Search Results

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

The human-robot interaction (HRI) is involved in a lift assistant system of manufacturing assembly line. The admittance model is applied to control the end effector motion by sensing intention from force of applied by a human operator. The variable admittance including virtual damping and virtual mass can improve the performance of the systems. But the tuning process of variable admittance is un-convenient and challenging part during the real test for designers, while the offline simulation is lack of learning process and interaction with human operator. In this paper, the Iterative learning algorithm is proposed to emulate the human learning process and facilitate the variable admittance control design. The relationship between manipulate force and object moving speed is demonstrated from simulation data. The effectiveness of the approach is verified by comparing the simulation results between two admittance control strategies.

A ductile failure criterion (DFC), which defines the stretching failure at localized necking (LN) and treats the critical damage as a function of strain path and initial sheet thickness, was proposed in a previous study. In this study, the DFC is revisited to extend the model to the low stress triaxiality domain and demonstrates on modeling forming limit curve (FLC) of TRIP 690. Then, the model is used to predict stretching failure in a finite element method (FEM) simulation on a TRIP 690 steel rectangular cup draw process at room temperature. Comparison shows that the results from this criterion match quite well with experimental observations.

This study evaluated the interactions between sheet steel, lubricant and measurement system under typical sheet forming conditions using a fixed draw bead simulator (DBS). Deep drawing quality mild steel substrates with bare (CR), electrogalvanized (EG) and hot dip galvanized (HDG) coatings were tested using a fixed DBS. Various lubricant conditions were targeted to evaluate the coefficient of friction (COF) of the substrate and lubricant combinations, with only rust preventative mill oil (dry-0 g/m2 and 1 g/m2), only forming pre-lube (dry-0 g/m2, 1 g/m2, and >6 g/m2), and a combination of two, where mixed lubrication cases, with incremental amounts of a pre-lube applied (0.5, 1.0, 1.5 and 2.0 g/m2) over an existing base of 1 g/m2 mill oil, were analyzed. The results showed some similarities as well as distinctive differences in the friction behavior between the bare material and the coatings.

Steel crankshafts are subjected to an induction heat treatment process for improving the operational life. Metallurgical phase transformations during the heat treatment process have direct influence on the hardness and residual stress. To predict the structural performance of a crankshaft using Computer Aided Engineering (CAE) early in the design phase, it is very important to simulate the complete induction heat treatment process. The objective of this study is to establish the overall analysis procedure, starting from capturing the eddy current generation in the crank shaft due to rotating inductor coils to the prediction of resultant hardness and the induced residual stress. In the proposed methodology, a sequentially coupled electromagnetic and thermal model is developed to capture the resultant temperature distribution due to the rotation of the inductor coil.

In the recent decades, tremendous effort has been made in automotive industry to reduce vehicle mass and development costs for the purpose of improving fuel economy and building safer vehicles that previous generations of vehicles cannot match. An accurate modeling approach of sheet metal fracture behavior under plastic deformation is one of the key parameters affecting optimal vehicle development process. FLD (Forming Limit Diagram) approach, which plays an important role in judging forming severity, has been widely used in forming industry, and localized necking is the dominant mechanism leading to fracture in sheet metal forming and crash events. FLD is limited only to deal with the onset of localized necking and could not predict shear fracture. Therefore, it is essential to develop accurate fracture criteria beyond FLD for vehicle development.

The market for electric vehicles and hybrid electric vehicles is expected to grow in the coming years, which is increasing interest in design optimization of electric motors for automotive applications. Under demanding duty cycles, the moving part within a motor, the rotor, may experience varying stresses induced by centrifugal force, a necessary condition for fatigue. Rotors contain hundreds of electrical steel laminations produced by stamping, which creates a characteristic edge structure comprising rollover, shear and tear zones, plus a burr. Fatigue properties are commonly reported with specimens having polished edges. Since surface condition is known to affect fatigue strength, an experiment was conducted to evaluate the effect of sample preparation on tensile and fatigue behavior of stamped specimens. Tensile properties were unaffected by polishing. In contrast, polishing was shown to increase fatigue strength by approximately 10-20% in the range of 105-107 cycles to failure.

The general benefits of automation are well documented. Order of magnitude improvements are achievable in processing speeds, production rates, and efficiency. Other benefits include improved process consistency (inversely, reduced process variation), reduced waste and energy consumption, and risk reduction to operators. These benefits are especially true for the automation of the aerospace paint removal (or "depaint") processes. Southwest Research Institute® (SwRI®) developed and implemented two systems in the early 1990s for depainting full-body fighter aircraft at Robins Air Force Base (AFB) at Warner Robins, Georgia, and Hill AFB at Ogden, Utah. These systems have been in production use, almost continuously for approximately 20 years, for the depainting of the F-15 Eagle and the F-16 Falcon fighter aircraft, respectively.

A dynamometer test methodology was developed for evaluation of HMMWV axle efficiency with hypoid gearsets, comparing those having various degrees of superfinish versus new production axles as well as used axles removed at depot maintenance. To ensure real-world applicability, a HMMWV variant vehicle model was created and simulated over a peacetime vehicle duty cycle, which was developed to represent a mission scenario. In addition, tractive effort calculations were then used to determine the maximum input torques. The drive cycle developed above was modified into two different profiles having varying degrees of torque variability to determine if the degree of variability would have a significant influence on efficiency in the transient dynamometer tests. Additionally, steady state efficiency performance is measured at four input pinion speeds from 700-2500 rpm, five input torques from 50 - 400 N⋅m, and two sump temperatures, 80°C and 110°C.

