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DOE OSTI2023

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗

NASA NTRS1992

Current status of the development of an ignition transient model for solid rocket motors

The primary objectives of the computational fluid dynamics (CFD) code are to calculate the pressure rise rate and the maximum chamber pressure which occurs during the first second of the Advanced Solid Rocket Motor (ASRM) action time. A specific objective is to determine the relative difference between the ignition transients produced during a single port igniter and that produced by a multiport igniter. Discussed here are the results obtained from the one dimensional code and the plans for the development of the three dimensional code. Much of the information is given in viewgraph form.

Luke, Gary D.↗

DOE OSTI2026

The Development of Kinetic and Radiation Hydrodynamics Modeling of Thermonuclear Burn Propagation in Isochoric p - 11 B Through the Support of the INFUSE Program

The report summarizes DOE INFUSE-supported work between HB11 Energy and the University of Rochester’s TriForce Institute to improve computational modeling of advanced fusion fuels, especially proton–boron-11 (p- 11 B). The project extended the TriForce particle-in-cell/Monte Carlo collision code to include physics needed for dense, high-temperature p- 11 B burn studies, including p- 11 B fusion reactions, three-alpha-particle reaction products, relativistic Coulomb collisions, large-angle nuclear scattering, bremsstrahlung radiation, inverse bremsstrahlung absorption, and photon transport. The upgraded models were verified against focused physics tests and against known deuterium–tritium burn behavior. The study then used one-dimensional spherical simulations to estimate the conditions required for thermonuclear burn propagation in isochoric p- 11 B fuel. The calculations found that burn propagation is possible in the model, but only under very extreme hot-spot conditions, such as about 7000 g/cm 3 at 500 keV or 9000 g/cm 3 at 300 keV for a 20-micron hot spot. These conditions are much more demanding than current demonstrated inertial confinement fusion hot spots. The report concludes that the INFUSE collaboration successfully advanced kinetic and radiation modeling capabilities for p- 11 B fusion and provided useful estimates of ignition requirements. However, the simulated fuel gains remain below what would be needed for practical inertial fusion energy, and further work is needed to reconcile differences among kinetic, radiation-hydrodynamic, and analytic models and to identify more achievable target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗

DOE OSTI2021

Autoignition and preliminary heat release of gasoline surrogates and their blends with ethanol at engine-relevant conditions: Experiments and comprehensive kinetic modeling

This work utilizes a rapid compression machine (RCM) to experimentally quantify autoignition and preliminary heat release characteristics for blends of 0 to 30% ethanol by volume into two surrogates (FGF-LLNL and FGF-KAUST) that represent a full boiling range gasoline (FACE-F). Experimental conditions cover pressures from 15 to 100 bar, temperatures from 700 to 1000 K, and diluted/stoichiometric and undiluted/lean fuel loading conditions representative of boosted spark-ignition and advanced compression ignition engines, respectively. Direct comparison is made with previously reported results for FACE-F/E0–E30 blends. Here, a detailed gasoline surrogate chemistry model is also proposed, and chemical kinetic modeling is undertaken using the proposed model to generate chemical insights into the compositional effects and ethanol blending effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Multi-dimensional modeling of mixture preparation in a direct injection engine fueled with gaseous hydrogen

With the recent advances of direct injection (DI) technology, introducing hydrogen into the combustion chamber through DI is being considered as a viable approach to circumvent backfire and pre-ignition encountered in early generations of hydrogen engines. As part of a broader vision to develop a robust numerical model to study hydrogen spark ignition (SI) combustion in internal combustion (IC) engines, the present numerical investigation focuses on mixture preparation in a hydrogen DI SI engine. This study is carried out with a single hole injector with gaseous hydrogen injected at 100 bar injection pressure. Simulations are carried out for high and low tumble configurations and validated against optical data acquired from planar laser induced fluorescence (PLIF) measurements. Varying mesh configurations are investigated for the impact on in-cylinder mixture distribution. A particular emphasis is placed on the effect of nozzle geometry and mesh orientation near the wall. Overall, the computational model is found to predict the mixture distribution in the combustion cylinder reasonably well. The results showed that the alignment of mesh with the flow direction is important to achieve good agreement between numerical analysis and optical measurement data.

