26 resultados para Dormant fault segment
em Universidad Politécnica de Madrid
Resumo:
El 12 de agosto de 2014, se registró un sismo de magnitud 5.1, a una profundidad focal de 4 km., en el segmento de falla Bellavista Catequilla, el mismo que fue registrado en 8 estaciones localizadas en la ciudad de Quito. Estas se encuentran ubicadas a distancias epicentrales entre 12 y 19 km. En este artículo se comparan las aceleraciones máximas obtenidas en campo libre, con las que se obtienen al emplear las ecuaciones de movimientos fuertes de Campbell y Borzognia (2013) y el de Zhao et al. (2006). Para ello previamente se determina un plano de ruptura del sismo, utilizando las ecuaciones propuestas por Leonard (2010) y la geometría de las fallas ciegas propuestas por Alvarado (2014). ABSTRACT: On August 12 th 2014, a magnitude 5.1 earthquake occurred at a depth of 4 km, in the Bellavista Catequilla fault segment. This event was recorded by 8 strong-motion stations located between 12 and 19 km from the epicenter, in the city of Quito. In this article, the maximum ground accelerations recorded in free field are compared with the accelerations estimated using the models by Campbell y Borzognia (2013) and Zh ao et al. (2006). To this end, the earthquake rupture plane is determined using the equations proposed by Leonard (2010) and the geometry of the blind fault system of Quito proposed by Alvarado (2014).
Resumo:
A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.
Resumo:
Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.
Resumo:
• Central America: – Regional studies in Central America (Seismic Hazard). – El Salvador Fault Zone (ESFZ). – Aguacaliente‐Navarro Fault Zone (ANFZ), Central Valley of Costa Rica. – Haiti (seismic hazard) • Spain: – Regional‐Nacional studies of seismic hazards (applications to building codes, eurocode, emergency plans, etc.) – Betic range zone, south of Spain. – Ibero‐Maghrebi region (collision zone)
Resumo:
This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)
Resumo:
We consider the problem of supporting goal-level, independent andparallelism (IAP) in the presence of non-determinism. IAP is exploited when two or more goals which will not interfere at run time are scheduled for simultaneous execution. Backtracking over non-deterministic parallel goals runs into the wellknown trapped goal and garbage slot problems. The proposed solutions for these problems generally require complex low-level machinery which makes systems difficult to maintain and extend, and in some cases can even affect sequential execution performance. In this paper we propose a novel solution to the problem of trapped nondeterministic goals and garbage slots which is based on a single stack reordering operation and offers several advantages over previous proposals. While the implementation of this operation itself is not simple, in return it does not impose constraints on the scheduler. As a result, the scheduler and the rest of the run-time machinery can safely ignore the trapped goal and garbage slot problems and their implementation is greatly simplified. Also, standard sequential execution remains unaffected. In addition to describing the solution we report on an implementation and provide performance results. We also suggest other possible applications of the proposed approach beyond parallel execution.
Resumo:
n this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein–Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.
Resumo:
Axonal outgrowth and the formation of the axon initial segment (AIS) are early events in the acquisition of neuronal polarity. The AIS is characterized by a high concentration of voltage-dependent sodium and potassium channels. However, the specific ion channel subunits present and their precise localization in this axonal subdomain vary both during development and among the types of neurons, probably determining their firing characteristics in response to stimulation. Here, we characterize the developmental expression of different subfamilies of voltage-gated potassium channels in the AISs of cultured mouse hippocampal neurons, including subunits Kv1.2, Kv2.2 and Kv7.2. In contrast to the early appearance of voltage-gated sodium channels and the Kv7.2 subunit at the AIS, Kv1.2 and Kv2.2 subunits were tethered at the AIS only after 10 days in vitro. Interestingly, we observed different patterns of Kv1.2 and Kv2.2 subunit expression, with each confined to distinct neuronal populations. The accumulation of Kv1.2 and Kv2.2 subunits at the AIS was dependent on ankyrin G tethering, it was not affected by disruption of the actin cytoskeleton and it was resistant to detergent extraction, as described previously for other AIS proteins. This distribution of potassium channels in the AIS further emphasizes the heterogeneity of this structure in different neuronal populations, as proposed previously, and suggests corresponding differences in action potential regulation.