The Hybrid Cellular Automaton (HCA) algorithm is a generative design approach used to synthesize conceptual designs of crashworthy vehicle structures with a target mass. Given the target mass, the HCA algorithm generates a structure with a specific acceleration-displacement profile. The extended HCA (xHCA) algorithm is a generalization of the HCA algorithm that allows to tailor the crash response of the vehicle structure. Given a target mass, the xHCA algorithm has the ability to generate structures with different acceleration-displacement profiles and target a desired crash response. In order to accomplish this task, the xHCA algorithm includes two main components: a set of meta-parameters (in addition target mass) and surrogate model technique that finds the optimal meta-parameter values. This work demonstrates the capabilities of the xHCA algorithm tailoring acceleration and intrusion through the use of one meta-parameter (design time) and the use of Kriging-assisted optimization.

There is growing interest in additive manufacturing technologies for prototype if not serial production of complex internal combustion engine components such as cylinder heads and pistons. In support of this general interest the authors undertook an experimental bench test to evaluate opportunities for cooling jacket improvement through geometries made achievable with additive manufacturing. A bench test rig was constructed using electrical heating elements and careful measurement to quantify the impact of various designs in terms of heat flux rate and convective heat transfer coefficients. Five designs were compared to a baseline - a castable rectangular passage. With each design the heat transfer coefficients and heat flux rates were measured at varying heat inputs, flow rates and pressure drops. Four of the five alternative geometries outperformed the baseline case by significant margins.

Commercially available Generation 3 (GEN3) advanced high strength steels (AHSS) have inherent capability of replacing press hardened steels (PHS) using cold stamping processes. 980 GEN3 AHSS is a cold stampable steel with 980 MPa minimum tensile strength that exhibits an excellent combination of formability and strength. Hot forming of PHS requires elevated temperatures (> 800°C) to enable complex deep sections. 980 GEN3 AHSS presents similar formability as 590 DP material, allowing engineers to design complex geometries similar to PHS material; however, its cold formability provides implied potential process cost savings in automotive applications. The increase in post-forming yield strength of GEN3 AHSS due to work and bake hardening contributes strongly toward crash performance in energy absorption and intrusion resistance.

The General Motors Reduced Scale Wind Tunnel Facility, which came into operation in the fall of 2015, is a new state-of-the-art scale model aerodynamic test facility that expands GM’s test capabilities. The new facility also increases GM’s aerodynamic testing through-put and provides the resources needed to achieve the growing demand for higher fuel economy requirements for next generation of vehicles. The wind tunnel was designed for a nominal model scale of 40%. The nozzle and test section were sized to keep wind tunnel interference effects to a minimum. Flow quality and other wind tunnel performance parameters are on par with or better than the latest industry standards. A 5-belt system with a long center belt and boundary layer suction and blowing system are used to model underbody flow conditions. An overhead probe traverse system is installed in the test section along with a model positioning robot used to move the model in an out of the test section.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

Model-based control strategies are important for meeting the dual objective of maximizing NOx reduction and minimizing NH3 slip in urea-SCR catalysts. To be implementable on the vehicle, the models should capture the essential behavior of the system, while not being computationally intensive. This paper discusses the adequacy of two different reduced order SCR catalyst models and compares their performance with a higher order model. The higher order model assumes that the catalyst has both diffusion and reaction kinetics, whereas the reduced order models contain only reaction kinetics. After describing each model, its parameter identification and model validation based on experiments on a Navistar I6 7.6L engine are presented. The adequacy of reduced order models is demonstrated by comparing the NO, NO2 and NH3 concentrations predicted by the models to their concentrations from the test data.

The Port Fuel Injector (PFI) Deposit Test is a performance-based test procedure developed by the Coordinating Research Council and adopted by state and federal regulatory agencies for fuel qualification in the United States. To date, Southwest Research Institute (SwRI) has performed over 375 PFI tests between 1991 and 1998 for various clients. This paper details the analyses of these tests. Of the 375 tests, 199 were performed as keep-clean tests and 176 were performed as clean-up tests. The following areas of interest are discussed in this paper: Keep-clean versus clean-up test procedures Linearity of deposit formation Injector position effects as related to fouling Dirtyup / cleanup phenomena Seasonal effects This paper draws the conclusion that it is easier to keep new injectors from forming deposits than it is to clean up previously formed deposits. It was found that injector deposit formation is generally non-linear.

The main objective of this paper is to demonstrate how flow and solidification simulation were used in the development of a new gating system design for three different magnesium alloys; and to determine the relative castability of each alloy based on casting trials. Prototype tooling for an existing 3-slide rear wheel drive automatic transmission case designed for aluminum A380 was provided by General Motors. Flow and solidification simulation were performed using Magmasoft on the existing runner system design using A380 (baseline), AE44, MRI153M and MRI230D. Based on the filling results, new designs were developed at Meridian for the magnesium alloys. Subsequent modeling was performed to verify the new design and the changes were incorporated into the prototype tool. Casting trials were conducted with the three magnesium alloys and the relative castability was evaluated.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

The equipment for collecting dilute exhaust samples involves the use of bag materials (i.e., Tedlar®) that emit hydrocarbons that contaminate samples. This study identifies a list of materials and treatments to produce bags that reduce contamination. Based on the average emission rates, baked Tedlar®, Capran® treated with alumina deposition, supercritical CO2 extracted Kynar® and supercritical CO2 extracted Teflon NXT are capable of achieving the target hydrocarbon emission rate of less than 15 ppbC per 30 minutes. CO2 permeation tests were also performed. Tedlar, Capran, Kynar and Teflon NXT showed comparable average permeation rates. Based on the criteria of HC emission performance, changes in measured CO2 concentration, ease of sealing, and ease of surface treatment, none of the four materials could be distinguished from one another.