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Statistical Energy Analysis (SEA) is an established high-frequency analysis technique for generating acoustic and vibration response predictions in the automotive, aerospace, machinery, and ship industries. SEA offers unique NVH prediction and target-setting capabilities as a design tool at early stages of vehicle design where geometry is still undefined and evolving and no prototype hardware is available yet for testing. The exact frequencies at which SEA can be used effectively vary according to the size and the amount of damping in the vehicle subsystems; however, for automotive design the ability to predict acoustic and vibration responses due to both airborne and structure-borne sources has been established to frequencies of 500 Hz and above. This paper presents the background, historical use, and current industrial applications of structure-borne SEA. The history and motivation for the development of structure-borne SEA are discussed.

For many years, the use of in-mold fasteners has been avoided for various reasons including: not fully understanding the load cases in the part, the fear of quality issues occurring, the need for servicing, or the lack of understanding the complexity of all failure modes. The most common solution has been the use of secondary operations to provide attachments, such as, screws, metal clips, heat staking, sonic welding or other methods which are ultimately a waste in the process and an increase in manufacturing costs. The purpose of this paper is to take the reader through the design process followed to design an in-molded attachment clip on plastic parts. The paper explores the design process for in-molded attachment clips beginning with a design concept idea, followed by basic concept testing using a desktop 3D printer, optimizing the design with physical tests and CAE analysis, and finally producing high resolution 3D prototypes for validation and tuning.

A three phase catalytic mathematical model was developed for analysis and optimization of the volatile reactor assembly (VRA) used on International Space Station (ISS) Water Processor. The Langmuir-Hinshelwood Hougen-Watson (L-H) expression was used to describe the surface reaction rate. Small column experiments were used to determine the L-H rate parameters. The test components used in the experiments were acetic acid, acetone, ethanol, 1-propanol, 2-propanol and propionic acid. These compounds are the most prevalent ones found in the influent to the VRA reactor. The VRA model was able to predict performance of small column data and experimental data from the VRA flight experiment.

The airflow that enters the front grille of a ground vehicle for the purpose of component cooling has a significant effect on aerodynamic drag (engine airflow drag). Furthermore, engine airflow is known to be capable of influencing upstream external airflow (interference drag). The combined effect of these phenomena is commonly referred to as cooling drag, which generally contributes up to 10% of total vehicle drag. Due to this coupled nature, cooling drag is difficult to understand as it contains influences from multiple locations around the vehicle. A good understanding of the sources of cooling drag is paramount to drive vehicle design to a low cooling drag configuration. In this work, a production level Lincoln MKZ was modified so that a number of variables could be tested in both static ground and moving ground wind tunnel conditions. All tests were conducted at 80 MPH.