Multi-component Surrogate Research Articles

Development of multi-component surrogate fuel for marine diesel considering fuel physical-chemical properties

Herein, as an alternative to heavy fuel oil (HFO), a multi-component surrogate fuel was developed, consisting n-tetradecane (6.36 %), n-hexadecane (4.25 %), i-hexadecane (20 %), n-eicosane (15 %), decalin (17 %), toluene (4.45 %), naphthalene (13 %), and phenanthrene (19.94 %). The proportions of the components of the surrogate fuel were determined by studying the chemical and physical characteristics of HFO. The surrogate fuel was optimized by matching the cetane number (CN), density at 20 °C, lower heating value (LHV), and hydrogen-carbon (H/C) ratio. The developed skeletal surrogate mechanism constituted 128 species and 375 reactions. It was extensively validated using various fundamental experiments based on its single components and HFO performance under relevant engine conditions. The predicted ignition delay time in shock tubes and the concentrations of primary species in jet stirred reactors and flow reactors were in good agreement with the previously measured values. The predicted laminar flame speed in counterflow configuration was close to the experimental data. The flame spray and combustion characteristics were found to be well produced by the proposed mechanism in a fuel ignition analyzer and a two-stroke marine diesel engine. The proposed skeletal mechanism exhibited reliable overall performance for combustion behavior, indicating that it can be used for modeling HFO in realistic engine applications.

An experimental and kinetic modeling study on low-temperature oxidation of gasoline and diesel/polyoxymethylene dimethyl ether (OME3) blends

In this work, the low-temperature oxidation of polyoxymethylene dimethyl ether (OME3) with multi-component surrogates for diesel (DS:60%n-heptane/20%cyclohexane/20%toluene) and gasoline (GS:20%n-heptane/60%iso-octane/20%toluene) blends was investigated respectively using a jet-stirred reactor (JSR) with a temperature range of 500–950 K, constant fuel fraction of 0.008, residence time (τ) of 2 s and near atmospheric pressure. Two detailed multi-component kinetic mechanisms were established to describe the low-temperature oxidation characteristics and the interaction of blended fuels. Generally, the oxidation process of highly-reactive OME3 and n-heptane is inhibited, while that of inactive fuels, including iso-octane, cyclohexane and toluene, are triggered and enhanced in various degrees in the blends. The OH radical acts as a bridge between high and low reactivity components. It is of interest that n-heptane reveals a quite different low-temperature oxidation behavior in diesel (DS) and gasoline (GS) surrogate respectively. In GS, the low-temperature oxidation of n-heptane is significantly inhibited, while in DS, the inhibition is mild, mainly due to the much different low-temperature oxidation characteristics of iso-octane and cyclohexane. As for OME3, it mainly improves the reactivity of the blends in the negative temperature coefficient (NTC) process. As for low-reactivity fuels of iso-octane and toluene, their low-temperature oxidations are completely triggered and dominated by highly-reactive fuels due to their weak OH build-up ability. On the contrary, when the low-temperature oxidation of cyclohexane is triggered, its self-enhancement also plays a crucial role in addition to the promoting effect from highly-reactive fuels. Therefore, cyclohexane reveals a promoting-ignition effect on the blended fuels, while iso-octane and toluene act as an inhibiting-ignition factor in blends.

Predictions of NOx and SOx in MILD regime based on thermal conversion of solid sewage sludge surrogates

