Transtensional Rupture within a Diffuse Plate Boundary Zone during the 2020 Mw 6.4 Puerto Rico Earthquake

On 7 January 2020, an Mw 6.4 earthquake occurred in the northeastern Caribbean, a few kilometers offshore of the island of Puerto Rico. It was the mainshock of a complex seismic sequence, characterized by a large number of energetic earthquakes illuminating an east–west elongated area along the southwestern coast of Puerto Rico. Deformation fields constrained by Interferometric Synthetic Aperture Radar and Global Navigation Satellite System data indicate that the coseismic movements affected only the western part of the island. To assess the mainshock’s source fault parameters, we combined the geodetically derived coseismic deformation with teleseismic waveforms using Bayesian inference. The results indicate a roughly east–west oriented fault, dipping northward and accommodating ∼1.4 m of transtensional motion. Besides, the determined location and orientation parameters suggest an offshore continuation of the recently mapped North Boquerón Bay–Punta Montalva fault in southwest Puerto Rico. This highlights the existence of unmapped faults with moderate-to-large earthquake potential within the Puerto Rico region.

Data-Driven Models for Gas Turbine Online Diagnosis

The lack of gas turbine field data, especially faulty engine data, and the complexity of fault embedding into gas turbines on test benches cause difficulties in representing healthy and faulty engines in diagnostic algorithms. Instead, different gas turbine models are often used. The available models fall into two main categories: physics-based and data-driven. Given the models’ importance and necessity, a variety of simulation tools were developed with different levels of complexity, fidelity, accuracy, and computer performance requirements. Physics-based models constitute a diagnostic approach known as Gas Path Analysis (GPA). To compute fault parameters within GPA, this paper proposes to employ a nonlinear data-driven model and the theory of inverse problems. This will drastically simplify gas turbine diagnosis. To choose the best approximation technique of such a novel model, the paper employs polynomials and neural networks. The necessary data were generated in the GasTurb software for turboshaft and turbofan engines. These input data for creating a nonlinear data-driven model of fault parameters cover a total range of operating conditions and of possible performance losses of engine components. Multiple configurations of a multilayer perceptron network and polynomials are evaluated to find the best data-driven model configurations. The best perceptron-based and polynomial models are then compared. The accuracy achieved by the most adequate model variation confirms the viability of simple and accurate models for estimating gas turbine health conditions.

A Wavelet-Based Diagnostic Framework for CRD Engine Injection Systems under Emulsified Fuel Conditions

The impact of the constituent oxides of nitrogen, carbon, sulphur, and other particulate matter which make up the gas emissions from diesel engines has motivated several control techniques for these pollutants. Water-in-diesel emulsions provide a reliable solution, but the wear effects on the fuel injection system (FIS) still pose remarkable concerns. Because pressure signals from the common rail (CR) reflect the dynamics associated with varying emulsion compositions and at varying engine RPMs, an investigative (and diagnostic) study was conducted on a KIA Sorento 2004 four-cylinder line engine at various water-in-diesel emulsion compositions and engine speeds. Alongside visual/microscopic inspections and spectral analyses, the diagnostic framework proposed herein functions on the use of standardized first-order differentials of the CR pressure signals to generate reliable continuous wavelet coefficients (CWCs) which capture discriminative spectral and transient information for accurate diagnosis. The results show that by extracting the CWCs from the first-order CR pressure differentials up to the 512th scale on a Mexican hat wavelet, adequate fault parameters can be extracted for use by a deep neural network (DNN) whose hyperparameters were globally optimized following a grid search. With a test accuracy of 92.3% against other widely-used ML-based diagnostic tools, the proposed DNN-based diagnostics tool was empirically assessed using several performance evaluation metrics.

Development of Smart Earth Leakage Circuit Breaker Using IoT and Power Electronics

The Smart Earth Leakage Circuit Breaker research is based on IoT& power electronics-based protective switchgear for domestic consumers for the protection against earth leakage faults. In this paper, we have shown how to create a custom web server using HTML and CSS language and hosting this webserver to ESP module using Serial Peripheral Flash File System (SPIFFS). Along with protection against earth fault it provides, controlling of tripping current or fault current, monitoring voltage, power, current, power factor parameters of the connected load, monitoring fault parameters, Indicating the device status whether the ELCB is on or off, and the condition of ELCB it is in faulty condition or healthy condition and to let the user set the value of the tripping current on the webserver at which the ELCB must trip.

