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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Revealing the interplay between “intelligent behavior” and surface reconstruction of non-precious metal doped SrTiO 3 catalysts during methane combustion

The impact of surface reconstruction of a model perovskite, SrTiO 3 (STO), on CH 4 activation for combustion and oxidative coupling was previously revealed that the reaction rate was proportional to the creation of Srterminated step sites. Doped perovskites (SrTi 1-x M x O 3 , M=metal dopant) present yet another form of reconstruction throughout the surface and the bulk, where the metal dopant can migrate in and out of the perovskite lattice, also known as "intelligent behavior". In this work, understanding the interplay between perovskite surface reconstruction (surface termination) and the "intelligent behavior" is tackled for the first time, and the catalytic consequences are probed with CH 4 combustion as a model reaction. A set of experimental techniques, including XRD, Raman spectroscopy, X-ray adsorption spectroscopy, kinetic measurements, as well as DFT calculations were used to understand the catalytic behavior of the reconstructed surfaces of Ni and Cu-doped STO for methane combustion. Here, we found that during methane oxidation, the diffusion of Ni and Cu into the lattice due to the "intelligent behavior" is accompanied by Sr enrichment on the surface of the perovskite. This Srenrichment process is reversible when Cu or Ni species exsolute as clusters/nanoparticles upon H 2 treatment. Such a surface reconstruction is found to greatly impact the catalytic activity of doped perovskites towards methane combustion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Autoignition of CRC diesel surrogates at low temperature combustion conditions: Rapid compression machine experiments and modeling

As federal programs require increasingly stringent engine emissions and fuel economy standards, these ambitions can only be met if next-generation combustion technology is developed focusing on high-efficiency and low-emissions engines. Recent research has indicated the need to operate engines at higher compression ratios and with low temperature combustion (LTC) to achieve the needed gains in engine efficiency and reductions in emissions. Because there is a lack of understanding of the chemistry of diesel fuel components and their mixtures at these LTC conditions, this limits the ability to develop predictive chemical kinetic models that can be used to optimize engine combustion. The current study aims to fill in gaps in fundamental combustion data on surrogate fuel mixtures relevant to diesel fuels. Specifically, four multicomponent diesel surrogates formulated by the Coordinating Research Council (CRC) to emulate an ultra-low-sulfur research-grade #2 certification diesel fuel (CFA), namely V0a (4 components), V0b (5 components), V1 (8 components), and V2 (9 components), have been investigated in a rapid compression machine (RCM) through determination of total and first-stage ignition delay times. Autoignition characteristics of lean to rich fuel/O 2 /N 2 mixtures, for the four CRC surrogates and CFA, have been measured using an RCM at LTC relevant pressures and temperatures, in the ranges of 10–20 bar and 650–1000 K, respectively. The equivalence ratios have been varied by independently changing the oxygen mole fraction and the fuel mole fraction in the test mixtures, thereby illustrating the individual effects of oxygen concentration and fuel loading on diesel autoignition. Autoignition results of these four CRC surrogates are compared among them and with those of CFA. Some degree of agreement in autoignition response between each CRC surrogate and CFA is observed, while discrepancies are also identified and discussed. In addition, a detailed chemical kinetic model for diesel surrogates has been developed and validated against these newly-acquired RCM data. We find that this model shows reasonable agreement with the overall ignition delay time results of the current RCM experiments. Chemical kinetic analyses of the developed model were further conducted to help identify the reactions controlling the autoignition processes and the consumption of fuel components in CRC surrogates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗
DOE OSTI2020

Assessment of various tar and soot treatment methods and a priori analysis of the steady laminar flamelet model for use in coal combustion simulation

