Active tectonics of the Alhama de Murcia fault, Betic Cordillera, Spain

We present an overview of the knowledge of the structure and the seismic behavior of the Alhama de Murcia Fault (AMF). We utilize a fault traces map created from a LIDAR DEM combined with the geodynamic setting, the analysis of the morphology, the distribution of seismicity, the geological information from E 1:50000 geological maps and the available paleoseismic data to describe the recent activity of the AMF. We discuss the importance of uncertainties regarding the structure and kinematics of the AMF applied to the interpretation and spatial correlation of the paleoseismic data. In particular, we discuss the nature of the faults dipping to the SE (antithetic to the main faults of the AMF) in several segments that have been studied in the previous paleoseismic works. A special chapter is dedicated to the analysis of the tectonic source of the Lorca 2011 earthquake that took place in between two large segments of the fault.

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper