Parameter Estimation and Uncertainty Quantification for Core Flooding

In light of our depleting fossil fuel reserves and the relatively `cheap' extraction of oil and in spite of the highly nonlinear nature of reservoirs, waterflooding has become big business. In recent times, the use of numerical reservoir simulation has not only become possible but has increasingly been used in the petroleum industry in the...

A Validation Infrastructure for Non-Ideal Compressible Fluid Dynamics: with applications to ORC Turbines

The objective of this thesis was to further the validation effort on the SU2 flow solver for non-ideal compressible flows. To do so, an uncertainty quantification infrastructure based on the V&V20 validation standard was developed. To determine whether a model error was present, the different sources of uncertainty were combined and then...

Bayesian Deep Learning for Dynamic System Identification

System identification is a mature field in physical sciences and an emerging field in social sciences, with a vast range of applications. Nevertheless, it remains of great focus in academia. The main challenge is the efficient use of data to generate good model fits. System identification involves multi-disciplinary techniques from statistical,...

Wind Farm Layout Optimisation Under Uncertainty Using Surrogate Models

This research aims to develop a method to create a wind farm layout that is robust against the uncertainty source, the inter-year variation of Weibull parameters and wind direction sector probabilities. A wind farm layout optimisation problem under uncertainty corresponds to optimisation under uncertainty (OUU), which is computationally...

Validation of the SU2 Flow Solver for Classical Non Ideal Compressible Fluid Dynamics

The validation of SU2 for modelling classical non-ideal compressible fluid dynamics will advance the research into efficient ORC turbomachinery design. This study determines the validity of the two-dimensional flow solver for predicting the isentropic expansion of Siloxane MM through a converging-diverging nozzle using...

Uncertainty in finite element analysis of a submarine`s hull

The Finite Element Method possess the intrinsic characteristic that, due to the assumptions made for the parameters of the problem being modelled, a deterministic uncertainty on the obtained results is always present. This research makes use of basic statistical concepts to obtain reference values for a possible quantification of this...

Bayesian Additive Regression Trees for data-driven RANS turbulence modelling

Turbulent flows are commonly encountered in scientific research or engineering applications and need simulations to be resolved. The Navier-Stokes equations govern the simulations of turbulent flows. One of the most common ways to solve the Navier-Stokes equations is to analyse the Reynolds averaged form (RANS). Next to the increasing...

The characterization of uncertainty for steady state multiphase flow models in pipelines

Steady state multiphase flow models are used for the design and operation of pipelines that are used in the oil and gas industry. The predictions obtained with these models contain uncertainties, which arise from model assumptions and simplifications, and from uncertainties in the input parameters. In this thesis we investigate the effect of...

Safe Flight Envelope Uncertainty Quantification using Probabilistic Reachability Analysis

Loss of Control is the primary contributor to aviation fatalities. To prevent this type of accident, flight envelope protection is considered to be a necessary development. The calculation of the Safe Flight Envelope provides a bound on the states that can safely be approached by the aircraft. Although theoretically accurate, some states may not...

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...

Determination of Relevant Spatial Scale in Reservoir Simulation

Under-sampling of the subsurface combined with scale differences in observations causes the estimation of geological parameters to be an ill-posed problem. As a result, only a subset of theoretically possible models can truly depict the reality. In reservoir modeling, we capture complexity and heterogeneity by representing the solution space...

Probabilistic analysis of manufacturing variability and wear of core engine components

In the framework of LuFo R\&T projects a number of Rolls-Royce Deutschland Low and High Pressure Compressor rotor blades were geometrically scanned at the beginning and end of their life cycle. Based on this data component wear, ageing and manufacturing variability across the life cycle of the engine can be derived. Using Computational Fluid...