Search Results

In electronic vehicles (EVs) or hybrid electronic vehicles (HEVs), an inverter system has a direct-current-link capacitor (DC-link capacitor) which provides reactive power, attenuates ripple current, reduces the emission of electromagnetic interference, and suppresses voltage spikes. A film capacitor has been used as the DC-link capacitor in high level power system, but the film capacitor's performance has deteriorated over operating time. The decreasing performance of the film capacitor may cause a problem when supplying and delivering energy from the battery to the vehicle's power system. Therefore, the lifetime prediction of the film capacitor could be one of critical factors in the EVs and HEVs. For this reason, the lifetime and reliability of the film capacitor are key factors to show the stability of the vehicle inverter system. There are a lot of methods to predict the lifetime of the film capacitor.

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.

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.