Thermal treatment of sewage sludge using a combination of gasification and combustion of the producer gas is an attractive option to produce sterilized high-notorious bio-char and recover energy from the feedstock. Given the high temperature of the producer gas after gasification, employing the MILD (Moderate or Intense Low Oxygen Dilution) combustion regime in the second stage might benefit the heat balance of the process and result in low emissions. The current work employs multi-component surrogates derived from solid fuel samples of various ultimate elemental compositions and moisture content, a stochastic reactor model for gasification, and a 1D counterflow diffusion flame configuration for combustion with a dedicated, detailed chemical mechanism. Using an improved methodology for emission measurement, we analyzed the combustion emissions of the wet producer gas from gasification, which includes fuel-NO precursors, sulfur components, and tar species up to a size of C11. The analysis confirms that thermal and fuel-NO emissions are reduced in the MILD regime. While high moisture content in the feedstock has been shown to enhance the formation of the pollutant via identified chemical pathways, different representations of fuel samples (ultimate composition) are found to have a significantly more considerable impact on the overall SOx and NOx emissions. The more sulfur is contained in the ultimate composition of the solid surrogate fuel, the more SOX is formed in the combustion stage. This direct relation does not hold for NO. The NO emissions in MILD combustion are the lowest in the performed simulations for the highest amount of fuel-bonded nitrogen. This is caused by the key role of the fuel-NO precursor ammonia (NH3) and its radicals that act in NO formation but also are a driving force in NO reduction. Given this key role of specific fuel-NO precursors, it is further highlighted that there is a significant difference in predicting NO, depending on the complexity of the fuel-NO precursors in the boundary condition of the flame calculation.

Replicating HCCI-like autoignition behavior: What gasoline surrogate fidelity is needed?

This work seeks to characterize the fidelity needed in a gasoline surrogate with the intent to replicate the complex autoignition behavior exhibited within advanced combustion engines, and specifically Homogeneous Charge Compression Ignition (HCCI). A low-temperature gasoline combustion (LGTC) engine operating in HCCI mode and a rapid compression machine (RCM) are utilized to experimentally quantify fuel reactivity, through autoignition and preliminary heat release characteristics. Fuels considered include a research grade E10 U.S. gasoline (RD5-87), three multi-component surrogates (PACE-1, PACE-8, PACE-20), and a binary surrogate (PRF88.4). Each fuel was studied at lean/HCCI-like conditions covering a wide range of temperatures and pressures that are representative of naturally aspirated to high boost engine operation. Detailed chemical kinetic modeling is also undertaken using a recently updated gasoline surrogate kinetic model to simulate the RCM experiments and to provide chemical insight into surrogate-to-surrogate differences.The LGTC engine experiments demonstrate nearly identical reactivity between PACE-20 and RD5-87 across studied conditions, while faster phasing is seen for both PACE-1 and PACE-8 due to their stronger intermediate- and low-temperature heat release (ITHR/LTHR) at naturally aspirated and boosted conditions, respectively. The RCM experiments reveal typical low-temperature, negative temperature coefficient (NTC) and intermediate-temperature autoignition behaviors at all pressure conditions for RD5-87, which are qualitatively reproduced by all surrogates. Quantitative discrepancies in both autoignition and preliminary heat release are observed for all surrogates, while their ability to replicate RD5-87 autoignition behavior follows the order of PACE-20 > PACE-1 > PACE-8 > PRF88.4. Excellent mapping is obtained between the LGTC engine and the RCM, where the engine pressure-time trajectories can be characterized by the regimes represented by the RCM autoignition isopleths. The kinetic model performs commendably when simulating both autoignition and preliminary heat release of PACE-20, while typically overpredicting ignition delay times for PACE-1, PACE-8 and PRF88.4 at high-pressure and low-temperature/NTC conditions. Sensitivity and rate of production (ROP) analyses highlight surrogate-to-surrogate differences in the governing chemical kinetics where n-pentane initiates rapid OH branching at a faster rate and an earlier timing for PACE-20 than iso-pentane does for PACE-1 and PACE-8, making it computationally more reactive than the other surrogates. The current study highlights the need to include non-standardized properties, such as the lean/HCCI-like autoignition characteristics, in addition to ASTM properties (e.g., RON, MON) as metrics of fuel reactivity and targets to be matched when formulating high-fidelity surrogates that fully capture gasoline advanced combustion behavior such as HCCI-like autoignition.