The Database of the Active Faults of Eurasia (AFEAD): Ontology and Design behind the Continental-Scale Dataset

Active faults are those faults on which movement is possible in the future. It draws particular attention to active faults in geodynamic studies and seismic hazard assessment. Here we present a high-detail continental-scale geodatabase: The Active Faults of Eurasia Database (AFEAD). It comprises 46,775 objects stored in the shapefile format with spatial detail sufficient for a map of scale 1:1M. Fault sense, a rank of confidence in activity, a rank of slip rate, and a reference to source publications are provided for each database entry. Where possible, it is supplemented with a fault name, fault zone name, abbreviated fault parameters (e.g., slip rate, age of the last motion, total offset), and text information from the sources. The database was collected from 612 sources, including regional maps, databases, and research papers. AFEAD facilitates a spatial search for local studies. It provides sufficient detail for planning a study of a particular fault system and guides deeper bibliographical investigations if needed. This scenario is particularly significant for vast Central and North Asia areas, where most studies are available only in Russian and hardcopy. Moreover, the database model provides the basis for GIS-based regional and continental-scale integrative studies. The database is available at https://doi.org/10.13140/RG.2.2.10333.74726 and via web map at http://neotec.ginras.ru/index/mapbox/database_map.html (last access: July 30, 2021). Some database representations with supplementary data are hosted at http://neotec.ginras.ru/index/english/database_eng.html.

Magnetic anomaly interpretation for a 2D fault-like geologic structures utilizing the global particle swarm method

We establish a method to elucidate the magnetic anomaly due to 2D fault structures, with an evaluation of first moving average residual anomalies utilizing filters of increasing window lengths. After that, the buried fault parameters are estimated using the global particle swarm method. The goodness of fit among the observed and the calculated models is expressed as the root mean squared (RMS) error. The importance of studying and delineating the fault parameters, which include the amplitude factor, the depth to the upper edge, the depth to the lower edge, the fault dip angle, and the position of the origin of the fault, is: (i) solving many problem-related engineering and environmental applications, (ii) describing the accompanying mineralized zones with faults, (iii) describing geological deformation events, (iv) monitoring the subsurface shear zones, (v) defining the environmental effects of the faults before organizing any investments, and (vi) imaging subsurface faults for different scientific studies. Finally, we show the method applied to two theoretical models including the influence of the regional background and the multi-fault effect and to real field examples from Australia and Turkey. Available geologic and geophysical information corroborates our interpretations.

Adaptive Fault Estimation for Hyperbolic PDEs

The new adaptive fault estimation scheme is proposed for a class of hyperbolic partial differential equations in this paper. The multiplicative actuator and sensor faults are considered. There are two cases that require special consideration: (1). only one type of fault (actuator or sensor) occurs; (2). two types of faults occurred simultaneously. To solve the problem of fault estimation, three challenges need to be solved: (1). No prior information of fault type is known; (2). Unknown faults are always coupled with state and input; (3). Only one boundary measurement is available. The original plant is converted to Observer canonical form. Two filters are proposed and novel adaptive laws are developed to estimate unknown fault parameters. With the help of the proposed update laws, the true state of the faulty plant can be estimated by the proposed observers composed of two filters. By selecting a suitable Lyapunov function, it is proved that under unknown external disturbance, the estimation errors of state parameters and fault parameters decay to arbitrarily small value. Finally, the validity of the proposed observer and adaptive laws is verified by numerical simulation.

Penentuan Karakteristik Mekanisme Gempa Tahun 2018-2019 Di Nusa Tenggara Menggunakan Metode Inversi Momen Tensor

Nusa Tenggara is one of the areas with a high level of seismic activity in Indonesia because this area is located between the Indian Ocean plate, which moves northward and pushes the Eurasian plate. One method that is often used to determine an earthquake's epicentre is the Tensor Moment Inversion method. This study aims to determine the moment tensor magnitude of each earthquake event and determine earthquake characteristics based on the earthquake focus mechanism in Nusa Tenggara from 2018 to 2019. The earthquake with a magnitude of ≥ 5.7 SR and to find out the fault parameters, namely strike, dip, and rake using waveform data. One method that is often used to determine an earthquake's epicentre is the Tensor Moment Inversion method. The results showed that the fault planes formed were reverse faults and oblique faults. It has been calculated the moment tensor for each of the six components, namely Mxx, Myy, Mzz, Mxy, Myz and Mxz. From the results of the focal analysis of the 2018-2019 Nusa Tenggara earthquake mechanism, the values of the fault plane orientation parameters such as strike, dip and rake are obtained. For strikes in Nusa Tenggara on area 1, namely: 73° to 122°, Dip: 20° to 72° and Rake: 53° to 139°. While in field 2 for a strike, it is 232° to 280°, Dip 28° to 75°, Rake: 52° to 102°.