Combustion Engine Applications Research Articles

The laminar burning velocity of propyl acetate at high pressures and temperatures

Since propyl acetate has the potential to be used as a biofuel in heat engines, it is necessary to ascertain and comprehend its combustion properties. Using equivalence ratios of 0.7–1.4, the laminar burning velocity of propyl acetate was studied in the constant volume combustion vessel at the initial pressures of 1, 2, and 4 bar and initial temperatures of 390 K, 420 K, and 450 K. The constant volume method was used to determine the burning velocity via extrapolations at the initial condition. In addition, a ten-fitted empirical correlation was formulated to calculate the burning velocity for pressures and temperatures as high as 8 bar and 534 K, respectively. The extrapolated burning velocity showed good agreement with the numerical simulation burning velocity, and the correlated burning velocity agreed well with the extrapolated burning velocity. The laminar burning flux was also investigated and was ascertained that laminar burning flux increases as the initial pressure and temperature increase. The fuel mixture density significantly influences the burning flux as the initial pressure rises, whereas the laminar burning velocity has a notable impact on the burning flux as the initial temperature rises. In summary, this study advances our knowledge of propyl acetate combustion, particularly concerning its flame propagation at higher pressures and temperatures and its potential application in combustion engines, and the data are of great engineering value for developing and understanding the combustion science of propyl acetate.

Numerical analysis of the hydrogen-air mixture formation process in a direct-injection engine for off-road applications

Among the different hydrogen premixed combustion concepts, direct injection (DI) is one of the most promising for internal combustion engine (ICE) applications. However, to fully exploit the benefits of this solution, the optimization of the mixture preparation process is a crucial factor. In the present work, a study of the hydrogen-air mixture formation process in a DI H2-ICE for off-road applications was performed through 3D-CFD simulations. First, a sensitivity analysis on the injection timing was carried out to select the optimal injection operating window, capable of maximizing mixture homogeneity, without a significant volumetric efficiency reduction. Then, different spray injector guiding caps were tested to assess their effect on in-cylinder dynamics and mixture characteristics consequently. Finally, the impact of swirl intensity on hydrogen distribution has been assessed. The optimization of the combustion chamber geometry has allowed the achievement of significant improvements in terms of mixture homogeneity.

Basics of Catalyst for Internal Combustion Engine Applications - Future Prospect of After-treatment Catalyst System for Ships Based on Past Land Application Technologies

Basics of Catalyst for Internal Combustion Engine Applications - Future Prospect of After-treatment Catalyst System for Ships Based on Past Land Application Technologies

Machine learning-based screening of fuel properties for SI and CI engines using a hybrid group extraction method

The design of high-performance fuels is crucial for achieving clean and efficient combustion of engines. In the current study, a framework for machine learning (ML) model-based fuel design is presented to identify compounds with desired properties for internal combustion engine (ICE) applications. Descriptors computed from newly proposed structural and positional-based group extraction method in this study are used as input in ML models due to the simplicity and computational-efficiency. The ML models were trained and validated using publically available experimental data for up to 1135 compounds. The results demonstrated a high level of predictive accuracy, with R2 values generally exceeding 0.99 for 11 physicochemical properties including melting point, boiling point, enthalpy of vaporization, surface tension, dynamic viscosity, low heating value, liquid density, yield sooting index, cetane number, research octane number and motor octane number. Furthermore, by employing the developed ML models to predict new data, a Fuel Property Database containing 1135 fuels with 12 fuel properties is established, enhanced by an interface for a user-friendly Fuel Physicochemical Properties Prediction Tool that facilitates swift property predictions and database expansion. The Pearson correlation coefficient (PCC) approach is subsequently employed to assess the correlation between descriptors and predicted or experimental properties. The strong agreement between the correlations affirms the effective predictive performance of the ML models within the calibrated data range. Additionally, a PCC analysis is conducted to reveal the individual effects of influential factors and their interactions, highlighting significant features like molecular weight size, degree of branching, and functional group content that influence physical and chemical properties, thereby providing valuable insights for fuel design and optimization. Finally, a initial comprehensive data-driven screening was carried out to identify potential fuel candidates that meet the key property limits for combustion applications in both spark-ignition (SI) and compression-ignition (CI) engines.

