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Reduced basis techniques and the method of mode-acceleration are applied to transient analysis of simple beam and truss structures. It is noted that the method of mode-acceleration effectively recovers the first Ritz vector used in Ritz procedures. The theoretical basis for Lanczos algorithms that generate Ritz vectors is explained. Both mode-acceleration and Ritz procedures are found, generally, to be more accurate than mode-displacement in calculation of transient shear stresses, moments and normal stresses. Reanalysis using Ritz vectors is discussed following Kitis and Pilkey [9] and Noor and Lowder [10].

The Indicated Mean Effective Pressure (IMEP) is a very important engine parameter, giving significant information about the quality of the cycle that transforms heat into mechanical work. For this reason, modern data acquisition systems display, on line, the cylinder pressure variation together with the corresponding IMEP. The paper presents a very simple algorithm for the calculation of IMEP, based on the correlation between IMEP and the gas pressure torque. It was found that that the IMEP may be calculated by a very simple formula involving only two harmonic components of the cylinder pressure variation. The computation of the two harmonic components is very easily performed because it does not involve the calculation of an average pressure and the cylinder volume variation. The method was experimentally validated showing differences less than 0.2% with respect to the IMEP calculated by the traditional method.

This paper focuses on the role and significance of linear momentum and kinetic energy in controlling air bags aboard vehicles. Among the results of the study are analytic and geometric models that characterize crash behavior and control algorithms that quantify crash severity and identify crash configurations. These results constitute an effective basis for crash-data design and air-bag control.

A new three-dimensional human head finite element model, consisting of the scalp, skull, dura, falx, tentorium, pia, CSF, venous sinuses, ventricles, cerebrum (gray and white matter), cerebellum, brain stem and parasagittal bridging veins has been developed and partially validated against experimental data of Nahum et al (1977). A frontal impact and a sagittal plane rotational impact were simulated and impact responses from a homogeneous brain were compared with those of an inhomogeneous brain. Previous two-dimensional simulation results showed that differentiation between the gray and white matter and the inclusion of the ventricles are necessary in brain modeling to match regions of high shear stress to locations of diffuse axonal injury (DAI). The three-dimensional simulation results presented here also showed the necessity of including these anatomical features in brain modeling.

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.

Conventional gear designs are characterized by the meshing teeth which have to accommodate bending loads with a high dynamic load content, together with high contact stresses under a reciprocal sliding. Accordingly, special materials with sophisticated heat treatments, and high fabrication accuracy are required for heavy-duty gears, such as being used in off-road vehicle transmissions The paper describes a novel concept for designing power transmission gears, which eliminates physical sliding between meshing profiles and separates bending and contact loading of the teeth. Geometrical sliding is accommodated by internal shear deformation in specially designed rubber-metal laminates, thus allowing materials with high bulk strength but poor contact properties (aluminum, titanium, fiber-reinforced composites, etc.) to be used for heavy-duty gears.

This paper summarizes a systematic approach to control of nonlinear automotive systems exposed to fast transients. This approach is based on a combined application of hardware characterization, which inverts nonlinearities, and conventional Proportional-plus-Integral-plus-Derivative (PID) control. The approach renders the closed-loop system dynamics more transparent and simplifies the controller design and calibration for applications in automotive industry. The authors have found this approach effective in presenting and teaching PID controller design and calibration guidelines to automotive engineering audience, who at times may not have formal training in controls but need to understand the development and calibration process of simple controllers.

Rattling in the inevitable clearances between engaging teeth of mechanical power transmission components, such as gears, gear couplings and clutches, etc., is becoming a more and more important issue, especially for automotive applications. An extensive research effort in this area is mostly dedicated to modeling of complex nonlinear processes that develop after the tooth separation occurs, or to experimental studies of these processes. The available abatement techniques for the rattling noise are expensive while not providing desirable noise reduction results. The paper presents a criterial condition for opening of clearances derived for a simplified model and clearly showing importance of various design parameters on possibility of commencement of the rattling process. Also, a novel rattling noise abatement technique is described, based on incorporating simple means for prolongation of the impact interactions between the co-impacting engaging teeth.

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.

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).

Multi-hole DI injectors are being adopted in the advanced downsized DISI ICE powertrain in the automotive industry worldwide because of their robustness and cost-performance. Although their injector design and spray resembles those of DI diesel injectors, there are many basic but distinct differences due to different injection pressure and fuel properties, the sac design, lower L/D aspect ratios in the nozzle hole, closer spray-to-spray angle and hense interactions. This paper used Phase-Contrast X ray techniques to visualize the spray near a 3-hole DI gasoline research model injector exit and compared to the visible light visualization and the internal flow predictions using with multi-dimensional multi-phase CFD simulations. The results show that strong interactions of the vortex strings, cavitation, and turbulence in and near the nozzles make the multi-phase turbulent flow very complicated and dominate the near nozzle breakup mechanisms quite unlike those of diesel injections.

