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AMS-STD-595A Color Chips Precise Color Matching, Individual Color Chips: A 3 x 5 inch color chip supplied in a 3 x 5 inch protective envelope for each AMS-STD-595 color, suitable for matching quality control inspection purposes. SAE Product Code: EA-10032 AMS-STD-595 – Colors Used in Government Procurement. This standard presents the colors used by Government Activities in a format suitable for color selection matching and for quality control inspection for paints and coatings. Standard is used with DoD and other Federal Agencies as a primary source of color reference.

technology breakthroughs. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. In the episode "Composite Materials: Advanced Materials and Lightweighting" (30:20), Molded Fiber Glass Companies, known for its deep involvement in the creative development of the molded fiberglass process for the Corvette, demonstrates the manufacturing of sheet molded composite for fiberglass parts. Tanom Motors introduces the Tanom Invader , a blend between an automobile and a motorcycle made exclusively with composite materials. Finally, Euro-Composites demonstrates the manufacturing of honeycomb core material made out of aramid paper and phenolic resin used in aircraft structures.

Polypropylene is typically reinforced with commodities that are non renewable and require a great deal of energy to produce. The marketplace needs a reinforcement that can offer beneficial physical properties, such as impact, while being attained from a renewable green source. Compounding flax fiber, which is traditionally an agricultural waste product burned by farmers, with polypropylene yields physical properties similar to traditional glass filled polypropylene. This combination should lead to cost saving opportunities while not sacrificing part performance. Presenter James Preston, Rhetech Inc.

Developing relatively cheap and widely available resources for heterogeneous solid catalyst synthesis is a promising approach for biodiesel fuel industry. Seashell which is essentially calcium carbonate can be used as a basic support for transesterification heterogeneous catalysts. In the present investigation, the alcoholysis of waste frying oil has been carried out using seashell-supported K3 PO4 as solid catalyst. Presenter Essam Oun Al-Zaini, PhD student, UNSW

There are several variables to consider when specifying a hydraulic hybrid system in a commercial vehicle. Parameters which can be controlled include various component sizes and some hybrid system calibration parameters. Presenter Paul Schwark, Bosch Rexroth AG

This set includes: SAE International Journal of Aerospace March 2010 - Volume 2 Issue 1 SAE International Journal of Commercial Vehicles October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Engines October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Fuels and Lubricants October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Materials and Manufacturing October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2 SAE International Journal of Passenger Cars - Electronic and Electrical Systems October 2009 - Volume 2, Issue 1 SAE International Journal of Passenger Cars - Mechanical Systems October 2009 - Volume 2, Issue 1 March 2010 - Volume 2, Issue 2

Abstract Exhaust manifolds are one of the most important components on the engine assembly, which is mounted on engine cylinder head. Exhaust manifolds connect exhaust ports of cylinders to the turbine for turbocharged diesel engine therefore they play a significant role in the performance of engine system. Exhaust manifolds are subjected to very harsh thermal loads; extreme heating under very high temperatures and cooling under low temperatures. Therefore designing a durable exhaust manifold is a challenging task. Computer aided engineering (CAE) is an effective tool to drive an exhaust manifold design at the early stage of engine development. Thus advanced CAE methodologies are required for the accurate prediction of temperature distribution. However, at the end of the development process, for the design verification purposes, various tests have to be carried out in engine dynamometer cells under severe operating conditions.

Abstract The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract In this article, a unique design for Hydro-Pneumatic Energy Harvesting Suspension HPEHS system is introduced. The design includes a hydraulic rectifier to maintain one-way flow direction in order to obtain maximum power generation from the vertical oscillation of the suspension system and achieve handling and comfort car drive. A mathematical model is presented to study the system dynamics and non-linear effects for HPEHS system. A simulation model is created by using Advanced Modeling Environment Simulations software (AMEsim) to analyze system performance. Furthermore, a co-simulation platform model is developed using Matlab-Simulink and AMEsim to optimize the PID controller parameters of the external variable load resistor applied on the generator by using Particle Swarm Optimization (PSO).

