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Turbulent Jet Ignition is an advanced pre-chamber initiated combustion system for an otherwise standard spark ignition engine found in current on-road vehicles. This next-generation pre-chamber design overcomes previous packaging obstacles by simply replacing the spark plug in a modern four-valve, pent roof spark ignition engine. Turbulent Jet Ignition enables very fast burn rates due to the ignition system producing multiple, distributed ignition sites, which consume the main charge rapidly and with minimal combustion variability. The fast burn rates allow for increased levels of dilution (lean burn and/or EGR) when compared to conventional spark ignition combustion, with dilution levels being comparable to other low temperature combustion technologies (homogeneous charge compression ignition - HCCI) without the complex control drawbacks.

This paper presents a computational investigation of the validity of eddy current testing (ECT) for defects embedded in steel using parametrically designed defects. Of particular focus is the depths at which defects can be detected through ECT. Building on this we characterize interior defects by parametrically describing them and then examining the response fields through measurement. Thereby we seek to establish the depth and direction of detectable cracks. As a second step, we match measurements from eddy current excitations to computed fields through finite element optimization. This develops further our previously presented methods of defect characterization. Here rough contours of synthesized shapes are avoided by a novel scheme of averaging neighbor heights rather than using complex Bézier curves, constraints and such like. This avoids the jagged shapes corresponding to mathematically correct but unrealistic synthesized shapes in design and nondestructive evaluation.

Turbulent jet ignition is a pre-chamber ignition enhancement method that produces a distributed ignition source through the use of a chemically active turbulent jet which can replace the spark plug in a conventional spark ignition engine. In this paper combustion visualization and characterization was performed for the combustion of a premixed propane/air mixture initiated by a pre-chamber turbulent jet ignition system with no auxiliary fuel injection, in a rapid compression machine. Three different single orifice nozzles with orifice diameters of 1.5 mm, 2 mm, and 3 mm were tested for the turbulent jet igniter pre-chamber over a range of air to fuel ratios. The performance of the turbulent jet ignition system based on nozzle orifice diameter was characterized by considering both the 0-10 % and the 10-90 % burn durations of the pressure rise due to combustion.

Deep learning based approaches for object detection are heavily dependent on the nature of data used for training, especially for vehicles driving in cluttered urban environments. Consequently, the performance of Convolutional Neural Network (CNN) architectures designed and trained using data captured under clear weather and favorable conditions, could degrade rather significantly when tested under cloudy and rainy conditions. This naturally becomes a major safety issue for emerging autonomous vehicle platforms relying on CNN based object detection methods. Furthermore, despite a noticeable progress in the development of advanced visual deraining algorithms, they still have inherent limitations for improving the performance of state-of-the-art object detection. In this paper, we address this problem area by make the following contributions.

Over the years, many studies have examined the natural gas flame characteristics with either CO2, H2O, or N2 dilution in order to investigate the exhaust gas recirculation (EGR) effect on the performance of natural gas vehicles. However, studies analyzing the actual EGR concentration are very scarce. In the present study, spherically expanding flames were employed to investigate the EGR effect on the laminar flame speed (LFS) and the burned gas Markstein length (Lb) of premixed CH4/air flames at 373 K and 3 bar. The EGR mixture was imitated with a mixture of 9.50% CO2 + 19.01% H2O + 71.49% N2 by mole. EGR ratios of 0%, 5%, 10%, and 15% were tested. Experimental results show that LFS values are lowered by 20-23%, 38-43% and 53-54% due to 5%, 10% and 15% EGR, respectively. Additionally, it was observed that Lb values slightly increase at high equivalence and EGR ratios, where CH4 flames are more stable and more stretched.

The automotive industry is subject to stringent regulations in emissions and growing customer demands for better fuel consumption and vehicle performance. Engine calibration, a process that optimizes engine performance by tuning engine controls (actuators), becomes challenging nowadays due to significant increase of complexity of modern engines. The traditional sweep-based engine calibration method is no longer sustainable. To tackle the challenge, this work considers two powerful global optimization methods: genetic algorithm (GA) and Bayesian optimization for steady-state engine calibration for single speed-load point. GA is a branch of meta-heuristic methods that has shown a great potential on solving difficult problems in automotive engineering. Bayesian optimization is an efficient global optimization method that solves problems with computationally expensive testing such as hyperparameter tuning in deep neural network (DNN), engine testing, etc.

