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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Economic and Environmental Analysis to Evaluate the Potential Value of Co-Optima Diesel Bioblendstocks to Petroleum Refiners

The U.S. petroleum refining sector is undergoing a period of historic transformation, catalyzed by the decarbonization of the U.S. economy. Diesel-boiling-range bioblendstocks have gained traction, owing to their superior fuel properties and environmental performance as compared to traditional petroleum fuels. This work couples refinery linear programming models with life cycle assessment to quantify the potential economic and environmental benefits, and trade-offs, of blending diesel-boiling-range bioblendstocks at petroleum refineries. Linear programming models were developed in Aspen Process Industry Modeling Systems (PIMS) for three representative petroleum refinery configurations of differing complexity. Seven diesel-boiling-range bioblendstocks: 4-butoxyheptane, 5-ethyl-4-propylnonane, soy biodiesel, sludge hydrothermal liquefaction diesel, polyoxymethylene ethers, renewable diesel, and hexyl hexanoate, were investigated to identify key fuel properties that influence refineries' economics and to track the effect of adding bioblendstocks on refinery-wide cradle-to-gate greenhouse gases (GHG) emissions. These analyses considered blending levels from 10 to 30 vol% and fuel demand projections over the period 2040 to 2050. This analysis determines that bioblendstock sulfur content and cetane number are the primary fuel attributes with the potential to provide value to refiners. Life cycle assessment results indicate that the use of diesel-boiling-range bioblendstocks can reduce cradle-to-gate refinery GHG emissions by up to ~ 40 % relative to conventional refinery operations when considering carbon uptake in the supply chain of the bioblendstock. Refinery-wide marginal GHG abatement costs range from 120 to 3,600 USD2016/metric tons carbon dioxide equivalent avoided across the scenarios evaluated. Reducing the price of bioblendstocks is identified as a key to their adoption.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS,ENERGY P↗
DOE OSTI2022

Evaluating Class 6 Delivery Truck Fuel Economy and Emissions Using Vehicle System Simulations for Conventional and Hybrid Powertrains and Co-Optima Fuel Blends

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Environmental, Economic, and Scalability Consideration of Selected Biomass-Derived Blendstocks for Mixing-Controlled Compression Ignition (MCCI) Engines

Co-Optimization of Fuels & Engines (Co-Optima) explores how simultaneous innovations in fuels and engines can boost fuel economy and vehicle performance while reducing emissions. The Analysis of Sustainability, Scale, Economics, Risk and Trade (ASSERT) team supports Co-Optima goals by evaluating environmental and economic drivers and the potential of bioblendstock candidates. The team assesses potential benefits or drawbacks of deploying co-optimized fuels and engines in the transportation sector. This presentation provides guidance into which Co-Optima bioblendstocks may be most economically and environmentally viable when scaled up.

biomass↗
DOE OSTI2022

Fuel property impacts on gaseous and PM emissions from a multi-mode single-cylinder engine

The U.S. Department of Energy’s Co-Optima initiative has focused on improving fuel economy and vehicle performance while reducing emissions through the simultaneous development of emerging sustainable fuels with beneficial properties and advanced combustion strategies. A major thrust has been the development of advanced compression ignition (ACI) combustion strategies of gasoline range fuels in combination with spark-ignited (SI) combustion in a single engine capable of multi-mode operation to achieve high power density with enhanced part load efficiency. The aim of this study was to further the understanding of how emissions from both ACI and SI strategies operating on the same fuels in the same engine are impacted by different fuel properties. This investigation focused on particulate matter (PM) and gaseous hydrocarbon emissions from 6 different fuels across 3 different combustion modes on the same single-cylinder engine designed for multi-mode operation: SI combustion, partial fuel stratification (PFS), and spark-assisted compression ignition (SACI). In each of these modes, 3 different CA50 phasings were studied such that all 6 fuels could be studied at the same phasings. Three of the six different fuels used were specially formulated in a previous investigation to study the impact of fuel distillation and aromatic content while maintaining the research octane number (RON) and octane sensitivity. Additionally, neat isooctane and two ethanol containing fuels (RD5-87 and Co-Optima E30) were studied. Different fuel and phasing impacts on emissions were observed across the three combustion modes. Fuel properties were found to impact soot PM and particle number more than the CA50 phasing, while the phasing had more impact on NOx emissions. The NOx emissions were reduced in the PFS mode for all fuels compared to SI combustion, but the SACI combustion mode did not reduce NOx emissions. Although PFS produced low soot PM emissions like SI, total PM mass emissions were significantly higher due to large organic carbon (OC) PM mass contribution. Both PFS and SACI had greater particle number emission than SI operation with small nuclei mode particles dominating in PFS compared to large agglomeration particles in SACI.

