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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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Rapid prediction of fuel research octane number and octane sensitivity using the AFIDA constant-volume combustion chamber

Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S>12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%-40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.

33 ADVANCED PROPULSION SYSTEMS↗

Enhancing $\phi$-sensitivity of ignition delay times through dilution of fuel-air mixture

The high $\phi$-sensitivity (η) of ignition delay time (τ IDT ) is one of the desirable fuel properties for the high-load extension of advanced compression ignition engine. Recent studies revealed the effectiveness of a high dilution rate (x D ) for enhancing η at the engine-relevant conditions. This study aims to quantify the effect of dilution on the η of isooctane using a combined experiment-simulation approach. The ignition delay of the isooctane/air mixture was measured with an Advanced Fuel Ignition Delay Analyzer (AFIDA) over the temperature range of 623 - 923 K at 10 bar pressure with global $\phi$ = 0.3 - 0.6, with and without 28.6% of additional N 2 dilution. For precise evaluation of experimental η, the facility effect of the AFIDA experiment was characterized with three-dimensional computational fluid dynamics (3-D CFD) simulation. The temperature in the combustion chamber from 3-D CFD indicated a substantial temporal dependency, varying up to ~52 K by charge-cooling of fuel injection and heat transfer from the wall. We introduced the dimensionless number θ(t) for characterizing the temporal profile of chamber temperature. Consideration of the facility effect using θ(t) resulted in better agreement between the experimental ..eta.. and zero-dimensional (0-D) kinetics simulation. The refined η were then further utilized to quantify the effectiveness of dilution to η The extent of η enhancement with dilution strategy was maximized at the low-temperature chemistry regime, increasing η by 77% with a 28.6% dilution rate. Further analysis on the dilution effect was carried out using 0-D kinetics simulation, revealing the critical dimensionless numbers relevant to the effectiveness of dilution to η enhancement. Here, this study is the first experiment-simulation combined research to quantify the effect of dilution on η, facilitating the kinetics model refinement for better reproduction of $\phi$-sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗

Validation of Octane Hyperboosting Phenomenon in Prenol and Structurally Related Olefinic Alcohols

Hyperboosting is a recently discovered phenomenon in which the research octane number (RON) of a blend is higher than both the neat blendstock and the neat fuel it was blended into. RON is a measure of a fuel's resistance to knock, and knock is a cause of engine inefficiency. Blends which exhibit hyperboosting are blends in which an overall improvement in engine efficiency may be expected. The first discovery of hyperboosting came from blending experiments in which prenol was blended into several different base fuels. Here, ignition delay time (IDT) measurements taken using a commercially available constant volume combustion chamber called the Advanced Fuel Ignition Delay Analyzer (AFIDA) are presented. The data show that some prenol blends have longer IDTs (lower reactivity) than either neat prenol or the base fuel, providing further evidence of hyperboosting. Additionally, more blending data is presented in which the base fuel is varied, which allows for a better understanding of hyperboosting sensitivity to chemical classes. The data indicate that aromatics may inhibit, and branched alkanes may enhance the magnitude of hyperboosting observed. Enthalpy of vaporization estimates are also given for several molecules which are blended into a 4-component surrogate. These estimates are derived from Equation of State simulations and reveal that there is no observable correlation between hyperboosting and enthalpy of vaporization. Blending data for molecules which share structural similarities with prenol are also presented. Structure property relationships are suggested, in which the double bond motif of prenol seems to play an important role in hyperboosting. This may help to understand hyperboosting and its underlying mechanism. Lastly, blending curves of surrogate blends with prenol experienced hyperboosting under lean (Homogeneous Charged Compression Ignition-HCCI) operating conditions, which validates that hyperboosting is not an artifact of the octane test methods, but inherent to the properties of prenol.

