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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗
NASA NTRS2001

Structure and Early Soot Oxidation Properties of Laminar Diffusion Flames

Soot is an important unsolved problem of combustion science because it is present in most hydrocarbon-fueled flames and current understanding of the reactive and physical properties of soot in flame environments is limited. This lack of understanding affects progress toward developing reliable predictions of flame radiation properties, reliable predictions of flame pollutant emission properties and reliable methods of computational combustion, among others. Motivated by these observations, the present investigation extended past studies of soot formation in this laboratory, to consider soot oxidation in laminar diffusion flames using similar methods. Early work showed that O2 was responsible for soot oxidation in high temperature O2-rich environments. Subsequent work in high temperature flame environments having small O2 concentrations, however, showed that soot oxidation rates substantially exceeded estimates based on the classical O2 oxidation rates of Nagle and Strickland-Constable and suggests that radicals such as O and OH might be strong contributors to soot oxidation for such conditions. Neoh et al. subsequently made observations in premixed flames, supported by later work, that showed that OH was responsible for soot oxidation at these conditions with a very reasonable collision efficiency of 0.13. Subsequent studies in diffusion flames, however, were not in agreement with the premixed flame studies: they agreed that OH played a dominant role in soot oxidation in flames, but found collision efficiencies that varied with flame conditions and were not in good agreement with each other or with Neoh et al. One explanation for these discrepancies is that optical scattering and extinction properties were used to infer soot structure properties for the studies that have not been very successful for representing the optical properties of soot. Whatever the source of the problem, however, these differences among observations of soot oxidation in premixed and diffusion flames clearly must be resolved. Motivated by these findings, the present study undertook measurements of soot and flame properties within the soot oxidation region of some typical laminar diffusion flames and exploited the new measurements to identify soot oxidation mechanisms for these conditions. Present considerations were limited to the early stages of soot oxidation (carbon consumption less than 70%) where reactions at the surface of primary soot particles dominate the process, rather than the later stages when particle porosity and internal particle oxidation become important as discussed by Neoh et al.

El-Leathy, A. M.↗
NASA NTRS2009

Smoke Point in Co-flow Experiment

The Smoke Point In Co-flow Experiment (SPICE) determines the point at which gas-jet flames (similar to a butane-lighter flame) begin to emit soot (dark carbonaceous particulate formed inside the flame) in microgravity. Studying a soot emitting flame is important in understanding the ability of fires to spread and in control of soot in practical combustion systems space. Previous experiments show that soot dominates the heat emitted from flames in normal gravity and microgravity fires. Control of this heat emission is critical for prevention of the spread of fires on Earth and in space for the design of efficient combustion systems (jet engines and power generation boilers). The onset of soot emission from small gas jet flames (similar to a butane-lighter flame) will be studied to provide a database that can be used to assess the interaction between fuel chemistry and flow conditions on soot formation. These results will be used to support combustion theories and to assess fire behavior in microgravity. The Smoke Point In Co-flow Experiment (SPICE) will lead to a o improved design of practical combustors through improved control of soot formation; o improved understanding of and ability to predict heat release, soot production and emission in microgravity fires; o improved flammability criteria for selection of materials for use in the next generation of spacecraft. The Smoke Point In Co-flow Experiment (SPICE) will continue the study of fundamental phenomena related to understanding the mechanisms controlling the stability and extinction of jet diffusion flames begun with the Laminar Soot Processes (LSP) on STS-94. SPICE will stabilize an enclosed laminar flame in a co-flowing oxidizer, measure the overall flame shape to validate the theoretical and numerical predictions, measure the flame stabilization heights, and measure the temperature field to verify flame structure predictions. SPICE will determine the laminar smoke point properties of non-buoyant jet diffusion flames (i.e., the properties of the largest laminar jet diffusion flames that do not emit soot) for several fuels under different nozzle diameter/co-flow velocity configurations. Luminous flame shape measurements would also be made to verify models of the flame shapes under co-flow conditions. The smoke point is a simple measurement that has been found useful to study the influence of flow and fuel properties on the sooting propensity of flames. This information would help support current understanding of soot processes in laminar flames and by analogy in turbulent flames of practical interest.