RCCI combustion of ammonia in dual fuel engine with early injection of diesel fuel

Ammonia has gained considerable attention as a valuable, carbon-free alternative fuel for internal combustion engine (ICE) applications. The growing interest in ammonia's potential as an energy source stems primarily from its advantageous storage and transport properties. The reactivity-controlled compression ignition (RCCI) combustion mode presents a promising avenue for overcoming the challenges intrinsic to conventional diesel engines, such as elevated nitrogen oxides (NOx) and particulate matter (PM) emissions. Additionally, it addresses the limitations of both homogeneous charge compression ignition (HCCI) combustion (limited operational range) and premixed charge compression ignition (PCCI) combustion (diminished power output). The application of an ammonia-based RCCI combustion strategy emerges as a viable pathway for harnessing ammonia as a fuel. In this study, a numerical simulation on a single-cylinder heavy-duty engine operated in RCCI mode is conducted utilizing ammonia and diesel as fuels. The engine is operated at medium load and 910 RPM. The simulation results are validated against experimental data sourced from existing literature. The study investigates the impact of varying ammonia energy fractions, injection timing, and intake valve close temperature (TIVC) on key operational characteristics of the engine including in-cylinder pressure, heat release rate (HRR), combustion efficiency (CE), indicated mean effective pressure (IMEP), and emission levels. The results indicated that increasing the ammonia energy fraction within the RCCI combustion mode, transitioning from 30 % to 70 %, leads to a notable enhancement in IMEP, while maintaining low levels of carbon monoxide (CO), hydrocarbons (HC), unburned ammonia, and nitrous oxide (N2O) as greenhouse gases (GHG). Furthermore, increasing ammonia's energy fraction yielded a discernible reduction in NOx emissions and carbon dioxide (CO2). Conversely, the RCCI combustion mode attained superiority over the dual fuel combustion mode by simultaneously elevating CE and diminishing emissions of GHG, (CO2 and N2O) as well as unburned NH3.

Effects of Injection Parameters and EHN Mixing on the Combustion Characteristics of Fueling Pure Methanol in a Compression Ignition Engine

As one of the most ideal alternative fuels for internal combustion engines, methanol can achieve near-zero carbon emissions. The main problem of methanol application in compression combustion engines is the phase lag caused by its poor combustion characteristics, but under low load conditions, the fuel activity can be improved by adding the cetane number improver EHN (Isooctyl nitrate), and the dependence on intake heating can be reduced to a certain extent. Based on a three-dimensional CFD simulation, the effects of methanol injection parameters and the addition of EHN on the combustion characteristics of a four-stroke exhaust turbocharged diesel engine were studied in this paper. With or without EHN, the increase in injection pressure and the advance in injection timing lead to an increase in the peak temperature, pressure, and heat release rate, as well as a shortening of the combustion duration. Adding EHN witnesses reduced requirements for methanol ignition, including a decreased peak temperature, pressure, and heat release rate, a significantly shortened ignition delay period, and an extended combustion duration, which thus results in a reduced indicated thermal efficiency. This study innovatively develops a 3D model of a compression combustion engine applicable to in-cylinder direct injection pure methanol fuel and EHN under small load conditions, which provides a reference for future research and development of small-load pure methanol compression combustion engines and has certain guiding significance.

A Quasi-Dimensional Burn Rate Model for Pre-Chamber-Initiated Jet Ignition Combustion

<div class="section abstract"><div class="htmlview paragraph">Prospective combustion engine applications require the highest possible energy conversion efficiencies for environmental and economic sustainability. For conventional Spark-Ignition (SI) engines, the quasi-hemispherical flame propagation combustion method can only be significantly optimized in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Pre-Chamber (PC) initiated jet ignition combustion systems significantly shift the flammability and flame stability limits towards higher dilution areas due to high levels of introduced turbulence and a significantly increased flame area in early combustion stages, leading to considerably increased combustion speeds and high efficiencies. By now, vehicle implementations of PC-initiated combustion systems remain niche applications, especially in combination with lean mixtures. This is also due to challenges regarding cold-start, combustion stability at low loads, and emissions. Nevertheless, PC ignition systems allow overall engine efficiencies >45%. Therefore, a market launch of an engine using globally lean mixtures ignited by a PC system is desirable. This requires a fast-running and predictive physical model to conduct robust design studies and complement existing testing methodologies (3D-CFD, experimental). This paper addresses the development of a quasi-dimensional burn rate model for PC ignition combustion systems. The presented modeling approach combines the well-established two-zone entrainment model (main-chamber) with a semi-empirical PC model that aims to detect the PC influence on the main-chamber combustion. Dedicated models predict the impact of the jet-induced turbulence and the increased flame area. The models are integrated into the so-called cylinder module developed at IFS (Institute of Automotive Engineering Stuttgart). For the model validation, measurement data of a single-cylinder research engine using different fuels (E100<sup>1</sup>, RON95E10<sup>2</sup>), loads (<i>IMEP</i> = 6 − 15 <i>bar</i>), excess air dilutions (<i>λ</i> = 1 − 2) and compression ratios (16.4<sup>1</sup>, 12.6<sup>2</sup>) are used, showing a satisfactory prediction of the burn rate and pressure curve.</div></div>

