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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

China's plug-in hybrid electric vehicle transition: An operational carbon perspective

Assessing the emissions of plug-in hybrid electric vehicle (PHEV) operations is crucial for accelerating the carbon–neutral transition in the passenger car sector. This study is the first to adopt a bottom-up model to measure the real-world energy use and carbon dioxide emissions of China’s top twenty selling PHEV models across different regions from 2020 to 2022. The results indicate that (1) the actual electricity intensity of the best-selling PHEV models (20.2–38.2 kWh/100 km) was 30–40 % higher than the New European Driving Cycle values, and the actual gasoline intensity (4.7–23.5 L/100 km) was 3–6 times greater than the New European Driving Cycle values. (2) The overall energy use of the best-selling models varied among different regions, and the energy use from 2020 to 2022 in Southern China was double that Northern China and the Yangtze River Middle Reach. (3) The top-selling models emitted 4.7 megatons of carbon dioxide nationwide from 2020 to 2022, with 1.9 megatons released by electricity consumption and 2.8 megatons released by gasoline combustion. Furthermore, targeted policy implications for expediting the carbon–neutral transition within the passenger car sector are proposed. In essence, this study explores and compares benchmark data at both the national and regional levels, along with performance metrics associated with PHEV operations. The main objective is to aid nationwide decarbonization efforts, focusing on carbon reduction and promoting the rapid transition of road transportation toward a net-zero carbon future.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Upcycling disposable face masks into fuel range iso-alkanes through hydropyrolysis coupled with vapor-phase hydrocracking

The COVID-19 pandemic has resulted in an alarming accumulation of plastic waste. Herein, an integrated hydropyrolysis and hydrocracking process was performed to upcycle disposable masks into fuel-range iso-alkanes over carbon supported ruthenium (Ru/C). Experimental results indicated that catalyst type significantly affected product distribution during the hydropyrolysis and vapor-phase hydrocracking of disposable masks. Compared with zeolites-induced catalytic cascade process where up to ~25.9 wt% yield of aromatic hydrocarbons such as toluene and xylenes were generated, a ~82.7 wt% yield of desirable iso-alkanes with a high C 5 –C 12 gasoline selectivity of 95.5% was obtained over Ru/C under 550 °C hydropyrolysis temperature and 300 °C hydrocracking temperature at 0.2 MPa H 2 . Further, the cascade hydropyrolysis and hydrocracking process also exhibited high adaptability and flexibility in upcycling single-use syringes, food packaging, and plastic bags, generating 79.1, 81.6, and 80.3 wt% yields of fuel range iso/n-alkanes, respectively. This catalytic cascade hydrotreating process provides an efficient and effective approach to convert pandemic-derived plastic waste into gasoline-range fuel products.

09 BIOMASS FUELS↗
DOE OSTI2020

Two trillion gallons: Fuel savings from fuel economy improvements to US light-duty vehicles, 1975–2018

Since 1975, the fuel economy of new light-duty vehicles sold in the U.S. has almost doubled. Fuel economy improvements on laboratory tests gradually became real improvements on the road as newer, more efficient vehicles replaced older less efficient ones. Fleet-wide fuel economy gains produced large fuel savings. In this paper, we show that fuel economy gains measured on laboratory test cycles, adjusted for on-road conditions and weighted by the distribution of vehicles by age and their relative use, closely match estimates by the Federal Highway Administration based primarily on traffic counts and motor fuel tax records. Furthermore, adjusting for the rebound effect of fuel economy on vehicle miles traveled, we estimate the fuel savings, CO 2 emissions reductions and dollars saved on fuel due to fuel economy improvements over the past 43 years. Through the end of 2018, estimated cumulative fuel savings amount to approximately 2 trillion gallons of gasoline. We estimate that roughly one-fifth of the savings can be attributed to gasoline price increases over the period and four-fifths to fuel economy and greenhouse gas (ghg) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A general predictive methodology for fuel-mixture properties up to supercritical conditions

