Статті в журналах: "Evaluation probabiliste des fautes"

1

Duprat, Frédéric, Alain Sellier, and Laurie Lacarrière. "Evaluation probabiliste du risque de corrosion par carbonatation." Revue Française de Génie Civil 8, no. 8 (November 2004): 975–97. http://dx.doi.org/10.1080/12795119.2004.9692637.

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Bourguignon, N., B. Veber, S. Godier, N. Frebourg, J. F. Lemeland, and B. Dureuil. "Evaluation de l'antibiothérapie probabiliste des péritonites post-opératoires en réanimation." Annales Françaises d'Anesthésie et de Réanimation 16, no. 6 (September 1997): 762. http://dx.doi.org/10.1016/s0750-7658(97)86322-8.

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Paradisopoulou, P. M., E. E. Papadimitriou, and J. Mirek. "SIGNIFICANT EARTHQUAKES NEAR THE CITY OF THESSALONIKI (NORTHERN GREECE) AND PROBABILITY DISTRIBUTION ON FAULTS." Bulletin of the Geological Society of Greece 50, no. 3 (July 27, 2017): 1389. http://dx.doi.org/10.12681/bgsg.11852.

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Stress triggering must be incorporated into quantitative earthquake probability estimate, given that faults are interacted though their stress field. Using time dependent probability estimates this work aims at the evaluation of the occurrence probability of anticipated earthquakes near the city of Thessaloniki, an urban center of 1 million people located in northern Greece, conditional to the time elapsed since the last stronger event on each fault segment of the study area. A method that calculates the macroseismic epicenter and magnitude according to macroseismic intensities is used to improve the existing earthquake catalog (from AD 1600 - 2013 with M≥6.0) in order to compute new interevent and elapsed time values which form the basis for time-dependent probability estimates. To investigate the effects of stress transfer to seismic hazard, the probabilistic calculations presented here employ detailed models of coseismic stress associated with the 20 June 1978 M=6.5 Thessaloniki which is the latest destructive earthquake in the area in the instrumental era. The combined 2015-2045 regional Poisson probability of M≥6.0 earthquakes is ~35% the regional time-dependent probability varies from 0% to 15% and incorporation of stress transfer from 0% to 20% for each fault segment.

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Seidou, O., B. Robert, C. Marche, J. Rousselle, and M. Lefebvre. "Construction probabiliste de scénarios d'apports à un réservoir." Canadian Journal of Civil Engineering 31, no. 1 (January 1, 2004): 146–54. http://dx.doi.org/10.1139/l03-108.

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The behaviour of a hydric system depends on three factors : (i) the state of the installation, (ii) the operating rules, and (iii) the inflows. While the first two factors are (in theory) known to the manager, the third can only be estimated by means of more or less precise forecasts. A significant part of the risk, to which is subjected the system at a given time, is induced by the uncertainty in the future inflows. The evaluation of this uncertainty is therefore a first step in the incorporation of risk into management. Its evaluation is then a stage preliminary to the integration of the risk in management. A method of construction of inflow scenarios starting from an arbitrary date t of the year is developed in this paper. It uses a Markovian process formerly developed by the authors to model short-term uncertainty in stream flow. These scenarios, which are not equiprobable, are built to reproduce the statistical behaviour of the river or reservoir and have the shape of an event tree whose structure is defined by the user before application of the method. Two examples of application on two rivers located in Quebec, Canada, are presented.Key words: reservoir operation, previsions, inflows, risk, uncertainty.

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Zhang, Jianlong, Ye Zhu, Yingfeng Ji, Weiling Zhu, Rui Qu, Zhuoma Gongqiu, and Chaodi Xie. "Earthquake Risk Probability Evaluation for Najin Lhasa in Southern Tibet." Applied Sciences 12, no. 18 (September 19, 2022): 9394. http://dx.doi.org/10.3390/app12189394.

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The probabilistic seismic hazard analysis (PSHA) method is effectively used in an earthquake risk probability evaluation in seismogenic regions with active faults. In this study, by focusing on the potential seismic source area in Najin Lhasa, southern Tibet, and by incorporating the PSHA method, we determined the seismic activity parameters and discussed the relationship of ground motion attenuation, the seismic hazard probability, and the horizontal bedrock ground motion acceleration peak value under different transcendence probabilities in this area. The calculation results show that the PSHA method divides the potential source area via specific tectonic scales and detailed tectonic markers, which reduces the scale of the potential source area and better reflects the uneven spatial distribution of seismic activity in the vicinity of Najin. The corrected attenuation relationship is also in line with the actual work requirements and is suitable for earthquake risk analysis. In addition, the major influences on the peak acceleration of ground motion in the study area are mainly in the potential source areas of Qushui (M7.5), Dangxiong (M8.5), and Kangma (M7.5). The peak horizontal ground motion acceleration (PGA) with a transcendence probability of 10% in 50 years is 185.9 cm/s2, and that with a transcendence probability of 2% in 50 years is 265.9 cm/s2.

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Zhou, Lintao, Qinge Wu, Hu Chen, and Tao Hu. "Interval fuzzy probability method for power transformer multiple fault diagnosis." Journal of Intelligent & Fuzzy Systems 41, no. 6 (December 16, 2021): 5957–68. http://dx.doi.org/10.3233/jifs-202083.

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Accurately diagnosing power transformer faults is critical to improving the operational reliability of power systems. Although some researchers have made great efforts to improve the accuracy of transformer fault diagnosis, accurate diagnosis of multiple faults is still a difficult problem. In order to improve the accuracy of transformer multiple faults diagnosis, a multiple fault diagnosis method based on interval fuzzy probability is proposed. Different from the previous methods which provide single-value probability, this method use probability interval to represent the occurrence degree of various possible faults, which can objectively predict the potential faults that occurring in a transformer and provide a more reasonable explanation for the diagnosis results. In the proposed method, the interval fuzzy set is used to describe the evaluation of state variables and the interval fuzzy probability model based on interval weighted average is applied to integrate the fault information. The representative matrix of fault types based on fuzzy preference relationship is established to estimate the relative importance of each gas in the dissolved gases. The proposed method can provide the probability of probable faults in transformer, help engineers quickly determine the type and location of faults, and improve the accuracy of diagnosis and maintenance efficiency of transformer. The effectiveness of the method is verified with case studies.

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Kourd, Yahia, Dimitri Lefebvre, and Noureddine Guersi. "Neural Networks and Fault Probability Evaluation for Diagnosis Issues." Computational Intelligence and Neuroscience 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/370486.

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This paper presents a new FDI technique for fault detection and isolation in unknown nonlinear systems. The objective of the research is to construct and analyze residuals by means of artificial intelligence and probabilistic methods. Artificial neural networks are first used for modeling issues. Neural networks models are designed for learning the fault-free and the faulty behaviors of the considered systems. Once the residuals generated, an evaluation using probabilistic criteria is applied to them to determine what is the most likely fault among a set of candidate faults. The study also includes a comparison between the contributions of these tools and their limitations, particularly through the establishment of quantitative indicators to assess their performance. According to the computation of a confidence factor, the proposed method is suitable to evaluate the reliability of the FDI decision. The approach is applied to detect and isolate 19 fault candidates in the DAMADICS benchmark. The results obtained with the proposed scheme are compared with the results obtained according to a usual thresholding method.

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8

Ju, Bu Seog, and WooYoung Jung. "Evaluation of Seismic Fragility of Weir Structures in South Korea." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/391569.