Abstract Reliability analysis of a large-scale system under random dynamic loads can be a very time-consuming task since it requires repeated studies of the system. In many engineering problems, for example, wave loads on an offshore platform, the excitation loads are defined using a power spectral density (PSD) function. For a given PSD function, one needs to generate many time histories to make sure the excitation load is modeled accurately. Global and local approximation methods are available to predict the system response efficiently. Each way has their advantages and shortcomings. The combined approximations (CA) method is an efficient method, which combines the advantages of local and global approximations. This work demonstrates two methodologies that utilize CA to reduce the cost of crude or separable Monte Carlo simulation (MCS) of linear dynamic systems when the excitation loads are defined using PSD functions.

Abstract Recently, electric heavy-duty tractor-trailers (EHDTTs) have assumed significance as they present an immediate solution to decarbonize the transportation sector. Hence, to illustrate the economic viability of electrifying the freight industry, a detailed numerical model to estimate the battery capacity for an EHDTT is proposed for a route between Washington, DC, to Knoxville, TN. This model incorporates the effects of the terrain, climate, vehicular forces, auxiliary loads, and payload in order to select the appropriate motor and optimize the battery capacity. Additionally, current and near-future battery chemistries are simulated in the model. Along with equations describing vehicular forces based on Newton’s second law of motion, the model utilizes the Hausmann and Depcik correlation to estimate the losses caused by the capacity offset of the batteries. Here, a Newton-Raphson iterative scheme determines the minimum battery capacity for the required state of charge.

Abstract A new concept of instantaneous wheel turn center (IWTC) is proposed to evaluate and improve multi-axle vehicle steering coordination performance. The concept of IWTC and its calculation method are studied. The index named dispersion of IWTC is developed to evaluate the vehicle steering coordination performance quantitatively. The simulation tests based on a three-axle off-road vehicle model are conducted under different vehicle velocities and lateral accelerations. The simulation results show that the turn centers of different wheels are disperse, and the dispersion becomes larger with the increase of vehicle velocities and lateral acceleration. Since suspension has important influences on vehicle steering performance, the genetic algorithm is used to optimize the suspension hard points and bushing stiffness, aiming at minimizing the dispersion of wheel turn centers (DWTC) to improve the vehicle steering coordination performance.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract A number of semi-deterministic and stochastic formulations of multi-degree of freedom, frequency domain load models for heavy truck chassis are proposed and evaluated. The semi-deterministic models aim at reproducing the damage of a specific vehicle, while the stochastic ones aim to describe a collection of vehicle loads. The stochastic models are divided into two groups: Monte Carlo based and models based on single spectrum matrices. In both cases, the objective is to provide a load model that may be used to produce a design with a certain probability of survival. The goodness of the models is evaluated through a comparison of their damage outcomes with the corresponding damages of a set of time domain loads. This original time domain load set consists of chassis accelerations collected from seven physical trucks.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract The following article illustrates the detailed study of the development of a unique flywheel-based regenerative braking system (f-RBS) for achieving regenerative braking in a commercial electric bus. The f-RBS is designed for installation in the front wheels of the bus. The particular data values for modeling the bus are taken from multiple legitimate sources to illustrate the development strategy of the regenerative braking system. Mechanical components used in this system have either been carefully designed and analyzed for avoiding fatigue failure or their market selection strategies explained. The positioning of the entire system is decided using MSC Adams View®, hence determining a suitable component placement strategy such that the f-RBS components do not interfere with the bus components. The entire system is modeled on MATLAB Simulink® with sufficient accuracy to get various results that would infer the performance of the system as a whole.

Abstract An accurate and rapid thermal model of an axle-brake system is crucial to the design process of reliable braking systems. Proper thermal management is necessary to avoid damaging effects, such as brake fade, thermal cracking, and lubricating oil degradation. In order to understand the thermal effects inside of a lubricated braking system, it is common to use Computational Fluid Dynamics (CFD) to calculate the heat generation and rejection. However, this is a difficult and time-consuming process, especially when trying to optimize a braking system. This article uses the results from several CFD runs to train a Stacked Ensemble Model (SEM), which allows the use of machine learning (ML) to predict the systems’ temperature based on several input design parameters. The robustness of the SEM was evaluated using uncertainty quantification.