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At least 55 records · Page 3

Considerations for the temperature stratification in a pre-burn constant-volume combustion chamber

In recent years, the Engine Combustion Network (ECN) has developed as a worldwide reference for understanding and describing engine combustion processes, successfully bringing together experimental and numerical efforts. Since experiments and numerical simulations both target the same boundary conditions, an accurate characterization of the stratified environment that is inevitably present in experimental facilities is required. The difference between the core-, and pressure-derived bulk-temperature of pre-burn combustion vessels has been addressed in various previous publications. Additionally, thermocouple measurements have provided initial data on the boundary layer close to the injector nozzle, showing a transition to reduced ambient temperatures. The conditions at the start of fuel injection influence physicochemical properties of a fuel spray, including near nozzle mixing, heat release computations, and combustion parameters. To address the temperature stratification in more detail, thermocouple measurements at larger distances from the spray axis have been conducted. Both the temperature field prior to the pre-combustion event that preconditions the high-temperature, high-pressure ambient, as well as the stratification at the moment of fuel injection were studied. To reveal the cold boundary layer near the injector with a better spatial resolution, Rayleigh scattering experiments and thermocouple measurements at various distances close to the nozzle have been carried out. The impact of the boundary layers and temperature stratification are illustrated and quantified using numerical simulations at Spray A conditions. Next to a reference simulation with a uniform temperature field, six different stratified temperature distributions have been generated. These distributions were based on the mean experimental temperature superimposed by a randomized variance, again derived from the experiments. The results showed that an asymmetric flame structure arises in the computed results when the temperature stratification input is used. In these predictions, first-stage ignition is advanced by 24 $\mu$s , while second-stage ignition is delayed by 11 $\mu$s. At the same time a lift-off length difference between the top and the bottom of up to 1.1 mm is observed. Furthermore, the lift-off length is less stable over time. Given the shown dependency, the temperature data is made available along with the vessel geometry data as a recommended basis for future numerical simulations.

42 ENGINEERING↗

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗

Modeling the impact of the fuel injection strategy on the combustion and performance characteristics of a heavy-duty GCI engine

Gasoline compression ignition (GCI) is a promising strategy to achieve high thermal efficiency and low emissions with limited modifications to the conventional diesel engine hardware. It is a partially premixed concept, which derives its superiority from higher volatility and longer ignition delay of gasoline-like fuels combined with higher compression ratio typical of diesel engines. Here, the present study investigates the combustion process in a GCI engine operating with different injection strategies using computational fluid dynamics (CFD). Simulations are carried out on a single cylinder of a multi cylinder heavy-duty compression ignition engine, which operates at a compression ratio of 17:1 and an engine speed of 1038 rev/min. Two different injection strategies viz., late injection (LI), and early pilot injection (EP) are investigated to understand their impact on combustion and performance of the engine. Renormalized group (RNG) k-ε model is used to describe in-cylinder turbulence and KH RT model is used to simulate the fuel spray breakup. The developed CFD methodology is validated against relevant experimental data under a wide range of operating conditions for each injection strategy. The developed CFD methodology was found to capture the engine combustion behavior quite well. Based on the validated CFD model, the differences in the progress of combustion event for the two injection strategies is highlighted. It was found that a larger pilot fuel mass fraction results in a steeper rise in the initial heat release rate which in turn influences the transition to mixing controlled combustion. In line with the experimental data, the study showed that the late pilot injection strategy with three injection pulses, results in higher performance compared to the other conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Effect of NO on DME-Methanol HCCI Combustion Using a Reduced Chemical Kinetics Mechanism

Methanol is an attractive fuel for the maritime sector due to its wide availability. Its direct use as a fuel, however, is accompanied by challenges such as high latent heat of vaporization and low cetane number. A potential solution to overcome the ignition properties of methanol could be through on-board generation of dimethyl ether (DME) via catalytic dehydration of methanol. The resulting mixture from dehydration can be mixed in with the intake air to generate a homogenous charge compression ignition (HCCI) preburn for subsequent direct injection (DI) mixing controlled compression ignition (MCCI) of neat methanol. Within that context, complementary experimental work found that the influence of combustion residuals on the heat release rate (HRR) was significant, specifically for residual NO. This finding motivated the present computational and kinetic evaluation of the effects of NO on the low (LTHR) and high (HTHR) temperature heat release rates. The strong influence of small quantities of NO on the combustion process of a DME/methanol/H2O mixture (low catalyst or reactor efficiency) necessitated a kinetics-based investigation into this phenomenon. A mechanism sourced from the existing literature with NO had 172 species and 1375 reactions, making it computationally expensive for use. Hence, a mechanism reduction effort was implemented, and a rate constant (k) tuning effort based on sensitivity analysis was needed to validate experimental results using a zero-dimensional engine model in Cantera. The reduced mechanism was able to successfully capture the negligible influence of NO addition on DME HCCI combustion, whereas an advancement in LTHR and HTHR for a DME/methanol/H2O mixture was kinetically confirmed. Reaction pathway analysis showed that addition of NO chemically counteracted the OH sink created by alcohols like methanol, increasing the effectiveness of DME ignition.

