Surrogate Mixtures Research Articles

Soot and Flame Structures in Turbulent Partially Premixed Jet Flames of Pre-Evaporated Diesel Surrogates with Admixture of OMEn

In this study, the soot formation and oxidation processes in different turbulent, pre-evaporated and partially premixed diesel surrogate flames are experimentally investigated. For this purpose, a piloted jet flame surrounded by an air co-flow is used. Starting from a defined diesel surrogate mixture, different fuel blends with increasing blending ratios of poly(oxymethylene) dimethyl ether (OME) are studied. The Reynolds number, equivalence ratio, and vaporization temperature are kept constant to ensure the comparability of the different fuel mixtures. The effects of OME addition on flame structures, soot precursors, and soot are investigated, showing soot reduction when OME is added to the diesel surrogate. Using chemiluminescence images of C2 radicals (line of sight) and subsequent Abel-inversion, flame lengths and global flame structure are analyzed. The flame structure is visualized by means of planar laser-induced fluorescence (PLIF) of hydroxyl radicals (OH). The spatial distribution of soot precursors, such as polycyclic aromatic hydrocarbons (PAHs), is simultaneously measured by PLIF using the same excitation wavelength. In particular, aromatic compounds with several benzene rings (e.g., naphthalene or pyrene), which are known to be actively involved in soot formation and growth, have been visualized. Spatially distributed soot particles are detected by using laser-induced incandescence (LII), which allows us to study the onset of soot clouds and its structures qualitatively. Evident soot formation is observed in the pure diesel surrogate flame, whereas a significant soot reduction with changing PAH and soot structures can be identified with increasing OME addition.

An improved manifold-projection trajectory based method for chemical kinetic mechanism reduction

An improved manifold-projection trajectory based dimension reduction algorithm (MTDR) to automatically generate skeletal chemical kinetic mechanisms was proposed and validated in this study. This algorithm is implemented by constructing an approximate manifold-based trajectory of the combustion system using Euclidean distances between two adjacent points and cosine similarities between two adjacent vectors in the manifold space, and then evaluating the importance of species by calculating the error of manifold-based trajectories before and after the projection of the manifold. In this method, the nature of the combustion system is well reflected since the combustion process information can be captured by the location of the state point in the manifold space. The calculation during the reduction process is simplified by using the manifold-based trajectory instead of the complex differential equations. Compared to our previous work, this study improves the prediction accuracy of the reduced mechanisms through a more comprehensive error evaluation in the mechanism reduction process. The detailed mechanisms of fuels including iso-cetane, iso-octane and gasoline surrogate mixtures of toluene, iso-octane and n-heptane were reduced to portray the prowess of the algorithm. It’s demonstrated that the number of species of the fuels is reduced from 492, 254 and 1389 to 95, 87 and 427 within an acceptable error, respectively. Meanwhile, the case of iso-octane mechanism reduction was chosen to compare the performance of MTDR with traditional methods including path flux analysis (PFA) and directed relation graph with error propagation and sensitivity analysis (DRGEPSA), and it is shown that the MDTR can generate more compact mechanism under a broad range of error limits.

A Reduced Kinetics Model for the Oxidation of Transcritical/Supercritical Gasoline Surrogate/Ethanol Mixtures Using Real Gas State Equations

ABSTRACT Efforts to combat the harmful effects of vehicle emissions on our environment and health include exhaust emissions and fuel efficiency regulations. One promising solution is direct fuel injection in supercritical conditions, where the fuel mixture is above critical temperature and pressure. This study presents a reduced kinetics mechanism (129 species and 1015 reactions) utilizing real gas equations to simulate the combustion of supercritical/transcritical gasoline surrogate/ethanol blends. It was developed by combining two reduced models – a Toluene reference fuel (TRF) with a Diisobutylene (DIB) and an ethanol model – and validated through simulations of ignition delay time (IDT). The Arrhenius parameters of key reactions for each fuel component were modified to improve accuracy. An adjusted Redlich-Kwong cubic state equation was employed to segregate each surrogate mixture tested as supercritical, transcritical, or subcritical. The new mechanism was then validated against experimental results using high-pressure conditions and the cubic Peng-Robinson and Redlich-Kwong equation of state parameters. Critical properties of each species were obtained through Joback’s Group Method and the Ambrose-Walton vapor pressure equation. The TRF/DIB/E mechanism results were consistent with shock tube experimental data at high pressure, indicating a potential for modeling combustion in ultra-high pressure direct injection engines.