ADVANCED PROPULSION SYSTEMS↗

Understanding how chemical structure affects ignition-delay-time $\phi$-sensitivity

$\phi$-sensitivity is the change in ignition delay time (IDT) with respect to the fuel-to-air equivalence ratio ($\phi$). High $\phi$-sensitivity is a desirable fuel property for applications in advanced compression ignition and multi-mode engine designs. Understanding how $\phi$-sensitivity depends on chemical structure is essential for selecting promising biofuels from the ever-growing list of proposed candidates. Here, we investigate the effect of chemical structure on $\phi$-sensitivity with experiment, simulation, and theory. Experimental Advanced Fuel Ignition Delay Analyzer (AFIDA) measurements for 2,4-dimethylpentane and diisopropyl ether provide evidence that branching and functional groups strongly impact $\phi$-sensitivity. Further insights into this dependence are obtained with 0-D kinetic simulations with existing mechanisms for n-pentane, diethyl ether, 3-pentanone, n-heptane, 2-methylhexane, 2,4-dimethylpentane, and 2,2,3-trimethylbutane. Quantum mechanical (QM) G4 calculations of low-temperature reactions help explain the observed experimental and simulation trends. Specifically, these QM calculations provide theoretical estimates of the ketohydroperoxide (KHP) dissociation rates, the HO 2 formation rates from peroxy radical (ROO), and the “cross-over” temperatures, i.e., the temperature at which ROO dissociation is favored compared to hydroperoxyl radical (QOOH) formation. Each of these reaction rates is compared to the n-alkane reference point to determine the impact of branching and different functional groups. Although kinetic mechanisms typically assume that KHP dissociation rates are invariant of chemical environment, our QM results suggest that this rate can span a range of roughly two orders of magnitude. We also discuss the importance of including the peroxy-hydroperoxy (OO-OOH) hydrogen transfer reaction for branched ethers. Finally, the insights gained assist in proposing a highly $\phi$-sensitive compound, namely, isopropyl propyl ether.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding fundamental effects of biofuel structure on ignition and physical fuel properties

The development of biochemicals and biofuels with advantaged properties of higher combustion efficiency at lower emission levels can be aided by a priori prediction of critical global characteristics based on molecular structure. Existing predictive techniques are incomplete for comprehensive ignition and physical fuel property prediction. Here this investigation focuses on filling this knowledge gap by developing a priori prediction techniques for predicting important ignition as well as physical fuel properties of promising advantaged biofuels. We demonstrate the utility of this a priori prediction technique on saturated (≤C 5 ) alcohols, both linear and branched in nature by correlating their molecular structure with both important ignition and physical properties of the fuels. This work utilizes a semi-automated method of predicting ignition characteristics via accurate fundamental-based calculations of the fuel radical cascades that govern low-temperature combustion. This numerical methodology is supported by the relevant fuel ignition delay time (IDT) and research octane number (RON) data experimentally measured by the Advanced Fuel Ignition Delay Analyzer (AFIDA). Phyiscal fuel property trends are also analyzed by correlating the molecular structure of the fuel to its physical characteristics. Based on their molecular structure, recommendations are made on an a priori method for selecting biofuels that have advantaged properties for the selected fuel application. Lastly, the utility of this investigation is extended beyond the subset of alcohols considered by analyzing the IDT trends of i-Pentanol and n-Hexanol, revealing the fidelity of the novel kinetic modelling approach and the accuracy of the predicted trends in this study.

