## Tesi etd-11062018-083217 |

Thesis type

Tesi di laurea magistrale

Author

BERNARDONI, FEDERICO

URN

etd-11062018-083217

Title

A stochastic approach to estimate the aerodynamic properties of the flow over irregular rough walls

Struttura

INGEGNERIA CIVILE E INDUSTRIALE

Corso di studi

INGEGNERIA AEROSPAZIALE

Supervisors

**relatore**Prof.ssa Salvetti, Maria Vittoria

**relatore**Prof. Leonardi, Stefano

Parole chiave

- turbulence
- polynomial chaos expansion
- roughness

Data inizio appello

27/11/2018;

Consultabilità

Secretata d'ufficio

Data di rilascio

27/11/2088

Riassunto analitico

In the present thesis a stochastic methodology is proposed to estimate aerodynamic quantities characterizing the flow over a rough surface.

An irregular rough surface is considered, whose geometrical parameters are characterized through a given Probability Density Function (PDF). The parameter space is sampled through the Latin Hypercube Sampling (LHS) method and a stochastic surrogate model is used to calculate the response function at each sample point, thus avoiding the need of carrying out computationally expensive wall resolved numerical simulations. The response surrogate model in the parameter space of the quantities of interest is built by using the Polynomial Chaos Expansion (PCE) starting from a few Direct Numerical Simulations (DNS) of sinusoidal rough wall geometries. Collecting the responses of all the samples with a statistical approach, the PDF of the quantities of interest, as well as their mean value and standard deviation, are reconstructed for the given irregular roughness. In the present study, only the variability of the streamwise wavelength has been taken into account to validate the procedure.

To assess the validity of the method, the drag coefficient, roughness function and turbulence intensities obtained with the stochastic approach are compared with those obtained in corresponding wall resolved DNS and a good agreement is obtained.

The computationally efficient and inexpensive prediction model is then thought to provide the quantities of quantities that characterize the flow to larger scale models

where the topography of the surfaces cannot be simulated due the grid resolution.

An irregular rough surface is considered, whose geometrical parameters are characterized through a given Probability Density Function (PDF). The parameter space is sampled through the Latin Hypercube Sampling (LHS) method and a stochastic surrogate model is used to calculate the response function at each sample point, thus avoiding the need of carrying out computationally expensive wall resolved numerical simulations. The response surrogate model in the parameter space of the quantities of interest is built by using the Polynomial Chaos Expansion (PCE) starting from a few Direct Numerical Simulations (DNS) of sinusoidal rough wall geometries. Collecting the responses of all the samples with a statistical approach, the PDF of the quantities of interest, as well as their mean value and standard deviation, are reconstructed for the given irregular roughness. In the present study, only the variability of the streamwise wavelength has been taken into account to validate the procedure.

To assess the validity of the method, the drag coefficient, roughness function and turbulence intensities obtained with the stochastic approach are compared with those obtained in corresponding wall resolved DNS and a good agreement is obtained.

The computationally efficient and inexpensive prediction model is then thought to provide the quantities of quantities that characterize the flow to larger scale models

where the topography of the surfaces cannot be simulated due the grid resolution.

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