Dispersal of high-burnup fuel fragment surrogate particles during and after loss-of-coolant accident tests

The issue of fuel fragmentation, relocation, and dispersal is critical in the licensing and use of high-burnup (>62GWd/MTU) nuclear fuel in light water reactors (LWRs). In this work, two test series are reported that examine the fragment dispersal during a burst event and an additional dispersal following the burst due to vibrations in the rod, such as those induced by accident recovery systems. To examine dispersal during the balloon and burst portion of a Loss-of-Coolant Accident event, HfO2 fragments and yttria-stabilized zirconia pellets were filled into an as-fabricated cladding tube, which was then pressurized and subjected to loss-of-coolant accident testing in steam. Results from this test were found to be highly non-prototypic, and dispersal was both significantly more violent and significantly greater in magnitude than identified for actual fuel tests. These findings were attributed to the conservative (more dispersive) nature of the particles chosen for dispersal and to the details of the test conditions used that led to particularly wide bursts. The second set of tests examined dispersal following the burst when vibrations were induced in the rod, primarily via recovery activities such as Emergency Core Cooling System actuation leading to rapid water addition. Post-burst dispersal testing was performed by inducing sinusoidal oscillations with 2–25 nm peak-to-peak amplitude and 2–5 Hz frequencies in pre-burst rods that had been refilled with HfO2 fragments or high-burnup fragment surrogate mixture of HfO2 fragments and yttria-stabilized zirconia sands. Testing revealed that rods with large burst openings (7 mm wide in this work) led to unmitigated dispersal from above the burst zone but that smaller bursts (5 mm wide), although still much larger than the mean fragment size of 3 mm, led to effectively no dispersal because of interparticle locking. Additionally, mixture and moisture were found to impact the amount of dispersal: mixtures increased dispersal, and moisture drastically reduced it. The implications of these findings on likely dispersal from actual fuel are discussed.

Hydrodeoxygenation of lignin bio-oil model compounds and surrogate mixtures over zeolite supported nickel catalysts

Bifunctional catalysts based on nickel supported on ZSM-5 and BETA zeolites were studied in the hydrodeoxygenation of lignin derived model compounds as well as in surrogate mixtures simulating the light fraction of lignin fast pyrolysis bio-oil. A screening of the hydrodeoxygenation reaction conditions (temperature, time, H2 pressure, catalyst amount) was carried out using the simplest phenolic compound, phenol. As in real lignin bio-oils more complex phenolic compounds are present, a series of relevant alkyl- and methoxy-substituted phenol and benzene (o- and m-cresol, catechol, anisole, guaiacol, syringol, creosol and 1,2,3-trimethoxybenzene) were also investigated as feedstocks. Furthermore, the effect of the different porous and acidic properties of the zeolitic supports was investigated in the hydrodeoxygenation of guaiacol. The conversion of the model phenolics and the yield of the respective (alkyl)cyclohexanes at relatively mild conditions (220 °C, 50 bar H2, 1 h) were in the range of 80–100% and 47–83%, respectively, being dependent mainly on the complexity/side-chain group of the phenolic/benzylic ring and on the balanced content of Brønsted acid sites of increased strength. Regarding the hydrodeoxygenation of the surrogate mixture (C7-C10 phenolics), 100% hydrodeoxygenation efficiency was achieved towards >60% yield of (alkyl)cyclohexanes (C6-C9 hydrocarbons). All hydrodeoxygenation tests were conducted in hexadecane as solvent/substrate in order to simulate model co-processing (i.e. bio-based phenolics with petroleum derived feedstocks) conditions. Reusability tests revealed the stability of the catalysts which showed partial (30%) deactivation after the third catalytic cycle.

