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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fuel Property-Informed Process Design for the Direct Catalytic Conversion of Cellulosics

The direct catalytic conversion of cellulosics (DC3) with supercritical methanol presents a promising pathway to completely solubilize woody biomass and produce >60% mass yield of C2-C6 oxygenates for light duty vehicle applications. Although the oxygenate composition can be tuned by modifying catalyst and process conditions, limited efforts to date have examined DC3 fuel properties for light duty fuel applications to iteratively inform conversion process design. In this work, we designed and evaluated multi-component surrogate bioblendstocks that represent major DC3 light oxygenates and refined catalyst formulations and distillation parameters to improve the resulting light duty fuel quality. Surrogate design for this novel fuel production pathway was based on a preliminary product slate that was systematically adjusted to determine impacts on fuel properties of interest including heating value, oxidative stability, and heat of vaporization, among others. The resulting predictions and measurements of these surrogates were then used to inform improvement of conversion process, and specifically, reformulation of the catalyst which resulted in production of a higher energy density fuel product primarily comprised of saturated alcohols. Fuel testing outcomes also informed downstream oxygenate separations requirements. This resulted in the production of a promising DC3 light-duty fuel blendstock with >15% greater energy density relative to ethanol, while maintaining high octane number and octane sensitivity.

BIOMASS FUELS↗
DOE OSTI2022

Physics-informed graph neural networks for predicting cetane number with systematic data quality analysis

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. Finally, this physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

SEM Milestone Report for MARMOT Validation Project

MARMOT is a meso-scale fuel code under development by NEAMS designed to predict the microstructure evolution of fuel materials to determine updated thermal and mechanical property models. These updated models can be used by engineering scale codes such as BISON. To support its development and validation the MARMOT Validation Project (MVP) was initiated and consists of extensive microstructure and thermal characterization of U-10Zr fuel material before and at discreet levels of irradiation. This report summarizes the SEM and EDS characterization of the lowest burnup samples (1.5% FIMA) and how they compare to pre-irradiation SEM and EDS.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Influence of Shear Strength Assumptions on BISON Debonding Simulations

Accurately predicting the thermomechanical response of buffer–IPyC debonding in TRISO fuel particles requires reliable mechanical property inputs for each coating layer, particularly the normal and shear strengths that influence interlayer delamination and stress concentrations. Micro tensile testing of AGR-2 fuel particles provided experimentally measured normal strengths for the buffer, IPyC, and buffer–IPyC interface; however, shear strength was not measured. As a result, BISON simulations of interface debonding must rely on assumed shear strength values, typically estimated as 20–40% of the measured ultimate tensile strength. This study evaluates how these assumed shear strength values influence cohesive zone model (CZM) predictions of buffer–IPyC separation in AGR 2 TRISO particles. Using micro tensile data from three AGR 2 compacts (2 1 3, 5 1 3, and 6 3 3), BISON simulations were performed with multiple shear strength assumptions to quantify their effect on radial and tangential stress evolution, debonding, and gap propagation. The results show that shear strength is a high sensitivity parameter: increasing the assumed shear strength significantly alters the stress distribution at the buffer–IPyC junction, shifts the predicted debonding location, and changes the extent of partial gap formation. While normal strength controls the initiation of interface separation, shear strength strongly influences the mode mixity of the failure process and the resulting stress concentrations transmitted to the IPyC and SiC layers. These findings highlight a critical gap in current TRISO mechanical characterization. Without experimentally measured shear strength, BISON simulations must rely on approximations that introduce uncertainty into predictions of coating layer integrity and fission product barrier performance. Future fuel qualification campaigns should therefore consider measurement of shear strength at the interlayer interfaces to reduce model uncertainty and improve the fidelity of TRISO fuel performance simulations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Re-Additization of Commercial Biodiesel Blends During Long-Term Storage