08 HYDROGEN↗

DOE OSTI2024

Ignition Delay Times and Chemical Kinetic Model Validation for Hydrogen and Ammonia Blending With Natural Gas at Gas Turbine Relevant Conditions

Ignition delay times from undiluted mixtures of natural gas (NG)/H 2 /Air and NG/NH 3 /Air were measured using a high-pressure shock tube at the University of Central Florida. The combustion temperatures were experimentally tested between 1000 and 1500 K near a constant pressure of 25 bar. As mentioned, mixtures were kept undiluted to replicate the same chemistry pathways seen in gas turbine combustion chambers. Recorded combustion pressures exceeded 200 bar due to the large energy release, hence why these were performed at the high-pressure shock tube facility. The data are compared to the predictions of the NUIGMech 1.1 mechanism for chemical kinetic model validation and refinement. An exceptional agreement was shown for stoichiometric conditions in all cases but strayed at lean and rich equivalence ratios, especially in the lower temperature regime of H 2 addition and all temperature ranges of the baseline NG mixture. Hydrogen addition also decreased ignition delay times by nearly 90%, while NH 3 fuel addition made no noticeable difference in ignition time. NG/NH 3 exhibited similar chemistry to pure NG under the same conditions, which is shown in a sensitivity analysis. Here, the reaction CH 3 + O 2 = CH 3 O + O is identified and suggested as a possible modification target to improve model performance. Increasing the robustness of chemical kinetic models via experimental validation will directly aid in designing next-generation combustion chambers for use in gas turbines, which in turn will greatly lower global emissions and reduce greenhouse effects.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Flame Chemistry Workshop: a perspective on challenges and strategic actions in combustion experiments and chemical kinetics modeling

Continued progress in the development of predictive models for combustion chemistry—including ignition and flame behavior, species evolution, and combustion system performance—relies on overcoming enduring and emerging challenges in experimental measurements, theoretical formulations, and chemical kinetics mechanism construction. As combustion science continues to coincide with advances in sustainable fuels development, plasma technologies, and automated modeling capabilities, the need for coordinated, community-driven strategies is essential. The Flame Chemistry Workshop (FCWS), held biennially before the International Symposium on Combustion, serves as a dedicated platform to identify, consolidate, and address these challenges in a structured and collaborative manner. This perspective arises from discussions at the 7th FCWS in Milan, Italy (2024), and presents a collective view of the critical barriers currently limiting progress. Across the five technical domains discussed during the 7th FCWS – sustainable fuels combustion, advanced diagnostics for combustion measurements, experiments and modeling in plasma combustion, artificial intelligence and automated methods for theory and mechanisms generation, and chemical kinetic models—a series of persistent and emerging scientific challenges were identified, highlighting the need for deeper integration between three areas: theory, experiments, and modeling. In conclusion, the present article concisely describes present challenges that were identified in each of the technical domains in an effort to streamline and coordinate solutions to accelerate progress in combustion science.

Chemical kinetics↗

DOE OSTI2020

Real Fuel Modeling for Gasoline Compression Ignition Engine

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode. A study detailing the development of the gasoline real fuel model was performed and various surrogates for gasoline fuel were investigated. The gasoline real fuel model will be used in subsequent CFD modelling activities for the development of an advanced mixed mode combustion system as part of the Department of Energy funded project DE-EE0008478.

Gasoline Compression Ignition, real fuel modeling,↗

DOE OSTI2025

Enhancing carbon storage through proactively managing fire-prone coniferous mountain forests

Mountain ecosystems typically serve as carbon (C) sinks. However, studies also suggest that they could be C sources due to climate warming, drought and insect-related mortality, wildfires, and management actions. We applied the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS), a process-based dynamic vegetation-ecosystem model, to investigate the role of ecosystem management in C storage under Mediterranean climate over the 21 st century. We modified LPJ-GUESS to include implementing mechanical thinning by vegetation size classes, components, and types along with a new mechanistic fire-occurrence model that accounts for wind speed and lightning ignition. Simulations show that mechanical thinning or prescribed fire performed 5-20 years in advance of a high-severity wildfire reduced direct wildfire C emissions by 38-66 %. Our results also show that long-term management actions repeated every 5-20 years, including thinning relatively small trees (diameters up to 7 inches or ∼178 mm), can maintain stable C levels in the forest and lower dead-fuel amounts. We found that, although prescribed fire mitigated wildfire severity, ecosystem C storage from reduced wildfire emissions can be outweighed by the added emissions from the prescribed fire themselves. Thinning plus removing and sequestering the thinned biomass can ensure that forests act as net C sinks through the end of the 21 st century. However, addition of prescribed fire is needed to reduce understory and lower the projected extent of high-severity wildfire. Achieving the competing goals of reducing wildfire and making the Sierra Nevada long-term C sink can be advanced through carefully coordinated thinning, sequestration of thinned biomass, and prescribed fire.