Review on Plasma-Assisted Ignition Systems for Internal Combustion Engine Application

Due to the depletion of conventional petroleum-based fuels and increasing environmental concerns, industries have been developing new combustion technologies with acceptable cost ranges and minimum system modifications for consumers. Among many approaches, the utilization of plasma ignition systems is considered as a promising pathway to achieve greener transportation while maintaining conventional internal combustion engine systems. Plasma contains highly reactive radicals, and those have a great potential of enhancing chemical reactions that are beneficial for reducing carbon emissions. The primary objective of this paper is to provide an overview of currently available plasma-assisted combustion systems including recent achievements in research and development, and technical challenges for successfully implementing a new ignition system. This review will introduce various plasma-assisted combustion approaches from worldwide projects, covering non-thermal and thermal plasma systems in internal combustion engines.

An automated machine learning framework for piston engine optimization

This study introduces an automated machine learning-based optimization framework for internal combustion engine applications. This framework includes a SuperLearner model, an ensemble of several base learners combined with optimization algorithms, and an active learning approach. The SuperLearner model's performance was maximized by optimizing the hyperparameters using an elitist-based genetic algorithm. This work aims to demonstrate the framework on a smaller dataset of size 64 sourced randomly from the literature dataset for a heavy-duty gasoline compression ignition engine. The database consisted of nine input features representing engine control parameters and five target features representing engine performance and emissions. The multi-objective problem was converted into a single objective problem to maximize a merit value. A merit value of 103.9 was achieved using this framework, which was higher than the best merit values found within the reduced (101.97) and source (103.2) datasets. This high merit value was obtained with about 96% lesser data than the source dataset. This study demonstrated that the developed framework could lead to optimum solutions, starting with smaller datasets and fewer additional experimental or simulation runs.

Artificial intelligence-driven design of fuel mixtures

High-performance fuel design is imperative to achieve cleaner burning and high-efficiency engine systems. We introduce a data-driven artificial intelligence (AI) framework to design liquid fuels exhibiting tailor-made properties for combustion engine applications to improve efficiency and lower carbon emissions. The fuel design approach is a constrained optimization task integrating two parts: (i) a deep learning (DL) model to predict the properties of pure components and mixtures and (ii) search algorithms to efficiently navigate in the chemical space. Our approach presents the mixture-hidden vector as a linear combination of each single component’s vectors in each blend and incorporates it into the network architecture (the mixing operator (MO)). We demonstrate that the DL model exhibits similar accuracy as competing computational techniques in predicting the properties for pure components, while the search tool can generate multiple candidate fuel mixtures. The integrated framework was evaluated to showcase the design of high-octane and low-sooting tendency fuel that is subject to gasoline specification constraints. This AI fuel design methodology enables rapidly developing fuel formulations to optimize engine efficiency and lower emissions.

A Quasi-Dimensional Burn Rate Model for Spark-Assisted Compression Ignition (SACI) Combustion

<div class="section abstract"><div class="htmlview paragraph">Future combustion engine applications require highest possible energy conversion efficiencies to reduce their environmental impact and be economically competitive. So far, spark-ignition (SI) engine combustion development mostly consisted of optimizing the hemispherical flame propagation combustion method. Thereby, a significant efficiency increase is only achievable in combination with high excess air dilution or increased combustion speed. However, with increasing excess air dilution, this is difficult due to decreasing flame speeds and flammability limits. Simultaneously, researchers have been investigating homogeneous charge compression ignition (HCCI) that achieves higher efficiencies due to its rapid volume reaction combustion and also enables high excess air dilution. However, the combustion is complex to control as it is initiated by auto-ignition (AI) processes. In-cylinder conditions reliably need to be reproduced to prevent damaging pre-ignitions. Consequently, HCCI has only been applied for low load operation. The spark-assisted compression ignition (SACI) represents a compromise between SI combustion and HCCI. Thereby, a flame propagation is initiated that triggers a controlled volume reaction in the remaining charge. By now, there is only one (mainly stoichiometric) application of SACI combustion in the market. In combination with lean mixtures, SACI allows overall efficiencies >40%. A market launch of a lean mixture SACI engine is therefore desirable. This requires a fast-running and predictive physical model to conduct robust concept studies in the early development process. This paper addresses the development of a quasi-dimensional burn rate model for the SACI combustion method. The modeling approach combines the well-established two-zone entrainment model (for flame propagation) with a multi pseudo-zone volume reaction model based on a distributed AI integral, which is linked to a detailed two-stage AI model. The model is integrated into the so-called cylinder module developed at IFS (Institute of Automotive Engineering Stuttgart). A validation versus measurement data shows a satisfactory prediction of the burn rate and pressure curve.</div></div>