Use of Artificial Neural Network to Develop Surrogates for Hydrotreated Vegetable Oil with Experimental Validation in Ignition Quality Tester

<div>This article presents surrogate mixtures that simulate the physical and chemical properties in the auto-ignition of hydrotreated vegetable oil (HVO). Experimental investigation was conducted in the Ignition Quality Tester (IQT) to validate the auto-ignition properties with respect to those of the target fuel. The surrogate development approach is assisted by artificial neural network (ANN) embedded in MATLAB optimization function. Aspen HYSYS is used to calculate the key physical and chemical properties of hundreds of mixtures of representative components, mainly alkanes—the dominant components of HVO, to train the learning algorithm. Binary and ternary mixtures are developed and validated in the IQT. The target properties include the derived cetane number (DCN), density, viscosity, surface tension, molecular weight, and volatility represented by the distillation curve. The developed surrogates match the target fuel in terms of ignition delay and DCN within 6% error range. This investigation will be of value to developing high-fidelity models to investigate HVO combustion and spray behavior. This will be beneficial to researchers advancing the design and development of compression ignition engines to efficiently operate on renewable fuels such as HVO.</div>

Experimental and kinetic modeling of soot formation in counterflow non-premixed flames of surrogate fuel components: n-dodecane and iso-dodecane

Normal dodecane (n-C12) and iso-dodecane (i-C12) are often used as components for surrogate mixtures of aviation and diesel fuels. Although studies have been performed to understand the combustion and spray behavior of dodecane isomers, the soot formation from the combustion of n- and i-C12 in non-premixed flames is not well studied. In this work, soot volume fraction (SVF) profiles of n- and i-C12 were measured across a wide range of strain rates and mixture conditions in a counterflow burner facility at the University of Connecticut. Neat and binary mixtures of n- and i-C12 were investigated to study the influence of alkane branching on soot formation. A soot model was developed and validated in this study by extending the detailed kinetic model developed at the Lawrence Livermore National Laboratory (LLNL) for the formation of polycyclic aromatic hydrocarbons (PAHs) to simulate soot formation and growth based on the discrete sectional method. Additional gas phase reactions forming pyrene and ring enlargement reactions were added to the existing PAH model. The LLNL kinetic model was validated with SVF data obtained in this work for n-C12 and i-C12 flames along with data available in literature for ethylene, iso-butene, n-heptane, and iso-octane. The soot precursor reactions added in this work were found to play a critical role in simulating the experimentally observed non-linear trend of the peak SVF with increased branched alkanes. Reaction path analysis was conducted to illustrate the fuel structure effects on soot formation pathways in n- and i-C12 mixtures. In view of the satisfactory agreement between modeling results and experimental data, as well as capturing the non-linear variation in peak SVF with the alkane branching for the first time, further investigation within the framework of the soot model is discussed and critical insights are provided into the reaction pathways which require further attention.

Speed of sound measurements and derived thermodynamic properties of bio-jet fuel components at saturation: N-butylcyclohexane

The composition of bio-jet fuels, i.e., the total content of hydrocarbons such as n-alkanes, iso-alkanes, cycloalkanes and aromatics, reached 85 % to 95 %, are mainly defining the thermophysical properties of bio-jet fuels. Short-chain cycloalkanes, such as n-butylcyclohexane, are one of the main components of bio-jet fuel. N-butylcyclohexane is included as one of the components of diesel fuel surrogate mixture. Therefore, more information on n-butylcyclohexane thermophysical properties in surrogate mixtures is required. In the present work the speed of sound in n-butylcyclohexane at saturation in the temperature range from (276 to 456) K has been measured using the pulse method with a constant (acoustic) sounding base. The combined expanded absolute and relative uncertainties (0.95 level of confidence, k = 2) of the temperature and speed of sound measurements are estimated to be 20 mK and 0.2 %, respectively. The measured speed of sound data together with reported density data were used to calculate the derived thermodynamic properties (kS,kT, and CP/CV) of n-butylcyclohexane at saturation.