Commercial biodiesel blends representative of the U.S. market were aged following procedure ASTM D4625, Standard Test Method for Middle Distillate Fuel Storage Stability at 43°C (110°F), with periodic monitoring of fuel properties indicative of oxidation. The oxidation stability—or oxidation reserve expressed as Rancimat induction period (IP)—gradually decreased from its initial value, as expected. At a predetermined IP threshold, an antioxidant was used to restore IP to the ASTM D7467 specification minimum of 6 six hours, referred to as re-additization. At lower IP values, the amount of antioxidant required increased significantly, and the effectiveness tended to be reduced. Once IP fell to essentially zero, the acid content increased to above the allowable limit. Insoluble material was detectable after the acid number increased out of specification. Storage life was increased with re-additization relative to the as-received fuels, as evidenced by longer time to produce acids. Experience in the field may vary based on storage conditions; however, these results indicate re-additization can significantly increase the storage life of biodiesel blends when used with regular monitoring of IP and acid number. An assessment of property changes during long-term storage showed the initial IP did not predict storage behavior, although fuels above the specification minimum remained stable for greater than 12 weeks of D4625 accelerated aging (1 one year simulated).

09 BIOMASS FUELS↗
DOE OSTI2020

Estimates for disk and ejecta masses produced in compact binary mergers

There is irresistible observational evidence that binary systems of compact objects with at least one neutron star are progenitors of short gamma-ray bursts, as well as a production site for r -process elements, at least when some matter is ejected by the merger and an accretion disk is formed. Here, the recent observations of gravitational waves in conjunction with electromagnetic counterparts fuel the need for models predicting the outcome of a given merger and the properties of the associated matter outflows as a function of the initial parameters of the binary. In this manuscript, we provide updated fitting formulas that estimate the disk mass for double neutron star binaries and ejecta masses for black hole–neutron star and double neutron star binaries, fitted to the results of numerical simulations. Our proposed fitting formulas improve on existing models by aiming for analytical simplicity, by covering a larger region of parameter space, and by accounting for regions of parameter space not covered by numerical simulations but with physically manifest merger outcomes.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

Air Force fuel mainburner/turbine effects programs

A program for the determination of fuel property effects on aircraft gas turbine engine mainburners and turbines is discussed. The six engines selected as test candidates are the J79, J85, J57, TF30, TF39, and F100. Fuels election is the responsibility of the contractors with two fuels as exceptions. The petroleum JP-4 is to be used as a baseline in all tests. The shale JP-4 is to be used in nearly all tests. Fuel properties are to be correlated with combustion system performance paramters. In addition, life predictions are to be made for combustor and turbine hardware. These predictions are to be based on a typical mission for each system, measured metal temperatures and temperature gradients, and oxidation/corrosion effects.

Jackson, T. A.↗
DOE OSTI2021

Post-irradiation examination of legacy high burnup fuel to support safety testing