Urban, David L.↗
DOE OSTI2026

Polyketide synthase-based controlled synthesis of polycyclopropanated fuel molecules

Reducing carbon emissions from aviation and long-distance transportation sectors requires the development of sustainable biofuels with suitable energy density, freezing point, and other physical properties. We previously demonstrated biological production of high energy polycyclopropanated fatty acids (POP-FAs, class I) using an iterative polyketide synthase (iPKS) pathway in a Streptomyces host. Here, we used a computational model of fuel properties to identify chain length and cyclopropanation control as critical steps to engineer this iPKS for biofuel applications. We next explored the natural diversity of POP biosynthesis by investigating homologous pathways. Then, by in vivo gene exchange, we determined cyclopropanase (CP) catalysis to be key for POP-FA engineering. Leveraging both natural and engineered pathway product diversity, we demonstrate targeted production of improved POP-FAs, namely shortened POP-FAs with predicted superior freezing point properties for aviation, as well as fully cyclopropane-saturated POP-FAs which should have superior energy-density. These precise and controllable modifications to POP-FA structure open the door for bioproduction of designer POP fuels.

Yin, Kevin↗
DOE OSTI2026

Development of a BISON validation case for the TRISO transient irradiations in NSRR using effective heat capacity methods

The current tristructural isotropic (TRISO) fuel assessment and validation database in BISON primarily covers steady- state irradiation and high-temperature furnace testing. Transient assessment cases are potentially needed to support U.S. industry efforts in designing and deploying commercial reactors using TRISO fuels. Historical transient tests in- volving TRISO fuels used highly conservative conditions compared to the typical high-temperature gas-cooled reactor accident scenarios. Despite this, modeling historical transient tests is fundamental for evaluating BISON’s predictive capabilities, adapting material properties for high-temperature and high-particle-power regimes, and developing a sys- tematic validation approach for TRISO transient applications. This work developed a 1D model of transient experiments carried out at the Nuclear Safety Research Reactor using BISON. BISON’s predictions of energy deposition, UO 2 melting onset, and molten volume fractions are compared against experimental measurements. Melting was modeled using an effective specific heat capacity model for UO 2 . We found that BISON’s predictions are in reasonable agreement with experimental data for low-energy-deposition cases, and that BISON overpredicts melting at higher energy depositions. We also discuss the potential causes of discrepancies between the simulated and measured results and propose ways to further develop the model. Although these simulations used conservative conditions compared to those expected for actual TRISO-fueled reactors, they extended the range of conditions reflected in the data in the existing BISON database for TRISO fuels.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1981

Fuel/oxidizer-rich high-pressure preburners

The analyses, designs, fabrication, and cold-flow acceptance testing of LOX/RP-1 preburner components required for a high-pressure staged-combustion rocket engine are discussed. Separate designs of injectors, combustion chambers, turbine simulators, and hot-gas mixing devices are provided for fuel-rich and oxidizer-rich operation. The fuel-rich design addresses the problem of non-equilibrium LOX/RP-1 combustion. The development and use of a pseudo-kinetic combustion model for predicting operating efficiency, physical properties of the combustion products, and the potential for generating solid carbon is presented. The oxygen-rich design addresses the design criteria for the prevention of metal ignition. This is accomplished by the selection of materials and the generation of well-mixed gases. The combining of unique propellant injector element designs with secondary mixing devices is predicted to be the best approach.

Schoenman, L.↗
DOE OSTI2023

Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗
DOE OSTI2020

Model Development for Multi-Component Fuel Vaporization and Flash Boiling

The objectives of this project are to improve the multi-component fuel droplet and film vaporization models used in internal combustion engine simulation, and to develop a comprehensive model to predict the characteristics of multi-component flash boiling spray. This work explores two approaches to fuel composition treatment for modeling multi-component fuel vaporization: one based on discretization and surrogates, and the other based on continuous thermodynamic distribution of fuel properties. The experimental data collected for model validation are done under three fuel form factors: droplet, spray, and thin film. The study on sprays also include experimentation under non-flash and flash boiling conditions, a phenomenon that enhances fuel vaporization. The main goals of this work are: Design and develop a multi-component fuel droplet and wall film vaporization model using both discrete and continuous thermodynamics methods. Design and develop an analytical model for multi-component flash boiling. Integrate the multi-component droplet and film model into multi-dimensional engine calculations to predict the fuel vaporization process under engine operation condition. Conduct multi-component droplet and fuel film vaporization experiments in a non-combusting chamber to verify the proposed vaporization models. Characterize flash boiling phenomena of multi-component fuel sprays by optical and laser diagnostic techniques. This report will detail the experimental setup and the numerical basis for developing a model to achieve the main goals listed above. Key features of observed multi-component fuel vaporization will be summarized at the end of each experimental sections, and corresponding model performance evaluation will be presented at the end of each model development section.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Impact of chemical ordering on thermodynamic properties of point defects and Xe substitutional in U-10Mo