This study focuses on the combustion visualization of spark ignition combustion in an optical single cylinder engine using natural gas and propane at several air to fuel ratios and speed-load operating points. Propane and natural gas fuels were compared as they are the most promising gaseous alternative fuels for reciprocating powertrains, with both fuels beginning to find wide market penetration on the fleet level across many regions of the world. Additionally, when compared to gasoline, these gaseous fuels are affordable, have high knock resistance and relatively low carbon content and they do not suffer from the complex re-fueling and storage problems associated with hydrogen.

Camless Variable Valve Actuation (VVA) technologies have been known for improving fuel economy, reducing emissions, and enhancing engine performance. VVA can be divided into electro-magnetic, electro-hydraulic, and electro-pneumatic actuation. A family of camless VVA designs (called LGD-VVA or Gongda-VVA) has been presented in an earlier SAE publication (SAE 2007-01-1295) that consists of a two-spring actuation, a bypass passage, and an electrohydraulic latch-release mechanism. The two-spring pendulum system is used to provide efficient conversion between the moving mass kinetic energy and the spring potential energy for reduced energy consumption and to be more robust to the operational temperature than the conventional electrohydraulic actuation; and the electrohydraulic mechanism is intended for latch-release function, energy compensation and seating velocity control.

Air-to-fuel (A/F) ratio is the mass ratio of the air-to-fuel mixture trapped inside a cylinder before combustion begins, and it affects engine emissions, fuel economy, and other performances. Using an A/F ratio and dual-fuel ratio control oriented engine model, a multi-input-multi-output (MIMO) sliding mode control scheme is used to simultaneously control the mass flow rate of both port fuel injection (PFI) and direct injection (DI) systems. The control target is to regulate the A/F ratio at a desired level (e.g., at stoichiometric) and fuel ratio (ratio of PFI fueling vs. total fueling) to any desired level between zero and one. A MIMO sliding mode controller was designed with guaranteed stability to drive the system A/F and fuel ratios to the desired target under various air flow disturbances.

Human intraspecific variation is a complex problem, but may be better understood by using computational models in tandem with knowledge about the genetic bases of phenotypic traits. These results can be used in a multitude of settings. To move closer to this goal, biologically-realistic mappings between genotype and phenotype are constructed using genetic algorithm and neural network-like models. These models allow for gene-gene and gene-environment interactions to be characterized in the resulting phenotype. Two types of model are introduced: a simple, two-layer model, and a more complex model. The final section will focus on trends of growth and development in relation to relationship to modeling anthropometric traits and other morphological phenomena.

Lower extremity (knee) injury prediction resulting from impact trauma is currently based on a bone fracture criterion derived from experiments on predominantly aged cadavers. Subsequent experimental and theoretical studies indicate that more aged, pathological specimens require higher, not lower, loads to initiate bone fracture. This suggests that a bone fracture criterion based solely on aged specimens may not be representative of the current driving population. In the current study, we sought to determine if cadaver age, physical size, sex, baseline joint pathology, or patellar geometry correlated with fracture load. An analysis was made of data from previous impact experiments conducted on fifteen isolated cadaver knees using a consistent impact protocol. The protocol consisted of sequentially increasing the impact energy with a rigid interface until gross fracture. Gross bone fractures occurred at loads of 6.9±2.0 kN (range 3.2 to 10.6 kN) using this protocol.

In developing a direct injection gasoline engine, the in-cylinder fuel air mixing is key to good performance and emissions. High speed visualization in an optically accessible single cylinder engine for direct injection gasoline engine applications is an effective tool to reveal the fuel spray pattern effect on mixture formation The fuel injectors in this study employ the unique multi-hole turbulence nozzles in a PFI-like (Port Fuel Injection) fuel system architecture specifically developed as a Low Pressure Direct Injection (LPDI) fuel injection system. In this study, three injector sprays with a narrow 40° spray angle, a 60°spray angle with 5°offset angle, and a wide 80° spray angle with 10° offset angle were evaluated. Image processing algorithms were developed to analyze the nature of in-cylinder fuel-air mixing and the extent of fuel spray impingement on the cylinder wall.

Electro-pneumatic valve actuators are used to eliminate the cam shaft of a traditional internal combustion engine. They are used to control the opening timing, duration, and lift of both intake and exhaust valves. A physics based nonlinear mathematical model called the level one model was built using Newton's law, mass conservation and thermodynamic principles. A control oriented model, the level two model, was created by partially linearizing the level one model for model reference parameter identification. This model reduces computational throughput and enables real-time implementation. A model reference adaptive control system was used to identify the nonlinear parameters that were needed for generating a feedforward control signal. The closed-loop valve lift tracking, valve opening and closing timing control strategies were proposed.