Investigation of Engine Combustion and Auto-ignition of a Multicomponent Surrogate Fuel with NTC Behavior Under Knocking Conditions

The occurrence of knocking combustion is limiting the efficiency of modern spark ignition engine operation. Thus, an understanding of the processes at the knock limit is required for further optimization of the combustion process. In this work, the combustion of a multicomponent Toluene Reference Fuel (TRF) in a single-cylinder research engine is investigated under knocking conditions. The fuel exhibits a negative temperature coefficient (NTC) regime for thermodynamic conditions relevant to the engine operation. A precursor model is used to capture the auto-ignition process. Under homogeneous conditions, a two-stage auto-ignition is observed. Inside the NTC regime, the temperature affects both first-stage and second-stage auto-ignition delay times. With a subsequently conducted multi-cycle engine LES, the effects of temperature stratification and turbulent flame propagation on the local auto-ignition process are investigated. It is observed, that the NTC behavior leads to a widespread two-stage auto-ignition. The knock intensity observed in the experiments is directly related to the mass consumed by auto-ignition. This is due to the fast consumption of the auto-ignited mass by the flame front. With that, the NTC behavior affects the local auto-ignition process in the unburned mixture while the flame propagation determines the knock intensity for the operating conditions at the knock limit.

Impact of Multi-Component Surrogates on the Performances, Pollutants, and Exergy of IC Engines.

Even though there is a pressing interest in clean energy sources, compression ignition (CI) engines, also called diesel engines, will remain of great importance for transportation sectors as well as for power generation in stationary applications in the foreseeable future. In order to promote applications dealing with complex diesel alternative fuels by facilitating their integration in numerical simulation, this paper targets three objectives. First, generate novel diesel fuel surrogates with more than one component. Here, five surrogates are generated using an advanced chemistry solver and are compared against three mechanisms from the literature. Second, validate the suggested reaction mechanisms (RMs) with experimental data. For this purpose, an engine configuration, which features a reacting spray flow evolving in a direct-injection (DI), single-cylinder, and four-stroke motor, is used. The RNG k-Epsilon coupled to power-law combustion models is applied to describe the complex in-cylinder turbulent reacting flow, while the hybrid Eulerian-Lagrangian Kelvin Helmholtz-Rayleigh Taylor (KH-RT) spray model is employed to capture the spray breakup. Third, highlight the impact of these surrogate fuels on the combustion properties along with the exergy of the engine. The results include distribution of temperature, pressure, heat release rate (HRR), vapor penetration length, and exergy efficiency. The effect of the surrogates on pollutant formation (, , ) is also highlighted. The fifth surrogate showed 47% exergy efficiency. The fourth surrogate agreed well with the maximum experimental pressure, which equaled 85 Mpa. The first, second, and third surrogates registered 400, 316, and 276 g/kg fuel, respectively, of the total CO mass fraction at the outlet. These quantities were relatively higher compared to the fourth and fifth RMs.

Spray Combustion Characteristics of Single/Multicomponent Surrogate Fuel for Aviation Kerosene

Abstract In this research, n-dodecane and world-average jet fuel (JW) are selected as single and multicomponent surrogate fuel of aviation kerosene to study the Jet-A spray combustion characteristics. The spray combustion phenomena are simulated using large eddy simulation coupled with detailed chemical reaction mechanism. Proper orthogonal decomposition method is applied to analyze the flow field characteristics, and the instantaneous velocity field is decomposed into four parts, namely, the mean part, coherent part, transition part, and turbulent part, respectively. The four parts have their own characteristics. In terms of different fuels, JW has a higher intensity of coherent structures and local vortices than n-dodecane, which promotes the fuel–air mixing and improves the combustion characteristics, and the soot formation is significantly reduced. In addition, with the increase of initial temperature, the combustion is more intense, the ignition delay time is advanced, the flame liftoff length is reduced, and soot formation is increased accordingly.

Investigation on the ignition delay prediction model of multi-component surrogates based on back propagation (BP) neural network

