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Electronic controls in internal combustion engines require an in-cylinder combustion sensor to produce a feedback signal to the ECU (Engine Control Unit). Recent research indicated that the ion current sensor has many advantages over the pressure transducer, related mainly to lower cost. Modified glow plugs in diesel engines, and fuel injectors in both gasoline and diesel engines can be utilized as ion current sensors without the addition any part or drilling holes in the cylinder head needed for the pressure transducer. Multi sensing fuel injector (MSFI) system is a new technique which instruments the fuel injector with an electric circuit to perform multiple sensing tasks including functioning as an ion sensor in addition to its primary task of delivering the fuel into the cylinder. It is necessary to fundamentally understand MSFI system.

This study reanalyzes the data from a recent experimental report from the University of Utah investigating the effect on driving performance of auditory-vocal secondary tasks (such as cell phone and passenger conversations, speech-to-text, and a complex artificial cognitive task). The current objective is to estimate the relative risk of crashes associated with such auditory-vocal tasks. Contrary to the Utah study's assumption of an increase in crash risk from the attentional effects of cognitive load, a deeper analysis of the Utah data shows that driver self-regulation provides an effective countermeasure that offsets possible increases in crash risk. For example, drivers self-regulated their following distances to compensate for the slight increases in brake response time while performing auditory-vocal tasks. This new finding is supported by naturalistic driving data showing that cell phone conversation does not increase crash risk above that of normal baseline driving.

Many approaches have been taken to determine the burning velocity in internal combustion engines. Experimentally, the burning velocity has been determined in optically accessible gasoline engines by tracking the propagation of the flame front from the spark plug to the end of the combustion chamber. These experiments are costly as they require special imaging techniques and major modifications in the engine structure. Another approach to determine the burning velocity is from 3D CFD simulation models. These models require basic information about the mechanisms of combustion which are not available for distillate fuels in addition to many assumptions that have to be made to determine the burning velocity. Such models take long periods of computational time for execution and have to be calibrated and validated through experimentation.

Emissions of Unburned Hydrocarbons (UHC) from diesel engines are a particular concern during the starting process, when after-treatment devices are typically below optimal operating temperatures. Drivability in the subsequent warm-up phase is also impaired by large cyclic fluctuations in mean effective pressure (MEP). This paper discusses in-cylinder wall temperature influence on unburned hydrocarbon emissions and combustion stability during the starting and warm-up process in an optical engine. A laser-induced phosphorescence technique is used for quantitative measurements of in-cylinder wall temperatures just prior to start of injection (SOI), which are correlated to engine out UHC emission mole fractions and combustion phasing during starting sequences over a range of charge densities, at a fixed fueling rate. Squish zone cylinder wall temperature shows significant influence on engine out UHC emissions during the warm-up process.

On-board fuel identification is important to ensure engine safe operation, similar power output, fuel economy and emissions levels when different fuels are used. Real-time detection of physical and chemical properties of the fuel requires the development of identifying techniques based on a simple, non-intrusive sensor. The measured crankshaft speed signal is already available on series engine and can be utilized to estimate at least one of the essential combustion parameters such as peak pressure and its location, rate of cylinder pressure rise and start of combustion, which are an indicative of the ignition properties of the fuel. Using a dynamic model of the crankshaft numerous methods have been previously developed to identify the fuel type but all with limited applications in terms of number of cylinders and computational resources for real time control.

The present investigation details an experimental procedure for frontal impact responses of a generic steel front bumper crush can (FBCC) assembly subjected to a rigid full and 40% offset impact. There is a paucity of studies focusing on component level tests with FBCCs, and of those, speeds carried out are of slower velocities. Predominant studies in literature pertain to full vehicle testing. Component level studies have importance as vehicles aim to decrease weight. As materials, such as carbon fiber or aluminum, are applied to vehicle structures, computer aided models are required to evaluate performance. A novel component level test procedure is valuable to aid in CAE correlation. All the tests were conducted using a sled-on-sled testing method. Several high-speed cameras, an IR (Infrared) thermal camera, and a number of accelerometers were utilized to study impact performance of the FBCC samples.

Previously, a 10-year-old (YO) pediatric thorax finite element model (FEM) was developed and verified against child chest stiffness data measured from clinical cardiopulmonary resuscitation (CPR). However, the CPR experiments were performed at relatively low speeds, with a maximum loading rate of 250 mm/s. Studies showed that the biomechanical responses of human thorax exhibited rate sensitive characteristics. As such, the studies of dynamic responses of the pediatric thorax FEM are needed. Experimental pediatric cadaver data in frontal pendulum impacts and diagonal belt dynamic loading tests were used for dynamic validation. Thoracic force-deflection curves between test and simulation were compared. Strains predicted by the FEM and the injuries observed in the cadaver tests were also compared for injury assessment and analysis. This study helped to further improve the 10 YO pediatric thorax FEM.