A predictive thermodynamic model is utilized for the calculation of fuel properties of oxymethylene dimethyl ethers (OME 3–4 ), surrogates for gasoline, diesel and aviation fuel, as well as alcohol blends with gasoline and diesel. The alcohols used for these blends are methanol, ethanol, propanol, butanol and pentanol; their mixing ratio ranges from 10 to 50% by volume. The model is based on the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EoS) and Vapor Liquid Equilibrium (VLE) calculations at constant temperature, density and composition. The model includes the association term, with the assumption of two association sites (2B scheme), to enable the modeling of alcohols. The pure-component parameters are estimated based on the Group Contribution (GC) method of various sources, as well as a parametrization model specifically designed for the case of OME 3–4 . The results of the computational model for the density, vapor pressure and distillation curves at various conditions, including high-pressure, high-temperature (HPHT), are compared to experimental and computational data available in the literature. In the cases where no measurements are available for the surrogates, experimental data for the corresponding target fuel are used, taking into consideration the inherent deviation in properties between real and surrogate fuel. Overall, the results are in good agreement with the data from the literature, with the average deviation not exceeding 12% for temperature (Kelvin) on the distillation curves, 10% for density and 46% for vapor pressure and the general trend being captured successfully. The use of different pure component parameter estimation techniques can further improve the prediction quality in the cases of OME3–4 and the aviation fuel surrogate, especially for the vapor pressure, leading to an average deviation lower than 18%. These results demonstrate the predictive capabilities of the model, which extend to a wide range of fuel types and pressure/temperature conditions. Through this investigation, the present work aims to establish the limits of applicability of this thermodynamic property prediction methodology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

An Experimental Study of Uncertainty Considerations Associated with Predicting Auto-ignition Timing using Livengood-Wu Integral Method

The application of the Livengood-Wu (LW) integral method as a tool to estimate knock onset in spark ignited (SI) engines and combustion phasing in advanced compression ignition (ACI) engines has been demonstrated through simulations several times. In this study, the effect of uncertainties associated with parameters required for the LW integral method, when used as a tool for model based control of ignition timing in an ACI engine, were experimentally studied using five full boiling range gasoline fuels. As a first step, the method was applied to experimental data from a rapid compression machine and it was found that the ability of the LW integral method to predict ignition timing was very sensitive to the performance of the chemical kinetic model of each fuel. The method was subsequently applied to experimental data from a single-cylinder gasoline engine with simple approximations for the LW integral input parameters, and it was found that the predicted time of ignition was significantly different from the actual start of combustion. Systematic evaluation of various parametric uncertainties conducted thereafter showed that the uncertainty in cylinder charge temperature has the greatest influence. Improved methods of estimating cylinder charge temperature are proposed to account for the previously determined corrections, to enable the use of the LW integral method for model based control of ignition timing.

Compression Ignition↗
DOE OSTI2022

Multi-stage heat release of multi-component fuels: Insights and implications for advanced engine operation

Multi-stage heat release (MSHR) is a unique phenomenon typically seen in lean/diluted and low- to intermediate-temperature combustion. Despite its relevance to advanced engine operation, the MSHR of multi-component fuels has barely been quantified. This study aims to characterize the MSHR of multi-component fuels in a rapid compression machine (RCM) at conditions representative of advanced combustion engines. New experimental data are first reported in the RCM at an equivalence ratio of 0.4, pressure of 60 bar and temperatures from 702 to 795 K for a research grade, multi-component gasoline surrogate, termed PACE-20. Here, experiments confirm the existence of MSHR for PACE-20 at all temperatures, and reveal the strong inhibiting effect of temperature on MSHR, where increasing temperature inhibits MSHR by suppressing first stage heat release and promoting second and third stage heat release. A detailed chemical kinetic model is also adopted to model the experiments, with good agreement observed. The response of MSHR characteristics to changes in different engine operating parameters (i.e., temperature, pressure, equivalence ratio and CO 2 dilution level) and fuel compositions (i.e., mole fraction of n-pentane, n-heptane, isooctane, cyclopentane, 1-hexene, ethanol and aromatics in PACE-20) is further evaluated via statistical analysis coupling quasi-random sampling, extensive computer experiments and high-dimensional model representation. The change in MSHR is characterized through 8 quantities of interest (QOIs), i.e., duration and extent of each heat release stage, and their standard deviations. The analysis highlights the dependence of the QOIs on the individual parameters as well as their interplays, with temperature exhibiting the strongest impact among all parameters. Furthermore, it is demonstrated that if MSHR is to be facilitated and combustion phasing is to be extended to enable engine operation at higher compression ratios, it is recommended to operate the engine at low intake temperatures, boosted intake pressures and high CO 2 dilutions (i.e., high EGR levels) with gasoline fuels containing more n-pentane and less aromatics.