Development of a diesel surrogate for improved autoignition prediction: Methodology and detailed chemical kinetic modeling

While the surrogate fuel approach has been successfully applied to the simulation of the combustion behaviors of complex gasoline and jet fuels, its application to diesel fuels has been challenging. One of the main challenges derives from the large molecular size of the representative surrogate components necessary to simulate diesel blends, as the development of detailed chemical kinetic models and their validation becomes more complex. In this study, a new surrogate mixture that emulates the chemical and physical properties of a well-characterized diesel fuel is proposed. An optimization procedure was used to select surrogate components that can match both the physical and chemical properties of the target diesel fuel comprehensively. The surrogate fuel mixture composition was designed to have fuel properties (e.g., boiling point, cloud point, etc.) that enable its use in future diesel engine experiments. A detailed kinetic model for the surrogate fuel mixture was developed by combining well-validated sub-mechanisms of each surrogate component from Lawrence Livermore National Laboratory. The ability of the surrogate mixture and kinetic model to emulate ignition delay times was assessed by comparing the simulated results with measurements for the target diesel fuel. Comparison of the experimental and simulated ignition delay times shows that the current surrogate mixture and kinetic model well capture the autoignition response of the target diesel fuel at varying conditions of pressure, temperature, oxygen concentration, and fuel concentration. The current study is one of the first to demonstrate the efficacy of detailed chemical kinetics for diesel range fuels by assembling validated sub-mechanisms for palette compounds and successfully simulating the autoignition characteristics of a target diesel fuel. The experimental ignition delay times of diesel measured with a rapid compression machine, the surrogate mixture, and the kinetic model developed shall aid in progress of understanding diesel ignition under engine relevant conditions.

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵ turbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

The impact of navy jet fuel (JP-5) and diesel fuel (F-76) on the swelling and tensile strength of additivity-manufactured and commercially-manufactured O-rings

This work explored the effect of military jet (JP-5) and diesel (F-76) fuels, surrogate mixtures, and pure compounds on the swelling and tensile strength of additively-manufactured (AM) acrylate O-rings and commercially-produced acrylate, nitrile, and Ford Motorcraft O-rings. The composition of the fuel was determined using two-dimensional gas chromatography (GC × GC) and the uptake of the organic compounds from surrogate mixtures into the AM O-rings was determined using gas chromatography. Exposure of the O-rings to various organic mixtures for 7 days produced volume changes that ranged from −3 to 155% for AM O-rings, 0 to 130% for commercial acylate O-rings, 1 to 260% for Buna-N O-rings, and −4 to 3% for Ford Motorcraft O-rings. The greatest swellings were found for the aromatic compounds followed by the cycloalkanes. JP-5 and F-76 fuels caused the AM O-rings to swell by 15.2 and 11.6%, respectively. A jet fuel surrogate containing 10% dodecane, 51% isocetane, 15% butylbenzene and 24% butylcyclohexane produced a similar swell (14.9%) to that of the JP-5, which contained 10.9% aromatics, 5.6% cycloaromatics, and 25% cycloalkanes. Diesel fuel surrogates containing 1-methylnapthalene produced much higher swells in the AM polymers (greater than 22%) than did the diesel fuel, illustrating that while this component may be good for enabling diesel surrogates to emulate the physical and combustion properties of diesel fuel, it also comes with increased swelling. Tensile strengths of the swollen O-rings were reduced by as much 90%. Evaporation of the fuels and components from the O-rings for more than 3 weeks returned most of the O-rings to their original size and tensile strength, suggesting that the short-term exposure did not adversely affect the O-rings.

