Abstract

Abstract
The class of subspace system identification algorithms is used here to derive new identification algorithms for 2-D causal, recursive, and separable-in-denominator (CRSD) state space systems in the Roesser form. The algorithms take a known deterministic input-output pair of 2-D signals and compute the system order (n) and system parameter matrices {A, B, C, D}. Since the CRSD model can be treated as two 1-D systems, the proposed algorithms first separate the vertical component from the state and output equations and then formulate a set of 1-D horizontal subspace equations. The solution to the horizontal subproblem contains all the information necessary to compute (n) and {A, B, C, D}. Four algorithms are presented for the identification of CRSD models directly from input-output data: an intersection algorithm, (N4SID), (MOESP), and (CCA). The intersection algorithm is distinguished from the rest in that it computes the state sequences, as well as the system parameters, whereas N4SID, MOESP, and CCA differ primarily in the way they compute the system parameter matrices {A1, C1}. The advantage of the intersection algorithm is that the identified model is in balanced coordinates, thus ideally suited for 2-D model reduction. However, it is computationally more expensive than the other algorithms. A comparison of all algorithms is presented.

Abstract
In this paper a new approach to gas leakage detection in high pressure natural gas transportation networks is proposed. The pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node massflow with the gas inventory variation in the pipe (linepack variation, proportional to the pressure variation) as the scheduling parameter. The massflow at the offtake node is taken as the system output. The system is identified by the Successive Approximations LPV System Subspace Identification Algorithm which is also described in this paper. The leakage is detected using a Kalman filter where the fault is treated as an augmented state. Given that the gas linepack can be estimated from the massflow balance equation, a differential method is proposed to improve the leakage detector effectiveness. A small section of a gas pipeline crossing Portugal in the direction South to North is used as a case study. LPV models are identified from normal operational data and their accuracy is analyzed. The proposed LPV Kalman filter based methods are compared with a standard mass balance method in a simulated 10% leakage detection scenario. The Differential Kalman Filter method proved to be highly efficient.

Abstract
A new approach to gas leakage detection in high pressure distribution networks is proposed, where two leakage detectors are modelled as a linear parameter varying (LPV) system whose scheduling signals are, respectively, intake and offtake pressures. Running the two detectors simultaneously allows for leakage location. First, the pipeline is identified from operational data, supplied by REN-Gasodutos and using an LPV systems identification algorithm proposed in [1]. Each leakage detector uses two Kalman filters where the fault is viewed as an augmented state. The first filter estimates the flow using a calculated scheduling signal, assuming that there is no leakage. Therefore it works as a reference. The second one uses a measured scheduling signal and the augmented state is compared with the reference value. Whenever there is a significant difference, a leakage is detected. The effectiveness of this method is illustrated with an example where a mixture of real and simulated data is used.

Abstract
The assessment of contaminants dispersion in Controlled Dumps (CD) of Municipal Solid Waste (MSW) is possible through the combination of geophysical, geochemical and geostatistical methods as described in this paper. The methodology applied in this study will contribute to evaluate the environmental consequences of the Matosinhos CD (N Portugal), which is set in a granitic crystalline geological context with a permeability controlled by differential weathering associated with fracturing. The statistical methods here described (Lepeltier, 1969; Matschullat et al. 2000) are adapted to use in geophysical data obtained from the resistivity profiles performed in the CD surroundings by the electrical resistivity method. Groundwater samples were collected in piezometers; upstream and downstream of the CD, with the aim of directly confirming the presence of contaminants indirectly detected by the geophysical and geostatistical methods. The combination of these different approaches allows an approach to the detection and delineation of contaminant plumes from these deposits.

Abstract
In a multidisciplinary approach, geological, geomorphologic, structural, hydrogeochemical and isotopic surveys were conducted on the Serra da Estrela groundwater system (central Portugal) in order to establish/develop a conceptual circulation model of the Caldas de Manteigas thermomineral system. A detailed study of the isotopic and geochemical composition of surface waters (e.g. Zzere River), shallow groundwaters (cold dilute springs), and thermomineral waters was carried out to characterize the distribution of isotopes in waters of this mountainous region, and to determine the origin and possible recharge locations of the thermomineral system. Special attention was dedicated to isotopic tracers and their role in the definition of the thermomineral waters' conceptual model, considering: (1) the delta(18)O fractionation gradient; (2) the mean isotopic composition of the thermomineral waters in the region; and (3) the estimation of snowmelt contribution as a source of groundwater recharge at Serra da Estrela. The recharge of the thermomineral aquifer takes place on the more permeable zones of the granitic massif, associated with the main tectonic structures, whereas the recharge of the shallow aquifers seems to take place mostly in the plateaus, although another part of the recharge may occur in the slopes of the Zzere River valley.