42 ENGINEERING↗
DOE OSTI2023

Evaluating the sustainability of the 2017 US biofuel industry with an integrated techno-economic analysis and life cycle assessment

The United States produced more than 66.2 billion Liters of biofuel, primarily in the form of corn ethanol (61 billion Liters) and soybean biodiesel (6 billion Liters), for the transportation industry in 2017. No work currently exists that evaluates both the economic and environmental outcomes of this industry with adequate geospatial resolution and national scope. In this study, a model framework is constructed to perform Techno-Economic Analysis and Life Cycle Assessment using high-resolution input datasets to provide a granular estimation of corn ethanol and soybean biodiesel sustainability performance in most counties in the United States in 2017 (the most recent year for which data is available). Results show a total life cycle, greenhouse gas emission volume of 99.5 million Mg CO 2-eq produced in 2017 by these two biofuels (94.8 million Mg from corn ethanol, and 4.7 million Mg from soybean biodiesel), excluding indirect land use change emissions. Further, this volume corresponds to a combined carbon intensity of 65.3 gCO 2-eq /MJ, which is a greenhouse gas improvement compared to petroleum-based gasoline (the carbon intensity of conventional gasoline is 93.0 gCO 2-eq /MJ). However, these biofuels are produced at an additional economic cost ($1.8 billion over the displaced gas/diesel). Additionally, these biofuels generate unfavorable impacts in other environmental categories when compared to petroleum-based fuels, particularly in areas of water, land, and nitrogen intensity. This work enables stakeholders to assess the specific value of biofuels as a means of emission reduction and determine if the attained improvements are worth the associated opportunity costs.

09 BIOMASS FUELS↗
DOE OSTI2023

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstraction by $CH_3O\dot{O}$ radicals

Hydrogen atom abstraction by methyl peroxy ($CH_3O\dot{O}$) radicals can play an important role in gasoline/ethanol interacting chemistry for fuels that produce high concentrations of methyl radicals. Detailed kinetic reactions for hydrogen atom abstraction by $CH_3O\dot{O}$ radicals from the components of FGF-LLNL (a gasoline surrogate) including cyclopentane, toluene, 1-hexene, n -heptane, and isooctane have been systematically studied in this work. Here, the M06-2X/6-311 ++ G(d,p) level of theory was used to obtain the optimized structure and vibrational frequency for all stationary points and the low-frequency torsional modes. The 1-D hindered rotor treatment for low-frequency torsional modes was treated at M06-2X/6-31G level of theory. The UCCSD(T)-F12a/cc-pVDZ-F12 and QCISD(T)/CBS level of theory were used to calculate single point energies for all species. High pressure limiting rate constants for all hydrogen atom abstraction channels were performed using conventional transition state theory with unsymmetric tunneling corrections. Individual rate constants are reported in the temperature range from 298.15 to 2000 K. Our computed results show that the abstraction of allylic hydrogen atoms from 1-hexene is the fastest at low temperatures. When the temperature increases, the hydrogen atom abstraction reaction channel at the primary alkyl site gradually becomes dominant. Thermodynamics properties for all stable species and high-pressure limiting rate constants for each reaction pathway obtained in this work were incorporated into the latest gasoline surrogate/ethanol model to investigate the influence of the rate constants calculated here on model predicted ignition delay times.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Co-Hydrotreatment of Yellow Greases and the Water-Insoluble Fraction of Pyrolysis Oil. Part I: Experimental Design to Increase Kerosene Yield and Reduce Coke Formation

Here, this paper reports the co-hydrotreatment of Biomass Technology Group commercial pyrolysis oil water-insoluble (WIS) phase (also known as pyrolytic lignin) and yellow greases (waste cooking oil), aiming to produce sustainable aviation fuels (SAFs). We use a sulfided NiMo/Al 2 O 3 blend with 16 wt % WIS and a central composite experimental design to identify processing conditions increasing kerosene yield and reducing coke formation. The input variables were: (1) reaction temperature (320, 350, and 380 °C), (2) initial hydrogen pressure (5, 6, and 7 MPa), and (3) amount of catalyst (0.7, 1.0, and 1.3 g). The hydrotreated oily phases were distilled to obtain gasoline (<150 °C), kerosene (150–250 °C), diesel (250–350 °C), and residual oil (>350 °C). The reaction temperature is the main factor affecting the yield of gaseous, solid, and liquid products. Meanwhile, a higher initial hydrogen pressure and catalyst loading increased the yield of kerosene and other distillates and decreased the coke formation. A high temperature correlated with a lower content of oxygenates in kerosene cuts. Based on our experimental results, we propose to conduct hydrotreatment studies at 380 °C, initial H 2 pressure of 7 MPa, and 1.3 g of catalyst. Under the identified conditions, it was possible to improve the kerosene yield to more than 20 wt % and reduce the yield of coke to close to 2.0 wt %. The chemical composition and fuel properties of the gasoline, kerosene, and diesel cuts were thoroughly analyzed. The content of aromatics and phenols in the kerosene fraction produced at the conditions identified in this project exceeded the recommended values for SAFs. New strategies (such as blending and more intense hydrotreatment to remove oxygenated compounds) need to be implemented to reduce the content of these molecules in our final product.