The ignition delay prediction model of three-component surrogates was established based on the back propagation (BP) neural network. The ambient temperature, ambient pressure, molar fraction of n-heptane, iso-octane and toluene were utilized as the input parameters. The ignition delay was utilized as the output parameter. The training and validation set only contained the 0-D simulation ignition delay of single- and two-component surrogates. But the trained BP neural network also showed a strong predictive ability towards the ignition delay of three component toluene primary reference fuel (TPRF) surrogates. Results show that the BP neural network with two hidden layers performs better than that with single hidden layer. With the optimization of genetic algorithm (GA) and particle swarm optimization (PSO) algorithm, the correlation coefficient is higher than 0.9996. The mean relative error (MRE) and the mean square error (MSE) are also maintained at a low level. The computational costs of 0-D simulation and BP neural network methods are compared. In 0-D simulation, the computational time of one case is 28 s. When the BP neural network is utilized, the computational time of 176 cases is just 3.2 s, which shows a significant improvement in the computation time. Through the mean impact value (MIV) analysis, the significance of each input variable to the output results is investigated. The input parameters of ambient temperature and molar fraction of iso-octane obtain the highest and lowest absolute value of MIV, respectively, indicating the major and minor effects on the ignition delay. Based on the predicted ignition delay of three-component TPRF surrogates, the research octane number (RON) and motor octane number (MON) can also be accurately predicted with the maximum deviance no more than 3 units. For real fuels of fuels for advanced combustion engines (FACE) gasolines, such as FACE A and FACE C gasolines, the surrogate fuel which has the same ignition delay at the specific pressure and temperature can be determined through the construction of the ignition delay look-up table of TPRF surrogates by the BP neural network. Following this method, the ignition delay of the real fuels can be matched accurately and the molar fraction of each component of the corresponding TPRF surrogates can also be acquired.

Modelling liquid film in modern GDI engines and the impact on particulate matter emissions – Part 1

This paper presents the details of a Computational Fluid Dynamics methodology to accurately model the process of mixture preparation in modern Gasoline Direct Injection engines, with particular emphasis on liquid film as one of the main causes of Particulate Matter formation. The proposed modelling protocol, centred on the Bai-Onera approach of droplets-wall interaction and on multi-component surrogate fuel blend models, is validated against relevant published data and then applied to a modern small-capacity GDI engine, featuring centrally-mounted spray-guided injection system. The work covers a range of part-load, stoichiometric and theoretically-homogeneous operating conditions, for which experimental engine data and engine-out Particle Number measurements were available. The results, based on the parametric variation of start of injection timing and injection pressure, demonstrate how both fuel mal-distribution and liquid film retained at spark timing, may contribute to PN emissions, whilst their relative importance vary depending on operating conditions and engine control strategy. Control of PN emissions and compliance with future, more stringent regulations remain large challenges for the engine industry. Renewed and disruptive approaches, which also consider the sustainability of the sector, appear to be essential. This work, developed using Siemens Simcenter CFD software as part of the Ford-led APC6 DYNAMO project, aims to contribute to the development of a reliable and cost-effective digital toolset, which supports engine development and diagnostics through a more fundamental assessment of engine operation and emissions formation.

Development of a multi-component surrogate fuel model of marine diesel engine

A fuel combustion mechanism was developed based on a multi-component surrogate fuel composed of n-tetradecane, toluene, methylcyclohexane (MCH), and ethanol, the four most common components of real diesel fuel. A decoupling methodology was used to develop the new surrogate fuel mechanism. The developed surrogate fuel model includes 97 species and 386 reactions. The accuracy of new mechanism was obtained by comparing with experiment data in shock tube, counterflow configuration and marine engine. The comparison results of the simulations and experiment were shown in this paper for ignition delay times (IDT). The deviations of calculations were within accepting error for n-tetradecane, toluene, methylcyclohexane, and ethanol respectively. The laminar flame speed was an important parameter to validate the accuracy of the mechanism. The variation trends were the same as the experimental results. The revised mechanism was coupled with computational fluid dynamic (CFD) to simulate the combustion of a marine engine. The influence of surrogate fuel components ratios were investigated based on the CFD model. The prediction results well coincided with the experimental results of in-cylinder pressure of the marine engine. However, the ratios of components in the surrogate fuel have large effect on the formation of NOx emissions, especially the content of n-tetradecane. The results suggest that the multi-component surrogate fuel mechanism is suitable for simulating the diesel combustion.

