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Ducted Fuel Injection (DFI) engines have emerged as a promising technology in the pursuit of a clean and efficient combustion process. This article aims at elucidating the effect of piston geometry on the engine performance and emissions of a metal DFI engine. Three different types of pistons were investigated and the main piston design features including the piston bowl diameter, piston bowl slope angle, duct angle and the injection nozzle position were examined. To achieve the target, computational fluid dynamics (CFD) simulations were conducted coupled to a reduced chemical kinetics mechanism. Extensive validations were performed against the measured data from a conventional diesel engine. To calibrate the soot model, genetic algorithm and machine learning methods were utilized. The simulation results highlight the pivotal role played by piston bowl diameter and fuel injection angle in controlling soot emissions of a DFI engine.

Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

Trim materials are often used for vibroacoustic energy absorption purposes within vehicles. To estimate the sound impact at a driver’s ear, the substructuring approach can be applied. Thus, transfer functions are calculated starting from the acoustic source to the car body, from the car body to the trim and, finally, from the trim to the inner cavity where the driver is located. One of the most challenging parts is the calculation of the transfer functions from the car body inner surface to the bottom trim surface. Commonly, freely laying mass-spring systems (trims) are simulated with a fixed boundary and interface phenomena such as friction, stick-slip or discontinuities are not taken into consideration. Such an approach allows for faster simulations but results in simulations strongly overestimating the energy transfer, particularly in the frequency range where the mass-spring system’s resonances take place.

Methanol is one of the most promising fuels for the decarbonization of the off-road and transportation sectors. Although methanol is typically seen as an alternative fuel for spark ignition engines, mixing-controlled compression ignition (MCCI) combustion is typically preferred in most off-road and medium-and heavy-duty applications due to its high reliability, durability and high-efficiency. In this paper, the potential of using ignition enhancers to enable methanol MCCI combustion was investigated. Methanol was blended with 2-ethylhexyl nitrate (EHN) and experiments were performed in a single-cylinder production-like diesel research engine, which has a displacement volume of 0.83 L and compression ratio of 16:1. The effect of EHN has been evaluated with three different levels (3%vol, 5%vol, and 7%vol) under low- and part-load conditions. The injection timing has been swept to find the stable injection window for each EHN level and load.

Ethanol blending is one method that can be used to reduce knock in spark ignition engines by decreasing the autoignition reactivity of the fuel and modifying its laminar flame speed. In this paper, the effects of ethanol blending on knock propensity and flame speed of petroleum and low-carbon gasoline fuels is analyzed. To do so, surrogate fuels were formulated for methanol-to-gasoline (MTG) and ethanol-to-gasoline (ETG) based on the fuels’ composition, octane number, and select physical properties; and 0-D and 1-D chemical kinetics simulations were performed to investigate reactivity and laminar flame speed, respectively. Results of MTG and ETG were compared against those of PACE-20, a well-characterized surrogate for regular E10 gasoline. Similarly to PACE-20, blending MTG and ETG with ethanol increases the fuel’s research octane number (RON) and sensitivity.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and soot emissions, but rapid control of the combustion timing remains a challenge. Partial Fuel Stratification (PFS) was demonstrated to be an effective approach to control combustion in LTGC engines. PFS is produced by a double-direct injection (DI) strategy with most of the fuel injected early in the cycle and the remainder of the fuel supplied by a second injection at a variable time during the compression stroke to vary the amount of stratification. Adjusting the stratification changes the combustion phasing, and this can be done on cycle-to-cycle basis by adjusting the injection timing. In this paper, the ability of PFS to control the combustion during wide engine load sweeps is assessed for regular gasoline and gasoline doped with 2-ethylhexyl nitrate (EHN). For PFS, the load control range is limited by combustion instability and poor combustion efficiency at low loads.

