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“Truck Ride” in this study refers to some vehicle ride parameters involved in tractor-trailer combinations. For the study, a mathematical model of a tractor-trailer vehicle as a vibrating system was developed. Principles of vibration theory were applied to the model while a digital computer was employed to investigate the complex system. To parallel the analytical investigation of the tractor-trailer vehicle, vehicle studies were conducted using a magnetic tape recorder and associated instrumentation installed in the tractor. Parameters studied included coupler position on the tractor, laden weight of trailer, spring rates of the different axles of the combination, damping capacity associated with each spring rate, vehicle speed, and “tar strip” spacing of the highway and cab mountings. The mathematical results were used as a basis for empirical study. A comparison of calculated and empirical data are reported.

This work introduces a new design algorithm to optimize progressively folding thin-walled structures and in order to improve automotive crashworthiness. The proposed design algorithm is composed of three stages: conceptual thickness distribution, design parameterization, and multi-objective design optimization. The conceptual thickness distribution stage generates an innovative design using a novel one-iteration compliant mechanism approach that triggers progressive folding even on irregular structures under oblique impact. The design parameterization stage optimally segments the conceptual design into a reduced number of clusters using a machine learning K-means algorithm. Finally, the multi-objective design optimization stage finds non-dominated designs of maximum specific energy absorption and minimum peak crushing force.

The present work was directed towards the design of a sideline microphone array specifically adapted to the visualization of automotive noise sources in the 500 Hz to 2000 Hz range. The particular design philosophy followed here involved the minimization of the array redundancy: i.e., the minimization of the number of pairs of microphones that are separated by the same distance in the same directions. The performance of sixty-four element microphone arrays designed according to this principle will be illustrated through the use of simulated motor vehicle passbys. In addition, their performance will be compared with more conventional array designs: e.g., elliptical, and spiral arrays.

The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

Swirl in Diesel engines is known to be an important parameter that affects the mixing of the fuel jets, heat release, emissions, and overall engine performance. The changes may be brought about through interactions of the swirling flow field with the spray and through modifications of the flow field. The purpose of this paper is to investigate the interaction of the swirl with sprays in a Diesel engine through a computational study. A multi-dimensional model for flows, sprays, and combustion in engines is employed. Results from computations are reported with varying levels of swirl and initial turbulence in two typical Diesel engine geometries. It is shown that there is an optimal level of swirl for each geometry that results from a balance between increased jet surface area and, hence, mixing rates and utilization of air in the chamber.

This work presents the implementation of the Efficient Global Optimization (EGO) approach for the design of composite materials under dynamic loading conditions. The optimization algorithm is based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design towards a global optimum. An expected improvement function is maximized during each iteration to locate the designs that update the metamodel until convergence. The algorithm solves single and multi-objective optimization problems. In the first case, the penetration of an armor plate is minimized by finding the optimal fiber orientations. Multi-objective formulation is used to minimize the intrusion and impact acceleration of a composite tube. The design variables include the fiber orientations and the size of zones that control the tube collapse.

A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

The latest US emission regulations require dramatic reductions in Nitrogen Oxide (NOx) emissions from vehicular diesel engines. Selective Catalytic Reduction (SCR) is the current technology that achieves NOx reductions of up to 90%. It is typically mounted downstream of the existing after-treatment system, i.e., after the Diesel Oxidation Catalyst (DOC) and Diesel Particulate Filter (DPF). Accurate prediction of input NO₂:NO ratio is useful for control of SCR urea injection to reduce NOx output and NH₃ slippage downstream of the SCR catalyst. Most oxidation of NO to NO₂ occurs in the DOC since its main function is to oxidize emission constituents. The DOC thus determines the NO₂:NO ratio as feedgas to the SCR catalyst. The prediction of NO₂:NO ratio varies as the catalyst in the DOC ages or deteriorates due to poisoning. Thus, the DOC prediction model has to take into account the correlation of DOC conversion effectiveness and the aging of the catalyst.

Accurate modeling of the transient structure of reacting diesel jets is important as transient features like autoignition, flame propagation, and flame stabilization have been shown to correlate with combustion efficiency and pollutant formation. In this work, results from Reynolds-averaged Navier-Stokes (RANS) simulations of flame lift-off in diesel jets are examined to provide insight into the lift-off physics. The large eddy simulation (LES) technique is also used to computationally model a lifted jet flame at conditions representative of those encountered in diesel engines. An unsteady flamelet progress variable (UFPV) model is used as the turbulent combustion model in both RANS simulations and LES. In the model, a look-up table of reaction source terms is generated as a function of mixture fraction Z, stoichiometric scalar dissipation rate Xst, and progress variable Cst by solving the unsteady flamelet equations.

Modern pulse-turbocharged systems produce a turbine operating environment that is dominated by unsteady flow. Effective utilization of the unsteady exhaust gas energy content at the turbine inlet is critical to achieving optimum system efficiency. This work presents predictions for turbocharger unsteady performance from a model based on the Euler equations with source terms (EEST). This approach allows the time-accurate performance of the turbine to be determined, allowing comparisons of actual energy utilization and that estimated from steady flow performance maps.