Unraveling the octane response of gasoline/ethanol blends: Paving the way to formulating gasoline surrogates

Ethanol is widely used as a gasoline octane booster, and yet, its blending response is not fully understood. Blending ethanol with gasoline most often leads to a synergistic effect (higher than expected relative to linear blending), but can also lead to a linear or antagonistic blending (lower than expected relative to linear blending). To address the knowledges gap in ethanol blending, this study provides new research octane number (RON) and motor octane number (MON) measurements of ethanol blended with various gasoline surrogates. The first set of blends are ternary mixtures, designed to study the interactions between primary reference fuels (PRFs) and certain gasoline components when blended with ethanol. These gasoline components are 1-hexene, 1,2,4-trimethylbenzene and cyclopentane, which, represents the olefin, aromatic and naphthenes classes in commercial gasoline fuels, respectively. The second set represents multicomponent surrogates for Fuels for Advanced Combustion Engines (FACE) gasolines, developed in our previous work (Badra et al., Applied Energy 2017 p. 778-793). This study developes an octane blending model of ethanol/gasoline surrogates that utilize the new measurements along with datasets available in literature. The model consists of the conventional linear by ethanol molar fraction correlation, with the addition of non-linearity terms that depend on base fuel properties, namely, the octane sensitivity and the mole fraction of gasoline components. The model can predict the octane numbers (RON and MON) of blends containing gasoline surrogates composed of n-heptane, n-pentane, iso-octane, iso-pentane, toluene, 124-trimethylbenzene, cyclopentane, cyclohexane (for RON only) and 1-hexene. To ensure the generality of the developed model and avoid over-fitting, the model is trained using 85% of the available dataset while the remaining measurements have been used to test the model. The proposed model outperforms many ethanol blending models available in literature with 87% of the RON and 83% of the MON measurements being within the reproducibility limits. This model can be integrated to the process of designing gasoline surrogates that contain ethanol.

A combustion model for multi-component fuels based on relative reactivity and molecular structure

A reliable multi-component surrogate fuel model needs to be able to represent both physical properties and chemical kinetics of a real fuel. However, enhancing the fidelity of a model with detailed description of physical and chemical behavior of all fuel components found in real fuels is limited by the prohibitive computational load to calculate the combustion chemistry of the fuel. Hence, it is desirable to achieve computational efficiency by reducing the number of chemical surrogates at the minimum expense of prediction accuracy. The objective of this work is to develop a model that can simulate the oxidation of multi-component fuels by representing the ignition characteristics of physical surrogate components with fewer chemical surrogates and achieve both computational efficiency and prediction accuracy. The main advantage of the model, called the Reactivity-Adjustment (ReAd) combustion model, is to accurately predict the reactivity of the physical surrogate components that the reaction mechanisms of which are not included in the reaction kinetics model employed in the simulation. The reactivity variation of local mixtures with different compositions is modeled by adjusting the reaction rate constants of selected control-reactions in the reaction mechanism of the representative chemical surrogates. An initial version of the model has been developed employing a single chemical surrogate to represent the combustion of diesel fuel which is modeled as multiple surrogate components to capture the physical properties of the real fuel. The model was extended to consider two more chemical surrogate components to represent the ignition characteristics of other chemical families than n-alkanes. This enabled to avoid the excessive adjustment of reaction rate constants that were necessary when a single chemical surrogate is used to represent the oxidation kinetics of entire multi-component fuels. The model was extensively tested for simulating oxidation processes of many fuels with a variety of fuel reactivity and in various combustion regimes. The results demonstrated that excellent accuracy of the ignition/combustion prediction was achieved while ensuring computational efficiency.

Implementation of multi-component diesel fuel surrogates and chemical kinetic mechanisms for engine combustion simulations