Soot formed in the fuel-rich regions of coal flames is known to have a significant impact on the radiative heat transfer characteristics of the flame. It is therefore important to account for the effect of soot radiation when simulating coal combustion systems. Several recent coal combustion studies have used acetylene as a surrogate for devolatilized tar and neglect soot formation altogether, while others have utilized empirical models for tar and soot or even chemical mechanisms which include tar and soot as species. In this work, we investigate several methods of treating coal-derived tar and soot and the impact each treatment has on predicted furnace temperature, particle mass loss, and other quantities of interest. Furthermore, we perform a priori comparisons of simulation results to calculations from a steady laminar flamelet model in order to assess the accuracy of a flamelet approach for each tar and soot treatment considered. Data used as a basis for the study is generated through One-Dimensional Turbulence (ODT) simulation of a coal combustion system in which high- fidelity models are used for gas phase chemistry and devolatilization, where char combustion is neglected.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Numerical analysis of particle dispersion and deposition in coal combustion using large-eddy simulation

High-fidelity modeling provides a useful approach to investigate the particle dispersion and deposition mechanism in pulverized coal combustion. To be able to analyze these detailed mechanisms, this work couples detailed multiphysics models for poly-dispersed turbulent, particle-laden flow, particle and gas phase reaction chemistry, convective, conductive and radiative heat transfer, ash formation and deposition with a Large-Eddy Simulation (LES) approach to numerically simulate coal combustion in a downfired self-sustained oxy-fuel combustor (OFC). It is necessary to explicitly capture all but the highest frequency dynamics of the turbulence and its coupling with each of the other physical phenomena using LES. Effects of subgrid-scale unresolved turbulence on the particle motions are also analyzed by a novel Stokes number analysis. Due to the inherent relation ship between coal combustion and ash deposition, this study integrates the improved ash deposition model into the numerical simulation. Overall simulation results are compared with experimentally measured data from the OFC. The simulation and measured data for the averaged gas temperature and deposition rates agree with 5% and 28%. This study shows that high-fidelity LES coupled with other detailed multiphysics models running on a exascale computing facility can provide a good representation of complex coal combustion and deposition in a laboratory-scale furnace.

multiphysics model↗
DOE OSTI2020

Effects of Zr substitution on soot combustion over cubic fluorite-structured nanoceria: Soot-ceria contact and interfacial oxygen evolution

Ceria is widely used as a catalyst for soot combustion, but effects of Zr substitution on the reaction mechanism is ambiguous. The present work elucidates effects of Zr substitution on soot combustion over cubic fluorite-structured nanoceria. The nanostructured CeO 2 , Ce 0.92 Zr 0.08 O 2 , and Ce0.84Zr0.16O2 composed of 5–6 nm crystallites display Tm-CO 2 (the temperature at maximum CO 2 yield) at 383, 355, and 375°C under 10 vol.% O 2 /N 2 , respectively. Additionally, the size of agglomerate decreases from 165.5 to 51.9–57.3 nm, which is beneficial for the soot-ceria contact. Moreover, Zr increases the amount of surface oxygen vacancies, generating more active oxygen (O2- and O-) for soot oxidation. Thus, the activities of Ce 0.92 Zr 0.08 O 2 and Ce 0.84 Zr 0.16 O 2 in soot combustion are better than that of CeO2. Although oxygen vacancies promote the migration of lattice O 2- , the enriched surface Zr also inhibits the mobility of lattice O 2- . Therefore, the Tm-CO 2 of Ce 0.84 Zr 0.16 O 2 is higher than that of Ce 0.92 Zr 0.08 O 2 . Based on reaction kinetic study, soot in direct contact with ceria preferentially decomposes with low activation energy, while the oxidation of isolated soot occurs through diffusion with high activation energy. The obtained findings provide new understanding on the soot combustion over nanoceria.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characteristics of the sub-micron ash aerosol generated during oxy-coal combustion at atmospheric and elevated pressures

