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”U” bolts are fixing elements and they are used to clamp an elastic joint. From the past, they still looking as an old design and unfortunately, suspension engineers are not specialists in fasteners and elastic joints. That is why we will show important assumptions and concepts to design and specifications this clamp element “U” bolt and its influence over leaf-springs. Currently, “U” bolt is used to clamp an elastic or elastic-plastic joint of heavy duty suspension, formed by leaf-spring, axle, spring pad, “U” bolt plate. This kind of suspension is typically used to trucks, buses and trailers. We are wondering, which one important assumption that an engineer must be careful when designs a new suspension changing from old designs to an updated technology. We provide a theoretical analysis and a FEA analysis to compare torque efficacy x leaf-spring reactions and what are effects this relationship can cause in a suspension.

High performance lubricant additive systems have been developed to formulate SAE 5W-30 passenger car engine oils which meet current and anticipated requirements of the North American original equipment manufacturers. The trend in North America is to recommend SAE 5W-30 oils that not only meet the API SF requirements for gasoline engines (“first-generation” oils), but also meet the stringent API CC requirement for light duty diesel engines (“second-generation” oils). Furthermore, the engine builders have issued “world specifications” for motor oils which incorporate additional “second-generation” SAE 5W-30 characteristics, such as enhanced API SF limits, improved fuel efficiency, an increased margin of bearing protection, and lower finished-oil phosphorus levels. The additive systems described herein exceed API SF and CC requirements as well as “second-generation” performance hurdles.

This paper presents a fatigue criterion based on stress invariants for the frequency-based analysis of multiaxial random stresses. The criterion, named “Projection-by-Projection” (PbP) spectral method, is a frequency-based reformulation of its time-domain definition. In the time domain PbP method, a random stress path is first projected along the axes of a principal reference frame in the deviatoric space, thus defining a set of uniaxial random stress projections. In the frequency-domain approach, the damage of stress projections is estimated from the stress PSD matrix. Fatigue damage of the multiaxial stress is next calculated by summing up the fatigue damage of every stress projection. The criterion is calibrated on fatigue strength properties for axial and torsion loading. The calculated damage is shown to also depend on the relative ratio of hydrostatic to deviatoric stress components.

Research information on solid lubricants has been compiled for consideration in the possible use of such materials in aircraft electrical equipment. Solid lubricants are capable of lubricating at the maximum temperatures (600° F) for aircraft electrical equipment. Many solids that adhere well to metals may be useful lubricants; those with layer-lattice structure usually give low friction. Solid lubricants are most commonly used as bonded films but the use of fluid carriers and surface reaction products have considerable merit.

Vehicle dynamics is a discipline of mechanical engineering that benefited of significant improvements thanks to the progress of computational engineering. Vehicle dynamics engineers are using CAE for the development of a vehicle with MBS and FEA. The concurrent use of these two technologies is a standard in the automotive industry. However the current simulation process is not fully efficient because local geometrical and material nonlinearities are not accurately modeled in classical MBS software. This paper introduces a methodology for vehicle dynamics simulation integrating MBS capabilities in one single nonlinear FEA environment enabling an accurate modeling of nonlinearity in vehicles.

This paper describes the application of statistical techniques known as Design of Experiments (D.O.E.) to efficiently use the results of numerical analysis data in order to improve the configuration of automotive systems. The general framework of these techniques is presented in a format aiming at the design engineer as their end user. Besides, a case study is presented with the purpose of illustrating their practical use. The first step of the case study is to build predictive models for the behaviour of the automotive system being developed by means of the Response Surface Method (RSM), using the proper D.O.E. options. Once these predictive models are available, automatic numerical optimization algorithms are used to improve the responses of interest for given operating conditions. Finally, the automotive systems are robust designed taking into account that the operating conditions vary randomly.

The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases.

Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

This paper, confined to the application of hard chrome plated liners to high-speed four-stroke diesel and gasoline engines, illustrates the increase in their popularity in the United Kingdom, and the advanced production methods which make this economically possible. The need for balanced engine life has long been apparent and is even more important today, the growth of motor transport having outstripped repair facilities. Iron bore life has been surpassed by improvement in the life of other component parts in the modern diesel engine. The provision of hard chrome plated liners can restore the balance. Further development and turbocharging of diesel engines has shown the need for a bore material capable of preventing scuffing and galling at elevated temperatures. Hard chrome has already proved itself in four-stroke engines under these conditions.

The objective of the development of the aerodynamic drag predictive tool CDaero was for use as a module for the Automobile Design Support System (AutoDSS). CDaero is an empirically based drag coefficient predictive tool based initially on the MIRA (Motor Industry Research Association) algorithm. The development philosophy was to be able to predict the aerodynamic drag coefficient of an automobile with knowledge of the features of the surface geometry control curves. These are the curves that control the 3-dimensional geometry as seen in the profile, plan and front and rear views. CDaero has been developed in a computing environment using the equation solver TKSolver™. Fifty-one input feature values are first determined from the automobile geometry and then entered into the program. CDaero models the drag coefficient with thirteen different components covering the basic body, as well as additional components such as the wheels, mud flaps, etc.

In today’s Automotive world, there is NO need to advocate “Light weighting”. Government policies for carbon footprint reduction combined with high safety standards are driving OEMs to adopt advanced manufacturing technologies. Steel hot forming is selected as most preferred way to reduce weight as it is easy to adopt and commercially known. It had many advantages compare to conventional cold stamping of standard and high tensile steel. The process consists of heating blank to nearly 1000 °C and quenching it in tool to for martensitic structure. Higher strength up to 2000 MPa can be achieved by this process. There are many examples where part weight is reduced by 15 to 20 % by this method. But Steel hot forming has limitation as specific density of steel is still high. Thus, there is limitation to its weight reduction capability. For further reduction, OEMs have started exploring Aluminium hot forming.

Buick engineers are well pleased with their '69 Chassis. Benefits of a unique front suspension camber curve are documented. The effects of various suspension parameters on ride and handling are explained. These were varied independently of one another in the course of evaluating over 30 suspension configurations.

‘Emotional controlling’ is a very efficient way to realize autonomous behaviour of digital human models by closed loop controls. In particular this is an emotional optimization procedure based upon the ‘Hedonic principle’ and thus following closely the human original. Emotional controlling will be outlined and illustrated by an example demonstrating the specific way force and posture induced discomfort is shaping our movements.

This specification covers the characteristics of glass beads used for peening, and provides for standard glass bead size numbers.

This specification covers the characteristics of glass beads used for peening, and provides for standard glass bead size numbers.