Climate solutions↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

The objective of this project is to improve the prediction of engine knock by developing a new combustion modeling framework. Engine knock is a limiting factor to constrain the increase of fuel efficiency for spark ignition (SI) engines in most passenger cars. Efforts to increase fuel efficiency, increasing the compression ratio or downsizing, lead to the increase in the tendency of the knock occurrence. The knock is an undesired ignition of the end-gas, unburned fuel/air mixture ahead of the spark-ignited premixed flame, resulting in rapid in-cylinder pressure rises and engine damages. The combustion modeling framework developed in this project can consider turbulence-chemistry interactions during end-gas ignition, while using a reasonably detailed chemical mechanism developed for ignition and combustion reactions under engine relevant conditions, and the subtle characteristics of spark-ignited flame propagation. It is developed in the context of large eddy simulation (LES), which can capture stochastic in-cylinder processes. The developed model is incorporated into a commercial software for engine simulation, CONVERGE CFD, as a user defined function, and validated. Engine knock and knock-free experiments as well as direct numerical simulation (DNS) of end-gas ignition in homogeneous turbulence are performed to help model development and provide data sets for model validation. With further validation, the developed model is expected to advance the predictive capability for engine knock simulations and thus contribute to improving the fuel efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Numerical investigation of a fueled pre-chamber spark-ignition natural gas engine

Pre-chamber spark-ignition (PCSI) is a leading advanced ignition concept for internal combustion engines with the potential to enable diesel-like efficiency in medium-duty/heavy-duty (MD/HD) natural gas (NG) engines. By leveraging distributed ignition sources from multiple turbulent jets, the PCSI technology can deliver extremely short combustion duration in ultra-lean mixtures and significantly improve the engine thermal efficiency. However, in the automotive industry there is a lack of adequate science base and predictive simulation tools required for commercial development of PCSI engines. Here, in this study, Reynolds-Average Navier-Stokes simulations are carried out to describe the combustion process in lean-burn NG engines, focusing on the combustion modeling approach. Two combustion models, multi-zone well-stirred reactor (MZ-WSR) and G-equation, are used to simulate the combustion process in an MD NG engine equipped with a fueled-PCSI system for four operating conditions close to the lean operating limit. A skeletal chemical mechanism and a laminar flame speed tabulation are used to compute the combustion accurately. Simulation results are compared with experimental data regarding measured cylinder pressure, heat release rate, and combustion duration. By dividing the PCSI combustion process into four distinct phases, the difference between the two models’ results for each phase is analyzed in detail. The MZ-WSR model overestimates the combustion duration for early flame kernel growth in the pre-chamber due to the lack of a specific formulation to take turbulence-chemistry interaction into account. Despite the prolonged combustion duration and low pressure built-up inside the pre-chamber, the model matches the combustion rate in the main-chamber. In contrast, the G-equation model delivers good agreements for the pre-chamber combustion and turbulent jet-driven combustion processes. However, the model starts to underestimate the combustion rate in the main-chamber, especially under ultra-lean mixture conditions. Finally, improvements are needed for both models to simulate the later combustion stage that occurred in the near-wall regions.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

An indirect approach to optimize the reaction rates of thermal NO formation for diesel engines

With stringent emission regulations, it has become more important for modern diesel engine manufacturers to accurately predict engine-out nitrogen oxide (NO x ) emissions across a wide range of operating conditions. Thermal NO is the major source of engine-out NO x in modern diesel engines. For thermal NO formation, several earlier studies have recommended the forward and reverse reaction rate coefficients of the rate-limiting reaction (O + N 2 ⇌ NO + N). However, due to deficiencies in sub-models and inadequacies of reduced chemical mechanisms to represent diesel combustion, these recommended values more often than not need to be adjusted in reduced order combustion models to accurately predict engine-out NO x . Hence, in this work a systematic and computationally efficient approach has been proposed to streamline the process of determining the optimum reaction rate coefficients. Here, to develop the optimization approach, four different production diesel engines with different operating conditions in terms of speed, load, and exhaust-gas recirculation have been considered. Numerical simulations have been performed using a detailed zero-dimensional velocity-composition-frequency transported probability density function (0D-VCF-tPDF) model that uses hundreds of notional particles to capture in-cylinder stratification. Four different combinations of hydrocarbon and NO x chemical mechanisms were used to represent chemistry. It was found that for the rate-limiting reaction, the pre-exponent factors (A f1 , A r1 ) and activation energies (E A,f1 , E A,r1 ) of the forward and reverse reaction rates follow a linear band in A f1 - E A,f1 and A r1 - E A,r1 space where predicted engine-out NO x match the measured values closely. By encompassing such bands from different engines and considering constraints on activation energies, a reduced search domain of pre-exponent factors and activation energies was constructed that is expected to be applicable to any diesel engine. Eventually, computationally efficient three-line and one-line search approaches were proposed to determine the optimum values of the pre-exponent factors and activation energies that led to a minimum error between measured and predicted engine-out NO x . Finally, these three-line and one-line NO x optimization approaches were applied to a fifth production diesel engine for which the 0D-VCF-tPDF model showed a very good predictive performance in terms of predicting peak pressure, 50% burn rate, and engine-out NO x when compared to measured and 3D-CFD values.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Predicting Fuel Properties and Emissions for Advanced Biofuels for Diesel Engines (CRADA Final Report)

