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An experimental and numerical study was conducted on the spray and mixture properties of a hole-type injector for direct injection (D. I.) gasoline engines. The Laser Absorption Scattering (LAS) technique was adopted to simultaneously measure the spatial concentration distributions and the mass of the liquid and vapor phases in the fuel spray injected into a high-pressure and high-temperature constant volume vessel. The experimental results were compared to the numerical calculation results using three-dimensional CFD and the multi-objective optimization. In the numerical simulation, the design variable of the spray model was optimized by choosing spray tip penetration, and mass of liquid and vapor phases as objective functions.

Development and integration of the cooling system for an automotive vehicle requires a balancing act between several performance and styling objectives. The cooling system needs to provide sufficient air for heat rejection with minimal impact on the aerodynamic drag, styling requirements and other criteria. An optimization of various design parameters is needed to develop a design to meet these objectives in a short amount of time. Increase in the accuracy of the numerical predictions and reduction in the turn-around time has made it possible for Computational Fluid Dynamics (CFD) to be used early in the design phase of the vehicle development. This study shows application of the CFD for robust design of the engine cooling system.

Continuous improvement of side airbag safety performance is an important step because it is associated with many public domain tests and regulations. Thus, occupant restraint with a side airbag is critical and it is necessary to develop tools that can be utilized to help in design of side airbags. Though many papers on side impact safety have been published, only a few papers are related to MADYMO simulations of side airbags. This paper describes an improved injury prediction and optimization approach using a MADYMO model for side impact. This model consists of 3 parts: dummy, trim and airbag in FEM. In this study, a side impact with a ES-2, EuroSID-2, was simulated in MADYMO as follows: First, component tests were conducted for trim and airbag respectively to establish correlation. Second, these component models were then integrated into a MADYMO model, which has high correlation with a crash simulator that is capable of replicating physical vehicle tests.

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept.

Simultaneously obtaining a linear temperature control curve along with the correct temperature stratification at module outlets is one of the most difficult tasks in developing an automotive HVAC module. Traditionally, Computational Fluid Dynamics (CFD) development of temperature control linearity has been accomplished by iteratively adjusting the location, size and orientation of baffles which redirect warm and cold airstreams. This approach demands considerable interaction from the engineer in building the computational mesh, defining boundary and operating conditions and post processing the simulation results. The present study was conducted to investigate the optimization of HVAC temperature regulation curves using the multi-objective optimization code modeFrontier (1, 3) in conjunction with CFD code, Fluent (2). An auxiliary HVAC module was selected for the present study.

Managing (minimizing and optimizing) the total mass of a vehicle is recognized as a critical task during the development of a new vehicle, as well as throughout its production lifecycle. This paper summarizes a literature review of, and investigation into, the strategies, methods and best practices for achieving low total mass in new vehicle programs, and/or mass reductions in existing production vehicle programs. Empirical and quantitative data and examples from the automotive manufacturers and suppliers are also provided in support of the material presented.

The present study had two aims: (1) to develop a model which reproduced the dummy lower leg kinematics observed in a high-speed test, and (2) to develop a methodology to assess various theoretical design parameters of a heel foam pad to reduce the risk of the lower extremity injuries. To address the first aim, a MADYMO sled simulation model was developed. The interior parts were represented mainly with finite element (FE) models, with intent to capture deformations and the reaction force directions. Moreover, the occupant responses were estimated from the refined version of the dummy model (i.e., the Hybrid III model; Q dummy model). The model was acceptably correlated to experiments. To address the second aim, the model was simplified for subsequent optimization of the heel foam pad.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.