The requirement of reduced emissions and improved fuel economy led the introduction of direct-injection (DI) spark-ignited (SI) engines. Dual-fuel injection system (direct-injection and port-fuel-injection (PFI)) was also used to improve engine performance at high load and speed. Ethanol is one of the several alternative transportation fuels considered for replacing fossil fuels such as gasoline and diesel. Ethanol offers high octane quality but with lower energy density than fossil fuels. This paper presents the combustion characteristics of a single cylinder dual-fuel injection SI engine with the following fueling cases: a) gasoline for PFI and DI, b) PFI gasoline and DI ethanol, and c) PFI ethanol and DI gasoline. For this study, the DI fueling portion varied from 0 to 100 percentage of the total fueling over different engine operational conditions while the engine air-to-fuel ratio remained at a constant level.

Injuries to the lower extremities are common during car accidents because the lower extremity is typically the first point of contact between the occupant and the car interior. While injuries to the knee, ankle and hip are usually not life threatening, they can represent a large societal burden through treatment costs, lost work days and a reduced quality of life. The aim of the current study was to specifically study injuries associated with the knee and to propose a methodology which could be used to prevent future knee injuries. To understand the scope of this problem, a study was designed to identify injury trends in car crashes for the years 1979-1995. The NASS (National Accident Sampling System) showed that 10% of all injuries were to the knee, second only to head and neck injuries. Most knee injuries resulted from knee-to-instrument panel contact. Subfracture injuries were most common (contusions, abrasions, lacerations) followed by gross fracture injuries.

This paper focuses on the numerical investigation of the mixing and combustion of ethanol and gasoline in a single-cylinder 3-valve direct-injection spark-ignition engine. The numerical simulations are conducted with the KIVA code with global reaction models. However, an ignition delay model mitigates some of the deficiencies of the global one-step reaction model and is implemented via a two-dimensional look-up table, which was created using available detailed kinetics models. Simulations demonstrate the problems faced by ethanol operated engines and indicate that some of the strategies used for emission control and downsizing of gasoline engines can be employed for enhancing the combustion efficiency of ethanol operated engines.

To increase robustness of the crush mode and to decrease repair costs after a crash, it is desirable for front and rear rails in an automotive vehicle to crush progressively. Here, progressive crush refers to a mode of axial crush that initiates near the tip of the rail and then progresses rearward in a controlled fashion. In this study, a new strategy is investigated to achieve progressively crushing designs during an automated design optimization study. This strategy employs the definition of crush zones along the length of a rail, and a design optimization problem statement that encourages maximum energy absorption in any particular crush zone to occur prior to any energy absorption in rearward zones. It is demonstrated that high performing designs with progressive crush can be obtained using the proposed approach.

Adaptive Cruise Control (ACC) technology is presently emerging in the automotive market as a convenience function intended to reduce driver workload. It allows the host vehicle to maintain a set speed and distance from preceding vehicles by a forward object detection sensor. The forward object detection sensor is the focal point of the ACC control system, which determines and regulates vehicle acceleration and deceleration through a powertrain torque control system and an automatic brake control system. This paper presents a design of an automatic braking system that utilizes a microprocessor-controlled brake hydraulic modulator. The alternatively qualified automatic braking means is reviewed first. The product level requirements of the performance, robustness, and durability for an automatic brake system are addressed. A brief overview of the presented system architecture is described.

The present communication reports on processing and interpreting velocity measurements in the wake of a cooling fan. Velocity data are typically phase averaged to create statistics that would be observed in a rotating frame of reference. The difference between any given instantaneous measurement and the phase mean value is often referred to as the fluctuating component of velocity. These deviations can be caused by a variety of mechanisms (blade vibration for example) and do not necessarily represent “turbulence”. A different approach using an eigenfunction decomposition of the data is used on a sample data set to help distinguish between cycle-to-cycle variations and turbulence.

In order to improve the reliability of fan design and the prediction of underhood engine cooling based on CFD, Valeo Motors and Actuators and Michigan State University have teamed up to develop a comprehensive experimental and numerical database. The initial focus has been on the simulations of the isolated fan environment in two different test facilities. To understand the discrepancies observed in the comparisons of integral performances, the first detailed hot wire measurements on the MSU test facility have been collected. The data are split into mean velocity components and RMS fluctuations. The former are successfully compared to three detailed turbulent numerical simulations of the corresponding facilities.