This paper is concerned with the effect of pressure on the particle size distribution and the size-segregated composition of the sub-micron ash aerosol created during oxy-coal combustion under near practical self-sustaining combustion conditions. The problem is important because pressurized oxy-coal combustion has been proposed as one promising technology to minimize CO 2 emissions. Sub-micron ash plays a major role in ash deposition mechanisms, which, in turn, can control boiler performance. In this work, the same bituminous coal was burned at pressures of 1, 8 and 15 bar in O 2 /CO 2 environments. Here, tests employed a 100 kW (rated) oxy-fuel combustor (OFC) operated at atmospheric pressure (1 bar) and a 300 kW (rated) entrained-flow pressurized reactor (EFPR) at elevated pressures (8 and 15 bar). Although these tests were conducted under near practical combustion conditions, confounding effects of peak flame temperature variations were minimized for the 1 bar and 15 bar tests, allowing the role of elevated pressure to be isolated. For the EFPR tests, a specially designed sampling system was used to sample sub-micron ash aerosols from the pressurized combustor and is described in detail. Results showed that at the same peak temperature but higher pressure, the fractions of ash aerosol partitioned into the PM 0.6 and PM 1 size fractions were greatly diminished. Moreover, elevated pressures caused significant changes in the composition of the (size-segregated) sub-micron aerosol, especially in its alkali content, which increased significantly. Examination of fractions of each element that ended up in the sub-micron fume suggested that, at constant temperature, the effect of pressure on vaporization of semi-volatile metals was very different from that on the release into the gas phase of non-volatile metals and could not be explained by equilibrium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Revealing the structure of a catalytic combustion active-site ensemble combining uniform nanocrystal catalysts and theory insights

Supported metal catalysts are extensively used in industrial and environmental applications. To improve their performance, it is crucial to identify the most active sites. This identification is, however, made challenging by the presence of a large number of potential surface structures that complicate such an assignment. Often, the active site is formed by an ensemble of atoms, thus introducing further complications in its identification. Being able to produce uniform structures and identify the ones that are responsible for the catalyst performance is a crucial goal. Here, we utilize a combination of uniform Pd/Pt nanocrystal catalysts and theory to reveal the catalytic active-site ensemble in highly active propene combustion materials. Using colloidal chemistry to exquisitely control nanoparticle size, we find that intrinsic rates for propene combustion in the presence of water increase monotonically with particle size on Pt-rich catalysts, suggesting that the reaction is structure dependent. We also reveal that water has a near-zero or mildly positive reaction rate order over Pd/Pt catalysts. Theory insights allow us to determine that the interaction of water with extended terraces present in large particles leads to the formation of step sites on metallic surfaces. These specific step-edge sites are responsible for the efficient combustion of propene at low temperature. This work reveals an elusive geometric ensemble, thus clearly identifying the active site in alkene combustion catalysts. These insights demonstrate how the combination of uniform catalysts and theory can provide a much deeper understanding of active-site geometry for many applications

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Numerical Investigation of Fuel Property Effects on Mixed-Mode Combustion in a Spark-Ignition Engine

In this research, lean mixed-mode combustion is numerically investigated using computational fluid dynamics (CFD) in a spark-ignition engine. A new E30 fuel surrogate is developed using a neural network model with matched octane numbers. A skeletal mechanism is also developed by automated mechanism reduction and by incorporating a NO x submechanism. A hybrid approach that couples the G-equation model and the well-stirred reactor model is employed for turbulent combustion modeling. The developed CFD model is shown to well predict pressure and apparent heat release rate (AHRR) traces compared with experiment. Two types of combustion cycles (deflagration-only and mixed-mode cycles) are observed. The mixed-mode cycles feature early flame propagation and subsequent end-gas auto-ignition, leading to two distinctive AHRR peaks. The validated CFD model is then employed to investigate the effects of NO x chemistry. The NO x chemistry is found to promote auto-ignition through the residual gas, while the deflagration phase remains largely unaffected. Sensitivity analysis is finally performed to understand effects of fuel properties, including heat of vaporization (HoV) and laminar flame speed (S L ). An increased HoV tends to suppress auto-ignition through charge cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased S L is found to significantly promote both flame propagation and end-gas auto-ignition. The promoting effect of S L on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end-gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Direct Numerical Simulation of Partial Fuel Stratification Assisted Lean Premixed Combustion for Assessment of Hybrid G-Equation/Well-Stirred Reactor Model