The accurate knowledge of defect energetics is critical to understanding the aging and irradiation behavior of U-10Mo nuclear fuel, which is selected as the fuel type for conversion of the United States High-Performance Research Reactors (HPRRs). Furthermore, using hybrid molecular dynamics and Monte Carlo (MDMC) simulation, we studied the impact of chemical ordering on the formation energies of vacancies, interstitials, and the solution energy of the Xe substitutionals. Instead of forming a random solid solution (RSS), substantial short-range-order (SRO) develops in U-10Mo, particularly at low temperatures. Mo atoms are found to repel each other and prefer U-rich local atomic environments within the 1st nearest neighbor (1NN) cutoff. Compared to the case of a RSS, the state with equilibrated Mo ordering shifts the distributions of vacancy and interstitial formation energies due to the dependence of defect energies on the local atomic environment, without a clear effect on Xe solution energy. In the operation temperature range (100–250 °C) of U-Mo fuels, neglecting SRO can lead to an inaccurate estimate of thermal equilibrium point defect concentrations by over an order of magnitude and incorrectly predict the preference among different types of dumbbells, highlighting the critical importance of accounting for the impact of chemical ordering for accurate atomistic calculations of defect properties.

Molecular dynamics and Monte Carlo (MDMC)↗
DOE OSTI2020

Modeling Oxygen Transport in High Surface Area Carbon Supports for Polymer-Electrolyte Fuel Cells

Here, an analytical model for resistance to oxygen transport in air electrodes containing carbon black supports with high surface area was developed by combining a Thiele modulus—effectiveness factor approach at the agglomerate scale (~150 nm) with nanoscale diffusional resistance in carbon micropores/pits (~5 nm). This paper extends an earlier model for transport resistance to platinum nanoparticles on low surface area carbon. Differences in transport resistances between catalyst layers with high and low surface area carbon blacks predicted by the model with reasonable geometric dimensions and physical properties are consistent with experimental observations.

08 HYDROGEN↗
DOE OSTI2020

Physically Based Modeling of PEMFC Cathode Catalyst Layers: Effective Microstructure and Ionomer Structure–Property Relationship Impacts

Abstract This work presents a pseudo-two-dimensional proton exchange membrane fuel cell (PEMFC) model incorporating Nafion ionomer structure–property relationships in the cathode catalyst layer (CL) to capture and explain losses at low Pt loading. Structural data from neutron reflectometry and thin film Nafion conductivity measurements predict variations in the oxygen diffusion coefficient and ionic conductivity with changing CL ionomer thickness and Pt loading. By including these structure–property relationships, predicted polarization curves agree closely with previously published experimental data from cells with Pt loadings between 0.025 and 0.2 mg/cm2. Results demonstrate that structure–property relationships based on physically measurable ionomer and CL properties provide a feasible interpretation of PEMFC CL phenomena for a range of Pt loadings and help explain previously unaccounted-for losses at low Pt. Results also show that simulations must account for surface species coverage variations in order to properly capture the kinetic losses. Finally, results suggest that an increase in ionomer thickness surrounding the C/Pt surfaces may lead to improved cell performance due to improved ionic conductivity.

Electrochemistry↗
DOE OSTI2022

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2004

CMC Property Variability and Life Prediction Methods for Turbine Engine Component Application

The ever increasing need for lower density and higher temperature-capable materials for aircraft engines has led to the development of Ceramic Matrix Composites (CMCs). Today's aircraft engines operate with >3000"F gas temperatures at the entrance to the turbine section, but unless heavily cooled, metallic components cannot operate above approx.2000 F. CMCs attempt to push component capability to nearly 2700 F with much less cooling, which can help improve engine efficiency and performance in terms of better fuel efficiency, higher thrust, and reduced emissions. The NASA Glenn Research Center has been researching the benefits of the SiC/SiC CMC for engine applications. A CMC is made up of a matrix material, fibers, and an interphase, which is a protective coating over the fibers. There are several methods or architectures in which the orientation of the fibers can be manipulated to achieve a particular material property objective as well as a particular component geometric shape and size. The required shape manipulation can be a limiting factor in the design and performance of the component if there is a lack of bending capability of the fiber as making the fiber more flexible typically sacrifices strength and other fiber properties. Various analysis codes are available (pcGINA, CEMCAN) that can predict the effective Young's Moduli, thermal conductivities, coefficients of thermal expansion (CTE), and various other properties of a CMC. There are also various analysis codes (NASAlife) that can be used to predict the life of CMCs under expected engine service conditions. The objective of this summer study is to utilize and optimize these codes for examining the tradeoffs between CMC properties and the complex fiber architectures that will be needed for several different component designs. For example, for the pcGINA code, there are six variations of architecture available. Depending on which architecture is analyzed, the user is able to specify the fiber tow size, tow spacing, weave parameter, and angle of orientation of fibers. By holding the volume fraction of the fibers constant, variations in tow spacing can be explored for different architectures. The CMC material properties are usually calculated assuming the component is manufactured perfectly. However, this is typically not the case so that a quantification of the material property variability is needed to account for processing and/or manufacturing imperfections. The overall inputs and outputs are presented using a regression software to rapidly investigate the tradeoffs associated with fiber architecture, material properties, and ultimately cost. This information is then propagated through lifing models and Larson-Miller data to assess timehemperature-dependent CMC strength. In addition, a first order cost estimation will be quantified from a current qualitative perspective. This cost estimation includes the manufacturing challenges, such as tooling, as well as the component cost for a particular application. Ultimately, a cost to performance ratio should be established that compares the effectiveness of CMCs to their current rival, nickel superalloys.