Safety/transient testing to evaluate performance under off-normal conditions is an essential pillar for both the development of Accident Tolerant Fuels (ATF) and the optimization of fuel operation economics beyond current discharge burnups. Among other factors, the successful interpretation of the transient testing results relies upon the knowledge of the initial conditions of the test, including the characteristics of the fuel system under scrutiny. When testing pre-irradiated material, the assumptions that the fuel and the cladding still have the same properties as in the pre-irradiation stage is obviously wrong and could affect the results of the test. This is particularly true the more burnup accumulates in the fuel rod and irradiation progresses. The knowledge of the initial microstructure of both fuel and cladding allows a clearer interpretation of the subsequent transient testing results, provides validation of the physical phenomena underlying the model predictions and eliminates the uncertainties related to the limited knowledge of the sample status before the test. One example is the phenomenon of fine fragmentation that occurs in Light Water reactor (LWR) fuel. During a Loss of Coolant Accident (LOCA) or Reactivity Initiated Transient (RIA) the fuel can severely fragment. During LOCA, high burnup fuel tend to finely fragment, which has raised safety concerns due to the increased likelihood of dispersal of such small particles once the cladding has burst and due to the increased fission gas release. Therefore, efforts have been devoted to the assessment of a pulverization threshold that could determine the conditions under which fine fragmentation is predominant. However, the lack of information regarding the initial conditions of the fuel, and the connections between those conditions and the pre-transient irradiation history, have hindered the development of a fully mechanistic fragmentation and pulverization criterion. The empirical relationships rely on conservative estimations, due to the lack of information on critical material properties and characteristics. More generally, experimental evidence of the irradiation-induced modifications at microstructural scale are necessary to determine the behavior of the material at the macroscopic scale, with the latter being the one of technological interest. Significant progress has been made in the last two decades in the developments of analytical materials science techniques that can be applied to highly radioactive materials, such as high burnup fuels. The availability of new techniques and the improvement of existing ones has enabled investigations previously not possible that can deepen the understanding of the fuel characteristics and properties at high burnup. The better knowledge of material behavior and irradiation-induced phenomena could help the prediction of its performance. In this context, the scope of the present work is to apply a wide portfolio of advanced characterization techniques to determine properties that are relevant for safety and performance. The results are interpreted in the context of engineering scale post-irradiation examinations and available information on the irradiation conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Microstructural heterogeneity of the buffer layer of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) nuclear fuel particles contain a layered spherical shell designed to retain fission products; however, failure occurs in rare cases—commonly initiated in the porous pyrocarbon buffer layer. Achieving a comprehensive understanding of the buffer-initiated failure mechanisms requires detailed characterization of the buffer porosity and its heterogeneous distribution across multiple length scales. Here we performed FIB-SEM tomography across the buffer layer thickness (~100 µm) to produce 3D reconstructions of the buffer microstructure with 50 nm spatial resolution. We found an average overall porosity of ~14%, which does not solely account for the low density of the buffer (50% of the theoretical density). Additionally, the local porosity and its fluctuation increase from the kernel interface towards the inner pyrocarbon (IPyC) layer, which we attribute to the chemical vapor deposition process conditions during the TRISO particle fabrication. Detailed characterization of the porous microstructure—including analysis of the pore size, distribution, shape, and orientation—provides insight into the process-structure-property-performance relations of TRISO nuclear fuel particles and will inform multiscale models designed to predict the failure of TRISO particles under irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Interplay between London Dispersion, Hubbard U , and Metastable States for Uranium Compounds

High-throughput computational studies of lanthanide and actinide chemistry with density-functional theory are complicated by the need for Hubbard U corrections, which ensure localization of the f-electrons, but can lead to metastable states. This work presents a systematic investigation of the effects of both Hubbard U value and metastable states on the predicted structural and thermodynamic properties of four uranium compounds central to the field of nuclear fuels: UC, UN, UO 2 , and UCl 3 . We also assess the impact of the exchange-hole dipole moment (XDM) dispersion correction on the computed properties. Overall, the choice of Hubbard U value and inclusion of a dispersion correction cause larger variations in the computed geometric properties than result from metastable states. Further, the weak dependence of structure optimization on metastable states should simplify future high-throughput calculations on actinides. Conversely, addition of the dispersion correction is found to offset the repulsion introduced by the Hubbard U term and provides greatly improved agreement with experiment for both cell volumes and heats of formation. The XDM dispersion correction is largely invariant to the chosen U value, making it a robust dispersion correction for actinide systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

High Weber number SMD correlations for pressure atomizers

Recently acquired experimental data are presented which reveal that, for Weber number (We) greater than 10.0, the atomization from simplex pressure atomizers is significantly greater than would be predicted from previously derived Sauter mean diameter (SMD) correlations. A different SMD correlation is required to accurately predict the experimental data. Below We of about 10.0, the atomization is dominated by inertial forces and bag-type breakup results. Above We of about 10.0, shear-type breakup occurs and results in a very fine spray which can accurately be predicted using a quadratic expression in Delta P. The correlation is extended to include fuel property effects, and SMD is found to vary linearly with fuel surface tension, while the influence of the fuel viscosity is not apparent.