42 ENGINEERING↗
DOE OSTI2022

Economic analysis of the benefits to petroleum refiners for low carbon boosted spark ignition biofuels

A refinery modeling framework is developed to estimate the benefits of blending high-quality biofuels directly with refinery gasoline components for attaining a premium grade fuel (also termed as Co-Optima Boosted SI gasoline here). Our results change the paradigm of bio-blendstocks (BBs) being competitors to fossil components, by identifying opportunities for refineries to add value to their product slate, from some favorable BB properties. This potential value can be characterized by calculating the breakeven value (BEV), as defined down below. The proposed modeling framework incorporates extensive data from (1) projected product over the next few decades, (2) crude oil and refinery products pricing, and (3) fuel specifications. The complete refinery models serve as a basis for assessing the value of biofuels, assuming profitability remains the same for representative petroleum refinery configurations. Our assessment showed wide range of variation of biofuels BEV from $\$$20-$\$$120/bbl, within the considered blending level and crude prices. Further, the BEV was correlated with the fuel octane ratings such as octane numbers (research, RON and motor octane numbers, MON) and both antiknock index (AKI, average of RON and MON) and sensitivity (S, difference between RON and MON), with a slightly higher correlation with the sensitivity. However, the expected decrease in gasoline demand for the upcoming years could negatively impact biofuels demand and value, in a business-as-usual scenario. Our analysis also showed a more valuable bio-blendstocks incorporation in smaller refineries since they can enhance the capabilities for producing specialty, high-value fuels/products, and introduce high octane-barrels into otherwise constrained blending operations. Additional implications towards refiners include opportunities to rebalance operations, access to high-value fuel markets, and synchronization with broader transportation industry trends. Furthermore, results indicate the value of Co-Optima boosted spark ignition (BSI) efficiency gains can extend to refiners to incentivize decarbonization and diversified feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2022

A comprehensive experimental and kinetic modeling study of di-isobutylene isomers: Part 1

We report di-isobutylene has received significant attention as a promising fuel blendstock, as it can be synthesized via biological routes and is a short-listed molecule from the Co-Optima initiative. Di-isobutylene is also popularly used as an alkene representative in multi-component surrogate models for engine studies of gasoline fuels. However, there is limited experimental data available in the literature for neat di-isobutylene under engine-like conditions. Hence, most existing di-isobutylene models have not been extensively validated, particularly at lower temperatures (< 1000 K). Most gasoline surrogate models include the di-isobutylene sub-mechanism published by Metcalfe et al. with little or no modification. The current study is undertaken to develop a detailed kinetic model for di-isobutylene and validate the model using a wide range of relevant experimental data. Part 1 of this study exclusively focuses on the low- to intermediate temperature kinetics of di-isobutylene. An upcoming part 2 discusses the high-temperature model development and validation of the relevant experimental targets. Ignition delay time measurements for the di-isobutylene isomers were performed at pressures ranging from 15 - 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 diluted in air and in the temperature range 650 - 900 K using two independent rapid compression machine facilities. In addition, measurements of species identified during the oxidation of these isomers were performed in a jet-stirred reactor and in a rapid compression machine. A detailed kinetic model for the di-isobutylene isomers is developed to capture the wide range of new experimental targets. For the first time, a comprehensive low-temperature chemistry submodel is included. The differences in the important reaction pathways for the accurate prediction of the oxidation of the two DIB isomers are compared using reaction path analysis. In conclusion, the most sensitive reactions controlling the ignition delay times of the DIB isomers under the pressure and temperature conditions necessary for autoignition in engines are identified.