Typical automotive body structures use resistance spot welding for most joining purposes. New materials, such as Advanced High Strength Steels (AHSS) are increasingly used in the construction of automotive body structures to meet increasingly higher structural performance requirements while maintaining or reducing weight of the vehicle. One of the challenges for implementation of new AHSS materials is weldability assessment. Weld engineers and vehicle program teams spend significant efforts and resources in testing weldability of new sheet metal stack-ups. In this paper, we present a methodology to determine the weldability of sheet metal stack-ups using an Artificial Neural Network-based tool that learns from historical data. The paper concludes by reviewing weldability results predicted by using this tool and comparing with actual test results.

Commotio Cordis (CC) is the second leading cause of mortality in youth sports. Impacts occurring directly over the left ventricle (LV) during a vulnerable period of the cardiac cycle can cause ventricular fibrillation (VF), which results in CC. In order to better understand the pathophysiology of CC, and develop a mechanical model for CC, appropriate injury criteria need to be developed. This effort consisted of impacts to seventeen juvenile porcine specimens (mass 21-45 kg). Impacts were delivered over the cardiac silhouette during the venerable period of the cardiac cycle. Four impact speeds were used: 13.4, 17.9, 22.4, and 26.8 m/s. The impactor was a lacrosse ball on an aluminum shaft instrumented with an accelerometer (mass 188 g - 215 g). The impacts were recorded using high-speed video. LV pressure was measured with a catheter. Univariate binary logistic regression analyses were performed to evaluate the predictive ability of ten injury criteria.

Internal combustion engine control requires feedback signals to the ECU in order to meet the increasingly stringent emissions standards. Reducing the number of on-board sensors needed for proper engine performance would reduce the cost and complexity of the electronic system. This paper presents a new technique to enable one engine element, the fuel injector, to perform multiple sensing tasks in addition to its primary task of delivering the fuel into the cylinder. The injector is instrumented within an electric circuit to produce a signal indicative of the ionization produced from the combustion process in electronically controlled diesel engines. The output of the multi sensing fuel injector (MSFI) system can be used as a feedback signal to the engine control unit (ECU) for injection timing and diagnostics of the injection and combustion processes.

As early as the 1950's, Gurdjian and colleagues (Gurdjian et al., 1955) observed that brain injuries could occur by direct pressure loading without any global head accelerations. This pressure-induced injury mechanism was "forgotten" for some time and is being rekindled due to the many mild traumatic brain injuries attributed to blast overpressure. The aim of the current study was to develop a finite element (FE) model to predict the biomechanical response of rat brain under a shock tube environment. The rat head model, including more than 530,000 hexahedral elements with a typical element size of 100 to 300 microns was developed based on a previous rat brain model for simulating a blunt controlled cortical impact. An FE model, which represents gas flow in a 0.305-m diameter shock tube, was formulated to provide input (incident) blast overpressures to the rat model. It used an Eulerian approach and the predicted pressures were verified with experimental data.

Hat sections made of steel are frequently encountered in automotive body structural components such as front rails. These components can absorb significant amount of impact energy during collisions thereby protecting occupants of vehicles from severe injury. In the initial phase of vehicle design, it will be prudent to incorporate the sectional details of such a component based on an engineering target such as peak load, mean load, energy absorption, or total crush, or a combination of these parameters. Such a goal can be accomplished if efficient and reliable data-based models are available for predicting the performance of a section of given geometry as alternatives to time-consuming and detailed engineering analysis typically based on the explicit finite element method.

The objective of this research is to investigate the effect of the blast load on the vehicle and occupant and identify the sensitivity of the vehicle parameters to the blast load, therefore figure out the design solution to protect the vehicle and occupant. CAE explicit commercial code, LSDYNA, is applied in this research with adopting CONWEP method for the blast load. The LSDYNA 95th percentile Hybrid III dummy model is used for occupant simulation. Seat, seat belt, and underbody and underbody armor are interested areas in the design to meet the survivability and weight target. The results show the protection can be effectively achieved through employing the new design method in three areas mentioned above.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. However, the mechanical properties of the pia-arachnoid complex and its influence on the overall response of the brain have not been well characterized. Consequently, finite element (FE) brain models have tended to oversimplify the response of the pia-arachnoid complex, possibly resulting in a loss of accuracy in the model predictions. The aim of this study was to determine, experimentally, the material properties of the pia-arachnoid complex under quasi-static and dynamic loading conditions. Specimens of the pia-arachnoid complex were obtained from the parietal and temporal regions of freshly slaughtered bovine subjects with the specimen orientation recorded. Single-stroke, uniaxial quasi-static and dynamic tensile experiments were performed at strain-rates of 0.05, 0.5, 5 and 100 s-1 (n = 10 for each strain rate group).