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In order to reduce earthquake damage of multifunctional weir systems similar to a dam structure, this study focused on probabilistic seismic risk assessment of the weir structure using the fragility methodology based on Monte Carlo simulation (MCS), with emphasis on the uncertainties of the seismic ground motions in terms of near field induced pulse-like motions and far field faults. The 2D simple linear elastic plain strain finite element (FE) model including soil structure foundations using tie connection method in ABAQUS was developed to incorporate the uncertainty. In addition, five different limit states as safety criteria were defined for the seismic vulnerability of the weir system. As a consequence, the results obtained from multiple linear time history analyses revealed that the weir structure was more vulnerable to the tensile stress of the mass concrete in both near and far field ground motions specified earthquake hazard levels. In addition, the system subjected to near field motions was primarily more fragile than that under far field ground motions. On the other hand, the probability of failure due to the tensile stress at weir sill and stilling basin showed the similar trend in the overall peak ground acceleration levels.

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Bonachera Martin, Francisco Javier, and Robert J. Connor. "Load Combinations for the Evaluation of Redundancy in Steel Bridges." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 4 (January 13, 2022): 524–37. http://dx.doi.org/10.1177/03611981211062162.

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Over the past decade, there has been considerable interest in the development of quantitative analytical procedures to determine if a primary steel tension member (PSTM) is a fracture critical member (FCM). Traditionally, this designation has most often been arbitrarily determined based simply on the bridge geometry, for example, the number of girders in the cross section, rather than an evaluation of the bridge in the faulted state. Clearly, such a redundancy evaluation must address the loading scenarios concurrent with failure of the PSTM, the likelihood of the member failure, the acceptable probability of load exceeding resistance in the faulted state, and the application of vehicular live load models. This research was conducted to develop a load model and load combinations that are specific to evaluating the performance of a bridge in the event a steel member was to fracture. Specifically, two load combinations were developed to evaluate the strength of a steel bridge, one for the event in which the failure of a PSTM occurs, and another for a post-failure service period. The development adhered to the reliability-based principles and procedures applied in the calculation of load combinations currently used in bridge engineering to facilitate direct implementation and to ensure consistency with current steel bridge design and evaluation procedures contained in the AASHTO LRFD Bridge Design Specifications.

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Spiegel, Gerald, and Albrecht P. Stroele. "Realistic Fault Modeling and Extraction of Multiple Bridging and Break Faults." VLSI Design 7, no. 2 (January 1, 1998): 163–76. http://dx.doi.org/10.1155/1998/83615.

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Fault sets that accurately describe physical failures are required for efficient pattern generation and fault coverage evaluation. The fault model presented in this paper uniquely describes all structural changes in the transistor net list that can be caused by spot defects, including bridging faults that connect more than two nets, break faults that break a net into more than two parts, and compound faults. The developed analysis method extracts the comprehensive set of realistic faults from the layout of CMOS ICs and for each fault computes the probability of occurrence. The results obtained by the tool REFLEX show that bridging faults connecting more than two nets account for a significant portion of all faults and cannot be neglected.

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Eslami, R., S. H. H. Sadeghi, and H. Askarian Abyaneh. "A Probabilistic Approach for the Evaluation of Fault Detection Schemes in Microgrids." Engineering, Technology & Applied Science Research 7, no. 5 (October 19, 2017): 1967–73. http://dx.doi.org/10.48084/etasr.1472.

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An important challenge in protection of a microgrid is the process of fault detection, considering the uncertainties in its topologies. Equally important is the evaluation of proposed methods as their incorrect performances could result in unreasonable power outages. In this paper, a new fault detection and characterization method is introduced and evaluated subject to the uncertainties of network topologies. The features of three-phase components together with the positive, negative and zero sequences of current and voltage waveforms are derived to detect the occurrence of a fault, its location, type and the engaged phases. The proposed method is independent of the microgrid topology. To evaluate the performance of the proposed method in various network topologies, a Monte Carlo scheme is developed. This is done by computing the expected energy not-supplied reliability index and the percentage of successful performance of the fault detection. Simulation results show that the proposed method can detect faults in various microgrid topologies with a very high degree of accuracy.

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Kiamanesh, Bahareh, Ali Behravan, and Roman Obermaisser. "Fault Injection with Multiple Fault Patterns for Experimental Evaluation of Demand-Controlled Ventilation and Heating Systems." Sensors 22, no. 21 (October 25, 2022): 8180. http://dx.doi.org/10.3390/s22218180.

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Heating, ventilation, and air-conditioning (HVAC) systems are large-scale distributed systems that can be subject to multiple faults affecting the electronics, sensors, and actuators, potentially causing high energy consumption, occupant discomfort, degraded indoor air quality and risk to critical infrastructure. Fault injection (FI) is an effective experimental method for the validation and dependability evaluation of such HVAC systems. Today’s FI frameworks for HVAC systems are still based on a single fault hypothesis and do not provide insights into dependability in the case of multiple faults. Therefore, this paper presents modeling patterns of numerous faults in HVAC systems based on data from field failure rates and maintenance records. The extended FI framework supports the injection of multiple faults with exact control of the timing, locality, and values in fault-injection vectors. A multi-dimensional fault model is defined, including the probability of the occurrence of different sensor and actuator faults. Comprehensive experimental results provide insights into the system’s behavior for concrete example scenarios using patterns of multiple faults. The experimental results serve as a quantitative evaluation of key performance indicators (KPI) such as energy efficiency, air quality, and thermal comfort. For example, combining a CO2 sensor fault with a heater actuator fault increased energy consumption by more than 70%.

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Smith, Stewart, Olesya Zimina, Surender Manral, and Michael Nickel. "Machine-learning assisted interpretation: Integrated fault prediction and extraction case study from the Groningen gas field, Netherlands." Interpretation 10, no. 2 (February 22, 2022): SC17—SC30. http://dx.doi.org/10.1190/int-2021-0137.1.

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Seismic fault detection using machine-learning techniques, in particular the convolution neural network (CNN), is becoming a widely accepted practice in the field of seismic interpretation. Machine-learning algorithms are trained to mimic the capabilities of an experienced interpreter by recognizing patterns within seismic data and classifying them. Regardless of the method of seismic fault detection, interpretation or extraction of 3D fault representations from edge evidence or fault probability volumes is routine. Extracted fault representations are important to the understanding of the subsurface geology and are a critical input to upstream workflows including structural framework definition, static reservoir and petroleum system modeling, and well planning and derisking activities. Efforts to automate the detection and extraction of geologic features from seismic data have evolved in line with advances in computer algorithms, hardware, and machine-learning techniques. We have developed an assisted fault interpretation workflow for seismic fault detection and extraction, demonstrated through a case study from the Groningen gas field of the Upper Permian, Dutch Rotliegend; a heavily faulted, subsalt gas field located onshore, northeast Netherlands. Supervised using interpreter-led labeling, we apply a 2D multi-CNN to detect faults within a 3D prestack depth migrated seismic data set. After prediction, we apply a geometric evaluation of predicted faults, using a principal component analysis to produce geometric attribute representations (strike azimuth and planarity) of the fault prediction. Strike azimuth and planarity attributes are used to validate and automatically extract consistent 3D fault geometries, providing geologic context to the interpreter and input to dependent workflows more efficiently.

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Zhang, Shi Gang, Cheng Rui Liu, Zheng Hu, and Xi Sen Wen. "Testability Evaluation of the Systems with Multi-Outcome Imperfect Tests." Applied Mechanics and Materials 303-306 (February 2013): 407–10. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.407.

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In the fault diagnosis systems, the measured value of a test is generally divided into several intervals to isolate the faults. Furthermore, in the realistic systems, the value may be distributed over different intervals with a probability if a fault occurs, which means that the tests are multi-outcome imperfect tests. In this paper, a calculation method of metrics of fault detection and fault isolation based on extended dependency matrix is proposed, which can be applied to evaluate the testability of a system and consequently play a role in the design process of diagnosis systems.

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Gelman, Len, Krzysztof Soliński, and Andrew Ball. "Novel Instantaneous Wavelet Bicoherence for Vibration Fault Detection in Gear Systems." Energies 14, no. 20 (October 18, 2021): 6811. http://dx.doi.org/10.3390/en14206811.

