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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.

Continuous efforts to improve thermal efficiency and reduce exhaust emissions of internal combustion engines have resulted in development of various solutions towards improved lean burn ignition systems in spark ignition engines. The Dual Mode, Turbulent Jet Ignition (DM-TJI) system is one of the leading technologies in that regard which offers higher thermal efficiency and reduced NOx emissions due to its ability to operate with very lean or highly dilute mixtures. Compared to other pre-chamber ignition technologies, the DM-TJI system has the distinct capability to work with a very high level of EGR dilution (up to ~40%). Thus, this system enables the use of a three-way catalyst (TWC). Auxiliary air supply for pre-chamber purge allows this system to work with such high EGR dilution rate. This work presents the results of experimental investigation carried out with a Dual Mode, Turbulent Jet Ignition (DM-TJI) optical engine equipped with a cooled EGR system.

Piston temperature plays a major role in determining details of fuel spray vaporization, fuel film deposition and the resulting combustion in direct-injection engines. Due to different heat transfer properties that occur in optical and all-metal engines, it becomes an inevitable requirement to verify the piston temperatures in both engine configurations before carrying out optical engine studies. A novel Spot Infrared-based Temperature (SIR-T) technique was developed to measure the piston window temperature in an optical engine. Chromium spots of 200 nm thickness were vacuum-arc deposited at different locations on a sapphire window. An infrared (IR) camera was used to record the intensity of radiation emitted by the deposited spots. From a set of calibration experiments, a relation was established between the IR camera measurements of these spots and the surface temperature measured by a thermocouple.

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.

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.

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.

Injury to the lower extremity during an automotive crash is a significant problem. While the introduction of safety features (i.e. seat belts, air bags) has significantly reduced fatalities, lower extremity injury now occurs more frequently, probably for a variety of reasons. Lower extremity trauma is currently based on a bone fracture criterion derived from human cadaver impact experiments. These impact experiments, conducted in the 1960's and 70's, typically used a rigid impact interface to deliver a blunt insult to the 90° flexed knee. The resulting criterion states that 10 kN is the maximum load allowed at the knee during an automotive crash when certifying new automobiles using anthropomorphic dummies. However, clinical studies suggest that subfracture loading can cause osteochondral microdamage which can progress to a chronic and debilitating joint disease.

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.

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.

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.

In an effort to create computer models to promote rapid, cost-effective prototyping while easing design changes, more information about how people interact with seats is needed. Predicting the occupant location, their geometry, and motion within a vehicle leads to a better determination of safety restraint location, controls reach, and visibility - factors that affect the overall operation of the vehicle. Based on the Michigan State University JOHN model, which provides a biomechanical simulation of the torso posture, experiments were conducted to examine the change of postures due to seat and interior package factors. The results can be incorporated into the posture prediction model of the RAMSIS program to give a more detailed prognosis of the spine curvature and refine the model-seat interactions. This paper will address findings of the experimental study with relation to model development.

Three dimensional numerical simulation of the transient turbulent jet and ignition processes of a premixed methane-air mixture of a turbulent jet ignition (TJI) system is performed using Converge computational software. The prechamber initiated combustion enhancement technique that is utilized in a TJI system enables low temperature combustion by increasing the flame propagation rate and therefore decreasing the burn duration. Two important components of the TJI system are the prechamber where the spark plug and injectors are located and the nozzle which connects the prechamber to the main chamber. In order to model the turbulent jet of the TJI system, RANS k-ε and LES turbulent models and the SAGE chemistry solver with a reduced mechanism for methane are used.