09 BIOMASS FUELS↗
DOE OSTI2024

Co-hydrotreatment of Bio-oil and Waste Cooking Oil to Produce Transportation Fuels

This paper reports the co-hydrotreatment of the heavy bio-oil fraction with waste cooking oil (WCO) using NiMo/γ-Al 2 O 3 catalyst, followed by the distillation of resulting deoxygenated oil and the characterization of resulting fuel cuts. The heavy BTG bio-oil fraction was obtained by removing the very reactive light-oxygenated compounds via rotary evaporation, subsequently mixed with 1-butanol. The resulting oil was blended with WCO and subjected to a two-step co-hydrotreatment process. The first step, called “stabilization,” is aimed at saturating highly reactive hydrogen-deficient compounds. The second step, called “deoxygenation,” aimed to remove bio-oil oxygen, primarily as H 2 O. This study examined the impact of varying bio-oil concentrations (0, 10, 20, 30, 40 wt.% of WCO) on the upgraded oil's yield, composition, and fuel properties. The resulting hydrotreated oil was distilled into gasoline-range, kerosene-range, and diesel-range hydrocarbons at <150 °C, 150 to 250 °C, and 250 to 350 °C, respectively. The yield of the hydrotreated oil indicates that as the bio-oil concentration increases, the amounts of coke (0.7 to 2.4 %) and water (2 to 10 wt. %) increase while the organic layer yields decrease (80 to 63 %). The coke yield was comparable to the coke yield obtained when co-processing the pyrolytic lignin fraction. This suggests that coke is formed from both the sugar oligomers and the lignin-derived oligomers. The UV-fluorescence analysis on the hydrotreated oil shows that more polycondensed and conjugated ring compounds formed as the bio-oil concentration is increased. These compounds are precursors of coke. FTIR results showed that most raw materials were converted to biofuels after the hydrotreatment. To achieve less than 1 wt. % of coke yield, blends with up to 20 wt. % pyrolysis oil should be used. An increase in bio-oil concentration leads to a slight increase in gasoline yield and a decrease in kerosene and diesel yields. The identified carbon species found in the fuel cuts include n-paraffin, iso-paraffin, cycloparaffin, and aromatics. Further, the jet fuel cut (kerosene) was characterized by density, surface tension, and viscosity. Our product conforms to the standard specifications for sustainable aviation fuels (Jet A-1). Further research is suggested to fine-tune the operating parameters for achieving reduced coke yield and enhanced kerosene yield.

09 BIOMASS FUELS↗
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 OSTI2023

Gas and Propane Combustion from Stoves Emits Benzene and Increases Indoor Air Pollution

Exposure pathways to the carcinogen benzene are well-established from tobacco smoke, oil and gas development, refining, gasoline pumping, and gasoline and diesel combustion. Combustion has also been linked to the formation of nitrogen dioxide, carbon monoxide, and formaldehyde indoors from gas stoves. To our knowledge, however, no research has quantified the formation of benzene indoors from gas combustion by stoves. Across 87 homes in California and Colorado, natural gas and propane combustion emitted detectable and repeatable levels of benzene that in some homes raised indoor benzene concentrations above well-established health benchmarks. Mean benzene emissions from gas and propane burners on high and ovens set to 350 °F ranged from 2.8 to 6.5 μg min –1 , 10 to 25 times higher than emissions from electric coil and radiant alternatives; neither induction stoves nor the food being cooked emitted detectable benzene. Benzene produced by gas and propane stoves also migrated throughout homes, in some cases elevating bedroom benzene concentrations above chronic health benchmarks for hours after the stove was turned off. Combustion of gas and propane from stoves may be a substantial benzene exposure pathway and can reduce indoor air quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗
DOE OSTI2025

Equitable Urban Electric Vehicle Charging: Feasibility and Benefits of Streetlight Charging in Kansas City Right-of-Way