Tyrewala, Daanish [ORNL] (ORCID:0000000208599324)↗

A Double-Wiebe Function for Reactivity Controlled Compression Ignition Combustion Using Reformate Diesel

Abstract Reactivity controlled compression ignition (RCCI) combustion has previously been proposed as a method to achieve high fuel conversion efficiency and reduce engine emissions. A single-fuel RCCI combustion strategy can have decreased fuel system complexity by using a reformate fuel for port fuel injection and the parent fuel (diesel) for direct injection. This paper presents a one-dimensional computational model of a compression ignition engine with single-fuel RCCI. A Wiebe function is used to predict the combustion process by representing the mass fraction burned (MFB) on a crank angle resolved basis. One single-Wiebe function (SWF) and two double-Wiebe functions(DWFs) were fitted to experimentally derive MFB data using the least-square method. The fitted results were compared with MFBs calculated from experimental data to verify the accuracy. The SWF did not fully capture the MFB curve with high fidelity while the detailed DWF captured the MFB curve within a root mean square error of 1.4%. The reduced double-Wiebe function (RDWF) also resulted in a predicted combustion profile with similar accuracy. Hence, the RDWF was used in a GT-power thermodynamic study to understand the effects of the low-temperature heat release (LTHR) fraction and combustion phasing on combustion characteristics. At optimum phasing of 5–10 crank angle degree after the top dead center, increasing the LTHR fraction from 20% to 60% resulted in the fuel conversion efficiency increasing from 39.5% to 41.1%, thus suggesting that the reformate fuel-based RCCI strategy is viable to unlock improved combustion performance.

Energy & Fuels↗

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗

Quantifying the effect of CO 2 gasification on pulverized coal char oxy-fuel combustion

Previous research has provided strong evidence that CO 2 and H 2 O gasification reactions can provide non-negligible contributions to the consumption rates of pulverized coal (pc) char during combustion, particularly in oxy-fuel environments. Fully quantifying the contribution of these gasification reactions has proven to be difficult, due to the dearth of knowledge of gasification rates at the elevated particle temperatures associated with typical pc char combustion processes, as well as the complex interaction of oxidation and gasification reactions. Gasification reactions tend to become more important at higher char particle temperatures (because of their high activation energy) and they tend to reduce pc oxidation due to their endothermicity (i.e. cooling effect). The work reported here attempts to quantify the influence of the gasification reaction of CO 2 in a rigorous manner by combining experimental measurements of the particle temperatures and consumption rates of size-classified pc char particles in tailored oxy-fuel environments with simulations from a detailed reacting porous particle model. The results demonstrate that a specific gasification reaction rate relative to the oxidation rate (within an accuracy of approximately +/- 20% of the pre-exponential value), is consistent with the experimentally measured char particle temperatures and burnout rates in oxy-fuel combustion environments. Conversely, the results also show, in agreement with past calculations, that it is extremely difficult to construct a set of kinetics that does not substantially overpredict particle temperature increase in strongly oxygen-enriched N2 environments. This latter result is believed to result from deficiencies in standard oxidation mechanisms that fail to account for falloff in char oxidation rates at high temperatures.

42 ENGINEERING↗

Accelerating Innovative Energy Solutions Using Combustion Simulations

Combustion-based transportation, electricity generation, and industrial heating in manufacturing constitute the three largest sectors of energy demand. Some of the recent technology development in these sectors are: switching to low-carbon fuels for the transportation sector, increasing energy efficiency in the power sector, and capturing carbon emissions from conventional power generators. Several teams at the National Renewable Energy Laboratory have been actively advancing research in these areas by leveraging computational modeling of combustion processes across the heavy-duty land based transportation, aviation, and power generation sectors. This article summarizes some of these efforts, demonstrating the potential of advanced computational techniques to generate technological solutions that will transform the global energy system.