Partial fuel stratification (PFS) is a promising fuel injection strategy to stabilize lean premixed combustion in spark-ignition (SI) engines. PFS creates a locally stratified mixture by injecting a fraction of the fuel, just before spark timing, into the engine cylinder containing homogeneous lean fuel/air mixture. Further, this locally stratified mixture, when ignited, results in complex flame structure and propagation modes similar to partially premixed flames and allows for faster and more stable flame propagation than a homogeneous lean mixture. This study focuses on understanding the detailed flame structures associated with PFS-assisted lean premixed combustion. First, a two-dimensional direct numerical simulation (DNS) is performed using detailed fuel chemistry, experimental pressure trace, and realistic initial conditions mapped from a prior engine large-eddy simulation (LES), replicating practical lean SI operating conditions. DNS results suggest that the conventional triple flame structure is prevalent during the initial stage of flame kernel growth. Both premixed and nonpremixed combustion modes are present with the premixed mode contributing dominantly to the total heat release. Detailed analysis further reveals the effects of flame stretch and fuel pyrolysis on flame displacement speed. Based on the DNS findings, the accuracy of a hybrid G-equation/well-stirred reactor (WSR) combustion model is assessed for the PFS-assisted lean operation in the LES context. It is found that the G-equation model qualitatively captures the premixed branches of the triple flame, while the WSR model predicts the nonpremixed branch of the triple flame. Finally, potential needs for improvements to the hybrid G-equation/WSR modeling approach are discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite

Combustion encompasses multiscale, multiphase reacting flow physics spanning a wide range of scales from the molecular scales, where chemical reactions occur, to the device scales, where the turbulent flow is affected by the geometry of the combustor. This scale disparity and the limited measurement capabilities from experiments make modeling combustion a significant challenge. Recent advancements in high-performance computing (HPC), particularly with the Department of Energy's Exascale Computing Project (ECP), have enabled high-fidelity simulations of practical applications to be performed. The major physics submodels, including chemical reactions, turbulence, sprays, soot, and thermal radiation, exhibit distinctive computational characteristics that need to be examined separately to ensure efficient utilization of computational resources. This paper presents the multiphysics solver for the Pele code suite, called PeleMP, which consists of models for spray, soot, and thermal radiation. Here, the mathematical and algorithmic aspects of the model implementations are described in detail as well as the verification process. The computational performance of these models is benchmarked on multiple supercomputers, including Frontier, an exascale machine. Results are presented from production simulations of a turbulent sooting ethylene flame and a bluff-body swirl stabilized spray flame with sustainable aviation fuels to demonstrate the capability of the Pele codes for modeling practical combustion problems with multiphysics. This work is an important step toward the exascale computing era for high-fidelity combustion simulations providing physical insights and data for predictive modeling of real-world devices.

42 ENGINEERING↗
DOE OSTI2024

A numerical study of ignition and flame development characteristics in GCI combustion using large eddy simulations and chemical explosive mode analysis

Here, this work investigates the ignition and flame development processes of low reactivity fuel combustion under compression ignition conditions based on the large eddy simulation approach. The chemical explosive mode analysis (CEMA) is employed to characterize the local combustion features, including gas-liquid fuel zone, auto-ignition, diffusion-assisted, extinction, cool flame and post-ignition zone, among which auto-ignition and post-ignition are found to play a key role in the overall heat release process. The local flame propagation modes in gasoline compression ignition (GCI) are determined by quantifying the relative magnitude of diffusion/chemistry at a representative progress variable in the pre-ignition zone. The results show that autoignition fronts and deflagration waves exist simultaneously in the ignition and intense high temperature heat release (HTHR) stages, but autoignition fronts dominate. In addition, the chemical kinetic processes of four heat release periods are analyzed. The heat release during the ignition period is found to be dominated by the reactions CH 3 + H (+M) <=> CH 4 (+M) and CH 3 CHO + H <=> CH 2 CHO + H 2 . The reaction CH 2 OH + OH <=> CH 2 O + H 2 O always plays an important role in the heat releases during the other three combustion stages including intense HTHR, moderate HTHR and post-combustion.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Modeling Combustion Reaction ODEs with Neural Networks

