Unsteady SpaRTA: Data-driven turbulence modelling for unsteady applications

Recent years have seen an increase in studies focusing on data-driven techniques to enhance modelling approaches like the two-equation turbulence models of Reynolds-averaged Navier-Stokes (RANS). Different techniques have been implemented to improve the results from these simulations. In particular, the main focus has been on overcoming the...

Model Assisted Probability of Detection of Phased Array Ultrasonic on an Aircraft Metallic Part

Skipping The Jacobian: (Hyper) Reduced Order Models For Moving Meshes

We present a reduced order model (ROM) for a one-dimensional nonlinear gas dynamics problem: the isentropic piston. The main body of the PDE, the geometrical definition of the mesh nodes, and the boundary conditions are parametrized. The full order model is obtained with a Galerkin finite element discretization, under the Arbitrary Lagrangian...

Development of a CFD data-driven surrogate model using the neural network approach for prediction of aircraft performance characteristics

Evaluation of aircraft performance for design, certification, and maintenance purposes requires aerodynamic knowledge for the entire flight envelope of an aircraft. Simplified models that relate geometric properties and flight conditions of an aircraft to its aerodynamic properties are simply not sufficient anymore, as non-linear aerodynamic...

Approximate basis and a priori closure models for energy-conserving reduced order modeling of fluid flows

Model order reduction (MOR) has been a field of active research in the past twenty years, more recently also in fluid dynamics. The main advantage of MOR is computational cost reduction, which, along with equally important accuracy, constitute main objective in the MOR community.<br/>A main ongoing issue is that data volumes in fluid flow...

Two-level preconditioning applied on the ssSNPBLUP model

The single-step single nucleotide polymorphism best linear unbiased prediction (ssSNPBLUP) model can potentially be used in animal breeding for genetic evaluations. It has been reported that this model has convergence issues when the Preconditioned Conjugate Gradient (PCG) method is applied. This is due to the linear system being ill-conditioned...

Experimental investigation of turbulent coherent structures interacting with a porous airfoil

Abstract: The flow field on solid and porous airfoils subjected to turbulence shed by an upstream cylindrical rod and the corresponding far-field noise radiations are studied through particle image velocimetry (PIV) and microphone measurements, respectively. Three different Reynolds numbers based on the rod diameter are considered in a range...

Precise absolute and relative navigation in Medium-Earth Orbits by means of Global Navigation Satellite Systems and Inter-Satellite Links

The first close-up image of a black hole has been taken recently by means of a network of high-resolution telescopes situated all around the globe, also known as Event Horizon Telescope (EHT). In that regard, this Master Thesis reviews the feasibility of establishing accurate inter-satellite baselines in a two-satellite constellation of...

POD-Based Deflation Method For Reservoir Simulation

Simulation of flow through highly heterogeneous porous media results in large ill-conditioned systems of equations. In particular, solving the linearized pressure system can be especially time-consuming. Therefore, extensive efforts to find ways to address this issue effectively are required. In this work, we introduce a POD-based deflation...

On POD-based Deflation Vectors for DPCG applied to porous media problems

We study fast and robust iterative solvers for large systems of linear equations resulting from simulation of flow trough strongly heterogeneous porous media. We propose the use of preconditioning and deflation techniques, based on information obtained frfrom the system, to reduce the time spent in the solution of the linear system.An important...

Flow reconstruction using Bayesian inference with model reduction techniques

RANS equations are nowadays widely used in industry because of their affordability in terms of computational costs. They reached a high level of complexity, as they involve systems of non-linear partial differential equations. However they still lack of generality as they are based on closure coefficients determined from fundamental real flow...

Reduced-Order Modelling for Production Optimisation

Production optimisation of a reservoir simulation problem can be very computationally demanding as the reservoir model may contain many variables and nonlinearities, thus many iterations may be needed to obtain an optimal production schedule. Using Proper Orthogonal Decomposition and Trajectory Piecewise Linearization (POD-TPWL) developed in [1]...

A Semi-Continuous Formulation for Goal-Oriented Reduced-Order Models

A semi-continuous formulation is introduced for finding bases which minimise the error in a specific output functional of a reduced-order model. The formulation is advantageous in that it can be easily applied to nonlinear problems and functionals. A general description of the approach is given, then explicit formulations are derived for the...

A Study of Reduced Order 4D-VAR with a Finite Element Shallow Water Model

Forecast models often depend on unknown parameters, such as model initial and boundary conditions, or other tunable parameters not necessarily having any physical meaning. Calibration of these parameters to minimize errors between forecasted and observed states is called data assimilation. A common approach in this context are variational...

Discovering an infinite prime flow by finding a Proximal Orbit Dense flow

In this document, the proof of the existence of an infinite prime flow, by showing that a Proximal Orbit Dense flow is prime, is examined. This proof has been given by Furstenberg, Keynes and Shapiro in the year 1973. This document investigates this proof thoroughly, as it is quite intricate and it requires a proficient amount of theory. As a...

Proper orthogonal decomposition of the flow in geometries containing a narrow gap

Geometries containing a narrow gap are characterized by strong quasi-periodical flow oscillations in the narrow gap region. The above mentioned phenomena are of inherently unstable nature and, even if no conclusive theoretical study on the subject has been published, the evidence shown to this point suggests that the oscillations are connected...