Cheplak, Matthew L.↗
DOE OSTI2022

Understanding Material Damage and Degradation through Thermal Property Instruments

Quantifying material damage and degradation under reactor conditions enables researchers to make important predictions regarding reactor safety and efficiency. More specifically, thermal property instruments serve as a powerful tool in quantifying the evolution of thermal properties under irradiation, and hence, are necessary in qualifying fuels and materials for reactor use. In addition to providing insight into thermal properties, some instruments may provide a new means of quantifying radiation damage, a challenge in modern nuclear materials research.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Initial Developments in Modeling Graphite Behavior

Graphite is used in High Temperature Reactor designs as a moderator, reflector and core material responsible for protecting the fuel and maintaining structural stability. From a safety perspective, it is imperative to be able to predict how graphite will behave under reactor operating conditions which may compromise the core’s structural integrity or fuel’s safety performance. The following report summarizes recent modeling work undertaken at Idaho National Laboratory which focuses on graphite degradation behavior. One phenomenon which is explored in this report and can cause significant degradation to graphite properties is oxidation. Oxidation behavior in graphite is highly temperature dependent. At low temperatures, oxygen can fully penetrate a component and cause a homogeneous damage profile. At high temperatures, only the graphite near the surface of a component is affected. Understanding and modeling this temperature dependence is essential to predicting graphite behavior. In this report, three graphite models are discussed. The first model is used to investigate strength loss after low temperature oxidation. It does this by generating an approximate graphite microstructure then determining the required load to cause crack propagation. It has been shown that the model reproduces the quasi brittle stress versus strain relationship observed in graphite. Strength loss results from the model are shown to match experimental values. The second model investigates strength loss under high temperature oxidation conditions. This model is more applicable to full scale graphite components where the oxidation damage is often inhomogeneous throughout a component. The third model computes stresses in graphite under reactor conditions. Specifically, the model incorporates the effect of creep, irradiation dose, thermal strains, and oxidation in order to predict internal stresses in a component. All of these models are implemented in the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open source, parallel finite element framework.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Development of a TRISO assessment case for BISON based on transient experiments in the NSRR

The tristructural isotropic (TRISO) fuel assessment and validation database currently available in BISON is based mainly on steady-state irradiation and high-temperature furnace testing. Transient assessment cases are needed to support ongoing U.S. industry efforts to design and deploy commercial reactors that utilize TRISO fuels. Most available historical transient tests involving TRISO fuels were characterized by power densities, temperatures, and energy depositions that were highly conservative with respect to typical high-temperature gas-cooled reactor (HTGR) accident conditions. Nonetheless, assessment of BISON's predictive capabilities, adaptation of material properties toward high-temperature and high-particle-power regimes, and development of a systematic approach to validating BISON for TRISO transient applications now motivate the modeling of historical transient tests. This work describes the development of 1-D thermal models of transient experiments conducted at the Nuclear Safety Research Reactor (NSRR) in Japan, with BISON predictions of energy deposition, UO2 melting onset, and molten volume fractions being compared against experimental measurements. Melting is accounted for by defining an effective specific heat capacity for UO2—one that leverages the material's heat of melting. BISON's predictions of energy deposition and molten volume fraction are in good agreement with the experimental data from the low-energy-deposition tests; however, BISON tends to overpredict melting at higher energy depositions. Though overly conservative compared to the operating conditions expected for near-term TRISO-fueled reactor applications, these simulations effectively exercise BISON TRISO models over a wider range of conditions than those encompassed by the existing assessment database. Potential contributors to the observed discrepancies are noted and additional future developments proposed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