With an increasing global emphasis on sustainability, electric vehicles (EVs) play a crucial role in reducing urban pollution and carbon emissions. For EVs to be widely adopted, equitable and convenient access to charging infrastructure is essential. Equity in this paper refers to the proactive engagement with the community to ensure that the benefits of streetlight charging are distributed equitably across diverse neighborhoods in Kansas City, providing fair charging opportunities and resources to all community members. This research explores the potential of utilizing streetlights—ubiquitous elements of urban electrical infrastructure—as low-cost, equitable EV charging solutions. Compared with conventional chargers, streetlight charging offers several notable advantages, including proximity to roadways, potential boosts to the local economy, and easier usage due to city ownership. These chargers also leverage existing power setups to minimize costs and maximize efficiency by reutilizing existing structures. In this manuscript, we introduce a systematic framework to develop, analyze, and evaluate a scalable and cost-effective streetlight charging solution. Initially, we employ a two-tiered site selection framework that accounts for both charging demand and equity considerations to identify optimal locations for streetlight chargers. We then assess the feasibility of these chargers through observational data from 23 units installed in Kansas City, Missouri, comparing their performance with traditional chargers. Here, our evaluation extends to the environmental impact, comparing reduced gasoline consumption and greenhouse gas (GHG) emission reductions between streetlights and regular charging stations. Our findings reveal that streetlight charging stations offer faster charging speeds than conventional stations, validating their viability for EV charging. Additionally, the duration of stay at streetlight chargers tends to be shorter, likely due to parking constraints or associated costs. Furthermore, streetlight-powered chargers demonstrate considerable environmental advantages, achieving 11.94% greater avoided gasoline consumption and 11.24% higher GHG reductions compared with regular charging stations, highlighting their substantial environmental benefits.

42 ENGINEERING↗
DOE OSTI2023

Global warming intensity of biofuel derived from switchgrass grown on marginal land in Michigan

Energy crops for biofuel production, especially switchgrass (Panicum virgatum), are of interest from a climate change perspective. Here, we use outputs from a crop growth model and life cycle assessment (LCA) to examine the global warming intensity (GWI; g CO 2 MJ –1 ) and greenhouse gas (GHG) mitigation potential (Mg CO 2 year –1 ) of biofuel systems based on a spatially explicit analysis of switchgrass grown on marginal land (abandoned former cropland) in Michigan, USA. We find that marginal lands in Michigan can annually produce over 0.57 hm 3 of liquid biofuel derived from nitrogen-fertilized switchgrass, mitigating 1.2–1.5 Tg of CO 2 year –1 . About 96% of these biofuels can meet the Renewable Fuel Standard (60% reduction in lifecycle GHG emissions compared with conventional gasoline; GWI ≤37.2 g CO 2 MJ –1 ). Furthermore, 73%–75% of these biofuels are carbon-negative (GWI less than zero) due to enhanced soil organic carbon (SOC) sequestration. However, simulations indicate that SOC levels would fail to increase and even decrease on the 11% of lands where SOC stocks >>200 Mg C ha –1 , leading to carbon intensities greater than gasoline. Results highlight the strong climate mitigation potential of switchgrass grown on marginal lands as well as the needs to avoid carbon rich soils such as histosols and wetlands and to ensure that productivity will be sufficient to provide net mitigation.

09 BIOMASS FUELS↗
DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Evaluation of Spray and Combustion Models for Simulating Dilute Combustion in a Direct-Injection Spark-Ignition Engine

Dilute combustion in spark-ignition engines has the potential to improve thermal efficiency by mitigating knock and by reducing throttling and wall heat losses. However, ignition and combustion processes can become unstable for dilute operation due to a lowered laminar flame speed, resulting in excessive cycle-to-cycle variability (CCV) of the combustion process. To compensate for the slower combustion in less reactive mixtures, a modified intake port geometry can be employed to generate a strong tumble flow in the cylinder and elevate turbulence levels around the spark plug, thereby promoting a faster transition to turbulent deflagration. Consequently, optimizing combustion chamber geometry and operating strategy is crucial to maximizing the benefits of using dilute combustion with enhanced in-cylinder turbulence across a wide range of operating conditions. Computational fluid dynamics (CFD) simulations can be utilized for virtual engine optimization tasks, but this would require the models to be truly predictive regarding the impact of changes to the engine design and operational parameters.In this study, multicycle large-eddy simulations (LES) are performed for a direct-injection spark-ignition engine to investigate the model performance in predicting engine combustion characteristics with respect to changes in the intake configuration. A tumble plate that blocks the lower part of the intake port inlet is used to vary the tumble. A set of CFD models that have been recently developed are employed, which takes into account the drag of nonspherical droplets, flash-boiling behavior of liquid sprays, spray-wall interaction, surrogate formulation of a research-grade E10 gasoline, and fast chemical kinetic solvers. Simulation results are compared to experimental engine data in terms of cylinder pressure, apparent heat release rate, mass fraction burned timing, and flame images. It is found that LES employing the state-of-the-art CFD models are capable of properly predicting the spray processes and reproducing the measured mean cylinder pressure for the case with the tumble plate. On the other hand, the LES over-predicts the combustion rate during the early combustion stage and under-estimates the CCV, and these discrepancies become larger when the tumble plate is removed.

computational fluid dynamics simulation↗