An experiment has been developed to investigate the ignition characteristics of ultra-lean premixed H2/air mixtures by a supersonic hot jet. The hot jet is generated by combustion of a stoichiometric mixture in a small prechamber. The apparatus adopted a dual-chamber design in which a small-volume (1% of the main chamber by volume) prechamber was installed within a large-volume main chamber. A small orifice (nozzle) connects the two chambers. Spark initiated combustion inside the prechamber causes a pressure rise and pushes the gases though the nozzle, resulting in a hot jet that would ignite the lean mixture in the main chamber. Simultaneous high-speed Schlieren photography and OH* Chemiluminescence were applied to visualize the jet penetration and the ignition processes inside the main chamber. Hot Wire Pyrometry (HWP) was used to measure temperature distribution of the transient hot jet.

Component sound quality is an important factor in the design of competitive diesel engines. One component noise that causes complaints is the gear rattle that originates in the front-of-engine gear train which drives the fuel pump and other accessories. The rattle is caused by repeated tooth impacts resulting from fluctuations in differential torsional acceleration of the driving gears. These impacts generate a broadband, impulsive noise that is often perceived as annoying. In most previous work, the overall sound quality of diesel engines has been considered without specifically focusing on predicting the perception of gear rattle. Gear rattle level has been quantified based on angular acceleration measurements, but those measurements can be difficult to perform. Here, the emphasis was on developing a metric based on subjective testing of the perception of gear rattle.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework.

The On-line Project Information System (OPIS) is a LAMP-based (Linux, Apache, MySQL, PHP) system being developed at NASA Ames Research Center to improve Agency information transfer and data availability, largely for improvement of system analysis and engineering. The tool will enable users to investigate NASA technology development efforts, connect with experts, and access technology development data. OPIS is currently being developed for NASA's Exploration Life Support (ELS) Project. Within OPIS, NASA ELS Managers assign projects to Principal Investigators (PI), track responsible individuals and institutions, and designate reporting assignments. Each PI populates a “Project Page” with a project overview, team member information, files, citations, and images. PI's may also delegate on-line report viewing and editing privileges to specific team members. Users can browse or search for project and member information.

Noise generation in axial piston machines can be attributed to two main sources; fluid borne and structure borne. Any attempt towards noise reduction in axial piston machines should focus on simultaneous reduction of these two sources. A multi-parameter multi-objective optimization approach to design valve plates to reduce both sources of noise for pumps which operate in a wide range of operating conditions has been detailed in a previous work (Seeniraj and Ivantysynova, 2008). The focus of this paper is to explain the background and to demonstrate the functionality and usefulness of the methodology for pump design.

The kinematic flow ripple for gerotor pumps is often used as a metric for comparison among different gearsets. However, compressibility, internal leakages, and throttling effects have an impact on the performance of the pump and cause the real flow ripple to deviate from the kinematic flow ripple. To counter this phenomenon, the ports can be designed to account for fluid effects to reduce the outlet flow ripple, internal pressure peaks, and localized cavitation due to throttling while simultaneously improving the volumetric efficiency. The design of the ports is typically heuristic, but a more advanced approach can be to use a numerical fluid model for virtual prototyping. In this work, a multi-objective optimization by genetic algorithm using an experimentally validated, lumped parameter, fluid-dynamic model is used to design the port geometry.

Today, there are several hundreds of manufacturing processes available to the designer to choose from, and the number is constantly increasing. The ability to choose a manufacturing process for a particular user need set in the early stage of the design process is necessary. In metalcasting alone, there are over forty different processes with different capabilities. A designer can benefit from knowing the manufacturing process alternatives available to him. Inaccurate process selection can lead to financial losses and market share erosion. This paper discusses a methodology for selection of a metalcasting process based on a number of user specified attributes or requirements. A model of user requirements was developed and these requirements were matched with the capabilities of each metalcasting process. The metalcasting process which best meets these needs is suggested.

In this paper, computations of pulsating flows in a duct with multiple inlets using the lattice Boltzmann method (LBM) are reported. As future emissions standards present a significant challenge for Diesel engine manufacturers, several options are being investigated to identify strategies to meet such regulations. Exhaust gas aftertreatment is one of the most important among them. As the performance of the various aftertreatment devices is sensitive to the flow conditions in the exhaust, a greater understanding of the flows under pulsating conditions in the presence of multiple cylinders is needed. The Lattice Boltzmann Method (LBM) is a relatively new and promising computational approach for applications to fluid dynamics problems. Two advantages of the method relative to traditional methods are ease of implementation and ease of parallelization and performance on parallel computers.

In Diesel engines, the vapor phase of the fuel jet is known to impinge on the walls. This impingement is likely to have an effect on mixing characteristics, the structure of the diffusion flame and on pollutant formation and oxidation. These effects have not been studied in detail in the literature. In this work, the structure of a laminar wall jet that is generated from the impingement of a free laminar jet on a wall is discussed. We study the laminar jet with the belief that the local structure of the reaction zone in the turbulent reacting jet is that of a laminar flame. Results from non-reacting and reacting jets will be presented. In the case of the non-reacting jets, the focus of the inquiry is on assessing the accuracy of the computed results by comparing them with analytical results. Velocity profiles in the wall jet, growth rates of the half-width of the jet and penetration rates are presented.