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Higher order spectra exhibit a powerful detection capability of low-energy fault-related signal components, buried in background random noise. This paper investigates the powerful nonlinear non-stationary instantaneous wavelet bicoherence for local gear fault detection. The new methodology of selecting frequency bands that are relevant for wavelet bicoherence fault detection is proposed and investigated. The capabilities of wavelet bicoherence are proven for early-stage fault detection in a gear pinion, in which natural pitting has developed in multiple pinion teeth in the course of endurance gearbox tests. The results of the WB-based fault detection are compared with a stereo optical fault evaluation. The reliability of WB-based fault detection is quantified based on the complete probability of correct identification. This paper is the first attempt to investigate instantaneous wavelet bicoherence technology for the detection of multiple natural early-stage local gear faults, based on comprehensive statistical evaluation of the industrially relevant detection effectiveness estimate—the complete probability of correct fault detection.

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Lu, Hao, Lei Wang, and Chao Quan Tang. "Reliability Analysis of the Main-Shaft Device of a Hoist System with Coupling Faults." Applied Mechanics and Materials 872 (October 2017): 286–92. http://dx.doi.org/10.4028/www.scientific.net/amm.872.286.

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In this paper, the reliability and reliability sensitivity of the main shaft device of a hoist system is studied. The main purpose of this paper is to provide a modeling method for the joint probability distribution of main shaft device with coupling faults based on the system reliability theory and copula function theory. The stochastic response of the main shaft device is obtained using design of experiment. The reliability of the main shaft device is calculated based on the fourth moment method. The reliability sensitivity is then deduced based on the reliability results. The joint probability of failure between correlated failure modes is estimated based on the Gumbel copula. The system reliability evaluation of the main shaft device is then calculated. A numerical example of a main shaft device is illustrated to validate the application of the proposed method. The method proposed in this study can be provided for the analysis and design of the main shaft device of deep well hoist as a necessary theoretical basis.

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Jones, R. M., P. Boult, R. R. Hillis, S. D. Mildren, and J. Kaldi. "INTEGRATED HYDROCARBON SEAL EVALUATION IN THE PENOLATROUGH, OTWAY BASIN." APPEA Journal 40, no. 1 (2000): 194. http://dx.doi.org/10.1071/aj99011.

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Seals are one of the main components of the petroleum system, yet their evaluation has received surprisingly little attention in terms of integrated risk assessment. This paper emphasises the need for an integrated multi-disciplinary approach for robust cap and fault seal evaluation so to minimise seal risk. The region of study is the Penola Trough, Otway Basin, where recent improvements in seismic quality, stratigraphic modelling and additional well control have greatly enhanced regional prospectivity.The Laira Formation has the lowest cap seal risk of Penola Trough strata based on empirical data. The Eumeralla Formation has a similar gamma ray log signature to the Laira Formation yet contains a higher frequency of sandy, relatively high permeability horizons. These horizons increase the likelihood of fault juxtaposition and the development of leaky windows that allow cross fault communication.Faults in the Penola Trough display fractal characteristics from seismic to core scale. A prediction of regional fault extension and deformation intensity below seismic resolution is viable since fault systems appear to be systematic. Extrapolation of fault populations to the millimetre scale shows good agreement with fault density recorded in core from a fault damage zone. Deformation intensities close to seismically resolvable faults are indicative of inner damage zone geometry where faults form linked cluster arrays. Microstructural fault analysis indicates the dominant fault processes in the Upper Crayfish Group are grain boundary sliding and cataclasis with gouge quartz cementation. Petrophysical analysis indicates these faults are able to support gas columns of up to 102 m.The relative probability of seal failure due to the development of effective structural permeability within the in-situ stress field indicates that planes at the greatest risk of failure are steeply dipping (>60°) and strike between 110°N and 200°N. Open fractures crosscutting pre-existing faults have been identified through microstructural examination and these may provide a mechanism for trap leakage and tertiary hydrocarbon migration. An integrated technique for mapping the relative risk of seal breach due to the development of effective structural permeability at the seismic scale is also presented.

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Terrier-Sedan, Monique, and Didier Bertil. "Active fault characterization and seismotectonic zoning of the Hispaniola island." Journal of Seismology 25, no. 2 (February 18, 2021): 499–520. http://dx.doi.org/10.1007/s10950-021-09985-0.

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AbstractDesigning a seismic source model based on the most complete description of potentially active faults and on the kinematics of their latest movements is an essential requirement in seismic hazard studies, at regional and local scales. A study to characterize active faults in the Hispaniola island (today’s Haiti and Dominican Republic) has been conducted in the framework of the probabilistic seismic hazard assessment for Santo Domingo (capital of the Dominican Republic). In this work, we present a seismotectonic map of Hispaniola and its surroundings, based on a compilation and synthesis of geological, geophysical, geodetic and seismological data. Based on these data, distinct seismic zone sources are proposed and classified as either intercrustal domains, major active faults or subduction zones. Each seismic source is described according to several parameters, including its mechanism and current rate of deformation, the associated seismicity and its estimated maximal magnitude. These results constitute an essential database for a homogeneous evaluation of the seismic hazards of Hispaniola.

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Jalali, Aghil Moradmand, Ramin Naghdi, and Ismael Ghajar. "Potential Evaluation of Forest Road Trench Failure in a Mountainous Forest, Northern Iran." Croatian journal of forest engineering 43, no. 1 (November 24, 2021): 169–84. http://dx.doi.org/10.5552/crojfe.2022.1330.

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After road construction in steep and mountainous areas, there is always a risk for trench failure. Estimation of this probability before forest road design and construction is urgent. Besides, to decrease failures costs and risks, it is necessary to classify their occurrence probabilities and identify the factors affecting them. The present study compares three statistical models of logistic regression, frequency ratio, and maximum entropy. The robust one was applied to generate trench failures susceptibility map of forest roads of two watersheds in Northern Iran. Also, all failures repairing costs were estimated, and subsequently, all existing roads were surveyed in the study area, detecting 844 failures. Among the recorded failures, 591 random cases (70%) were used in modeling, and others (30%) were used as validation data. The digital layers, including failure locations, were prepared. Three failure susceptibility maps were simulated using the outputs of the mentioned methods in the GIS environment. The resulted maps combined with repair cost prices were analyzed to statistically evaluate the repair cost unit per meter of forest road and per square meter of failure. The results showed that the logistic regression model had an Area Under Curve (AUC) of 74.6% in identifying failure-sensitive areas. The probabilistic frequency ratio and Entropy models showed 68.2 and 65.5% accuracy, respectively. Based on the logistic regression model, the distance to faults and terrain slope factors had the highest effects on forest road trenches failures. According to the result, about 43.25% of the existing road network is located in »high« and »very high« risky areas. The estimated cost of regulating and profiling trenches and ditches along the existing roads was approximately 108,772 $/km.

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Islam, Md Rashedul, Young-Hun Kim, Jae-Young Kim, and Jong-Myon Kim. "Detecting and Learning Unknown Fault States by Automatically Finding the Optimal Number of Clusters for Online Bearing Fault Diagnosis." Applied Sciences 9, no. 11 (June 6, 2019): 2326. http://dx.doi.org/10.3390/app9112326.

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This paper proposes an online fault diagnosis system for bearings that detect emerging fault modes and then updates the diagnostic system knowledge (DSK) to incorporate information about the newly detected fault modes. New fault modes are detected using k-means clustering along with a new cluster evaluation method, i.e., multivariate probability density function’s cluster distribution factor (MPDFCDF). In this proposed model, a heterogeneous pool of features is constructed from the signal. A hybrid feature selection model is adopted for selecting optimal feature for learning the model with existing fault mode. The proposed online fault diagnosis system detects new fault modes from unknown signals using k-means clustering with the help of proposed MPDFCDF cluster evaluation method. The DSK is updated whenever new fault modes are detected and updated DSK is used to classify faults using the k-nearest neighbor (k-NN) classifier. The proposed model is evaluated using acoustic emission signals acquired from low-speed rolling element bearings with different fault modes and severities under different rotational speeds. Experimental results present that the MPDFCDF cluster evaluation method can detect the optimal number of fault clusters, and the proposed online diagnosis model can detect newly emerged faults and update the DSK effectively, which improves the diagnosis performance in terms of the average classification performance.

