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The paper presents the main reasons for the increasing market share of vehicles with the capacity to run on random bio fuel blends. It describes the philosophy and basic layout of current integral flex mixture preparation systems. The paper demonstrates the necessity to introduce a series of new high-performance analysis tools for further improvement of the mixture preparation system and in particular the fuel injector performance. The paper continues with a discussion of the basic structure of the interactive Virtual Engine Model approach applied to fuel injector atomizer optimization. Test results obtained by application of the new tools to two different series production flex engines are presented. The impact of the improved spray formation capability of the optimized fuel injector atomizers is explained and experimental vehicle FTP-cycle data are reported and discussed.

A unique differential assembly was needed for the Lawrence Technological University (LTU) SAE Formula race car. Specifically, a differential was required that had torque sensing capabilities, perfect reliability, high strength, light weight, the ability to withstand inertia and shock loading, a small package, no leaks, the ability to support numerous components. In that regard, an existing differential was selected that had the torque sensing capabilities, but had deficiencies that needed to be fixed. Those deficiencies included the following: Differential unit was over 4 kg unmounted, with no housing. This was considered too heavy, when housed properly. Bearing surface was provided on only one end of the carrier. This design provides insufficient bearing surface to support either the differential housing or half-shafts The internal drive splines integral to the case are not optimized for a perpendicular drive/axle arrangement, such as, a chain drive.

To stay competitive, new products require faster development time at low cost and good quality. Defense as well as commercial industries are forced to use analytical tools to stay competitive in a tough market. The use of simulation tools and approximation techniques in evaluating product performance during the early stages of the product development has a major impart on the product development efficiency, effectiveness, and lead time. Building physical prototypes of complex systems is expensive and it is difficult and time consuming to develop them. It is extremely beneficial to know as much as possible about the product performance and to optimize its dynamic characteristics before the first physical prototype is built.

A vehicle’s exterior fit and finish, in general, is the first system to attract customers. Automotive exterior engineers were motivated in the past few years to increase their focus on how to optimize the vehicle’s exterior panels split lines quality and how to minimize variation in fit and finish addressing customer and market required quality standards. The design engineering’s focus is to control the deviation from nominal build objective and minimize it. The fitting process follows an optimization model with the exterior panel’s location and orientation factors as independent variables. This research focuses on addressing the source of variation “contributed factors” that will impact the quality of the fit and finish. These critical factors could be resulted from the design process, product process, or an assembly process. An empirical analysis will be used to minimize the fit and finish deviation.

Cooling fans have many applications in industrial and electronic fields that remove heat away from the system. The process of designing a new cooling fan with optimal performance and reduced acoustic sources can be fairly lengthy and expensive. The use of CFD with support of mesh morphing, along with the development of optimization techniques, can improve the acoustic’s performance of the fan model. This paper presents a new promising method which will support the design process of a new cooling fan with improved performance and less acoustic surface power generation. The CFD analysis is focused on reducing the acoustic surface power of a given cooling fan’s blade using the surface dipole acoustic power as the objective function, which leads to an optimized prototype design for a better performance. The Mesh Morpher Optimizer (MMO) in ANSYS Fluent is used in combination with a Simplex model of the broadband acoustic modeling.

Today's strict fuel economy requirement produces the need for the cars to have really optimized shapes among other characteristics as optimized cooling packages, reduced weight, to name a few. With the advances in automotive technology, tight global oil resources, lightweight automotive design process becomes a problem deserving important consideration. It is not however always clear how to modify the shape of the exterior of a car in order to minimize its aerodynamic resistance. Air motion is complex and operates differently at different weather conditions. Air motion around a vehicle has been studied quite exhaustively, but due to immense complex nature of air flow, which differs with different velocity, the nature of air, direction of flow et cetera, there is no complete study of aerodynamic analysis for a car. Something always can be done to further optimize the air flow around a car body.

A computer code oriented to S.I. engine control and powertrain simulation is presented. The model, developed in Matlab-Simulink® environment, predicts engine and driveline states, taking into account the dynamics of air and fuel flows into the intake manifold and the transient response of crankshaft, transmission gearing and vehicle. The model, derived from the code O.D.E.C.S. for the optimal design of engine control strategies now in use at Magneti Marelli, is suitable both for simulation analysis and to achieve optimal engine control strategies for minimum consumption with constraints on exhaust emissions and driveability via mathematical programming techniques. The model is structured as an object oriented modular framework and has been tested for simulating powertrain system and control performance with respect to any given transient and control strategy.

The 1999 Lawrence Technological University (LTU) drive train consists of a sprocket and chain assembly that delivers the torque, developed by a 600cc Honda F3 engine, to the rear wheels. The torque is transferred through a limited-slip, torque sensing differential unit comprised of a gear set in a student designed housing. The 1999 differential is a second-generation aluminum housing. The idea of using aluminum was first attempted with the 1998 team who successfully completed and used aluminum despite much complexity and a few design flaws. Therefore, in the LTU Formula Team's continuing effort to optimize the design, a new less complex design was conceived to house the gear set. This innovative design reduces the number of housing components from three in 1998, to two in 1999.

The first part of the paper gives an overview of the environmental conditions with which a future two stroke powered vehicle must comply and explains the reasons for which a direct gasoline injection into the combustion chamber offers a potential solution. The paper continues with a description of the fuel/air mixture injection used in the F.A.S.T. concept and gives a detailed overview of the layout of the 125 cc engine to which it is applied. The structure of its electronic engine management system, mandatory for the necessary control precision, is presented. Hereafter is made a short introduction to the visualization and numerical computation tools used for the engine design optimization. The paper concludes with a detailed presentation and discussion of the experimental results obtained with the engine operated, either in steady state and transient conditions on an engine test rig, and mounted in a classic small dimension two-wheel vehicle submitted to road tests.

AASHTO I-Beam is a standard structural concrete part for bridge sections. The flexural performance of an AASHTO I-Beam is critical for bridge design. This paper presents an application of Digital Image Correlation (DIC) Method in full-scale AASHTO I-Beam flexural performance study. A full-scale AASHTO I-Beam pre-stressed with steel strands is tested by three-point bending method. The full-scale AASHTO I-Beam is first loaded from 0 kips to 100 kips and is then released from 100 kips to 0 kips. A dual-camera 3D Digital Image Correlation (DIC) system is used to measure the deflection and strain distribution during the testing. From the DIC results, the micro-crack generation progress during the loading progress can be observed clearly from the measured DIC strain map. To enable such a large-scale DIC measurement, the used DIC setup is optimized in terms of the optical imaging system and speckle pattern size.

Formula SAE Collegiate Competition teams now regularly integrate aerodynamic body kits with their vehicles which have significant benefits in producing downforce. This use of body kits (or aero packages) and the improvement to vehicle aerodynamics they provide, have resulted in these systems becoming a necessity for any team wishing to remain competitive in Formula SAE (FSAE). To address this the Lawrence Technological University (LTU) Formula SAE team incorporated an aerodynamic body kit into their 2018 vehicle. Using computational fluid dynamics (CFD) an aerodynamic analysis was performed comparing the efficacy of a car that did not have an aero package to a car that did. Two separate simulation programs were employed to effectively and accurately assess this change. By using both SolidWorks and SimScale software to generate data, the results of each were compared to assess the accuracy of each.