08 HYDROGEN↗

Challenges in Kinetic modeling of ammonia pyrolysis

Ammonia pyrolysis reactions have implications for its ignition and oxidation in engines and gas turbines. In the present work, the chemistry of ammonia pyrolysis is investigated by kinetic modeling and theory. Rate constants for key reactions are carefully evaluated based on available experimental and theoretical results. The high pressure limit k1,∞ for NH 2 + H (+M) ⇄ NH 3 (+M) (R1) is calculated to be essentially the collision frequency, indicating that dissociation of ammonia in combustion processes will be at or close to the low pressure limit even at engine and gas turbine conditions. The chemical kinetic model is validated against reported shock tube measurements of NH 3 , NH 2 , and NH in ammonia pyrolysis. Predictions are in good agreement with observations for dilute conditions (≤ 0.5% NH 3 ), but the model appears to underpredict the NH 3 consumption rate at longer times in less dilute mixtures. At short reaction times, thermal dissociation of NH3, together with the NH 3 + H reaction, controls conversion. At longer times, secondary reactions involving NH 2 and NH become important due to their impact on the radical pool. Predictions become sensitive to formation and consumption of diazene (tHNNH and cHNNH). Several of the key steps in the ammonia pyrolysis mechanism are radical-radical reactions that are difficult to measure accurately and challenging to calculate theoretically, and a more comprehensive experimental characterization is desirable to support further model development.

10 SYNTHETIC FUELS↗

CFD modeling of non-catalytic, partial-oxidation engine reformer for flare mitigation

Flaring associated natural gas is commonly employed in the oil and gas industry to reduce methane (CH 4 ) emissions but generates carbon dioxide (CO 2 ) and harmful pollutants, significantly contributing to air pollution and posing risks to public health. To mitigate this impact, M2X Energy Inc. has developed a small-scale, modular gas-to-methanol system. This system features an engine reformer that performs fuel-rich partial oxidation of wellhead gas to produce syngas—a mixture of carbon monoxide (CO) and hydrogen (H 2 )—followed by a downstream reactor for methanol synthesis. This study focused on computational fluid dynamics (CFD) modeling of the engine reformer to simulate partial oxidation chemistry, predict the rich-burn operating limit, and assess syngas quality, ultimately aiding in design and operational optimization. The CFD model, developed within a Reynolds-Averaged Navier-Stokes (RANS) turbulence framework, incorporated sub-models for turbulent combustion, a chemical mechanism with polycyclic aromatic hydrocarbon (PAH) pathways, and soot emissions to accurately capture the fuel-rich, turbulent jet ignition and combustion processes. Model validation against experimental data showed good agreement across pre- and main-chamber pressures, apparent heat release rates, and exhaust gas concentrations of key species (H 2 , CO, CO 2 , CH 4 ) for varying intake equivalence ratios. Here, the model identified a rich-burn operating limit near a fuel-air equivalence ratio of 2.35, consistent with experimental observations. Furthermore, syngas quality analysis revealed that extending the rich-burn limit through engine reformer optimization could enhance syngas production, contributing to higher methanol synthesis efficiency.

Computational Fluid Dynamics↗

Quantitative investigation of sooting dynamics in droplet combustion using an automated image analysis algorithm

This paper reports an image analysis approach using a newly-developed open-source program to extract quantitative measurements of soot volume fraction (SVF) from digital video images of burning n-heptane droplets. The automated program developed in this work can analyze images of fixed and untethered droplets to quantify sooting dynamics. The images analyzed in the program were taken from experiments carried out in the Multi-user Droplet Combustion Apparatus (MDCA) onboard the International Space Station (ISS). In these experiments, video imaging of burning droplets was obtained using backlighting by a laser diode with a wavelength of 653 nm. Here, the light was collimated before it passed through the droplet and soot-containing region, after which the light was then attenuated and projected onto the camera’s sensors. This technique facilitates the measurements of SVF based on the principles of the full field light extinction method (FFLEM). The measurements provide quantitative data that reveal the sooting dynamics of liquid fuels during droplet combustion processes. The analyses of a soot-attenuating image (ISS n-heptane, untethered droplet) at an instant during the burning show that the SVF distribution has a peak at the soot shell location. It then decreases due to soot oxidation when the location is further away from the burning droplet. Regarding temporal effects on the maximum SVF (SVF max ), results show that SVF max first increases after the burning is initiated until a peak value is reached, after which SVF max decreases. The SVF max values identified in this study for n-heptane are quantitatively consistent with previously reported values for fiber-supported droplets and are reached relatively early in the burning history. n-Heptane images are also analyzed to show the effects of initial droplet sizes on the maximum soot volume fraction. Results show that SVF max decreases with increasing initial droplet size, which is consistent with visual observations of less soot formed and dimmer flame brightness as Do increases.