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Savran, William H., Maximilian J. Werner, Warner Marzocchi, David A. Rhoades, David D. Jackson, Kevin Milner, Edward Field, and Andrew Michael. "Pseudoprospective Evaluation of UCERF3-ETAS Forecasts during the 2019 Ridgecrest Sequence." Bulletin of the Seismological Society of America 110, no. 4 (July 21, 2020): 1799–817. http://dx.doi.org/10.1785/0120200026.

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ABSTRACT The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic-type aftershock sequences (UCERF3-ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3-NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3-ETAS and UCERF3-NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude-number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3-ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.

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Paliaroutis, Georgios Ioannis, Pelopidas Tsoumanis, Nestor Evmorfopoulos, George Dimitriou, and Georgios I. Stamoulis. "SET Pulse Characterization and SER Estimation in Combinational Logic with Placement and Multiple Transient Faults Considerations." Technologies 8, no. 1 (January 10, 2020): 5. http://dx.doi.org/10.3390/technologies8010005.

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Integrated circuit susceptibility to radiation-induced faults remains a major reliability concern. The continuous downscaling of device feature size and the reduction in supply voltage in CMOS technology tend to worsen the problem. Thus, the evaluation of Soft Error Rate (SER) in the presence of multiple transient faults is necessary, since it remains an open research field. In this work, a Monte-Carlo simulation-based methodology is presented taking into consideration the masking mechanisms and placement information. The proposed SER estimation tool exploits the results of a Single Event Transient (SET) pulse characterization process with HSPICE to obtain an accurate assessment of circuit vulnerability to radiation. A new metric, called Glitch Latching Probability, which represents the impact of the masking effects on a SET, is introduced to identify gate sensitivity and, finally, experimental results on a set of ISCAS’ 89 benchmarks are presented.

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Gnanavel, S., M. Sreekrishna, Vinodhini Mani, G. Kumaran, R. S. Amshavalli, Sadeen Alharbi, Mashael Maashi, et al. "Analysis of Fault Classifiers to Detect the Faults and Node Failures in a Wireless Sensor Network." Electronics 11, no. 10 (May 18, 2022): 1609. http://dx.doi.org/10.3390/electronics11101609.

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Technology evaluation in the electronics field leads to the great development of Wireless Sensor Networks (WSN) for a variety of applications. The sensor nodes are deployed in hazardous environments, and they are operated by isolated battery sources. Network connectivity is purely based on power availability, which impacts the network lifetime. Hence, power must be used wisely to prolong the network lifetime. The sensor nodes that fail due to power have to detect quickly to maintain the network. In a WSN, classifiers are used to detect the faults for checking the data generated by the sensor nodes. In this paper, six classifiers such as Support Vector Machine, Convolutional Neural Network, Multilayer Perceptron, Stochastic Gradient Descent, Random Forest and Probabilistic Neural Network have been taken for analysis. Six different faults (Offset fault, Gain fault, Stuck-at fault, Out of Bounds, Spike fault and Data loss) are injected in the data generated by the sensor nodes. The faulty data are checked by the classifiers. The simulation results show that the Random Forest detected more faults and it also outperformed all other classifiers in that category.

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Banton, O., P. Lafrance, and J. P. Villeneuve. "Evaluation de la vulnérabilité des eaux souterraines à la contamination par les pesticides. Une Application du Logiciel VULPEST dans la Région de Portneuf (Québec, Canada)." Water Quality Research Journal 24, no. 1 (February 1, 1989): 163–78. http://dx.doi.org/10.2166/wqrj.1989.009.

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Abstract Dans les zones d’activités agricoles du Canada, on observe l’apparition de plus en plus fréquente de cas de contamination d’eau de puits municipaux ou privés par des pesticides. L’étude présentée dans cet article constitue une application d’une méthode d’évaluation probabiliste de la vulnérabilité des eaux souterraines réalisée au moyen de la modélisation stochastique. Le logiciel VULPEST, qui est destiné à l’évaluation prédictive de la vulnérabilité, est basé sur la simulation du transport du pesticide dans la zone non-saturée du sol. Il a été appliqué sur un site agricole du Québec présentant une contamination des eaux souterraines par le pesticide aldicarbe avec des concentrations pouvant atteindre 30 µg/L. Pour cette étude, des prélèvements de sol ont été effectués sur neuf stations réparties sur un maillage de 80 m x 80 m, afin de déterminer les caractéristiques des distributions statistiques des principaux paramètres physiques. L’application du logiciel VULPEST sur le site de Ste-Catherine, comté de Portneuf, a montré la vulnérabilité de ce site au pesticide concerné. Les résultats, qui ont été comparés aux mesures de concentration réelles, ont montré la qualité des prévisions qui auraient pûe réalisées grâce au logiciel, avant même l’application du pesticide.

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25

Fadaeefath Abadi, Mostafa, Mohammad Hosseini Rahdar, Fuzhan Nasiri, and Fariborz Haghighat. "Fault Identification and Fault Impact Analysis of The Vapor Compression Refrigeration Systems in Buildings: A System Reliability Approach." Energies 15, no. 16 (August 9, 2022): 5774. http://dx.doi.org/10.3390/en15165774.

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The Vapor Compression Refrigeration System (VCRS) is one of the most critical systems in buildings typically used in Heating, Ventilation, and Air Conditioning (HVAC) systems in residential and industrial sections. Therefore, identifying their faults and evaluating their reliability are essential to ensure the required operations and performance in these systems. Various components and subsystems are included in the VCRS, which need to be analyzed for system reliability. This research’s objective is conducting a comprehensive system reliability analysis on the VCRS by focusing on fault identification and determining the fault impacts on these systems. A typical VCRS in an office building is selected for this research regarding this objective. The corresponding reliability data, including the probability distributions and parameters, are collected from references to perform the reliability evaluation on the components and subsystems of the VCRS. Then the optimum distribution parameters have been obtained in the next step as the main findings. Additionally, by applying optimization techniques, efforts have been taken to maximize the system’s reliability. Finally, a comparison between the primary and the optimized systems (with new distribution parameters) has been performed over their lifetime to illustrate the system’s improvement percentage.

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26

Thenhaus, Paul C., Joseph I. Ziony, William H. Diment, Margaret G. Hopper, David M. Perkins, Stanley L. Hanson, and S. T. Algermissen. "Probabilistic Estimates of Maximum Seismic Horizontal Ground Acceleration on Rock in Alaska and the Adjacent Continental Shelf." Earthquake Spectra 1, no. 2 (February 1985): 285–306. http://dx.doi.org/10.1193/1.1585266.

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Estimates of ground motion hazard from earthquakes in Alaska and the adjacent continental shelf indicate that, for all the exposure times considered, the predicted values of peak acceleration are highest in the Gulf of Alaska and near the major active strike-slip faults of southern Alaska. The evaluations assume a Poisson model of earthquake occurrence and are based on seismic source zones delineated from regional geologic considerations and the historical record of earthquakes. Calculated peak acceleration values for a return period of 100 years range as high as 0.4 g in the Gulf of Alaska sector between Kodiak and Kayak Islands, are about 0.2 g near Anchorage, and 0.1 g near Fairbanks. Values for most of the rest of the state are estimated to be less than .04 g; however, most of the southern Alaska industrial and population base lies within the 0.2 g contour. For a return period of 500 years, peak accelerations are estimated as high as 0.8 g for parts of southeastern Alaska near the Fairweather fault, 0.6 g or greater for part of the Gulf of Alaska, and are about 0.45 g and 0.2 g, respectively, for the Anchorage and Fairbanks areas. Values of acceleration for a return period of 2,500 years exceed 0.6 g for much of southern Alaska and are 0.8 g or greater near the Fairweather and central Denali faults; estimated values are 0.1 g or greater for nearly all of onshore Alaska and for the continental shelf areas of the Bering Sea, Norton and Kotzebue Sounds, southern Chukchi Sea and southeastern Beaufort Sea.