Recent developments have led to the formulation of multi-component surrogates that closely match physical and chemical properties of diesel fuels. These surrogates have been characterized and extensively tested in constant pressure vessels as well as engine experiments. The adoption of such surrogates in simulations is an important step towards predictive engine simulations. However, significant challenges remain in adoption of such surrogates. The complex chemical kinetics associated with a multi-component fuel leads to an extremely large and stiff chemistry mechanism with thousands of species. Such chemistry mechanisms are prohibitive to be directly used in engine simulations using traditional solvers due to the excessively-high computational cost. This work describes some of the experimental investigations of a 4-component diesel fuel surrogate in constant volume combustion chambers that provide useful validation datasets for numerical models. In addition, a chemical kinetic mechanism for the multi-component diesel surrogate with 1544 species is proposed. A previously validated unsteady flamelet model, accelerated by a sparse solver and analytical Jacobian, is used to implement large chemistry mechanisms for realistic diesel engine simulations. A flamelet solver is used to generate multi-dimensional unsteady flamelet libraries for the multi-component surrogate for a range of conditions. This approach is then used in a large eddy simulation (LES) framework to model combustion of the 4-component surrogate in a constant pressure spray vessel over a range of ambient oxygen conditions. The current chemistry mechanism and computational methodology can capture the two-step ignition delay as well as flame lift-off length trends observed in the experiments. Some of the low temperature combustion characteristics are analyzed in detail. The computational setup and the validation results demonstrate the feasibility of using these latest multi-component fuel surrogates for engine simulations by leveraging multi-dimensional chemistry tabulation methods.Highlights:1. Detailed experiments with the multicomponent V0A surrogate were carried out in the High Temperature Pressure Vessel facility.2. A detailed chemistry mechanism with 1544 species was developed for the V0A surrogate.3. The LSODES based flamelet tabulation method was used to implement and validate these high-fidelity surrogates and mechanisms in engine relevant LES calculations.

Evaluation of the surrogates capacity to reproduce the laminar burning velocities and the sensitivity to stretching of a commercial kerosene under constant volume combustion conditions

These last years, aircraft manufacturers and environmental international bodies have set drastic targets concerning turbo-engines pollution and consumption reduction. To reach the objectives of pollutant emission and consumption reductions, innovative solutions such as constant-volume combustion are in development. Characterizing the propagation of a kerosene-air flame in this kind of combustion is necessary. Particularly, the knowledge of fundamental properties like the laminar burning velocity in laminar adiabatic conditions can be useful for the design of efficient innovative turbo-engines.A new spherical combustion chamber developed in Institut PPRIME and the associated post-processing procedure are first validated using a n-decane/air premixed flame, and a good agreement is obtained with the literature. Measurements of laminar burning velocities and Markstein lengths of commercial kerosene/air mixture and kerosene surrogates/air are then performed at various temperatures (T0 = 400 K to 470 K), pressures (P0 = 0.1 MPa to 0.5 MPa) and equivalence ratios (Φ = 0.6 to 1.5). Two mono-component surrogates are tested as a representative of commercial kerosene (n-decane and n-dodecane), with two multi-component surrogates: the Dagaut surrogate (n-decane/n-propylbenzene/n-propylcyclohexane) and the MURI2 surrogate (n-dodecane/iso-octane/1,3,5-trimethylbenzene/n-propylbenzene). Additionally, numerical simulations of laminar burning velocities are performed using JetSurF 2.0 and the Luche reduced chemical kinetic mechanism, representing respectively mono-component surrogates and the Luche surrogate. They are able to represent correctly the experimental measurements. A comparison of the different employed surrogates with commercial kerosene is also performed to evaluate the ability of these surrogates to reproduce the laminar burning velocity properties of the commercial kerosene.

A functional-group-based approach to modeling real-fuel combustion chemistry – I: Prediction of stoichiometric parameters for lumped pyrolysis reactions