Methanol emerges as a compelling renewable fuel for decarbonizing engine applications due to a mature industry with high production capacity, existing distribution infrastructure, low carbon intensity and favorable cost. Methanol’s high flame speed and high autoignition resistance render it particularly well-suited for spark-ignition (SI) engines. Previous research showed a distinct phenomenon, known deflagration-based knock in methanol combustion, whereby knocking combustion was observed albeit without end-gas autoignition. This work studies the implications of deflagration-based knock on noise emissions by investigating the knock intensity and combustion noise at knock-limited operation of methanol in a single-cylinder direct-injection SI engine operated at both stoichiometric and lean (λ = 2.0) conditions. Results are compared against observations from a premium-grade gasoline.

Optimizing fuel injection spray is essential to comply with stringent future emission regulations for hybrid vehicles and internal combustion engine vehicles, and the spray characteristics and geometry must be robust for various engine operating conditions. This study presents experimental and numerical assessments of spray for lateral-mounted gasoline direct injection (GDI) sprays with different plume arrangements to analyze collapse characteristics, which can significantly deteriorate the geometry and characteristics of fuel sprays. Novel spray characterization methods are applied to analyze complex spray collapse behaviors using LED-based diffusive back-illuminated extinction imaging (DBIEI) and 3D computed tomographic (CT) image reconstruction. High-fidelity computational fluid dynamics (CFD) simulations are performed to analyze the detailed spray characteristics besides experimental characterization.

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. In the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied.

For 2D surface temperature monitoring applications, a variant of Electrical Impedance Tomography (EIT) was evaluated computationally in this study. Literature examples of poor sensor performance in the center of the 2D domains away from the side electrodes motivated these efforts which seek to overcome some of the previously noted shortcomings. In particular, the use of ‘sensing skins’ with novel tailored baseline conductivities was examined using the EIDORS package for EIT. It was found that the best approach for detecting a temperature hot spot depends on several factors such as the current injection (stimulation) patterns, the measurement patterns, and the reconstruction algorithms. For well-performing combinations of these factors, customized baseline conductivities were assessed and compared to the baseline uniform conductivity.

Molecular decomposition is a key chemical process in combustion systems. Particularly, the spatio-temporal information related to a fuel’s molecular breakdown is of high-importance regarding the development of combustion models and more specifically about chemical kinetic mechanisms. Most experiments rely on a variety of ultraviolet or infrared techniques to monitor the fuel breakdown process in 0-D type experiments such as those performed in shock-tubes or rapid compression machines. While the information provided by these experiments is necessary to develop and adjust kinetic mechanisms, they fail to provide the necessary data for applied combustion models to be predictive regarding the fuel’s molecular breakdown. In this work, we investigated the molecular decomposition of a fuel by applying high-speed planar laser Rayleigh scattering (PLRS).

Knock in spark-ignition (SI) engines has been a subject of many research efforts and its relationship with high efficiency operating conditions keeps it a contemporary issue as engine technologies push classical limits. Despite this long history of research, literature is lacking coherent and generalized descriptions of how knock is affected by changes in the full cylinder temperature field, residence time (engine speed), and air/fuel ratio. In this work, two dimensionless numbers are applied to fully 3D SI conditions. First, the characteristic time of autoignition (ignition delay) is compared against the characteristic time of end-gas deflagration, which was used to predict knocking propensity. Second, the temperature gradient of the end-gas is compared against a critical detonation-based temperature gradient, which predicts the knock intensity.

As a part of NASA’s efforts in space, options are being examined for an Artemis moon base project to be deployed. This project requires a system of interconnected, but separate, DC microgrids for habitation, mining, and fuel processing. This in-place use of power resources is called in-situ resource utilization (ISRU). These microgrids are to be separated by 9-12 km and each contains a photovoltaic (PV) source, energy storage systems (ESS), and a variety of loads, separated by level of criticality in operation. The separate microgrids need to be able to transfer power between themselves in cases where there are generation shortfall, faults, or other failures in order to keep more critical loads running and ensure safety of personnel and the success of mission goals. In this work, a 2 grid microgrid system is analyzed involving a habitation unit and a mining unit separated by a tie line.