The project will investigate variations in biofuel composition and optimize performance in combustion for conventional and future compression ignition engines. It will evaluate a variety of bio-derived molecules in the diesel range that can be produced using technology in ExxonMobil’s portfolio as well as fuels that cover the range of potential molecular structures for robust model development. Changes in fuel/air premixing and stratification in advanced engines could alter the relationship between fuel properties and performance in comparison to current generation spray combustion approaches. NREL experience in fuel and combustion modeling will enable development of general rules for predicting performance of a wide range of biofuel options.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Quantitative metrics for evaluating thermonuclear design codes and physics models applied to the National Ignition Campaign

In this study, physics models and design codes for hot dense plasmas undergoing thermonuclear burn are evaluated objectively using statistical metrics that compare the difference between calculations and data relative to the experimental uncertainties. The analysis is applied to the National Ignition Campaign (NIC) because it is relevant, comprehensive, and well documented. The statistics confirm that a key process afflicting NIC performance is mix driven by hydrodynamic instabilities as approximated here using the KL model [G. Dimonte and R. Tipton, Phys. Fluids 18, 085101 (2006)]. New physics models are also presented for instability-driven magnetic fields [B. Srinivasan et al., Phys. Rev. Lett. 108, 165002 (2012)] and the Coulomb logarithm for electron–ion thermal relaxation [G. Dimonte and J. Daligault, Phys. Rev. Lett. 101, 135001 (2008)]. The plasma-generated magnetic fields improve the agreement between code and data in a statistically significant manner by reducing the electron thermal conduction in the hot-spot via the Hall term. The Coulomb logarithm is presented in a numerically practical form that incorporates recent theoretical advances. However, it does not improve the agreement between the code and data because the thermal relaxation is so fast in non-ignited NIC plasmas that the typical 20% error does not change the tight coupling between electrons and ions. Even with these improved physics models, the one-dimensional simulations presented here are not able to describe the high-convergence NIC implosions in a statistically acceptable manner. Of the heroic multi-dimensional simulations of Clark et al. [Phys. Plasmas 23, 056302 (2016)], only those in three-dimensions satisfy the statistical acceptance criterion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2012

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

West, Jeff↗

DOE OSTI2020

Autoignition behavior of gasoline/ethanol blends at engine-relevant conditions

Ethanol is an attractive oxygenate increasingly used for blending with petroleum-derived gasoline yielding beneficial combustion and emissions behavior for a range of internal combustion engine schemes, including stoichiometric spark-ignition and low temperature combustion (LTC). As such, it is important to fundamentally understand the autoignition behavior of gasoline/ethanol blends. This work utilizes a rapid compression machine (RCM) and a homogeneous charge compression ignition (HCCI) engine to experimentally quantify changes in fuel reactivity, through ignition delay times and preliminary heat release, for blends of 0 to 30% vol./vol. into a full boiling range research gasoline (FACE-F). Diluted/stoichiometric and undiluted/fuel-lean conditions are explored covering a wide range of compressed temperatures and pressures relevant to conventional and advanced, gasoline combustion engines. Detailed chemical kinetic modeling is undertaken using a recently updated gasoline surrogate model in conjunction with a five-component surrogate to model the RCM experiments and provide chemical insight into the perturbative effects of ethanol on the autoignition process. The diluted/stoichiometric RCM measurements reveal that within the low-temperature regime ethanol retards first-stage and main ignition delay times, and suppresses both the rates and extents of low-temperature heat release (LTHR), while within the intermediate-temperature regime ethanol only causes slight changes. Good agreement of ignition delay time and preliminary heat release prediction is found between model and experimental results. Sensitivity and flux analyses further show that ethanol blending effects are dominated by the competition between the H-atom abstraction from ethanol and other fuel components by OH radical at low temperatures and by HO 2 radical at intermediate temperatures. These findings are consistent across both fuel loading conditions explored in this study. In addition, when HCCI engine experiments are mapped onto undiluted/lean RCM measurements under a constant combustion phasing scenario, good correspondence between the two apparatuses is observed for LTHR and start of high-temperature heat release. Finally, the current study highlights the importance of characterizing LTHR in predicting fuel behaviors in high-boost/low-temperature engines, and demonstrates that RCM experiments can provide an alternative, and more-efficient avenue for such characterization.

02 PETROLEUM↗