Low‐tar, highly burnable gas production from the gasification of pelletized palm empty fruit bunch

AbstractGasification is an attractive method to convert lignocellulosic biomass into a combustible gas mixture for electricity and power generation. To control the tar concentration in the produced gas to be within the allowable limit of downstream applications, it is important for a gasification system to be integrated with a tar removal process. In this study, an integrated gasification system consisting of a downdraft gasifier and a secondary catalytic tar‐cracking reactor was designed and tested for the gasification of pelletized oil palm empty fruit bunch. To further purify the producer gas, the system was also integrated with a cyclone, a water scrubber, and a carbon‐bed filter. Biomass was fed at a rate of 5 kg/h, while the air equivalence ratio (ER) and the gasification temperature were set at 0.1 and 800°C, respectively. In total, 5 kg of the specially developed low‐cost Fe/activated carbons (AC) catalyst was used in the hot gas catalytic tar‐cracking reactor. Results indicate that our integrated gasification system was able to produce a clean burnable gas with a lower heating value (LHV) of 9.05 MJ/Nm3, carbon conversion efficiency (CCE) of 79.4%, cold gas efficiency (CGE) of 89.9%, and H2 and CH4 concentrations of 29.5% and 10.3%, respectively. The final outlet gas was found to only contain 32.5 mg/Nm3 of tar, thus making it suitable for internal combustion engine (ICE) application.

Pneumatic and Optical Characterization and Optimization of Hydrogen Injectors for Internal Combustion Engine Application

To achieve future emission targets for internal combustion engines, the use of hydrogen gas generated by renewable energy sources (known as “green” hydrogen) instead of fossil fuels plays a key role in the development of new combustion-based engine concepts. For new hydrogen engine generations, there are different challenges concerning the injector layout and functionality. Especially when talking about direct hydrogen injection, the key challenge is to ensure a proper mixing between hydrogen and the combustion air—the mixing of gas with a gas is not trivial as shown in this article. In terms of injector functionality, it must be ensured that the requested amount of hydrogen gas needs to be provided in time and, on the other hand, accurately metered to provide an appropriate mixing formation quality inside the combustion chamber. This contribution discusses deep injector analysis techniques with pneumatic and optical approaches for an improved overall understanding of functionality and effects caused by operation with a gaseous fuel. A metering technique for gas flow characterization and, for test simplification, a comparison of hydrogen with helium and nitrogen as possible surrogate gases indicate that helium and nitrogen can act as a substitute for hydrogen in functional testing. Furthermore, this contribution focuses on the usability of helium instead of hydrogen for the determination of spray properties. This is shown by the comparison of spray propagation images that were observed with the Schlieren technique in a pressure vessel proving comparable spray properties. In a next step, the usage of spray-guiding devices to improve the global gas distribution during the injection period is discussed. Here, it turns out that the volume increase does obviously not depend on the nozzle design. Thus, the advantage of multi-hole guiding-devices is based on its flexible gas-jet orientation.

Effect of natural gas direct injection (NGDI) on the performance and knock behavior of an SI engine

