Abstract
In this paper we design a model based method to locate a leakage and estimate its size in a gas network, using a linearised version of an hyperbolic PDE. To do this, the problem is reduced to two identical ODEs, allowing in this way for a representation of the pressure as well as the mass flow in terms of its system of fundamental solutions. Then using the available measurements at the grid boundary points, the correspondent coefficients can be determined. Assuming pressure continuity, we check for consistency of the coefficients in order to find faulty pipelines. Thence, the location of the leakage can be found either graphically or using a numerical method for a specific pipe. Next, its size can also be estimated. © Springer International Publishing Switzerland 2017.

Abstract
In this paper we propose to model a high pressure gas network using a quadripole approach. Although being simple, the proposed model seems to be adequate to network analysis and control, and is directly extendible to more complex networks, i.e., networks with junctions and loops. The model is proven to be liable on a case study constructed from data supplied by REN Gasodutos, where we investigate the effect of a leakage on the mass flow and pressure along the pipeline with the final objective to define a model based methodology for leakage detection and location. © Springer International Publishing Switzerland 2017.

Abstract

Abstract
Knowledge of walls and other structural elements construction characteristics and techniques is mandatory in the maintenance and restoration of historical buildings. Such information is obtained from documents or by comparing with monuments of the same period. Documents are difficult to obtain and comparison with other buildings can be inaccurate. The use of direct invasive techniques may be considered but they are likely to damage structures or compromise buildings stability. Thus, indirect high-resolution methods are adapted to these investigations. This work describes a GPR and a Seismic Transmission Tomography survey to investigate the walls and columns of the 14th century Batalha Abbey (UNESCO heritage site). High-resolution GRP data revealed the dimensions and thicknesses of different walls and the structure and nature of materials inside them. The Seismic Transmission Tomography survey, supported by high-resolution photogrammetry scanning for accurate positioning of sources and geophones, was carried out to investigate the Abbey columns. Seismic velocities distribution inside the columns characterized their interior and clarified the nature of the materials used. Columns construction followed the same technique and used the same materials. However, each column depicts a different velocity zonation that could correspond to different stages of deterioration for each one.

Abstract
Model-Based learning is a methodology that facilitates students' construction of scientific knowledge, which, sometimes, includes restructuring their mental models. Taking into consideration students' learning process, its aim is to promote a deeper understanding of phenomena's dynamics through the manipulation of models. Our aim was to ascertain whether the use of three different types of models, integrated into an intervention program whose goal was to teach the "seismic effects on soils and buildings", would influence the learning process of graduation students or not. For a better understanding of the results, the data were collected and analyzed through a combination of methods using, simultaneously, quantitative and qualitative method. And results not only confirmed the importance of the use of models, but also led us to the conclusion that despite the potential and limitations of all three models, mixed models are better for restructuring students' mental models and the development of meaningful learning.

Abstract
Simple statistical models were developed to relate available meteorological data with daily river discharge (RD) for rivers not influenced by melting of ice and snow. In a case study of the Vouga River (Portugal), the RD could be determined by a linear combination of the recent (P (R)) and non-recent (P (NR)) atmospheric precipitation history. It was found that a simple linear model including only P (R) and P (NR) cannot account for low RD. The model was improved by including non-linear terms of precipitation that accounted for the water loss. Additional improvement of the models was possible by including average monthly air temperature (T). The best model was robust when up to 60% of the original data were randomly removed. The advantage is the simplicity of the models, which take into account only P (R), P (NR) and T. These models can provide a useful tool for RD estimation from current meteorological data.