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It is known that SEA is a rapid and simple methodology for analyzing complex vibroacoustic systems. However, the SEA principle is not always valid and one has to be careful about the physical conditions at which the SEA principle is acceptable. In this study, the appropriate damping loss factor of the vehicle interior cavity is studied in the viewpoint of the modal overlap factor of the cavity and the decay per mean free path (DMFP) of the cavity. Virtual SEA tests are performed with an FE model combination, which is suggested by a previous study of Stelzer et al. for the simulation of the sound transmission loss (STL) of vehicle panel structure. The FE model combination is consisting of the body in white (BIW), an acoustical-excited hemisphere-shaped exterior cavity, and the interior cavity. It is found that the DMFP of the interior cavity is appropriate between 0.5 ~ 1 dB for applying SEA principle.

Industrial requirements imply optimizing the development cycle, reducing manufacturing costs and reaching marketable product maturity as fast as possible. The design stage often involves multiple sites and various partners. In this context, the use of computer simulation becomes absolutely necessary to meet industrial needs. Nevertheless, this activity can be effective only if it is integrated correctly in the industrial organization. In the aeronautical and space systems industry, mechanical specifications often require the use of composites reinforced by continuous carbon fibers. The goal of this article is to describe how, on a time frame of nearly twenty years, a series of scientific and technical tasks were carried out in partnership in order to develop, validate and implement Resin Transfer Molding (RTM) flow simulation and cure analysis for high performance composites. The research stage started at the university in 1991.

The technical feasibility of applying anaerobic digestion for reduction and stabilization of the organic fraction of solid wastes generated during space missions was investigated. This process has the advantages of not requiring oxygen or high temperature and pressure while producing methane, carbon dioxide, nutrients, and compost as valuable products. High-solids leachbed anaerobic digestion employed here involves a solid-phase fermentation with leachate recycle between new and old reactors for inoculation, wetting, and removal of volatile organic acids during startup. After anaerobic conversion is complete, the compost bed may be used for biofiltration and plant growth medium. The nutrient-rich leachate may also be used as a vehicle for nutrient recycle. Physical properties of representative waste feedstocks were determined to evaluate their space requirements and hydraulic leachability in the selected digester design.

Aerodynamic simulation results are most of the time compared to wind tunnel results. It is too often simplistically believed that it suffice to take the CAD geometry of a car, prepare and run a CFD simulation to obtain results that should be comparable. With the industry requesting accuracies of a few drag counts when comparing CFD to wind tunnel results, a careful analysis of the element susceptible of creating a difference in the results is in order. In this project a detailed 1:4 scale model of the Hyundai Genesis was tested in the model wind tunnel of the FKFS. Five different underbody panel configurations of the car were tested going from a fully paneled car to a car without panels. The impact of the moving versus static ground was also tested, providing over all ten different experimental results for this car model.

The main objective of this work is to demonstrate the merits of the Adjoint method to provide comprehensive information for shape sensitivities and design directions to achieve low drag vehicle shapes. The adjoint method is applied to a simple 2D airfoil and a 3D vehicle shape. The discrete Adjoint equations in the flow solvers are used to investigate further potential shape improvements of the low drag vehicle shapes. The low drag vehicle used in this study was designed earlier using the conventional approach (i.e., extensive use of wind tunnel testing). The goal is to use the already low drag vehicle shape and reduce its drag even further using the adjoint methodology without using the time-consuming and the high cost of wind tunnel testing. In addition, the present study is intended to compare the results with the other computational techniques such as surface pressure gradients method.

During icing wind tunnel experiments, the calibration process of the spray nozzle and aerothermal systems introduces experimental uncertainty that can potentially compromise the reliability of the test results. Therefore, performing sensitivity analysis (SA) or uncertainty quantification (UQ) studies is not only essential to determine the influence of uncertainties on the ice shape and aerodynamic performance but also crucial to identify the most significant icing parameter uncertainty. However, given the wide range of icing envelopes, it is not practical to conduct SA and UQ by experimental method because a lot of evaluations are required for SA and UQ study. In this study, we addressed these challenges by using a deep learning-based reduced-order modeling technique.

Diagonalized alternating-direction implicit (DADI) method is implemented in the Eulerian hyperbolic droplet solver, ICEPAC, for efficient high-order accurate analysis of aircraft icing. Detailed techniques for implementing the DADI method considering hyperbolicity characteristics are discussed. For the Eulerian droplet equation system to be strictly hyperbolic, additional source terms regarding artificial droplet pressure are included. Validations of the present implicit solver are conducted using two- and three-dimensional steady benchmark tests: NACA0012 airfoil, NACA23012 airfoil, and a swept wing. Also, the oscillating airfoil SC2110 case was analyzed to verify the robustness and efficiency of the proposed solver. In addition, the computational cost of the current implicit solver is considerably lower than that of the explicit multi-stage solver.