09 BIOMASS FUELS↗

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

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

97 MATHEMATICS AND COMPUTING↗

Comparing Cetane Number Measurement Methods

Cetane number is one of the most important fuel performance metrics for mixing controlled compression-ignition “diesel” engines, quantifying a fuel’s propensity for autoignition when injected into end-of-compression-type temperature and pressure conditions. The historical default and referee method on a Cooperative Fuel Research (CFR) engine configured with indirect fuel injection and variable compression ratio is cetane number (CN) rating. A subject fuel is evaluated against primary reference fuel blends, with heptamethylnonane defining a low-reactivity endpoint of CN = 15 and hexadecane defining a high-reactivity endpoint of CN = 100. While the CN scale covers the range from zero (0) to 100, typical testing is in the range of 30 to 65 CN. Alternatively, several constant-volume combustion chamber (CVCC)-based cetane rating devices have been developed to rate fuels with an equivalent derived cetane number (DCN) or indicated cetane number (ICN). These devices measure ignition delay for fuel injected into a fixed volume of high-temperature and high-pressure air to simulate end-of-compression-type conditions. In this study, a range of novel fuel compounds are evaluated across three CVCC methods: the Ignition Quality Tester (IQT), Fuel Ignition Tester (FIT), and Advanced Fuel Ignition Delay Analyzer (AFIDA). Resulting DCNs and ICNs are compared for fuels within the normal diesel fuel range of reactivity, as well as very high (~100) and very low DCNs/ICNs (~5). Distinct differences between results from various devices are discussed. This is important to consider because some new, high-efficiency advanced compression-ignition (CI) engine combustion strategies operate with more kinetically controlled distributed combustion as opposed to mixing controlled diffusion flames. These advanced combustion strategies may benefit from new fuel chemistries, but current rating methods of CN, DCN, and ICN may not fully describe their performance. In addition, recent evidence suggests ignition delay in modern on-road diesel engines with high-pressure common rail fuel injection systems may no longer directly correlate to traditional CN fuel ratings. Simulated end-of-compression conditions are compared for CN, DCN, and ICN and discussed in the context of modern diesel engines to provide additional insight. Results highlight the potential need for revised and/or multiple fuel test conditions to measure fuel performance for advanced CI strategies.

47 OTHER INSTRUMENTATION↗

Effect of the ..beta..-Hydroxy Group on Ester Reactivity: Combustion Kinetics of Methyl Hexanoate and Methyl 3-Hydroxyhexanoate

One of the major biofuels used today is biodiesel, composed of fatty acid methyl esters. The fats and oils feedstocks used to make biodiesel are in relatively short supply. To meet increasing global demand, engineered microorganisms have been developed to catalyze conversion of sugar to fatty acid esters that contain unique ..beta..-hydroxy-esters. This study investigated the effect of a hydroxyl group on the combustion characteristics of methyl esters by comparing the chemical behavior of methyl hexanoate (MHx) and methyl 3-hydroxyhexanoate (M3OHHx) - used as surrogates for diesel-boiling-range esters with longer fatty acid chains. The oxidation of these esters was studied experimentally in a flow reactor at 0.84 and 10 bar, 600 to 1,100 K, and stoichiometric conditions; and in a constant volume combustion chamber at 5 and 10 bar, 600 to 900 K, and equivalence ratios of 0.3 and 0.6. MHx was more reactive in the constant volume chamber at temperatures below 800 K at 10 bar and equivalence ratio of 0.6. MHx also exhibited a higher indicated cetane number (16.4) than M3OHHx (8.1). We investigated this reactivity trend using an updated MHx kinetic model and M3OHHx model developed as part of this work. The kinetic models predicted that radicals formed from MHx were consumed by low-temperature chemistry reactions, whereas the M3OHHx reactivity was significantly governed by the ..beta..-radical (on the same carbon as the OH group) chemistry which mainly terminated via the less reactive chain propagation pathway to methyl-3-oxohexanoate + HO2. This study extends our understanding of structural effects on ester reactivity, which will allow for accurate surrogate formulation and performance simulations.

AFIDA↗

Fuel Properties and Kinetics

The Co-Optimization of Fuels and Engines (CoOptima) program is focused on a two-pronged approach to develop new, lower net-carbon fuels and advanced engine technologies in tandem. This effort brings nine national labs and several university and industry partners together to simultaneously identify new fuel candidates and to further engine technology development in the light-, medium-, and heavy-duty vehicle sectors with a focus on fuel economy and emission reduction. The fuel properties and kinetics project is aimed at achieving a better understanding of fuel property kinetics and how they impact engine performance such that more efficient and lower emitting engines can be made a reality. Several promising biofuel candidates were identified through tiered screening approaches and were evaluated utilizing unique bench-scale measurement techniques. Kinetic models were developed to describe autoignition and soot pre-cursor formation mechanisms to identify the most promising candidates that advanced various combustion strategies.

ADVANCED PROPULSION SYSTEMS↗