Resumo:
The cisternal organelle that resides in the axon initial segment (AIS) of neocortical and hippocampal pyramidal cells is thought to be involved in regulating the Ca(2+) available to maintain AIS scaffolding proteins, thereby preserving normal AIS structure and function. Through immunocytochemistry and correlative light and electron microscopy, we show here that the actin-binding protein ?-actinin is present in the typical cistenal organelle of rodent pyramidal neurons as well as in a large structure in the AIS of a subpopulation of layer V pyramidal cells that we have called the "giant saccular organelle." Indeed, this localization of ?-actinin in the AIS is dependent on the integrity of the actin cytoskeleton. Moreover, in the cisternal organelle of cultured hippocampal neurons, ?-actinin colocalizes extensively with synaptopodin, a protein that interacts with both actin and ?-actinin, and they appear concomitantly during the development of these neurons. Together, these results indicate that ?-actinin and the actin cytoskeleton are important components of the cisternal organelle that are probably required to stabilize the AIS.
Resumo:
In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.
Resumo:
The city of Lorca (Spain) was hit on May 11th 2011 by two consecutive earthquakes with 4.6 and 5.2 Mw respectively, causing casualties and important damage in buildings. Lorca is located in the south-east region of Spain and settled on the trace of the Murcia-Totana-Lorca fault. Although the magnitudes of these ground motions were not severe, the damage observed was considerable over a great amount of buildings. More than 300 of them have been demolished and many others are being retrofitted. This paper reports a field study on the damage caused by these earthquakes. The observed damage is related with the structural typology. Further, prototypes of the damaged buildings are idealized with nonlinear numerical models and their seismic behavior and proneness to damage concentration is further investigated through dynamic response analyses.
Resumo:
In this paper fault detection and isolation (FDI) schemes are applied in the context of the surveillance of emerging faults in an electrical circuit. The FDI problem is studied on a noisy nonlinear circuit, where both abrupt and incipient faults in the voltage source are considered. A rigorous analysis of fault detectability precedes the application of the fault detection (FD) scheme; then, the fault isolation (FI) phase is accomplished with two alternative FI approaches, proposed as new extensions of that FD approach. Numerical simulations illustrate the applicability of the mentioned schemes.
Resumo:
In this paper a new method for fault isolation in a class of continuous-time stochastic dynamical systems is proposed. The method is framed in the context of model-based analytical redundancy, consisting in the generation of a residual signal by means of a diagnostic observer, for its posterior analysis. Once a fault has been detected, and assuming some basic a priori knowledge about the set of possible failures in the plant, the isolation task is then formulated as a type of on-line statistical classification problem. The proposed isolation scheme employs in parallel different hypotheses tests on a statistic of the residual signal, one test for each possible fault. This isolation method is characterized by deriving for the unidimensional case, a sufficient isolability condition as well as an upperbound of the probability of missed isolation. Simulation examples illustrate the applicability of the proposed scheme.
Resumo:
In this paper, the applicability of the FRA technique is discussed as a method for detecting inter-turn faults in stator windings. Firstly, this method is tested in an individual medium-voltage stator coil with satisfactory results. Secondly, the tests are extended to a medium-voltage induction motor stator winding, in which inter-turn faults are performed in every coil end of one phase. Results of the frequency response in case of inter-turn faults are evaluated in both cases for different fault resistance values. The experimental setup is also described for each experiment. The results of the application of this technique to the detection of inter-turn faults justify further research in optimizing this technique for preventive maintenance.
Resumo:
Locating stator-winding ground faults accurately is a very difficult task. In this paper the grounding circuit measurements are evaluated in order to obtain information about the stator ground-fault location in synchronous generators. In power generators grounded through a high impedance, the relation between the neutral voltage and the phase voltage provide a first estimation of the fault location. The location error by using this ratio depends on the fault resistance and the value of the capacitance to ground of the stator winding. However, the error added by ignoring the value of the fault resistance is the most relevant term. This location estimation and the location error have been evaluated through the data of a real synchronous machine.