09 BIOMASS FUELS↗
DOE OSTI2025

Co-optimization of fuel properties, combustion system geometry, and injection strategy for conventional diesel fuel

Here, studies have shown that fuel properties can impact an engine’s operation in several ways, including ignition delay, sooting tendency, mixture formation, and combustion temperature. In mixing-controlled compression ignition (MCCI) engines, the fuel system design and piston bowl geometry significantly affect combustion performance and emissions. Based on current information, it is difficult to draw conclusions about fuel property effects and sensitivities. The central fuel hypothesis approach used in the US Department of Energy Co-Optima program has worked well for spark ignition fuels: identifying critical fuel property ranges is sufficient to screen fuel blends that are expected to maximize efficiency and reduce pollutant emissions. However, for MCCI-relevant fuels, the information gained from past studies is not sufficient to build such a merit function or to allow for performing a similar screening of fuel blends. It is hypothesized that a co-optimization of a fuel’s physical and chemical properties, combustion system geometry, and injection strategy could leverage synergies between the effects of the fuel properties and geometries, resulting in improved performance over state-of-the-art. A machine learning–assisted unconstrained global optimization algorithm was used to explore a design space comprising 23 independent variables. The results show that physical property effects were minimal even for large variations in fuel properties, and the only interaction effect that was observed was the effect of varied fuel density parameters on fuel/air mixture formation. Nevertheless, these interactions were not sufficient in magnitude to significantly affect optimization results. Therefore, analysis of the results suggests that fuel physical properties cannot be leveraged in a co-optimization context to increase engine efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Evaluation of erosion potential of bio-based multicomponent blendstocks using experimentally-validated computational fluid dynamics

The optimization of the fuel-engine interface and associated performance is a significant goal for CoOptima and the industry. The strategic driver for fuel-engine optimization is clear: diesel optimization can significantly reduce emissions including NOx, particulate matter, and CO2 emissions. Previous evaluations of ethanol and diesel blends raised significant concerns with fuel injector erosion using ethanol blends. While Sylvatex’s technology can use ethanol, it also utilizes a surfactant and water to compatibilize and modify ethanol blends, thereby controlling its impact in diesel engines. The results from the project will (1) provide important insights into complex fuels and erosion, which will be used to design additional, improved formulations; and (2) expand capabilities of Argonne’s cavitation-induced erosion risk assessment (CIERA) tool to model multi-component systems, furthering Co-Optima objectives.

09 BIOMASS FUELS↗
DOE OSTI2022

Co-Optimization of Fuels & Engines Findings and Impact (FY2015-FY2021 Report)

Breakthroughs from the U.S. Department of Energy Co-Optimization of Fuels & Engines (Co-Optima) initiative could make it possible to more rapidly cut emissions, reduce dependence on international petroleum, and contribute to ambitious national goals to slow global warming on the land, in the air, and across the water. Findings from the 6-year collaborative undertaking are now available in this report.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Rational Optimization of Microbial Processing for High Yield CO 2 -to-Isopropanol Conversion: Cooperative Research and Development Final Report, CRADA Number CRD-20-17114

This project focuses on the production of the fuel blendstock isopropanol using a CO 2 -fixing Clostridium by metabolic engineering and process optimizations. The project will initiate from a baseline isopropanol producer and pursue isopropanol production at high carbon-conversion efficiency. We will lead engineering work by in-depth pathway analyses including thermodynamics optimization, enzyme expense analysis, metabolic robustness analysis, and -omics analysis. The isopropanol production will be optimized via genome editing followed by fermentation optimizations. This project will deliver a novel microbial process that efficiently converts waste CO 2 to isopropanol at ~g/L titer level within 18-months. This project will layout a solid knowledge basis and technology platform for renewable CO 2 valorization to bio-blendstock that help achieve Co-Optima and Shell's goals.