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27

Duenas Arana, Guillermo, Osama Abdul Hafez, Mathieu Joerger, and Matthew Spenko. "Integrity monitoring for Kalman filter-based localization." International Journal of Robotics Research 39, no. 13 (October 8, 2020): 1503–24. http://dx.doi.org/10.1177/0278364920960517.

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The problem of quantifying robot localization safety in the presence of undetected sensor faults is critical when preparing for future applications where robots may interact with humans in life-critical situations; however, the topic is only sparsely addressed in the robotics literature. In response, this work leverages prior work in aviation integrity monitoring to tackle the more challenging case of evaluating localization safety in Global Navigation Satellite System (GNSS)-denied environments. Localization integrity risk is the probability that a robot’s pose estimate lies outside pre-defined acceptable limits while no alarm is triggered. In this article, the integrity risk (i.e., localization safety) is rigorously upper bounded by accounting for both nominal sensor noise and other non-nominal sensor faults. An extended Kalman filter is employed to estimate the robot state, and a sequence of innovations is used for fault detection. The novelty of the work includes (1) the use of a time window to limit the number of monitored fault hypotheses while still guaranteeing safety with respect to previously occurring faults and (2) a new method to account for faults in the data association process.

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28

Wedmore, Luke N. J., Tess Turner, Juliet Biggs, Jack N. Williams, Henry M. Sichingabula, Christine Kabumbu, and Kawawa Banda. "The Luangwa Rift Active Fault Database and fault reactivation along the southwestern branch of the East African Rift." Solid Earth 13, no. 11 (November 14, 2022): 1731–53. http://dx.doi.org/10.5194/se-13-1731-2022.

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Abstract. Seismic hazard assessment in slow straining regions is challenging because earthquake catalogues only record events from approximately the last 100 years, whereas earthquake recurrence times on individual faults can exceed 1000 years. Systematic mapping of active faults allows fault sources to be used within probabilistic seismic hazard assessment, which overcomes the problems of short-term earthquake records. We use Shuttle Radar Topography Mission (SRTM) data to analyse surface deformation in the Luangwa Rift in Zambia and develop the Luangwa Rift Active Fault Database (LRAFD). The LRAFD is an open-source geospatial database containing active fault traces and their attributes and is freely available at https://doi.org/10.5281/zenodo.6513691. We identified 18 faults that display evidence for Quaternary activity, and empirical relationships suggest that these faults could cause earthquakes up to Mw 8.1, which would exceed the magnitude of historically recorded events in southern Africa. On the four most prominent faults, the median height of Quaternary fault scarps varies between 12.9 ± 0.4 and 19.2 ± 0.9 m, which suggests they were formed by multiple earthquakes. Deformation is focused on the edges of the Luangwa Rift: the most prominent Quaternary fault scarps occur along the 207 km long Chipola and 142 km long Molaza faults, which are the rift border faults and the longest faults in the region. We associate the scarp on the Molaza Fault with possible surface ruptures from two 20th century earthquakes. Thus, the LRAFD reveals new insights into active faulting in southern Africa and presents a framework for evaluating future seismic hazard.

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29

Ameyaw, Daniel Adofo, Sandra Rothe, and Dirk Söffker. "A novel feature-based probability of detection assessment and fusion approach for reliability evaluation of vibration-based diagnosis systems." Structural Health Monitoring 19, no. 3 (June 27, 2019): 649–60. http://dx.doi.org/10.1177/1475921719856274.

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Structural health monitoring systems are based on suitable sensor techniques allowing online and offline supervision of technical systems. The quantification of sensors/measurement devices is a key issue for qualifying their effectiveness and efficiency and therefore to ensure safe operations. Probability of detection serves as a performance measure for quantifying the reliability of conventional nondestructive testing procedures taking into account statistical variability of sensor-based measurements. For vibration-based supervision approaches and fault detection and isolation methods, the probability of detection approach cannot be applied similarly. This results mainly from the complexity of the dynamical behavior of systems monitored in relation to faults, sensors position (observability), and the related feature extraction or monitoring task. In this contribution, probability of detection evaluation of vibration-based fault detection of elastic mechanical structures to be monitored is developed. Beside a principal discussion of the problem serving as introduction, an example using different sensor types in combination with mechanical modifications of an elastic beam is presented. The a90/95-criteria representing probability of 90% detection at a confidence level of 95% is examined to the measurements and related outcomes. Based on the analysis of a suitably chosen feature (like eigenfrequency or band power) and dependent on the mechanical modes considered, the efficiency and deficiency of the different combinations are shown. Based on the proposed approach, a new insight into the usefulness of different sensor type and fault position combination becomes possible. To improve the detection quality, suitable assumptions in combination with sensor/information fusion are applied to feature-based analysis as detection task using vibration measurements. In addition, based on an experimental evaluation, it can be concluded that a suitable fault-feature probability of detection analysis can be successfully implemented as a new reliable measure for vibration-based fault detection and isolation approaches. Furthermore, decision fusion as the combination of different measurements will allow the improvement of results. Dependent on noise analysis, a trade-off between flaw size detection and probability of falsely characterizing a fault with a90/95 reliability level can be attained.

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30

Kaviris, George, Angelos Zymvragakis, Pavlos Bonatis, Vasilis Kapetanidis, and Nicholas Voulgaris. "Probabilistic and Scenario-Based Seismic Hazard Assessment on the Western Gulf of Corinth (Central Greece)." Applied Sciences 12, no. 21 (November 3, 2022): 11152. http://dx.doi.org/10.3390/app122111152.

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The Gulf of Corinth (Central Greece) is one of the most rapidly extending rifts worldwide, with its western part being the most seismically active, hosting numerous strong (M ≥ 6.0) earthquakes that have caused significant damage. The main objective of this study was the evaluation of seismic hazard through a probabilistic and stochastic methodology. The implementation of three seismotectonic models in the form of area source zones via a logic tree framework revealed the expected level of peak ground acceleration and velocity for return periods of 475 and 950 years. Moreover, PGA values were obtained through the stochastic simulation of strong ground motion by adopting worst-case seismic scenarios of potential earthquake occurrences for known active faults in the area. Site-specific analysis of the most populated urban areas (Patras, Aigion, Nafpaktos) was performed by constructing uniform hazard spectra in terms of spectral acceleration. The relative contribution of each selected fault segment to the seismic hazard characterizing each site was evaluated through response spectra obtained for the adopted scenarios. Almost all parts of the study area were found to exceed the reference value proposed by the current Greek National Building Code; however, the three urban areas are covered by the Eurocode 8 regulations.

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31

Niu, Gang, Yajun Zhao, and Van Tung Tran. "Fault detection and isolation based on bond graph modeling and empirical residual evaluation." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 3 (May 22, 2014): 417–28. http://dx.doi.org/10.1177/0954406214536381.

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Fault detection and isolation are critical for safety related complex systems like aircraft, trains, automobiles, power plants and chemical plants. In order to realize a robust and real time monitoring and diagnosis for these types of multi-energy domain systems, this paper presents a novel scheme that integrates bond graph modeling for fault signatures establishment, and a multivariate state estimation technique-based empirical estimation for residual generation followed by a Sequential Probability Ratio Test-based residual evaluation for monitoring alarm. Once a fault is detected and alerted, a synthesized non-null coherence vector is created, and then matched with the pre-designed fault signatures matrix to isolate possible faults. To identify the effectiveness of the proposed methodology, a simulation for pneumatic equalizer control unit of locomotive electronically controlled pneumatic brake is conducted. The experimental results show that satisfied performance of fault detection and isolation can be obtained with lower miss alarm and timely response, which make it suitable for complex systems modeling and intelligent maintenance.