42 ENGINEERING↗

Coal polymer composites prepared by fused deposition modeling (FDM) 3D printing

Coal is a vital energy resource worldwide, but pollutants and greenhouse gases from its combustion cause environmental problems. To explore the non-combustion approach to use and valorize coal, anthracite and lignite were blended with polyamide 12 (PA 12) through FDM printing in this work and compared in the composites. By adding lignite, Young’s modulus improved with increasing loading to 50 wt% while tensile strength leveled off among the composites, compared to that of PA 12. By contrast, the addition of anthracite decreased the tensile performance at all loadings. Rheology tests and morphology analyses suggested that the interactions between fillers (anthracite and lignite) and PA 12 may cause differences in tensile properties. In addition, the printed lignite composites showed improved thermal conductivity (~ twofold), indicating lignite demonstrates the potential to build functional composites. This work provides a strategy to use lignite in composites by 3D printing for value-added products and reduces the demand for petroleum-based polymers. Overall, our approach diverts lignite from combustion processes and alleviates the negative impact of lignite use on the environment.

36 MATERIALS SCIENCE↗

Reactivity of net-zero carbon alcohol fuels and their corresponding aldehyde intermediates on PGM-based commercial oxidation catalysts for lean-burn emissions control

Alcohol net-zero carbon fuels will play a significant role in decarbonization of the hard-to-electrify transportation sectors. However, the combustion process in alcohol-fueled engines generate toxic aldehydes. For commercialization of net-zero carbon fuels on engines, compliance with the stringent U.S. EPA regulations is necessary. Here, this contribution focuses on reactivity of alcohols and aldehydes on commercial diesel oxidation catalysts (DOC) to inform selection of future net-zero carbon fuels. Alcohol (and aldehyde) light-off temperatures were measured on aged DOCs under full synthetic engine-exhaust conditions. Methanol was the most reactive, while ethanol completely oxidized at higher temperatures. Alcohols typically formed less reactive aldehyde intermediates. DRIFTS revealed strongly adsorbing surface formates and acetates during methanol and ethanol oxidation, respectively, resulting in inhibition effects. Preliminary alcohol oxidation mechanisms combining flow reactor and DRIFTS observations are presented. Aldehydes inhibited CO oxidation. Minimal N 2 O formation was observed for the alcohols investigated.

Alcohol oxidation↗

An experimental and kinetic modeling study of the pyrolysis of isoprene, a significant biogenic hydrocarbon in naturally occurring vegetation fires

Isoprene dominates the carbon flux emitted by vegetation and constitutes 40% of non-methane biogenic emissions worldwide. Despite pyrolysis experiments at temperatures above 1000 K showing a link between isoprene combustion and aromatic species formation, comprehensive mechanistic research on isoprene is scarce in the literature. Here, in this work, we carry out an experimental and theoretical study to build, for the first time, a chemical kinetic model describing isoprene pyrolysis. The formation of polycyclic aromatic hydrocarbon (PAH) precursor species, often observed in vegetation fire plumes, is partially explained by isoprene pyrolysis experiments and theoretical modeling. Molecular dynamics (MD) simulations unveil reaction pathways from allylic isoprenyl radicals to allene and cyclopentadiene (CPD) intermediates, two relevant species detected in the experiments. Rate constants for these identified pathways are calculated using variational transition state theory to update the kinetic model, which is validated against single-pulse shock tube (SPST), and jet-stirred reactor (JSR) experimental data in the temperature range of 850–1690 K. The kinetic model presents satisfactory agreement with the SPST experimental data, and a reaction pathway analysis shows that association of propargyl radicals results in benzene formation. The JSR pathway analysis also identifies the prominent reactions for CPD, benzene, styrene, and toluene formation. Our model does not reproduce the CPD experimental profiles, indicating that additional studies are necessary. Overall, our findings advance the understanding of isoprene pyrolysis and its related atmospheric pollutants in naturally occurring vegetation fires where smoldering and oxygen-deficient combustion processes are present.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigation of near-field jet stability of a single-hole injector based on fast X-ray phase contrast imaging and image feature matching