Traumatic brain injury (TBI) continues to be a major health problem, with over 500,000 cases per year with a societal cost of approximately $85 billion in the US. Motor vehicle accidents are the leading cause of such injuries. In many cases of TBI widespread disruption of the axons occurs through a process known as diffuse axonal injury (DAI) or traumatic axonal injury (TAI). In the current study, an in vivo TAI model was developed using spinal nerve roots of adult rats. This model was used to determine functional and structural responses of axons to various strains and displacement rates. Fifty-six L5 dorsal nerve roots were each subjected to a predetermined strain range (<10%, 10-20% and >20%) at a specified displacement rate (0.01 mm/sec and 15 mm/sec) only once. Image analysis was used to determine actual strains on the roots during the pull.

Complete validation of any finite element (FE) model of the human brain is very difficult due to the lack of adequate experimental data. However, more animal brain injury data, especially rat data, obtained under well-defined mechanical loading conditions, are available to advance the understanding of the mechanisms of traumatic brain injury. Unfortunately, internal response of the brain in these experimental studies could not be measured. The aim of this study was to develop a detailed FE model of the rat brain for the prediction of intracranial responses due to different impact scenarios. Model results were used to elucidate possible brain injury mechanisms. An FE model, consisting of more than 250,000 hexahedral elements with a typical element size of 100 to 300 microns, was developed to represent the brain of a rat. The model was first validated locally against peak brain deformation data obtained from nine unique dynamic cortical deformation (vacuum) tests.

Propagation-based and phase-enhanced x-ray imaging was developed as a unique metrology technique to visualize the internal structure of high-pressure fuel injection nozzles. We have visualized the microstructures inside 200-μm fuel injection nozzles in a 3-mm-thick steel housing using this novel technique. Furthermore, this new x-ray-based metrology technique has been used to directly study the highly transient needle motion in the nozzles in situ and in real-time, which is virtually impossible by any other means. The needle motion has been shown to have the most direct effect on the fuel jet structure and spray formation immediately outside of the nozzle. In addition, the spray cone-angle has been perfectly correlated with the numerically simulated fuel flow inside the nozzle due to the transient nature of the needle during the injection.

Cerebral blood vessels are an integral part of the brain and may play a role in the response of the brain to impact. The purpose of this study was to quantify the effects of surrogate vessels on the deformation patterns of a physical model of the brain under various impact conditions. Silicone gel and tubing were used as surrogates for brain tissue and blood vessels, respectively. Two aluminum cylinders representing a coronal section of the brain were constructed. One cylinder was filled with silicone gel only, and the other was filled with silicone gel and silicone tubing arranged in the radial direction in the peripheral region. An array of markers was embedded in the gel in both cylinders to facilitate strain calculation via high-speed video analysis. Both cylinders were simultaneously subjected to a combination of linear and angular acceleration using a two-segment pendulum.

A high carbon, high silicon and high manganese steel containing about 1% carbon, 3.0% silicon and 2.0% manganese has been developed. This steel has been synthesized using the concepts from Austempered Ductile Cast Iron (ADI) technology. The influence of austempering process on the microstructure and the room temperature mechanical properties of this steel was investigated. The influence of microstructure on the plain strain fracture toughness of this new steel was also examined. Four batches of compact tension and cylindrical tensile samples were prepared from this steel as per ASTM standards E-399 and E-8 respectively. Two batches of specimens were processed by traditional quenching and tempering process while other two batches were austempered. The microstructures were characterized by X-ray diffraction and optical metallography.

Even under steady state operating conditions, the pressure variation in individual cylinders, and the corresponding gas-pressure torque are subjected to small random fluctuations from cycle to cycle. The gas-pressure torque of a cylinder may be expressed as a sum of harmonically variable components, each harmonic being affected by these fluctuations. A probabilistic model of the vector interpreting such a harmonic component is developed and used to determine the statistical parameters of the resultant random vector representing the corresponding harmonic order of the engine torque. At the low frequencies of the lowest harmonic orders of the engine torque the crankshaft behaves like a rigid body. This behavior permits to correlate the statistical parameters of the same harmonic components of the resultant torque and of the measured engine speed. This correlation is proved by experiments and used to identify faulty cylinders.