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32

Mo, Ruokun, and Weifeng Shi. "Ranking method of equipment failure risk in shipboard power system." Journal of Physics: Conference Series 2351, no. 1 (October 1, 2022): 012035. http://dx.doi.org/10.1088/1742-6596/2351/1/012035.

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The realization of equipment failure risk ranking in shipboard power systems is of positive significance to the rapid recovery of ship power system faults. To effectively improve the speed and accuracy of ship fault recovery, accident plans are developed according to ranking results for the top n equipment with high risk. A risk ranking method for distribution equipment is proposed, which takes the outage power, failure probability, MTTR (mean time to repair), and equipment priority of distribution equipment as evaluation indexes, and uses the ENTROPY-TOPSIS analysis method. Taking the DDG-1000 destroyer as an example, the ranking of the failure risk of shipboard power distribution equipment is realized. The calculated results are consistent with the theoretical results, which proves the correctness of the proposed method.

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33

Li, Yingshun, Aina Wang, and Xiaojian Yi. "Fire Control System Operation Status Assessment Based on Information Fusion: Case Study." Sensors 19, no. 10 (May 14, 2019): 2222. http://dx.doi.org/10.3390/s19102222.

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In traditional fault diagnosis strategies, massive and disordered data cannot be utilized effectively. Furthermore, just a single parameter is used for fault diagnosis of a weapons fire control system, which might lead to uncertainty in the results. This paper proposes an information fusion method in which rough set theory (RST) is combined with an improved Dempster–Shafer (DS) evidence theory to identify various system operation states. First, the feature information of different faults is extracted from the original data, then this information is used as the evidence of the state for a diagnosis object. By introducing RST, the extracted fault information is reduced in terms of the number of attributes, and the basic probability value of the reduced fault information is obtained. Based on an analysis of conflicts in the existing DS evidence theory, an improved conflict evidence synthesis method is proposed, which combines the improved synthesis rule and the conflict evidence weight allocation methods. Then, an intelligent evaluation model for the fire control system operation state is established, which is based on the improved evidence theory and RST. The case of a power supply module in a fire control computer is analyzed. In this case, the state grade of the power supply module is evaluated by the proposed method, and the conclusion verifies the effectiveness of the proposed method in evaluating the operation state of a fire control system.

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34

Baize, Stéphane, Edward Marc Cushing, Francis Lemeille, and Hervé Jomard. "Updated seismotectonic zoning scheme of Metropolitan France, with reference to geologic and seismotectonic data." Bulletin de la Société Géologique de France 184, no. 3 (March 1, 2013): 225–59. http://dx.doi.org/10.2113/gssgfbull.184.3.225.

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Abstract This work presents the seismotectonic zoning scheme of Metropolitan France developed by the IRSN (French Institute for Radioprotection and Nuclear Safety) within the framework of its seismic hazard assessment activities. It is the outcome of many years of work following the publication of the “seismotectonic atlas” in 1993 [Grellet et al., 1993]. This scheme supports the assessment of seismic hazard by IRSN. It takes into account the most recent data concerning the deep and surface geology, as well as those related to seismotectonics and tectonic activity. It finally includes 67 surface seismotectonic zones (STZ), as well as a catalogue of 74 faults or structures (named hereafter “potential active faults”) for which indications of Neogene to Quaternary displacement can be inferred. The description of the zoning scheme comes along with an estimation of the uncertainty on the boundary location between adjacent STZ. We also qualitatively determine a “relevance order” for each limit, so as to illustrate their reliability to separate regions of different seismogenic potential. Also, we attributed to the faults an indication whose purpose is to reflect the recent character of their activity, and thus their seismotectonic potential. This assessment of uncertainties was undertaken to better integrate the zoning scheme in the general approach, which arises from recent studies, namely the propagation of the uncertainties in seismic hazard evaluation, whether deterministic or probabilistic.

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35

Duan, Shixuan, Yanjun Li, Yuyuan Cao, Xingye Wang, Xudong Li, and Zejian Zhao. "Health Assessment of Landing Gear Retraction/Extension Hydraulic System Based on Improved Risk Coefficient and FCE Model." Applied Sciences 12, no. 11 (May 26, 2022): 5409. http://dx.doi.org/10.3390/app12115409.

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The health of the landing gear retraction/extension(R/E) hydraulic system may be assessed using fuzzy comprehensive evaluation (FCE), however the traditional FCE method depends solely on human assessment by specialists, which is excessively subjective. To address the issue of excessive human subjective variables in the assessment, an improved FCE model based on enhanced risk coefficient is provided, which includes four consideration indexes: failure probability, failure severity, failure detection difficulty, and failure repair difficulty. To reduce subjective human judgment errors entirely due to expert experience, the improved FCE takes into account the likelihood of failure using a statistical method, the severity of failure using a fault simulation analysis based on the LMS Imagine.Lab AMESim simulation platform, and the difficulty of fault detection and repair using the aircraft manufacturer’s professional maintenance information. As part of the evaluation model, the range of health assessment values and accompanying treatment methods are included, making it easier to implement on a daily basis in aircraft maintenance. As a final step, the simulation is evaluated, and the simulated faults are calculated.

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36

Zhang, Fuqiang, Zerong Yang, Ting Li, Yue Jia, Dan Zhou, and Luyao Xie. "Research on the early warning method of transformer fire fault in ocean booster station based on fault tree model." E3S Web of Conferences 252 (2021): 02044. http://dx.doi.org/10.1051/e3sconf/202125202044.

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As the heart of the sea booster station, the transformer has an extremely important position. When the transformer has various faults, it is very easy to cause a fire accident, so the safe operation of the transformer is very important. First, use the fault tree analysis method to construct a transformer fire fault tree evaluation model for different types of fire fault events during the operation of the transformer, then through the calculation of the fire failure probability, the number of measuring points of the composite fire detector is obtained and the measuring points are reasonably arranged to detect the operation status of the transformer in real time. Therefore, it is of great significance to ensure the safe and reliable operation of offshore booster station by improving the accuracy of transformer fire warning.

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37

Li, Zhixing, Songjiu Han, Jianguo Wang, Xueping Ren, and Chao Zhang. "Time-Delayed Feedback Tristable Stochastic Resonance Weak Fault Diagnosis Method and Its Application." Shock and Vibration 2019 (June 9, 2019): 1–13. http://dx.doi.org/10.1155/2019/2097164.

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Pulses caused by rotating mechanical faults are weak and often submerged in strong background noise, which can affect the accuracy of fault detection. To solve this problem, we study the stochastic resonance phenomenon of a tristable potential system based on strong noise background and also investigate the influence of time-delayed feedback on this stochastic resonance model. The effects of time-delayed feedback strength on potential energy, steady-state probability density function, and signal-to-noise ratio (SNR) are discussed. The results show that stochastic resonance can be enhanced or suppressed by adjusting the delay time and feedback strength. Combined with bearing fault diagnosis simulation research and experimental verification evaluation, the proposed time-delayed feedback tristable stochastic resonance fault diagnosis method is more effective than the classical stochastic resonance method.

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38

Yang, Pei, Junfeng Qiao, and Gang Wang. "Research on transformer condition evaluation based on oil chromatography differentiation threshold." Journal of Physics: Conference Series 2387, no. 1 (November 1, 2022): 012011. http://dx.doi.org/10.1088/1742-6596/2387/1/012011.