It is well know that the internal flow field and nozzle geometry affected the spray behavior, but without high-speed microscopic visualization, it is difficult to characterize the spray structure in details. Single-hole diesel injectors have been used in fundamental spray research, while most direct-injection engines use multi-hole nozzle to tailor to the combustion chamber geometry. Recent engine trends also use smaller orifice and higher injection pressure. This paper discussed the quasi-steady near-nozzle diesel spray structures of an axisymmetric single-hole nozzle and a symmetric two-hole nozzle configuration, with a nominal nozzle size of 130 μm, and an attempt to correlate the observed structure to the internal flow structure using computational fluid dynamic (CFD) simulation. The test conditions include variation of injection pressure from 30 to 100 MPa, using both diesel and biodiesel fuels, under atmospheric condition.

Requirements for reduced fuel consumption with simultaneous reductions in regulated emissions require more efficient operation of Spark Ignited (SI) engines. An advanced valvetrain coupled with Gasoline Direct injection (GDi) provide an opportunity to simultaneously reduce fuel consumption and emissions. Work on a flex fuel GDi engine has identified significant potential to reduce throttling by using Early Intake Valve Closing (EIVC) and Late Intake Valve Closing (LIVC) strategies to control knock and load. High loads were problematic when operating on gasoline for particulate emissions, and low loads were not able to fully minimize throttling due to poor charge motion for the EIVC strategy. The use of valve deactivation was successful at reducing high load particulate emissions without a significant airflow penalty below 3000 RPM. Valve deactivation did increase the knocking tendency for knock limited fuels, due to increased heat transfer that increased charge temperature.

Dynamic data, forces, moments and displacements are widely used parameters in a simulation environment for design and testing. These results may be obtained from field tests, laboratory measurements, and numerical simulations. The correctness of the simulation results depends strongly on the models and numerical solution techniques. This paper presents a preliminary examination of the differences between results obtained from the computer code DADS (Dynamic Analysis and Design System) [1] and the field data for the response of a military tank. The differences are analyzed by standard statistical methods in the frequency domain. The statistical tests show that DADS results differ from the measured field data and that the errors are not white noise. Moreover, the principal frequencies of the differences are identified.

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.

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.

The effect of biodiesel on the Particulate emissions is gaining significant attention particularly with the drive for the use of alternative fuels. The particulate matter (PM), especially having a diameter less than 50 nm called the Nanoparticles or Nucleation mode particles (NMPs), has been raising concerns about its effect on human health. To better understand the effect of biodiesel and its blends on particulate emissions, steady state tests were conducted on a small-bore single-cylinder high-speed direct-injection research diesel engine. The engine was fueled with Ultra-Low Sulfur Diesel (ULSD or B-00), a blend of 20% soy-derived biodiesel and 80% ULSD on volumetric basis (B-20), B-40, B-60, B-80 and 100% soy-derived biodiesel (B-100), equipped with a common rail injection system, EGR and swirl control systems at a load of 5 bar IMEP and constant engine speed of 1500 rpm.

Effects of fuel cell material properties on water management were numerically investigated using Volume of Fluid (VOF) method in the FLUENT. The results show that the channel surface wettability is an important design variable for both serpentine and interdigitated flow channel configurations. In a serpentine air flow channel, hydrophilic surfaces could benefit the reactant transport to reaction sites by facilitating water transport along channel edges or on channel surfaces; however, the hydrophilic surfaces would also introduce significantly pressure drop as a penalty. For interdigitated air flow channel design, it is observable that liquid water exists only in the outlet channel; it is also observable that water distribution inside GDL is uneven due to the pressure distribution caused by interdigitated structure. An in-situ water measurement method, neutron imaging technique, was used to investigate the water behavior in a PEM fuel cell.

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.

This paper aims to develop some enhanced identification algorithms for real time characterization of battery dynamics. The core of such a system is advanced system identification techniques that provide fast tracking capability to update battery cell's individual models in real-time operation. Due to inevitable measurement noises on voltage and current observations, the identification algorithms must perform under both input and output noises, leading to more challenging issues than standard identification problems. It is shown that typical battery models may not be identifiable, unique battery model features require modified input/output expressions, and standard least-squares identification methods will encounter identification bias. This paper devises modified model structure and algorithms to resolve these issues. System identifiabihty, algorithm convergence, identification bias, and bias correction mechanisms are established.