Kennedy, J. B.↗
DOE OSTI2024

Prediction of Redox Potentials for U, Np, Pu, and Am in Aqueous Solution

The redox properties of the actinides in aqueous solution are important for fuel production/reprocessing and understanding the environmental impact of nuclear waste. The redox potentials for U, Np, Pu, and Am in oxidation states from 0 up to VII (as appropriate) in aqueous solutions have been predicted at the density functional theory level with the B3LYP functional, Stuttgart small core pseudopotential basis sets for the actinides, and explicit (30H 2 O molecules)/implicit treatment of the aqueous solvent using the self-consistent reaction field COSMO and SMD approaches for the implicit solvation. The predictions of the structural parameters of clusters incorporating first and second solvation shells are consistent with the available experimental data., Our results are typically within 0.2 V of the available experimental data using two explicit solvation shells with an implicit solvent model. The use of the PW91 functional substantially improved the prediction of the Pu(VI/V) redox couple. The redox couples for An(VI/IV) and An(V/IV) which involve the addition of protons and removal of the actinyl oxygens led to slightly larger differences from experiment. Here, the An(IV/0) and An(III/0) couples were reliably predicted with our approach. Predictions of the unknown An(II/I) redox potentials were negative, consistent with expectations, and predictions for unknown An(VII/VI), An(III/II), and An(II/0) redox couples improve prior estimates.

Actinides↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
DOE OSTI2023

An Integrated Approach to Predicting Ash Deposition and Heat Transfer in Coal-Fired Boilers

The overall goal of this project is to develop via measurements and simulations an advanced online technology to predict, monitor and manage fireside ash deposition in a coal-fired boiler allowing for more efficient operations under a range of load conditions and fuel property variability. With this in place fuel sorting and blending can be done upstream and operations can be optimized to compensate for load and fuel properties. In support of this objective, three experimental campaigns were undertaken during the course of the project to measure ash deposition rates within the boiler at different fuel flow rates and its ash composition variability. Simulations of the experimental conditions representing actual geometry, operational scenarios in terms of air flow rates, coal flow rates as well as coal compositions, heating values, and particle size distributions were also carried out. Deposition rates were predicted using a unique particle kinetic energy and viscosity based ash deposition methodology whose validity was ascertained by comparing against deposition rate measurements for widely varying operating conditions and ash compositions in a lab-scale furnace. With a unique end-to-end combustion modeling methodology established and different simulation scenarios carried out, the results from our computational fluid dynamic (CFD) simulations in conjunction with the plant data summarized in this report were used to refine Microbeam Technology Incorporated’s MTI CSPI-CT Tool to predict and monitor fire-side ash deposition under a range of load conditions and fuel property variability in real time.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Numerical study on spray collapse process of ECN spray G injector under flash boiling conditions

This work features a numerical study of the spray collapse process that occurs under flash-boiling, gasoline-direct-injection conditions. The Engine Combustion Network's Spray G injector was modeled, and iso-octane, n-hexane, and propane were used as fuels with the goal to investigate fuel property effects. The development of individual jets and jet-to-jet interaction were analyzed to reveal the physical mechanisms of spray collapse. The results agreed qualitatively well with the experimental data of propane available from the literature and the predictions revealed the model's ability to capture the near-nozzle shock structures witnessed in the experiments. Simulations showed that the flow development of flashing sprays was strongly tied with the fuel properties. Specifically, under-expanded jets were not observed with iso-octane due to the fuel's low vapor pressure. In the case of n-hexane, the jets were under-expanded, and a low-pressure core was observed inside the jets due to the flow expansion. With propane, the very strong expansion caused the flow to become transonic and generate a unique shock structure near the nozzle exit. The shock structure revealed the formation of primary shock cells within the jets and secondary shock cells induced by jet-to-jet interaction. Based on the results, the spray collapse under flash boiling conditions was mainly attributed to two effects, i.e., the decrease in pressure at the spray center induced by the low-pressure cores inside and between the jets, and the isolation effect due to the jet-to-jet interaction which contributed to maintain the pressure differential between the spray center and the ambient.

42 ENGINEERING↗
DOE OSTI2024

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗
NASA NTRS1975

Selected technology for the gas industry

A number of papers were presented at a conference concerned with the application of technical topics from aerospace activities for the gas industry. The following subjects were covered: general future of fossil fuels in America, exploration for fossil and nuclear fuels from orbital altitudes, technology for liquefied gas, safety considerations relative to fires, explosions, and detonations, gas turbomachinery technology, fluid properties, fluid flow, and heat transfer, NASA information and documentation systems, instrumentation and measurement, materials and life prediction, reliability and quality assurance, and advanced energy systems (including synthetic fuels, energy storage, solar energy, and wind energy).

Source record↗