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Abstract As one of the important power transmission and transformation equipment, the reliability of transformer is directly related to the safe operation of power system. At present, the on-line monitoring technology based on dissolved gas analysis in oil is widely valued by researchers all over the world because it can continuously monitor the operation status of transformers and timely and effectively find the early faults of transformers. In this paper, the on-site oil chromatography data are differentiated and classified according to the voltage level of the transformer. The curve fitting method is used for statistical analysis and to build a distribution model. The cumulative probability is associated with the defect rate and failure rate of the equipment, and the corresponding threshold value is obtained by using the inverse cumulative distribution function as the attention value and warning value. By using this method, the attention values of the volume fraction of dissolved gas in oil and the gas production rate of dissolved gas in the existing national standards are improved, and the corresponding warning values are calculated to make the warning mechanism more flexible and reliable.

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39

Ilozobhie, A. J., and D. I. Egu. "Correlative modeling techniques to reducing uncertainties in a complex marginal field in the Niger Delta." Global Journal of Pure and Applied Sciences 24, no. 2 (December 18, 2018): 202–13. http://dx.doi.org/10.4314/gjpas.v24i2.10.

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Deterministic and probabilistic re-evaluation was used in handling predetermined six uncertainties in five wells in Isand reservoir. Results of low case (LC) modeled string showed that the I-sand reservoir is severely deformed by faults and this was confirmed with a predicted high case (HC) modeled string. When structure was sensitized at a bulk volume of 10,964STB with porosity of 0.266, water saturation of 0.43 and net to gross ratio (NTG) of 0.75 and initial oil formation volume factor (Boi) of 2.2bbl/stb, the resultant estimated stock tank initial oil in place (STOIIP) gave 5,892,752.65STB or the base case. The corresponding STOIIP for the low and high case are 5,198,470.887STB and 6,451,196.678STB. Results of deterministic analysis shows that the low case results gave a minimum value of 5.20MMSTB for structures and maximum value of 6.2MMSTB for water saturation. High case results revealed a maximum of 6.45MMSTB for structures and a minimum value of 5.69MMSTB for water saturation. Results of high, low and base cases were used to quantify some of the uncertainties in the volumetric estimation and subsequently in the probabilistic method. This work clearly shows the viability of the pragmatic approach used to quantify the uncertainty ranges in reservoir parameters and their impact on the statics volumes as well as recovery. Keywords: deterministic, probabilistic, modeled, structures, water saturation, net to gross ratio

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40

Guo, Junjun, Yitong Gu, Weihong Wu, Shihyu Chu, and Xinzhi Dang. "Seismic Fragility Assessment of Cable-Stayed Bridges Crossing Fault Rupture Zones." Buildings 12, no. 7 (July 19, 2022): 1045. http://dx.doi.org/10.3390/buildings12071045.

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Current studies lack probabilistic evaluations on the performance of fault-crossing bridges. This paper conducts seismic fragility analyses to evaluate the fragility of cable-stayed bridges with the effects of fault ruptures. Synthetic across-fault ground motions are generated using existing simulation methods for the low-frequency pulses and high-frequency residuals. Incremental dynamic analysis is utilized to generate the seismic responses of the bridge. The optimal intensity measure (IM) for a cable-stayed bridge that crosses a fault is identified based on the coefficient of determination (R2). Root-mean-square velocity (Vrms) is found to be the best IM for cable-stayed bridges traversed by fault ruptures, instead of the commonly used ones such as peak ground acceleration or velocity (PGA or PGV). Fragility curves for the critical components of fault-crossing cable-stayed bridges, including pylons, cables, and bearings, are developed using the IM of Vrms, and are subsequently compared with those for the cable-stayed bridge near faults. Results show that the bearings on transition piers are the most vulnerable component for fault-crossing cable-stayed bridges because of the rotation of their girder. Compared to cable-stayed bridges near faults, pylons and bearings are more vulnerable in the transverse direction for cable-stayed bridges crossing faults, whereas the vulnerability of cables is comparable.

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41

Hasanspahić, Nermin, Vlado Frančić, Igor Rudan, and Lovro Maglić. "Analysis of Navigation Safety Regarding Tankers in Narrow Waterways." Journal of Maritime & Transportation Science 55, no. 1 (December 2018): 201–17. http://dx.doi.org/10.18048/2018.00.13.

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Sailing of tanker ships in specific navigation areas, such as narrow waterways, is a particularly delicate navigational venture, where one of the greatest related risks is grounding. Grounding of a tanker in a narrow waterway is an event that can cause many adverse consequences, the most important among them being environmental pollution, explosion or onboard fire damaging the ship, injuries and lost lives of crewmembers. Factors affecting the safety of tanker navigation in narrow waterways can be principally divided into geometric, traffic, meteorological and oceanological factors, ship design factors and marine equipment faults as well as human-related factors. With a view to minimizing the possibility of grounding or contact, the assessment of risks is to be considered indispensable and primarily aimed at influencing accident probability and/or consequence factors as its most important objective. The paper analyses the safety of tanker navigation in narrow waterways based on the assessment of risk of grounding. The event influential probability factors that are taken into consideration comprise the narrow waterway category, meteorological and oceanological conditions, traffic density and VTS coverage of the navigable area, while factors such as ship speed, bottom type, hull quality and loading condition are factors related to consequences. Using the risk assessment matrix, estimated values used for evaluation of the safety of tanker navigation in narrow waterways are assigned to probability factors and factors of consequences.

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42

Cheng, Jiangzhou, Cai Zhu, Wenlong Fu, Canxia Wang, and Jing Sun. "An Imitation medical diagnosis method of hydro-turbine generating unit based on Bayesian network." Transactions of the Institute of Measurement and Control 41, no. 12 (February 10, 2019): 3406–20. http://dx.doi.org/10.1177/0142331219826665.

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In order to improve the intelligent level of fault diagnosis and condition maintenance of hydropower units, an Imitation medical diagnosis method (IMDM) is proposed in this study. IMDM uses Bayesian networks (BN) as the technical framework, including three components: machine learning BN model, expert empirical BN model, and maintenance decision model. Its characteristics are as follows: (i) the machine learning model uses a new node selection method to solve the problem that the traditional fault diagnosis model is difficult to connect with the state monitoring system. (ii) The expert experience BN model improves the traditional method: using the fault tree model to transform the BN structure, Noisy-Or model to simplify conditional probability table, and fuzzy comprehensive evaluation method to obtain the conditional probability. (iii) By introducing the expected utility theory, a maintenance decision model is innovated, which makes sure the optimal maintenance decision scheme after the fault can be better selected. The performance of this proposed method is evaluated by using the experimental data. The results show that the accuracy of the fault reasoning model is higher than 80%, and the maintenance decision model successfully selects 236 optimal maintenance decision schemes from 3159 schemes generated by 13 faults.

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43

Bartys, Michal. "Fault compensation effect in fault detection and isolation." ACTA IMEKO 10, no. 3 (September 30, 2021): 91. http://dx.doi.org/10.21014/acta_imeko.v10i3.1056.

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<p class="Abstract">This paper discusses the origin and problem of the fault compensation effect. The fault compensation effect is an underrated common side effect of the fault isolation approaches developed within the Fault Detection and Isolation (FDI) community. In part, this is justified due to the relatively low probability of such an effect. On the other hand, there is a common belief that the inability to isolate faults due to this effect is the evident drawback of model-based diagnostics. This paper shows how, and under which conditions, the fault compensation effect can be identified. In this connection, the necessary and sufficient conditions for the fault compensation effect are formulated and exemplified by diagnosing a single buffer tank system in open and closed-loop arrangements. In this regard, we also show the drawbacks of a bi-valued residual evaluation for fault isolation. In contrast, we outline the advantages of a three-valued residual evaluation. This paper also brings a series of conclusions allowing for a better understanding of the fault compensation effect. In addition, we show the difference between fault compensation and fault-masking effects.</p>

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Kim, Euiho, Jaeyoung Song, Yujin Shin, Saekyul Kim, Pyo-Woong Son, Sulgee Park, and Sanghyun Park. "Fault-Free Protection Level Equation for CLAS PPP-RTK and Experimental Evaluations." Sensors 22, no. 9 (May 7, 2022): 3570. http://dx.doi.org/10.3390/s22093570.