Effect of thermal dynamics and column geometry of pressure swing adsorption on hydrogen production from natural gas reforming

The present study investigates hydrogen purification from a surrogate gas using spent coffee grounds as a medium. The study was conducted using Aspen adsorption software, and the process was examined under isothermal, adiabatic, and non-adiabatic conditions. The surrogate gas mixture comprised 70% hydrogen and 30% carbon dioxide and was introduced into two stainless steel chambers containing the coffee media. The pressure was altered from 101.3 to 150 kPa as the chamber underwent the adsorption process. At an adsorption time of 60 s, all three conditions exhibited similar levels of purity and recovery, with the isothermal mode producing the highest values. Additionally, the effect of heat dissipation and column geometry on the adsorption performance was investigated by comparing the conventional isothermal column with the rectangular non-adiabatic plate column. The plate column is rectangular, with two chambers that use the heat generated during adsorption to regenerate the opposite column during the blowdown step. This effect was evaluated under different adsorption times of 30–180 s and hydrogen feed concentrations of 70–90%. The plate column had higher hydrogen purity and recovery of 99.99% and 77.41%, respectively, compared to 99.56 and 71.12% of the cylindrical column. Overall, the results indicate that spent coffee grounds can be effectively used as a medium to purify hydrogen from a surrogate gas mixture. A rectangular non-adiabatic plate column can further enhance the purification process by improving purity and recovery responses.

Advances in PAH mixture toxicology enabled by zebrafish.

Polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds produced by a variety of petrogenic and pyrogenic sources. PAHs inherently occur in the environment in complex mixtures. The early life-stage zebrafish model is a valuable tool for high-throughput screening (HTS) for toxicity of complex chemical mixtures due to its rapid development, high fecundity, and superb sensitivity to chemical insult. Zebrafish are amenable to exposure to surrogate mixtures as well as extracts of environmental samples and effect-directed analysis. In addition to its utility to HTS, the zebrafish has proven an excellent model for assessing chemical modes of action and identifying molecular initiating and other key events in an Adverse Outcome Pathway framework. Traditional methods of assessing PAH mixture toxicity prioritize carcinogenic potential and lack consideration of non-carcinogenic modes of action, assuming a similar molecular initiating event for all PAHs. Recent work in zebrafish has made it clear that while PAHs belong to the same chemical class, their modes of action can be divergent. Future research should use zebrafish to better classify PAHs by their bioactivity and modes of action to better understand mixture hazards.

Laminar flame speed measurements of a gasoline surrogate and its mixtures with ethanol at elevated pressure and temperature

Laminar Flame speed measurements of a gasoline surrogate and mixtures of it with ethanol were conducted using a heated, constant-volume vessel. A spherical propagating flame was observed using a high-speed camera, and laminar flame speed was determined therefrom. The gasoline surrogate, which serves as the baseline for the current study, consisted of four components, namely, iso-octane, n-heptane, toluene, and 1-hexene. Different mixtures of the gasoline surrogate and ethanol were studied, governed by the ethanol percentage in the mixture. That is, E0, E30, E50, and E85 mixtures represent 0%, 30%, 50%, and 85% ethanol in the gasoline surrogate mixture by liquid volume, respectively. Initial temperatures of 335, 359, and 408 K and initial pressures of 1 and 3 bar were investigated. The findings of this study are compared to results in the literature, which show good agreement for E0 but some deviation for the E30 blend. In general, the study showed an increase in laminar flame speed as the ethanol percentage increases in the mixture. Similarly, increasing the initial temperature with fixed ethanol percentage resulted in an increase in laminar flame speed, as expected. In contrast, increasing the initial pressure with fixed Ethanol percentage showed a decrease in laminar flame speed. Finally, the results are compared to an existing chemical kinetics model designed for ethanol and gasoline. Although agreement between the model and data is reasonable and mostly within about 10%, some improvement to the kinetics model is needed to uniformly lower the calculated flame speeds.

