Statistical inverse analysis and stochastic modeling of transition

Abstract

A computational method is introduced to infer statistical information on boundarylayer perturbations upstream of laminar-turbulent transition in a supersonic boundary layer. The method uses the intermittency function as a basis, which specifies the amount of time a flow is turbulent at a given streamwise location. The methods yields a joint probability density function for amplitude and frequency of boundary-layer perturbations upstream of transition. It relies on linear stability theory to link the probability density function with the intermittency. In order to infer parameters governing the function, we perform a statistical inverse analysis using the Markov chain Monte Carlo method. The approach is applied to a synthetic test case and to experimental data.

Stochastic design of high altitude propellers

“…Apart from the wind, there are other sources of uncertainty such as the low 25 Reynolds phenomena [6]. That phenomena characterizes the stratospheric propellers and causes a high variability in the aerodynamic coefficient of the blade sections [7]. The high variability makes impossible to assure the aerodynamic performance of the propeller.…”

Estudio del sistema motopropulsivo para Pseudo-satélites = Design of the propulsion system for High Altitude Pseudo-Satellites

“…A parte del viento, hay otras fuentes de incertidumbre que también deberían de tenerse en cuenta. Una de las más relevantes, y que ya ha sido mencionada anteriormente en esta tesis, es causada por el bajo número de Reynolds que origina una alta variabilidad en los coeficientes aerodinámicos de cada una de las secciones [143]. Esta alta variabilidad hace que, a efectos prácticos, sea imposible asegurar unosúnicos coeficientes aerodinámicos en los que cada perfil vaya a trabajar a lo largo de la operación.…”