The unique properties of natural gas (NG), including high availability and lower cost compared with other fossil fuels, make it attractive in internal combustion engine (ICE) application. NG is composed mainly of methane and has greater knock resistance than gasoline, enabling higher compression ratios (CR). In contrast with the distinctive advantages, the NG fueled engines suffer from lower power and torque outputs. To address the subject, this study proposes an approach employing NG direct injection (NGDI) strategy (with higher volumetric efficiency unlike port injection), enabling a higher CR irrespective of knock limit. This work applies reactive computational fluid dynamics (CFD) to investigate spark ignited co-combustion of direct-injected NG with port-admitted gasoline. The results are validated against experimental data. In all simulated cases, the equivalence ratio (i.e., ∅ = 1) and the total input energy are kept constant. Engine performance is evaluated for three CRs (10.5, 11.5, and 12.5:1), five proportion of CNG (RCNG) and at part- and full-load conditions at an engine speed of 1500 rpm. Results indicated that while running RCNG = 100 % with a CR of 10.5:1, carbon monoxide (CO) and carbon dioxide (CO2) emissions were decreased by 29.3 % and 23.5 % respectively, compared to RCNG = 0 %. The corresponding emission reduction at CR = 11.5:1 was 27.1 % and 24 %; at CR = 12.5:1 they were 29.6 % and 23.5 % respectively. At each CR, the knock intensity at full load fell significantly as the percentage of NG increased. At a CR of 12.5:1, ringing intensity (RI) at full load decreased by 88.6 % when using RCNG = 100 %, instead of RCNG = 0 %. Under the same conditions, RCNG = 25 % cut RI by 56 %.

Fracture-based transient thermo-mechanical analysis of reciprocating engine thermal barrier coatings

The durability of thermal barrier coatings for reciprocating internal combustion engine applications was investigated using a coupled, unsteady fracture-based thermomechanics model. The intra-cycle engine heat flux varies substantially in magnitude and has frequency similar to that of the coating thermal timescale, giving rise to relatively large spatial temperature nonuniformity within the coating that varies temporally. A finite difference scheme was used to calculate the temperature field. An analytical model that assumes equi-biaxial stress followed by plane strain delamination was used to evaluate an energy release rate that represents the driving force for cracking. Because the location and time of the peak energy release rate cannot be established a priori, they were computed for all times in the cycle. The peak energy release rate was found to occur later in the cycle than the peak surface temperature, and was often located within the coating as compared to at the coating–substrate interface where there was a mismatch in coefficient of thermal expansion. Coating thickness was found to affect both the magnitude of the peak energy release rate and its location. The residual stress, which arises from the coating deposition process, was found to have a significant effect on the peak energy release rate, and may be a process parameter that can be used to promote coating life. The computational framework demonstrated insight regarding the trade-off between engine thermodynamic performance and coating durability.

Novel secondary standard for calibration of dynamic pressure sensors

Abstract Recent research activities in dynamic pressure metrology have been mainly focusing on the development of primary standards like the shock tube or drop-weight apparatus to establish traceability to SI. However, these calibration facilities require a high level of expertise leading to elaborate and time-consuming calibrations. The development of secondary calibrators, based on the reference sensor principle, offering efficient and cost-effective calibrations is essential to meet the needs for industry and to disseminate the dynamic pressure quantity to a wide end-user community. This paper reports a novel secondary calibrator for dynamic pressure measurements up to 300 bar with an expanded uncertainty of about 3.0 %. A heating option enable calibrations at elevated temperatures up to 200 °C making it an ideal solution for convenient calibrations of dynamic pressure transducers used for measurement in internal combustion engine applications.

Tyre pyrolytic oil fuel blends in a modern compression ignition engine: A comprehensive combustion and emissions analysis

There is abundant worldwide research into combustion engine applications for tyre pyrolysis oil (TPO). However, most studies are methodologically outdated in terms of their assumed technology, either with regard to TPO production or engine application, or in their analytical approaches. The variety of radically different studies produce conflicting or ambiguous results, rendering TPÓs role as a feasible future fuel uncertain. This study is the first to provide state-of-the art combustion analysis results for thoroughly-evaluated TPO fraction optimised in a modern, industry-grade pyrolytic reactor. The fuel blends are selected for engine tests, taking into account the overall availability/compatibility of their TPO fractions with diesel. Testing with a modern, sophisticated single-cylinder research engine provides detailed analysis of combustion and both regulated and unregulated emissions. Emissions results are supported by FTIR analysis of exhaust gases, including identification of 23 species. The results show that contemporary Tier 4-compliant combustion systems with multi-pulse injection can handle high TPO-content fuels without needing re-calibration. With diesel/TPO blends of up to 40% TPO admixture, combustion phasing is substantially delayed (by 3CAD) only at near-idle loads and particularly when using heavy exhaust gas recirculation. The consequential differences in performance and emissions diminish over the test cycle. Current US EPA Tier 4 emission limits are not particularly challenging for TPO, even at 40% blending rate, but its elevated levels of particulate matter (25% increase over test cycle versus diesel baseline), sulphur oxides, aromatics and formic acid present health concerns and potential maintenance issues. These should be considered when assessing the fueĺs life-cycle environmental impact. The increase in emissions of those species correlates directly with fuel sulphur content (0.5% for neat TPO fraction), polyaromatic hydrocarbons fraction (0.49%) and acidity. Further optimisation of TPÓs composition in the reactor and via improved fuel post-processing can address these issues.