Landfill gas upgrading using amine-functionalized silica sorbents

ABSTRACT Separation of acid gases such as CO2 from biogas is a key step for its purification before biomethane is used in various applications such as injection into a pipeline or use as a vehicle fuel. In this study, the single step purification of real biogas (locally collected landfill gas) was demonstrated using (3-Aminopropyl) triethoxysilane (APTES)-grafted SBA-15. The sorbent was optimized between amine amount and accessibility to adsorption sites. In studies using a surrogate mixture of CH4/CO2 the sorbent recorded an adsorption capacity of 0.85 mmolCO2/gads under dry conditions and this decreased to 0.72 mmolCO2/gads when the surrogate biogas was saturated with steam. Even though the capacity was further decreased to 0.55 mmolCO2/gads using real landfill gas, it remained fairly stable over 5 cycles despite the presence of impurities, namely hydrogen sulfide (68 ppm). In all cases, the capacity was regenerated with a thermal treatment in inert gas at 100°C. The results suggested possibilities for a single step purification unit to remove acid gasses and water and provide potential for a streamlined operation for the separation of carbon dioxide from biogas. The enhanced economics should propel the move toward a green energy future.

On the super adiabatic flame temperature (SAFT) of toluene primary reference fuels

Toluene primary reference fuel (TPRF) mixtures containing iso-octane (i-C8H18), n-heptane (n-C7H16), and toluene (C6H5CH3) are commonly used as gasoline surrogates. We report the occurrence of super adiabatic flame temperature (SAFT) during the premixed combustion of TPRF mixtures in air. Both 1-D premixed flame and 0-D (well-stirred) reactor configurations have been considered for chemical kinetic analysis with Cantera version 2.5.1. A recently developed detailed gasoline surrogate mechanism (C3MechV3.3) has been used for the 0-D reactor analysis. On the other hand, the flame structures have been simulated with a skeletal mechanism. To ensure accurate analysis, the mechanisms used in this work have been validated at SAFT relevant conditions against experimental data from literature. For the first time in literature, post-flame heat release and brute force reaction sensitivity analysis have been performed to identify important reactions contributing towards SAFT in TPRF surrogates. The degree of superadiabaticity for 1-D and 0-D cases have been expressed with non-dimensional parameters ξ1D and ξ0D respectively. The results show that ξ1D and ξ0D increase with the increase in iso-octane content in TPRF compositions, while n-heptane and toluene have minor influence on SAFT. Key chemical observations to the SAFT mechanism in gasoline surrogate mixtures include: 1) The competition between the exothermic reaction zone and the endothermic post-flame region causes SAFT. 2) Both 1-D flame and 0-D reactor analysis show that the reactions involving H, OH, and C3 species have major influence on SAFT. 3) Iso-octane augments SAFT as its β-scission product iso-butene (i-C4H8) influences the post-flame endothermicity and C3 species formation.

An experimental auto-ignition and kinetic modelling study of binary and ternary cyclopentane/toluene/diisobutylene/iso-octane mixtures

Ignition delay times are measured for binary mixtures of cyclopentane/toluene, cyclopentane/2,4,4-trimethylpent-1-ene and ternary mixtures of cyclopentane/iso-octane/toluene, cyclopentane/iso-octane/2,4,4-trimethylpent-1-ene. The experiments are performed using a high-pressure shock tube and a rapid compression machine for stoichiometric mixtures in ‘air’, in the temperature range of 650 – 1450 K and at pressures of 25 and 40 bar. A detailed chemical kinetic model is used to simulate the experimental ignition delay times. It has been formulated using NUIGMech1.2 as the base chemistry to which has been added cyclopentane, iso-octane, 2,4,4-trimethylpent-1-ene and toluene sub-mechanisms from the literature. This work provides valuable insights into the reactivity of the blending behaviour of toluene, iso-octane and 2,4,4-trimethylpent-1-ene with cyclopentane. The model is used to understand the chemical influence of these fuels on the reactivity of cyclopentane. Reaction path and sensitivity analyses of each of the cyclopentane blends using the combined mechanism are performed and these are discussed. Our analysis furthers the understanding of binary (naphthene/aromatic, naphthene/olefin) and ternary (naphthene/iso-alkane/olefin and naphthene/iso-alkane/aromatic) mixtures and helps improve the development of predictive models for multi-component gasoline surrogate mixture blends.