An extravehicular activity (EVA) path-planning and navigation tool, called the Mission Planner, has been developed to assist with pre-mission planning, scenario simulation, real-time navigation, and contingency replanning during astronaut EVAs, The Mission Planner calculates the most efficient path between user-specified waypoints. Efficiency is based on an exploration cost algorithm, which is a function of the estimated astronaut metabolic rate. Selection of waypoints and visualization of the generated path are realized within a 3D mapping interface through terrain elevation models. The Mission Planner is also capable of computing the most efficient path back home from any point along the path.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Full-load operation of a small-displacement spark-ignition direct-injection (SIDI) engine was thoroughly investigated by means of computational analysis and engine measurements. The performance is affected by many different factors, which can be grouped as those pertaining to volumetric efficiency, to mixing and stratification, and to system issues, respectively. Volumetric efficiency is affected by flow losses, tuning and charge cooling. Charge cooling due to spray vaporization is often touted as the most significant benefit of direct-injection on full-load performance. However, if wall wetting occurs, this benefit may be completely negated or even reversed. The fuel-air mixing is strongly affected by the injection timing and characteristics at lower engine speeds, while at higher engine speeds the intake flow dominates the transport of fuel particles and resultant vapor distribution. A higher injector flow rate enhances mixing especially at higher engine speeds.

Development of anti-whiplash technology is one of the hottest issues in the automotive safety field because of the frequent occurrence of rear impact accidents. We analyzed the whiplash mechanism and conducted a study to seek the optimized seat characteristics with BioRID II and MADYMO simulations. A parameter study was made to construct a conceptual theory to decrease NIC, Neck Injury Criteria, with the MADYMO model. As a result of the study, head restraint position and seatback stiffness were found to affect dummy movement and injury values. Applying the NIC mechanism and the influential parameters to the MADYMO model, the optimized seat characteristics for whiplash prevention were obtained.

The existing vehicle designs exhibit a high level of coupling. For instance the coupling in the suspension and steering systems manifests itself through the change in wheel alignment parameters (WAP) due to suspension travel. This change in the WAP causes directional instability and tire-wear. The approach of the industry to solve this problem has been twofold. The first approach has been optimization of suspension link lengths to reduce the change in WAP to zero. Since this is not possible with the existing architecture, the solution used is the optimization of the spring stiffness K to get a compromise solution for comfort (which requires significant suspension travel and hence a soft spring) and directional stability (which demands least possible change in wheel alignment parameters and hence a stiff spring).

With the revolutionary advances in computing power and software technology, the future trend of integrating design and CFD analysis software package to realize an automated design optimization has been explored in this study. The integrated process of UG, ICEMCFD, and FLUENT was accomplished using iSIGHT for vehicle Aero/Thermal applications. Process integration, CFD solution strategy, optimization algorithm and the practicality for real world problem of this process have been studied, and will be discussed in this paper. As an example of this application, the results of an underhood thermal design will be presented. The advantage of systematical and rapid design exploration is demonstrated by using this integrated process. It also shows the great potential of computer based design automation in vehicle Aero/Thermal development.

Analytical study of vehicle idle shake performance is standard NVH work within the vehicle development process. Robust design for idle shake performance takes variations into account besides nominal design based performance evaluation. In other words, in addition to the nominal design, Robust Design includes additional evaluations that may incorporate variation due to manufacturing, usage or the environment. This paper presents an example of how to obtain a robust design through performing Robust Optimization on idle shake performance with respect to powertrain mount rates and their tolerance variation. The paper describes a two-phase process that has been systematically implemented to analytically obtain a robust design. In the first phase, performance variation assessment is conducted. Then a Robust Optimization is performed to obtain a robust design.

Determining the fundamental role of gravity in vital biological systems in space is one of six science and research areas that provides the philosophical underpinning for why NASA exists. The study of cells, tissues, and microorganisms in a spaceflight environment holds the promise of answering multiple intriguing questions about how gravity affects living systems. To enable these studies, specimens must be maintained in an environment similar to that used in a laboratory. Cell culture studies under normal laboratory conditions involve maintaining a highly specialized environment with the necessary temperature, humidity control, nutrient, and gas exchange conditions. These same cell life support conditions must be provided by the International Space Station (ISS) Cell Culture Unit (CCU) in the unique environment of space. The CCU is a perfusion-based system that must function in microgravity, at unit gravity (1g) on earth, and from 0.1g up to 2g aboard the ISS centrifuge rotor.