Fuel spray is very effective in controlling the combustion process to improve engine performance and reduce emissions. Understanding the spray unstability during the injection process is of importance to improve the control of spray characteristics and engine operation. In this study, near-field biodiesel jets were recorded using fast X-ray phase contrast imaging and the flow features inside the jet were extracted using Speeded Up Robust Features (SURF) method. Here, the image similarity by feature matching was successfully used to represent the near-field jet stability. Based on the jet stability, an injection process can be divided into five stages: an unstable stage at needle opening, a partially stable transition stage at needle opening, a stable stage, a stable transition stage at needle closing and an unstable stage at needle closing. The ranges of needle lift for five stages were also determined. The jet unstability is highly related to the cavitation formation and gas purging process during needle opening. The variation of stable jet feature is dependent on the needle lift at needle closing. Higher needle lift for the similar jet feature at needle opening indicates a hydraulic delay compared to needle closing. Finally, the possible reasons of jet feature formation and feature detection used on the multi-hole injector are discussed.

33 ADVANCED PROPULSION SYSTEMS↗

Development of simplified model for injection rate prediction of diesel injectors during transient and steady operation

Determining the injection rate of the diesel injector during the transient short injection operations is a critical matter to enhance the combustion process by improving air/fuel mixture formation. In this regard, numerous injection models have been suggested in the literature to predict the injection rate accurately. However, such algorithms have not precisely predicted the rate of injection (ROI) in transient short injection events. In addition, most of those models require many input parameters to characterize hydraulic and mechanical subsystems in the injector, which can make them inconvenient to tune for different injector specifications, in other words not suitable for universal usage. Therefore, our study aims to develop a simple injection model that can predict injection rate precisely in the short and long injection durations considering relatively fewer input parameters. The model traces the pressure variation inside the sac based on the bulk modulus theory to predict nozzle exit velocity, thus the injection rate of the injector. In the algorithm, the bulk modulus of fuel (E) and discharge coefficients of the nozzle hole and needle seat (C d,H and C d,N ) have been considered to vary rather than set constant during the injection process since such flow parameters would have a critical impact on the flow development at the transient stage, thus affecting the injection rate of diesel injectors. Here with this modelling strategy, the accuracy of the new model on ROI prediction was confirmed with acceptable model error for both short and long injection durations by validating against experimental results. To understand the effect of the new model scheme on ROI prediction, ROI results with the new model have been discussed by comparing it with the ROI results predicted with constant flow parameters.

42 ENGINEERING↗

Examining experimental nitrogen-based emissions trends from ammonia/diesel and ammonia/hydrogen/diesel combustion

Ammonia has garnered interest as an alternative fuel for power sectors with heavy payload and distance requirements, such as shipping. In this study, ammonia was used in a dual-fuel compression-ignition combustion strategy to overcome some of its technical barriers, using a diesel pilot to ignite a premixed mixture of ammonia and air. Mixtures of premixed ammonia and hydrogen were also explored to evaluate whether the inclusion of hydrogen improves nitrogen-based emissions from the combustion process. A single-cylinder version of a Cummins ISB 6.7 L engine platform was used to experimentally study these effects at various global air/fuel ratios and hydrogen energy fractions. Hydrogen inclusion produced pronounced NOx and N2O emissions, while inclusion of trapped residuals increased N2O but reduced NOx. The two most recent and relevant mechanisms available in the literature—those from Xu and Zhang-Ren-Kokjohn—were used in a chemical kinetics analysis to examine the observed differences in the NOx trends from two dual-fuel ammonia/diesel datasets: (1) in which a portion of the premixed ammonia was substituted with hydrogen and (2) in which the effect of hot trapped residuals was evaluated with only ammonia/air premixed mixtures. The analysis with both mechanisms showed agreement with experimental trends; however, contributions from thermal vs. fuel-borne NOx pathways showed disagreement. A reaction pathway analysis showed that the HNO to NO pathway was the key to NO formation in the mixture.

Tyrewala, Daanish [ORNL] (ORCID:0000000208599324)↗

Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine

Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.

Direct injection↗