction history is presented. The technique is based on taking the logarithmic derivative of the nuclear reaction history, called the 𝛼 curve, and allowing a mathematical decoupling of the mass, volume, and thermal reactivity in the fusion reaction rate equation. During thermal runaway, where the thermal temperature dominates the burn dynamics, a maximum in the 𝛼 curve is found where there is a maximum in the first derivative of the thermal fusion reactivity, an effect to the deuterium-tritium (DT) fusion cross-section resonance. This provides a distinct signature related to the fundamental nature of the DT fusion nuclear resonance and signifies the transition into the fusion thermal instability. Impacts of charged particle transport on the effect are also assessed and the analytical formulas are compared and found to be in agreement with radiation hydrodynamic codes.

high-energy-density plasmas↗

Computational Methods for Multi-Physics Simulation of Melting in Steelmaking

Iron and steel production accounts for approximately 8% of global carbon dioxide (CO) emissions. Pathways to decarbonize include replacing fossil fuels in iron ore reduction and electrifying other steelmaking processes. Iron pellets produced by hydrogen, called Hydrogen Direct Reduced Iron (HDRI), have property differences from those produced using conventional DRI processes. These differences may impact melting in electric arc furnaces (EAF) and other downstream processes. The physical properties of iron pellets vary significantly with temperature during heating, complicating predictions of their behavior. In this project, we seek to develop an integrated simulation, including the fluid flow and convective thermal transport around the pellet particle. We also examine conduction and phase changes within the particle as they impact the melting process. We use adaptive mesh refinement (AMR) to resolve both the changing size of the particle and the complex physics of the interaction between the pellet and the surrounding fluid. We base our simulations on the AMReX-incflo module, which allows large-scale Navier-Stokes simulation while resolving the changing particle size during melting. As we advance our numerical tools, we anticipate an improved understanding of the dynamics of HDRI melting, which will, in turn, accelerate the adoption of low-carbon technologies in the steelmaking industry.

AMReX↗