Derived cetane number prediction of jet fuels and their functional group surrogates using liquid phase infrared absorption

Derived cetane number (DCN) is an important fuel property relevant to ignition in compression ignition engines. The measurement of IR spectra of neat liquid fuels along with robust models for DCN potentially opens pathways for DCN sensing using miniaturized sensors for engine control. For neat liquid fuels, there are practical measurement difficulties because of strong absorption features in the mid-infrared. This study assesses the viability of using subsets of the IR spectrum, primarily 2400–800cm−1, which contains the fingerprint region, for generating models for DCN. IR absorption spectra in the liquid phase and associated DCNs were experimentally collected on a dataset including some real jet fuels, hydrocarbon components that span the range of chemical functional groups encountered in those jet fuels, and mixtures of those components. Four machine learning models were used to evaluate the association of liquid IR absorption over different spectral ranges to fuel DCN. Non-linear models, including Convolutional Neural Networks performed excellently. Regions likely to exhibit saturation can be excluded without problems in generating models. A spectral resolution of 14 cm−1 appears to be optimal for measurements. There is no loss in accuracy in limiting the modeling only to the 2400–800 cm−1 region. Although only a few real fuel mixtures were assessed in this way, models were able to yield good predictions for these fuels, even though the model was trained primarily on simpler surrogate mixtures exhibiting the same chemical functional groups.

Assessment of hydrocarbons for gasoline surrogate: An optimization study

A fuel surrogate is a model fuel that replicates combustion phenomena of real transportation fuels within computational framework. Successful surrogate formulation would be emulating multiple physical and chemical properties that are most influential to combustion characteristics using a minimum number of surrogate components. To achieve this goal, utilization of hydrocarbons with proper representation of actual constituents of real fuels is one of the most critical requirements. The major goal of this paper is to identify hydrocarbons that have a great potential to advance the current gasoline surrogates in terms of emulations in hydrocarbon class composition and combustion related properties, and to promote further experimental and computational investigations for those hydrocarbons. In this paper, 19 hydrocarbons including the ones that have not been used for gasoline surrogate applications are assessed through an optimization approach. Surrogate mixtures are formulated for petroleum-derived gasoline fuels using new hydrocarbons along with conventional gasoline surrogate components (n-heptane, iso-octane, toluene, 1-hexene), and potential improvements in target property emulations by addition of the new surrogate components are evaluated. Among four hydrocarbon classes investigated in this study which are iso-alkane, cycloalkane, aromatic, and olefin, optimized results indicate that expanding iso-alkane representation by using multiple iso-alkane components with different molecular size is the most effective approach to emulate various target properties of typical gasoline batches. Also, among 19 new hydrocarbons tested, 2-methylbutane appears to be a favorable option for a small iso-alkane, 2,2,3,3-tetramethylhexane for a large iso-alkane, cyclopentane for a cycloalkane, and 1,2,4-trimethylbenzene for a large aromatic. With a new surrogate palette that includes these promising hydrocarbons, surrogate mixtures are formulated for 5 different batches of gasoline, which shows capabilities to emulate composition characteristics and target properties tested, including knock resistance and distillation curve.

Experimental and modeling approach for the optimization of oily water recovered from fast pyrolysis of woody biomass

Woody biomass consists of wood chips, leaves, branches, stems etc. They contain highest weight percentage of oily water compared to any other biomass. On woody biomass’ fast pyrolysis, high percentage of FPBO is obtained with char/ash, pyrolytic gases and oily water in considerable amount. The focus of this research is to obtain an optimized temperature at which the oily water recovered from biomass after fast pyrolysis is highest without much affecting the generation of bio-oil. The weight percentage of oily water recovery is affected by several factors- vapor residence time, condensation temperature, operating temperature and moisture content. The weight percentage of oily water is approximately 10.62% with 56.41% of bio-oil generation. The result is obtained at a temperature of 550 °C, further to which increase in oily water content started decreasing the bio-oil generation with very fast rate. This experimental result is analyzed, a surrogate mixture on various assumptions is prepared and a model is prepared using UNIFAC. There is a slight difference in weight percentage of oily water on experimental and modeling approach due to the ageing of surrogate mixture and assumptions in modeling.