SIMULATION STUDY OF BREAKUP AND ATOMIZATION CHARACTERISTICS OF GASOLINE-ETHANOL (GASHOLS) FUEL BLENDS

To meet the increasingly stringent constraints on mobile and point emissions in the wake of the dwindling fortunes of fossil fuels, evaluation of hybrid fuels for application in combustion engines has become an imperative, especially in the third world countries. This paper presents, modeling of atomization characteristics of gasoline-ethanol fuel blends. Fuel breakup models and correlations between flow patterns and droplet characteristics were adopted and implemented in OpenFOAM Computational Fluid Dynamics (CFD) modeling suite for direct gasoline injector using a simple cylindrical mesh structure at constant volume. The Rosin Rammler distribution model was used to generate the number of spray particles injected into the cylinder. The spray modeling and atomization employed the use of blob sheet model and Kelvin-Helmholtz-Rayleigh-Taylor (KH-RT) model while the numerical technique for simulating atomization process by CFD included the use of governing equations such as Eulerian for gas phase, Lagrangian for disperse phase and turbulence modeling. The effects of fuel blends, injection pressure, ambient gas pressure and spray cone angle were evaluated on the axial spray tip penetration, spray width, and overall Sauter Mean Diameter (SMD). The SMD was seen to be affected by varying the degree of injection cone angle. The spray tip penetration lengths were larger for higher injection cone angles while higher penetration lengths were obtained at higher injection pressures. One salient conclusion drawn from the modeling is that as the number of particle increased, the density of clusters became smaller.

Enhancing AW/EP tribological characteristics of biolubricant synthesized from chemically modified cotton methyl-esters by using nanoparticle as additives

PurposeThe purpose of this study is to improve the tribological characteristics of cotton-biolubricant by adding nanoparticles at extreme pressure (EP) conditions in comparison with commercial lubricant SAE-40.Design/methodology/approachThis research involved the synthesis of cotton-biolubricant by transesterification process and then the addition of nanoparticles in it to improve anti wear (AW)/EP tribological behavior. SAE-40 was studied as a reference commercial lubricant. AW/EP characteristics of all samples were estimated by the four-ball tribo-tester according to the American Society for Testing and Materials D2783 standard.FindingsThe addition of 1-Wt.% TiO2 and Al2O3 with oleic acid surfactant in cotton-biolubricant decreased wear scar diameter effectively and enhanced the lubricity, load-wear-index, weld-load and flash-temperature-parameters. This investigation revealed that cotton-biolubricant with TiO2 nano-particle additive is more effective and will help in developing new efficient biolubricant to replace petroleum-based lubricants.Research limitations/implicationsCotton biolubricant with TiO2 nano-particles appeared as an optimistic solution for the global bio-lubricant market.Originality/valueNo one has not studied the cotton biolubricant with nanoparticles for internal combustion engine applications at high temperature and EP conditions.

Spray characteristics of biofuels for advance combustion engines

This study investigates spray characteristics, flashing and non-flashing, of unsaturated neem biodiesel (BD), biodiesel-ethanol (BDE50) blend, and diesel for application in advanced combustion engines. Fuel properties, injection pressure, nozzle geometry, and the surrounding ambient gas conditions govern the spray breakup and air-fuel mixing. The spray characteristics of fuel is studied at various injection pressure and ambient gas densities using the high-speed shadowgraphy technique. BDE50 shows improved spray dispersion with distinct tree-shaped spray morphology at ambient density of 1.14 kg/m 3 and injection pressure of 50 MPa. Theoretical analysis confirms occurrence of cavitation due to high volatile component (ethanol) in biofuel mixture and throttling conditions. At high ambient gas density and injection pressure, diesel and BDE50 exhibit high spray cone angle. Neem biodiesel maintains high tip penetration and low cone angle due to poor atomization. The study recommends use of BDE50 blend for achieving improved mixture formation in engines. • Dual (reactivity) biofuels spray atomization strongly controls the air-fuel mixing and combustion. • Cavitation induced flashing with BDE50 spray shows improved spray dispersion with distinct tree shaped spray morphology. • Theoretical analysis confirms cavitation (in BDE50) by throttling conditions. • Recommended to use the BDE50 instead of biodiesel for achieving the improved mixture formation.