09 BIOMASS FUELS↗
DOE OSTI2024

Independent Fuel Property Effects of Fuel Volatility on Low Temperature Heat Release and Fuel Autoignition (Final Report)

This Cooperative Research and Development Agreement (CRADA) project between Argonne National Laboratory (ANL), Oak Ridge National Laboratory (ORNL), and Shell Global Solutions (Shell) was initiated as part of a Directed Funding Opportunity (DFO) call for proposals from the Co-Optimization of Fuels and Engines (Co-Optima) initiative. Shell had observed that volatile fuels suppress low temperature heat release (LTHR) more than expected based on conventional gasoline autoignition metrics: research octane number (RON) and motor octane number (MON). The role of LTHR contributes to autoignition phenomena for both boosted spark ignition (BSI) and advanced compression ignition (ACI) combustion modes. ACI combustion modes are applicable to large engines in the hard-to-electrify applications such as off-road, rail, and marine. Thus, having a reliable understanding of autoignition phenomena, including being able to accurately account for the effects of fuel volatility, is particularly important as new synthetic and bio-fuel compositions are considered.This CRADA project aimed to test the hypothesis that the decreased LTHR is due to preferential evaporation of multicomponent fuels when using direct injection (DI) fueling technology, creating composition and reactivity stratification. A custom set of fuels was designed and blended to test this hypothesis by Shell, with experimental engine studies at ORNL and engine combustion modeling by ANL. However, the initial experimental findings did not show the expected effect of fuel volatility suppressing LTHR. Instead, the LTHR propensity observed was independent of the fuel volatility. Due to the unexpected experimental result, the remainder of the experimental effort was redirected to study the effect of fuel volatility on emissions under spark-ignited cold-start conditions. However, as with the LTHR experiments, the cold start effort did not show a meaningful effect of fuel volatility on cold start emissions. Meanwhile, improved engine CFD models have been developed for both LTHR and cold start operations for the Shell fuels with different volatilities. While the simulation efforts were not pursued further due to the insignificant effects of fuel volatility as shown in experiments, the models developed can be easily retooled for off-road, rail, and marine applications.

09 BIOMASS FUELS↗
DOE OSTI2024

Characterization of Biomass-Based Fuels and Fuel Blends for Low-Emissions, Advanced Compression Ignition Engines (Final Report)

The goal of the Co-Optima program was to accelerate deployment of co-optimized fuels and engines that will reduce fuel consumption, and criterion pollutants and greenhouse gas (GHG) emissions for both spark and compression-ignited engines. In this project, combustion measurements from a constant pressure flow rig (CPFR) with optical access were used to assess fundamental combustion behavior of number of different candidate fuels and fuel blends. This chamber and its peripheral systems allowed stable control of ambient air pressure and temperature and fuel injection pressure and timing for hundreds of repeat injections allowing statistical interpretation of the results. The optical diagnostics enabled capturing of liquid length, vapor length, ignition timing, lift-off length as well as localized (temporal and spatially resolved) mixture refractive index, flame structure, and soot mass. The operating conditions allowed the study of combustion conditions promoting lean lifted flame combustion (LLFC), a mixing-controlled low-temperature combustion (LTC) strategy to reduce soot production in Advanced Compression Ignition (ACI) engines.

09 BIOMASS FUELS↗
DOE OSTI2024

Development of High-Fidelity and Efficient Modeling Capabilities for Enabling Co-Optimization of Fuels and Multi-Mode Engines

The objective of this closely coordinated research project is to develop improved physical sub-models and innovative numerical algorithms to enable accurate and efficient predictions of multi-mode combustion to support EERE’s Co-Optima program. To this end, a research pro-gram is proposed that seeks • to develop accurate submodels for predicting multi-mode combustion regimes, wall-heat transfer, non-equilibrium plasma ignition, and combustion-mode transition, • to develop dynamic load-rebalancing algorithms and efficient semi-implicit time-integration schemes for enabling exascale computing, • to validate the computational submodels against experiments and direct numerical simulation (DNS) data in conjunction with sensitivity analysis, and • to support the direct transition of the resulting sub-models into other engine-simulation tools through the development of self-contained modules. All sub-models will be integrated into the open-source exascale engine-simulation platform Nek5000.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Impact of Biofuel Blending on Hydrocarbon Speciation and Particulate Matter from a Medium-Duty Multimode Combustion Strategy

