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FLOWS is a recently developed ICES subsystem for applications in the field of hydraulic engineering. It is able to compute steady as well as unsteady flows in hydraulic networks of given dimensions. This means that is does not optimize any parameters describing the network. The network may be composed of open and closed channels, reservoirs and flow control devices such as pumps, weirs etc. This covers water supply networks, estuaries, river and canal networks etc. Besides this, FLOWS computes the transport of pollutant in a hydraulic network. The method is restricted to such problems where the concentration is nearly uniform over the cross-section and where density differences have a negligible effect on the flow. Possible applications are cooling water circuits, salt intrusion etc. Some experience with respect to the flow computations 1S reported. Appendices give details about the numerical approximation and its accuracy, and about the use of the subsystem.

The contribution of Distributed generation (DG) to Electric Power Systems is evident, as it contributes to all major drivers of System´s sustainability (open market, security of supply and environment) propagated by EU directives. However, it is still not clear what impacts DG has on the Distribution System Operator´s (DSO) operations, which is in charge of providing a safe environment and technical conditions for their consumers and to DG as a newcomer in the system. This thesis addresses the issues related to Technical and Economic impacts of DG on remuneration of DSO. Using a Reference Network Model (RNM), an impact assessment is performed by analyzing changes in the grid´s operation through grid reinforcement costs, energy losses, and quality of service indices, under different scenarios of DG penetration in the Distribution network. Based on the obtained results recommendations have been made for alteration of DSO´s remuneration scheme for the case of a DSO in Spanish regulatory framework.

This paper describes an investigation on the usefulness of Bayesian Networks in the safety assessment of dune coasts. A network has been created that predicts the erosion volume based on hydraulic boundary conditions and a number of cross-shore profile indicators. Field measurement data along a large part of the Dutch coast has been used to train the network. Corresponding storm impact on the dunes was calculated with an empirical dune erosion model named duros+. Comparison between the Bayesian Network predictions and the original duros+ results, here considered as observations, results in a skill up to 0.88, provided that the training data covers the range of predictions. Hence, the predictions from a deterministic model (duros+) can be captured in a probabilistic model (Bayesian Network) such that both the process knowledge and uncertainties can be included in impact and vulnerability assessments.

Development of pore network models based on detailed topological data of the pore space is essential for predicting multiphase flow in porous media. In this work, an unstructured pore network model has been developed to simulate a set of drainage and imbibition laboratory experiments performed on a two-dimensional micromodel. We used a pixel-based distance transform to determine medial pixels of the void domain of micromodel. This process provides an assembly of medial pixels with assigned local widths that simulates the topology of the porous medium. Using this pore network model, the capillary pressure-saturation and capillary pressure-interfacial area curves measured in the laboratory under static conditions were simulated. On the basis of several imbibition cycles, a surface of capillary pressure, saturation and interfacial area was produced. The pore network model was able to reproduce the distribution of the fluids as observed in the micromodel experiments. We have shown the utility of this simple pore network approach for capturing the topology and geometry of the micromodel pore structure.