Real fuels are complex mixtures of hundreds of molecules, which makes it challenging to unravel their combustion chemistry. Several approaches in the literature have helped to clarify fuel combustion, including multi-component surrogates, lumped fuel chemistry modeling, and functional-group based methods. This work presents an innovative advancement to the lumped fuel chemistry modeling approach, using functional groups for mechanism development (FGMech). Stoichiometric parameters of lumped fuel decomposition reactions dictate the population of the key pyrolysis products, previously obtained by fitting experimental data of real-fuel pyrolysis. In this work, a functional group-based approach is proposed, which can account for real-fuel variability and predict stoichiometric parameters without experimentation. A database of the stoichiometric parameters and/or yields of key pyrolysis products was first constructed for approximately 50 neat fuels, based on previous pyrolysis data and a lumped kinetic model we developed. The effects of functional groups on the stoichiometric parameters and/or yields of key pyrolysis products were then identified and quantified. A quantitative structure-stoichiometry relationship was developed by multiple linear regression (MLR) model, which was used to predict the stoichiometric parameters and/or yields of key pyrolysis products based on ten input features (eight functional groups, molecular weight, and branching index). Products from the pyrolysis of surrogate mixtures and real-fuels were predicted using the MLR model and validated against experimental data in the literature. Comparison with the stoichiometric parameters from the HyChem experiment-based approach (Xu et al., 2018) showed that the predicted values in this work were in reasonable agreement (generally within a factor of two). When the stoichiometric parameters in the jet fuel (POSF 10325) HyChem kinetic model were replaced with this functional-group based prediction, only minor discrepancies were observed in the predictions of key pyrolysis products and global combustion parameters (such as ignition delay times and laminar flame speeds). Sensitivity analysis on stoichiometric parameters revealed their different roles in predicting speciation and global parameters. The functional group approach for predicting stoichiometric parameters in this work was the first step towards developing FGMech for modeling real-fuel combustion chemistry. Further development of the FGMech model's thermodynamic, kinetic, and transport data will be presented in a following study.

Ignition delay time measurements of diesel and gasoline blends

Blends of diesel and gasoline can be used to achieve certain desired ignition characteristics in advanced compression ignition engine concepts. In this work, ignition delay times were measured for two blends of diesel and gasoline in two shock tubes and in a rapid compression machine. These blends comprised of 50/50 and 25/75 volumetric% of diesel and gasoline, respectively. To ensure complete vaporization of the blends, the prepared samples were analyzed with nuclear magnetic resonance (NMR) and laser absorption. The analyses revealed full evaporation, and negligible decomposition/oxidation occurred during mixture preparation. Ignition delay measurements covered wide ranges of temperatures (710–1349 K), pressures (10 and 20 bar), and equivalence ratios (0.5, 1.0 and 2.0). The measured ignition delay times of the two dieseline blends are compared with experimental data of low- to mid-octane gasoline and low- to high-cetane fuels. The measured data are also compared with the simulated ignition delay times of primary reference fuel (PRF) and toluene primary reference fuels (TPRF) surrogates. Multi-component surrogates are proposed for the dieseline blends, and the measured ignition delays of the multi-component surrogates and the dieseline blends are in very good agreement.

Spatio-temporal identification of plume dynamics by 3D computed tomography using engine combustion network spray G injector and various fuels

Understanding of plume direction and mixture quality in a combustion chamber is crucial to improve engine performance. While a variety of diagnostics using laser and x-ray facilities have been applied to identify plume direction, most applications require sophisticated experimental setup as well as troubleshooting for light attenuation or scattering issues. In this study, we acquire temporally and spatially resolved liquid volume fraction by three-dimensional tomographic reconstruction of ensemble-averaged extinction images to produce unique information on plume movement and growth in the midst of a multi-plume spray. Measurements were carried out in a constant-flow spray vessel coupled with high-speed Mie-scattering, diffused back-illumination extinction, and schlieren imaging. Four different fuels, a single component iso-octane, a multi-component surrogate with di-isobutylene, a multi-component fuel with olefinic molecular structure, and a 70% standardized gasoline 30% ethanol (e30) blend were injected using Engine Combustion Network (ECN) Spray G injector under ECN G2 (50 kPa absolute), G3 (100 kPa absolute), and G3HT (G3 with 393 K ambient temperature) conditions. Planar slices, available from the tomographically reconstructed extinction data, confirmed greater plume-to-plume interaction for the flash-boiling G2 iso-octane condition with an approximately 6° smaller plume direction angle relative to the injector axis, compared to the nozzle drill angle. The olefinic and e30 fuels, which have broader distillation curves, exhibited stronger plume growth and eventual complete spray plume collapse and longer time for evaporation. Using the 3D dataset, we show that factors that increase plume growth also create more interaction between plumes to ultimately reduce the plume direction angle.