Renewably sourced hydrogen is seen as promising sustainable carbon-free alternative to conventional fossil fuels for use in hard to decarbonize sectors. As the hydrogen supply builds up, dual-fuel hydrogen-diesel engines have a particular advantage of fuel flexibility as they can operate only on diesel fuel in case of supply shortages, in addition to the simplicity of engine modification. The dual-fuel compression ignition strategy initiates combustion of hydrogen using short pilot-injections of diesel fuel into the combustion chamber. In the context of such engine combustion process, the impact of hydrogen addition on the ignition and combustion behavior of a pilot diesel-spray is investigated in a heavy-duty, single-cylinder, optical engine. To this end, the spatial and temporal evolution of two-stage autoignition of a diesel-fuel surrogate, n-heptane, injected into a premixed charge of hydrogen and air is studied using optical diagnostics.

The thermal operational safety (TOS) of a vehicle ensures that no component exceeds its critical temperature during vehicle operation. To enhance the current TOS validation process, a data-driven approach is proposed to predict maximum component temperatures of a new vehicle project by leveraging the historical thermal wind tunnel data from previous vehicle projects. The approach intends to support engineers with temperature predictions in the early phase and reduce the number of wind tunnel tests in the late phase of the TOS validation process. In the early phase, all measurements of the new vehicle project are predicted. In the late phase, a percentage of measurements with the test vehicle used for the model training and the remaining tests are predicted with the trained ML model. In a first step, data from all wind tunnel tests is extracted into a joint dataset together with metadata about the vehicle and the executed load case.

Predicting the aerodynamic performance of an aircraft in icing conditions is critical as failures in an aircraft’s ice protection system can compromise flight safety. Aerodynamic effects of icing have typically relied on RANS modeling, which usually struggles to predict stall behavior, including those induced by surface roughness. Encouraged by recent studies using LES that demonstrate the ability to predict stall characteristics on full aircraft with smooth wings at an affordable cost [1], this study seeks to apply this methodology to icing conditions. Measurements of lift, drag, and pitching moments of a NACA23012 airfoil under clean and iced conditions are collected at Re = 1.8M. Using laser scanned, detailed representations of the icing geometries, LES calculations are conducted to compare integrated loads against experimental measurements in both clean and iced conditions at various angles of attack through the onset of stall [2].

Modeling of icing is important for the design of aircraft lifting surfaces and for the design of efficient propulsion systems. The computational modeling of ice accretion prediction is important to replace the expensive experimental techniques for calculating the ice shapes in Icing tunnels, and the first step toward modeling ice accretion is to accurately compute the droplet collection efficiency which acts as the input to the accretion model. In this work, we perform large-eddy simulations of supercooled droplet transport and impingement onto complex aircraft geometries using a Lagrangian particle approach. We assess the improvement in modeling droplet impingement by computing the droplet collection efficiency and by comparing with the existing experimental data.

A novel advanced combustion strategy that employs the kinetically controlled compression ignition of gasoline whose autoignition is sensitive to fuel concentration is termed Low Temperature Gasoline Combustion. The LTGC method can achieve high thermal efficiency with a commercially available fuel while generating ultra-low soot and NOx emissions relative to the conventional combustion modes. At high loads, a double direct injection (D-DI) strategy is used where the first injection generates a background premixed charge while a second compression stroke injection controls the level of fuel stratification on a cycle-to-cycle basis to manage the heat release rates. With lower loads, this combustion performance of this D-DI strategy decreases as the background charge becomes increasingly lean. Instead, a single direct injection (S-DI) is used at lower loads to maintain an adequate combustion efficiency.

Liquefied Petroleum Gas (LPG), as a common alternative fuel for internal combustion engines is currently widespread in use for fleet vehicles. However, a current majority of the LPG-fueled engines, uses port-fuel injection that offers lower power density when compared to a gasoline engine of equivalent displacement volume. This is due to the lower molecular weight and higher volatility of LPG components that displaces more air in the intake charge due to the larger volume occupied by the gaseous fuel. LPG direct-injection during the closed-valve portion of the cycle can avoid displacement of intake air and can thereby help achieve comparable gasoline-engine power densities. However, under certain engine operating conditions, direct-injection sprays can collapse and lead to sub-optimal fuel-air mixing, wall-wetting, incomplete combustion, and increased pollutant emissions.