The goal of this thesis is to provide a reader with a comprehensive outlook on the cost-pricing process in a real FMCG company. Firstly, the thesis concentrates on the theoretical background of cost methodologies and pricing strategies from a perspective of a private firm. Secondly, the thesis presents a tool, which calculates the reflection of the change in the commodity cost on the shelf price of a good. Thirdly, statistical testing is applied in order to identify if the model could correlate with reality based on historical data. In this part the thesis discusses the limitations of the model and gives more real life examples of how the price is set, besides the commodity influence. Thanks to it, a reader will be able to draw conclusions from the given information and deeper understand the complexity of the FMCG market industry.

The main focus of this work is on the non-Newtonian effects on the inertial instabilities in shear flows. Both inelastic (Carreau) and elastic models (Oldroyd-B and FENE-P) have been employed to examine the main features of the non-Newtonian fluids; shear-thinning, shear-thickening and elasticity. Several classical configurations have been considered; flow past a circular cylinder, in a lid-driven cavity and in a channel. We have used a wide range of tools for linear stability analysis, modal, non-modal, energy and sensitivity analysis, to determine the instability mechanisms of the non-Newtonian flows and compare them with those of the Newtonian flows. Direct numerical simulations have been also used to prove the results obtained by the linear stability analysis. Significant modifications/alterations in the instability of the different flows have been observed under the action of the non-Newtonian effects. In general, shear-thinning/shear-thickening effects destabilize/stabilize the flow around the cylinder and in a lid driven cavity. Viscoelastic effects both stabilize and destabilize the channel flow depending on the ratio between the viscoelastic and flow time scales. The instability mechanism is just slightly modified in the cylinder flow whereas new instability mechanisms arise in the lid-driven cavity flow. We observe that the non-Newtonian effect can alter the inertial flow at both baseflow and perturbation level (e.g. Carreau fluid past a cylinder or in a lid driven cavity) or it may just affect the perturbations (e.g. Oldroyd-B fluid in channel). In all the flow cases studied, the modifications in the instability dynamics are shown to be strongly connected to the contribution of the different terms in the perturbation kinetic energy budget. / <p>QC 20140113</p>

Real-world large-scale complex networks such as the Internet, social networks and biological networks have increasingly attracted the interest of researchers from many areas. Accurate modelling of the statistical regularities of these large-scale networks is critical to understand their global evolving structures and local dynamical patterns. Traditionally, the Erdos and Renyi random graph model has helped the investigation of various homogeneous networks. During the past decade, a special computational methodology has emerged to study complex networks, the outcome of which is identified by two models: the Watts and Strogatz small-world model and the Barabasi-Albert scale-free model. At the core of the complex network modelling process is the extraction of characteristics of real-world networks. I have developed computer simulation algorithms for study of the properties of current theoretical models as well as for the measurement of two real-world complex networks, which lead to the isolation of three complex network modelling essentials. The main contribution of the thesis is the introduction and study of a new General Two-Stage growth model (GTS Model), which aims to describe and analyze many common-featured real-world complex networks. The tools we use to create the model and later perform many measurements on it consist of computer simulations, numerical analysis and mathematical derivations. In particular, two major cases of this GTS model have been studied. One is named the U-P model, which employs a new functional form of the network growth rule: a linear combination of preferential attachment and uniform attachment. The degree distribution of the model is first studied by computer simulation, while the exact solution is also obtained analytically. Two other important properties of complex networks: the characteristic path length and the clustering coefficient are also extensively investigated, obtaining either analytically derived solutions or numerical results by computer simulations. Furthermore, I demonstrate that the hub-hub interaction behaves in effect as the link between a network's topology and resilience property. The other is called the Hybrid model, which incorporates two stages of growth and studies the transition behaviour between the Erdos and Renyi random graph model and the Barabasi-Albert scale-free model. The Hybrid model is measured by extensive numerical simulations focusing on its degree distribution, characteristic path length and clustering coefficient. Although either of the two cases serves as a new approach to modelling real-world large-scale complex networks, perhaps more importantly, the general two-stage model provides a new theoretical framework for complex network modelling, which can be extended in many ways besides the two studied in this thesis.