Performance of Naphtha in Compression Ignition Modes Using Multicomponent Surrogate Fuel Model

Gasoline compression ignition (GCI) engines have been considered a promising technology for achieving diesel-like efficiency with less NOx and soot emissions than diesel engines. In recent research, naphtha has emerged as a suitable fuel for GCI owing to its octane number and its potential to reduce CO2 and production costs. The present work develops a multicomponent surrogate fuel model for heavy and light naphtha fuels by matching their distillation profiles and covering the measured concentrations of the various hydrocarbon classes and properties. The developed naphtha multicomponent surrogate model shows better prediction results than the primary reference fuel (PRF) surrogate model and exhibits good agreement with the measured data. The performance of naphtha in compression ignition (CI) combustion modes is investigated using the surrogate model and engine experiments. Naphtha fuels under CI combustion modes show better soot, HC, and CO emissions than diesel owing to the longer ignition delay and higher burned gas temperature. Moreover, as naphtha fuels are less affected by the injection pressure, naphtha CI engines appear to operate at a lower injection pressure than diesel engines.

Development of a practical reaction model of polycyclic aromatic hydrocarbon (PAH) formation and oxidation for diesel surrogate fuel

A practical reaction model for the formation and oxidation of polycyclic aromatic hydrocarbons (PAHs) up to coronene (A7) was developed focusing on two diesel surrogate fuels, i.e., a single-component surrogate including n-heptane and a multi-component surrogate including iso-octane, n-decane, methylcyclohexane, and toluene, for engine simulations. The important PAH relevant reactions are identified by using the global sensitivity analysis of the up-to-date detailed mechanisms. In the reduced PAH reaction model, the up-to-date reaction channels involving PAH formation were considered, and the variations and characteristics of the formation pathways of benzene and large PAHs for large alkanes, aromatics, and cycloalkanes with the fuel molecular structure were captured with the present under wide operating conditions. By integrating the PAH reaction model with a reduced oxidation mechanism of the two diesel surrogates, the final chemical mechanism of diesel oxidation consists of 137 species and 447 reactions. The chemical mechanism was extensively validated against the fundamental experimental data including ignition delay times in shock tubes and species profiles in premixed laminar flames, diffusion flames, and jet-stirred reactors (JSR). The performance of the mechanism for the predictions of PAHs from the oxidation of individual component, their mixtures, and diesel fuel was comprehensively evaluated. The computational results indicate that the effect of fuel structure on the PAH formation is satisfactorily reproduced by the present mechanism. Based on pathway analysis in the premixed flame, the contribution of the components in the diesel surrogate for the PAH formation behavior is understood.

Quantitative measurements of preferential evaporation effects of multicomponent gasoline fuel sprays at ECN Spray G conditions

A two-tracer laser-induced fluorescence technique is used to quantify the effects of preferential evaporation of multicomponent fuels on the fuel component distribution. The technique is based on the simultaneous detection of the fluorescence of two aromatic tracers with complementary evaporation characteristics matched to different components of a multicomponent fuel. Relative variations in the spatial distribution of tracer distribution as a consequence of preferential evaporation are determined from the ratio of laser-induced fluorescence signals measured within two distinct spectral bands. A thermodynamic model is then used to relate the ratio map with the fuel component map. The accuracy and precision of the method are characterized from determining the laser-induced fluorescence signal ratio within two identical spectral bands. Measurements are performed in a high-pressure high-temperature vessel equipped with an eight-hole injector. The Engine Combustion Network Spray G target conditions are chosen as reference conditions at injection. The only difference with these target conditions is the use of a multicomponent surrogate fuel. Parametric variations around these target conditions are also performed in order to investigate their effect on the preferential evaporation effect. The ambient temperature is varied between 525 and 625 K and the injection pressure is reduced from 200 to 100 bar. The impact of ethanol addition is also studied with two different fuel mixtures in addition to the reference surrogate fuel: E20 and E85 which feature 20% and 85% of pure ethanol within surrogate, respectively. A significant preferential evaporation effect is observed in this condition representative of engine applications and results in a spatial segregation between low- and high-volatility fuel components, respectively, at the tail and tip of the plumes. This effect is enhanced by the addition of ethanol and the decrease in ambient temperature and injection pressure.