The U.S. Department of Energy’s Co-Optima initiative simultaneous focused on diversifying fuel sources, improving efficiency, and reducing emissions through using novel combustion strategies and sustainable fuel blends. For medium-duty/heavy-duty diesel engines, research in this area has led to the development of a multimode strategy that uses premixed charge compression ignition (PCCI) at low loads and conventional diesel combustion (CDC) at mid–high loads. The aim of this study was to understand how emissions were impacted when using PCCI instead of CDC at low loads and switching to an oxygenated biofuel blend. It provides a detailed speciation of the hydrocarbon (HC) and particulate matter (PM) emissions from a multimode medium-duty engine operating at low loads in PCCI and CDC modes and high loads in CDC. The effect of the oxygenated biofuel blend on emissions was studied at all three mode–load conditions using #2 ULSD and a bio-derived fuel (25% hexyl hexanoate (HHN)) blended in #2 ULSD. The PCCI mode effectively decreased NOx, total HC, and PM/PN emissions, with a substantial decrease in larger particles (≥50 nm). A PM/PN reduction was observed at high loads with the 25% HHN fuel. While the total HC emissions were not impacted by fuel type, the detailed HC analysis exposed changes in the HC’s composition.

09 BIOMASS FUELS↗
DOE OSTI2023

Development of a Supercharged Octane Number and a Supercharged Octane Index

Gasoline knock resistance is characterized by the Research and Motor Octane Number (RON and MON), which are rated on the CFR octane rating engine at naturally aspirated conditions. However, modern automotive downsized boosted spark ignition (SI) engines generally operate at higher cylinder pressures and lower temperatures relative to the RON and MON tests. Using the naturally aspirated RON and MON ratings, the octane index (OI) characterizes the knock resistance of gasolines under boosted operation by linearly extrapolating into boosted “beyond RON” conditions via RON, MON, and a linear regression K factor. Using OI solely based on naturally aspirated RON and MON tests to extrapolate into boosted conditions can lead to significant errors in predicting boosted knock resistance between gasolines due to non-linear changes in autoignition and knocking characteristics with increasing pressure conditions. Here, a new “Supercharged Octane Number” (SON) method was developed on the CFR engine at increased intake pressures, which improved the correlation to boosted knock-limited automotive SI engine data over RON for several surrogate fuels and gasolines, including five “Co-Optima” RON 98 fuels and an E10 regular grade gasoline. Furthermore, the conventional OI was extended to a newly introduced Supercharged Octane Index (OI S ) based on SON and RON, which significantly improved the correlation to fuel knock resistance measurements from modern boosted SI engine knock-limited spark advance tests. This demonstrated the first proof of concept of a SON and OI S to better characterize a fuel’s knock resistance in modern boosted SI engines.

42 ENGINEERING↗
DOE OSTI2023

Deep reinforcement learning to discover multi-fuel injection strategies for compression ignition engines

Over the past several decades, regulation of compression ignition engine emissions has become increasingly stringent as concern about the environmental and health implications of these emissions has grown. These changing constraints have led to a series of new, alternative fuel injection strategies that aim to maintain power output while reducing in-cylinder generated emissions by operating in the low-temperature combustion (LTC) regime. These advanced injection strategies are created and retuned for individual combinations of engine geometry, fuel, and emissions constraints. Deep reinforcement learning has been shown to be an effective alternative to traditional optimization approaches for highly combinatorial control problems, such as discovering the optimal injection schedules for compression ignition engines. In this study, we deploy a previously presented deep reinforcement learning framework to iteratively optimize a series of engine geometries over a range of increasingly strict NO x emissions regulations. We then examine the resulting injection schedules. We discuss the potential for using this deep reinforcement learning framework for fuel selection screening and for discovering unique injection strategies for different engine geometries and future emissions standards.

33 ADVANCED PROPULSION SYSTEMS↗