Reduced Order Modeling of Aviation Environmental Design Tool with Proper Orthogonal Decomposition and Kriging

A high fidelity simulation is preferred for its remarkable accuracy for engineering problems. However, it requires long computational time, which leads to significant overhead and eventually hinders its application to design study. To overcome such impediments, a reduced-order method is utilized. Reducedorder method can effectively represent a simulation output as a linear combination of a basis and weighting coefficients on a low dimensional space. To construct a reducedorder model, this research adopts proper orthogonal decomposition to collect an empirical orthogonal basis and ordinary Kriging interpolation to predict weighting coefficients. Afterwards, this research applies reduced-order methodology to an aviation environmental design tool for the rapid prediction of arrival and departure noise.