The chemistry of combustion reactions is complex as it involves many species and reactions. In practice, such a system is often modeled computationally using an empirically derived chemical mechanism. Given the large range of reaction rates, the system is then time evolved using a stiff ODE solver. However, even when reduced chemical mechanisms are employed, the system can become computationally expensive for two-dimensional or three-dimensional systems. Such systems can also face problems with instability. As such, it is desirable to find a cheaper, stable alternative to solving the reaction system. Neural networks offer the potential to learn these reaction ODEs and time evolve a combustion reaction in a more cost-efficient manner than stiff ODE solvers. In this study, a variety of neural networks are trained on zero-dimensional Cantera simulations of methane combustion with varying initial conditions. Several predictive approaches as well as several neural network architectures (artificial neural network with dropout, ResNet, and Neural ODE) are compared in their ability to predict combustion trajectories. Promising models are then identified.

combustion kinetics↗
DOE OSTI2022

Low-Cost Recyclable Oxygen Carrier and Novel Process for Chemical Looping Combustion

The University of North Dakota, through its Institute for Energy Studies and Energy & Environmental Research Center, partnered with Envergex LLC, Barr Engineering and Microbeam Technologies to develop a transformational enabling technology for advancement of Chemical Looping Combustion technology. Industrial support was provided by Carbontec Energy Corporation. The project targeted the two biggest challenges to chemical looping combustion: (1) High costs of oxygen carrier replacement/loss due to expensive manufacturing and high replacement rates from physical attrition and/or decrease in reactivity, and (2) Inherently slow fuel char conversion which represents the rate-limiting step for chemical looping combustion and results in very large equipment sizes, and overall lower carbon dioxide capture efficiency. The project activities were addressed in a series of seven tasks. Task 1 extended throughout the entire project and oversaw project management and execution. Task 2 and 3 focused on development and evaluation of the novel oxygen carrier. Task 4 to 7 focused on design of the novel reactor, testing with the novel oxygen carrier and a techno-economic assessment of the process. The list of tasks are: Task 1 – Project management and planning, Task 2 – Laboratory scale oxygen carrier manufacturing and assessment, Task 3 – Modeling and laboratory-scale evaluation of oxygen carrier performance with coal, Task 4 – 10-kilowatt thermal integrated system installation, Task 5 – Scaled-up oxygen carrier manufacturing, Task 6 – 10-kilowatt testing, and Task 7 – Process design and techno-economic analysis.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines

In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.

Maldonado Puente, Bryan↗
DOE OSTI2021

Spray and combustion characteristics of butanol-diesel and hexanol-diesel blends under high-altitude conditions

Due to their excellent fuel properties, butanol and hexanol are considered as two promising renewable fuels for diesel engine applications. The objective of this work is to investigate and compare the spray and combustion characteristics of butanol-diesel and hexanol-diesel blends under high-altitude conditions. A constant volume combustion chamber was used to provide the desired environment. Experiments were conducted under various ambient temperatures ranging from 800 K to 1200 K and various ambient densities ranging from 11 kg/m3 to 15 kg/m3. Fuel blends with 20% blend ratio (B20 and H20) and neat diesel were used as test fuels. The spray and combustion characteristics of the test fuels were analyzed using measured liquid penetration length, ignition delay, combustion duration, flame lift-off length (FLoL), and spatially integrated natural luminosity (SINL). Here the results revealed that B20 and H20 had shorter liquid penetration length than diesel under low ambient temperature and density conditions due to their higher volatility. The blended fuels showed significantly longer ignition delay than diesel under low ambient temperature conditions, but it could be overcome by increasing the ambient temperature. Adding butanol and hexanol into diesel both extended FLoL especially under low ambient temperature and density conditions, but the effects of hexanol was less dramatic compared to butanol due to its lower latent heat of vaporization and higher chemical reactivity. Both B20 and H20 showed lower SINL than diesel under any conditions, indicating their ability of reducing soot emissions. However, no apparent differences could be found between these two fuels until the ambient temperature dropped to 800 K.

42 ENGINEERING↗