Evolución tectónica del borde norte de la cuenca del Bajo Segura. Implicaciones en la evolución de la falla de Crevillente (sector Abanilla-Alicante)

En este estudio presentamos los resultados del análisis estructural del borde norte de la cuenca del Bajo Segura, en la cordillera Bética oriental. En este borde se desarrolla el sinclinal de Crevillente; se trata de un pliegue de propagación de falla con geometría de crecimiento y vergente al sur asociado a la falla de Crevillente (sector Abanilla-Alicante). El estudio cuantitativo de la discordancia progresiva asociada a dicho pliegue ha puesto de manifiesto que la actividad de esta falla se inició en el Tortoniense, aumentó durante el Messiniense y, a partir de ese momento se ha mantenido constante o ha disminuido durante el Plioceno y el Cuaternario. La escasez de depósitos cuaternarios deformados no implica que no exista actividad cuaternaria de la falla de Crevillente (sector Abanilla-Alicante), ya que la mayoría de los depósitos más recientes son discontinuos o se localizan al sur, alejados de la zona de máxima deformación. Por otro lado, el hecho de que la actividad de la falla del Bajo Segura, situada en el borde meridional de la cuenca, se iniciara durante el Plioceno, parece indicar una migración de la deformación hacia el sur.

Water reduction in waste-activated sludge by resettling and filtration in batch. Phase (1): pilot-scale experiments to optimize performance

This article describes an effective procedure for reducing the water content of excess sludge production from a wastewater treatment plant by increasing its concentration and, as a consequence, minimizing the volume of sludge to be managed. It consists of a pre-dewatering sludge process, which is used as a preliminary step or alternative to the thickening. It is made up of two discontinuous sequential stages: the first is resettling and the second, filtration through a porous medium. The process is strictly physical, without any chemical additives or electromechanical equipment intervening. The experiment was carried out in a pilot-scale system, consisting of a column of sedimentation that incorporates a filter medium. Different sludge heights were tested over the filter to verify the influence of hydrostatic pressure on the various final concentrations of each stage. The results show that the initial sludge concentration may increase by more than 570% by the end of the process with the final volume of sludge being reduced in similar proportions and hydrostatic pressure having a limited effect on this final concentration. Moreover, the value of the hydrostatic pressure at which critical specific cake resistance is reached is established.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.