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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).

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

Efficient methods for simulating operators performing part handling tasks in manufacturing plants are needed. The simulation of part handling motions is an important step towards the implementation of virtual manufacturing for the purpose of improving worker productivity and reducing injuries in the workplace. However, industrial assembly tasks are often complex and involve multiple interactions between workers and their environment. The purpose of this paper is to present a series of industrial simulations using the Human Motion Simulation Framework developed at the University of Michigan. Three automotive assembly operations spanning scenarios, such as small and large parts, tool use, walking, re-grasping, reaching inside a vehicle, etc. were selected.

This is a short presentation over the differences between soft soldering and the brazing, CuproBraze®, manufacturing techniques. Additional process equipment is described and production principles are explained.

The so-called Modified Martempering discussed in this work differs from the standard martempering by that the temperature of the quenching bath is below the Ms point. In spite of the fact the lower temperature increases the severity of quenching, this also usually avoids the bainite formation, and by this reason, it is possible to make a fair comparison between different processes, which result in different microstructures. The present study shows the results in terms of mechanical properties, impact resistance in special of a cold work tool steel class, after being heat treated by the isothermal modified martempering process, as well as a comparison with the conventional quenching and tempering process and the austempering as well.

The innovation term has been so widely misused that the confusion observed among the companies trying to get themselves into the innovation realm is a common and natural consequence. The lack of understanding of the innovation dynamics, flow and metrics generally culminate in a non-well-thought implementation of innovation processes and policies that are usually tragic in the short term. The most common consequences are the loss of credibility of the innovation process in general among leaders and employees, and the loss of credibility of the company as an innovative company among suppliers, partners and customers, causing these companies to abandon this powerful tool and, as consequence, to limit their capabilities to compete in the future. In order to prevent this from happening, companies that were not built upon innovation will need to grow capability and change cultural priorities to match the demands of the innovation process.

This paper describes the validation of RAMSIS, a 3-D CAD human model for ergonomic vehicle evaluation. At GM NAO, the model’s capability to correctly predict position and posture in vehicle CAD environments was tested. H- and Eye point locations between RAMSIS manikins and their human counterparts were compared. At GM/SAAB the model’s postural discomfort predictability was evaluated. Changes in postural discomfort predictions of the RAMSIS manikins were compared to that of the human subjects when they evaluated two different driving buck conditions. We concluded that RAMSIS has good position, posture and postural discomfort prediction capabilities and is a useful CAD ergonomic evaluation and design tool for vehicle interiors.

Recent trends in signal processing have led to the discovery and implementation of wavelets as tools of many different applications. This paper focuses on their use as a tool for transient extraction. From the Discrete Wavelet Transform (DWT), specific coefficients are picked using a coherence-based criterion. These coefficients are then taken back to the time domain as the extracted transient. If the extracted transient is a response from a measured input, then a frequency response function can be formulated.

A practical approach for evaluating and validating global system designs for Squeak and Rattle performance is proposed. Using simple slip and rattle models, actual sound and vibration data, and the fundamentals of audiological perception, analysis tools adapted from Chaos Theory are used to establish threshold levels of performance and identify system characteristics which are significant contributors to Squeak and Rattle. Focus on system design is maintained by using a simple rattle noise indicator and relating rattle events to levels of dynamic motion (acceleration, velocity, etc.). The threshold level is defined as the level of acceleration at which the system moves from a non-rattling state to a rattling state. The approach is demonstrated with a simple analytical model applied to an experimental structure under dynamic load.

This paper describes the validation of RAMSIS, a 3-D CAD human model for ergonomic vehicle evaluation at General Motors (GM). The model’s capability to correctly predict position and posture in vehicle CAD environments was tested. H- and Eye point locations between RAMSIS manikins and their human counterparts were compared. We concluded that RAMSIS has good position and posture prediction capabilities and is a useful CAD ergonomic evaluation and design tool for vehicle interiors.

Noise Path Analysis techniques (NPA) have been developed and refined by the automotive industry for structure-borne noise and vibration evaluation of their products. Off-highway vehicles, particularly those with enclosed cabs, are excellent candidates for the application of these techniques. Like automobiles, many off-highway machines are typically driven by a rotating power source, have a well-defined acoustic receiver space, and use some form of isolation between source and receiver sub-systems. These structural characteristics make NPA a useful tool for identifying dominant sources and energy transfer paths. The objectives of this paper are to revisit the fundamental theory of matrix inversion as it applies to NPA techniques, and to address the common setup and measurement issues encountered when acquiring noise path data on off-highway machines. A general overview of the procedures involved in applying NPA to an off-highway machine will be presented.

Several very different order tracking and analysis techniques for rotating equipment have been developed recently that are available in commercial noise and vibrations software packages. Each of these order tracking methods has distinct trade-offs for many common applications and very specific advantages for special applications in sound quality or noise and vibrations troubleshooting. The Kalman, Vold-Kalman, Computed Order Tracking, and the Time Variant Discrete Fourier Transform as well as common FFT based order analysis methods will all be presented. The strengths and weaknesses of each of the methods will be presented as well as the highlights of their mathematical properties. This paper is intended to be an overview of currently available technology with all methods presented in a common format that allows easy comparison of their properties. Several analytical examples will be presented to thoroughly document each methods' behavior with different types of data.

Sound intensity measurement techniques that used a two-microphone configuration, were first developed in the late 1970s. Originally, the focus was on improving precision during testing or post-processing. However, with the advent of modern, sophisticated equipment, the focus has shifted to the apparatus. Availability of phase-matched microphones has made post-test correction obsolete as the microphones eliminate a majority of the errors before the data is even collected. This accuracy, however, comes at a cost, as phase-matched microphones are highly priced. This paper discusses employing the method of improving post-processing precision, using inexpensive, current equipment. The phase error of the system is corrected using a simple calibration technique and a handheld phase calibrator that is similar to the one used for amplitude calibration of microphones.

The AutoDrive Challenge competition sponsored by General Motors and SAE gives undergraduate and graduate students an opportunity to get hands-on experience with autonomous vehicle technology and development as they work towards their degree. Michigan Technological University has participated in the AutoDrive Challenge since its inception in 2017 with students participating through MTU’s Robotic System Enterprise. The MathWorks Simulation Challenge has been a component of the competition since its second year, tasking students with the development of perception, control and testing algorithms using MathWorks software products. This paper presents the pedagogical approach graduate student mentors used to enable students to build their understanding of autonomous vehicle concepts using familiar tools. This approach gives undergraduate students a productive experience with these systems that they may not have encountered in coursework within their academic program.