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Centimeter level augmentation system (CLAS) of the quasi-zenith satellite system (QZSS) is the first precise point positioning-real time kinematic (PPP-RTK) augmentation system of the global navigation satellite system (GNSS), which is currently providing services for Japan. CLAS broadcasts the state-space representation of correction messages along with integrity messages regarding satellite faults and the quality index of each correction. In other GNSS augmentation systems, such as the space-based augmentation system (SBAS) of GNSS, the quality indices of correction messages are used to generate fault-free protection levels that represent a position bound containing a true user position with a probability of missed detections. Although the protection level equations are well defined for the SBAS, a protection level equation for the CLAS PPP-RTK service has not been rigorously discussed in the literature. This paper proposes a fault-free protection level equation for the PPP-RTK methods that considers the probability of correct integer ambiguity fixes in the GNSS carrier phase measurements as well as the CLAS correction quality messages. The computed protection levels with position errors were experimentally compared by processing the GNSS measurements from the GNSS Earth Observation Network (GEONET) stations in Japan and the L6 messages from the CLAS broadcast using the virtual reference station-real time kinematic (VRS-RTK) techniques. Our results, based on the GEONET dataset spanning 7 days, showed that the computed protection levels using the proposed equations were larger than the position errors for all epochs. In the dataset, the RMS errors of the CLAS VRS-RTK position were 4.6 and 14 cm in the horizontal and vertical directions, respectively, whereas the horizontal protection levels ranged from 25 cm to 2.3 m and the vertical protection levels ranged from 50 cm to 5.2 m based on fault-free integrity risk of 10−7.

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Cazes, Dean, and Meir Kalech. "Model-Based Diagnosis with Uncertain Observations." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (April 3, 2020): 2766–73. http://dx.doi.org/10.1609/aaai.v34i03.5664.

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Classical model-based diagnosis uses a model of the system to infer diagnoses – explanations – of a given abnormal observation. In this work, we explore how to address the case where there is uncertainty over a given observation. This can happen, for example, when the observations are collected by noisy sensors, that are known to return incorrect observations with some probability. We formally define this common scenario for consistency-based and abductive models. In addition, we analyze the complexity of two complete algorithms we propose for finding all diagnoses and correctly ranking them. Finally, we propose a third algorithm that returns the most probable diagnosis without finding all possible diagnoses. Experimental evaluation shows that this third algorithm can be very effective in cases where the number of faults is small and the uncertainty over the observations is not large. If, however, all possible diagnoses are desired, then the choice between the first two algorithms depends on whether the domain's diagnosis form is abductive or consistent.

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46

Ghaychi Afrouz, Setareh, Alireza Farzampour, Zahra Hejazi, and Masoud Mojarab. "Evaluation of Seismic Vulnerability of Hospitals in the Tehran Metropolitan Area." Buildings 11, no. 2 (February 5, 2021): 54. http://dx.doi.org/10.3390/buildings11020054.

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The Tehran metropolitan area is extremely vulnerable to earthquakes due to the location of its active faults and its dense population. Assessing the probable damage of a high magnitude earthquake on buildings and facilities relies on a precise structural survey, which has an empirical basis depending on historic ground motions. The probability of damage and failure in discrete limits based on different ground motions is estimated by fragility curves. Using the most matching fragility curves for buildings in Tehran, the vulnerability of the hospitals in the capital, as one of the most critical structures in crisis management of disasters, was investigated in this study. Subsequently, the existing fragility curves, developed for Tehran and the other seismic prone countries such as Japan and the United States, were compared considering the typology of Tehran’s hospitals. Finally, the possible damages for each hospital were calculated based on the most conservative fragility curve and the most pessimistic scenario, which were used to evaluate the seismic vulnerability of hospitals and health care systems for different damage states. After zoning the damage of therapeutic areas of Tehran, it was observed that at least 2% to 10% damage occurred in all hospitals of Tehran, and none of the healthcare centers would remain structurally undamaged after a strong earthquake with the moment magnitude of 7 or more. In addition, the healthcare buildings could be prone to significant structural damage, especially in southern parts, which necessitates proactive management plans for Tehran metropolitan area.

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Van Schagen, Esther. "The Hidden Potential of Regulatory Impact Assessments (RIAs) in the Private Law Acquis." European Review of Private Law 22, Issue 1 (February 1, 2014): 69–87. http://dx.doi.org/10.54648/erpl2014004.

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Summary: This article argues that regulatory impact assessments (RIAs) are an important method to improve the private law acquis that are currently overlooked. Many problems of unpredictability and inconsistency can be traced to poor regulatory choices in the private law acquis, including the overenthusiastic use of blanket clauses and the lack of coordination in the development of the acquis. RIAs are a very suitable means to prompt the legislator to reconsider these choices. The use of RIAs however currently shows severe shortcomings. Particularly, RIAs frequently contain doubtful and unsubstantiated assumptions, and they do not neutrally assess the benefits and detriments of all possible ways to develop the acquis. These shortcomings should be addressed if RIAs are to contribute to the quality of the private law acquis. A more thorough evaluation of past and future measures such as minimum and maximum harmonization, guidance, databases, and self-regulation and more coordination would contribute to the predictability and consistency of the private law acquis. Résumé: Cet article propose que les analyses d'impact sont un moyen important pour améliorer l'acquis de droit privé qui est maintenaint négligé. Beaucoup des problèmes d'imprévibilité et inconsistance peuvent être attribués aux mauvais choix politiques, ainsi que le trop enthousiast emploi des clauses générales et l'absence de coordination dans la formation de l'acquis. Les analyses d'impact sont un moyen apte à inciter le législateur à réviser ces choix. Toutefois, des erreurs graves se présentent dans l'emploi des analyses d'impact, en particulier les hypothèses douteux et le défaut d'une analyse neutre des bénéfices et des détriments de tous moyens possibles pour développer l'acquis. Si les analyses des impacts pourraient s'améliorer la qualité del'acquis de droit privé, il faut que ces fautes seront rectifiés.

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Li, Xiongli, Fei Xiao, Youlin Hu, and Huikai Peng. "Research on Recognition of Topological Relations Between Residential Lines in Low Voltage Station Area Based on Correlation Analysis Algorithm and Probabilistic Decision Method." Journal of Nanoelectronics and Optoelectronics 16, no. 7 (July 1, 2021): 1107–14. http://dx.doi.org/10.1166/jno.2021.3053.

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In order to solve the problems of low accuracy and incomprehensive recognition of the topological relationship between households in the station area and the incomplete recognition results in traditional methods, a method for identifying topological relationships between household changes in low-voltage stations based on correlation analysis algorithm and probabilistic decision method is proposed. The BIRCH method is used to cluster the topological relationship characteristics of the household line changes in the low-voltage station area, and the topological relationship characteristics are obtained through clustering parameter initialization, clustering implementation and clustering evaluation, and the user phases in the topological relationship are identified according to the feature clustering results. The correlation analysis method is used to analyze the similarity of the voltage sequence of the points to be identified and the comprehensive similarity of all the faults of the target distribution transformer and the auxiliary distribution transformer, and set a similarity threshold to determine whether the points to be identified belong to the same station area. Finally, based on the probabilistic decision-making method, the identification of the topological relationship of the low-voltage station area household line change is completed. The experimental results show that this method can not only identify the topological relationship of single distribution transformer outage, but also identify the topological relationship of multiple distribution transformer outage. The accuracy of the identification result is high, and the identification loss function is low, which indicates that the identification result of this method is reliable and comprehensive.

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49

Li, Xiongli, Fei Xiao, Youlin Hu, and Huikai Peng. "Research on Recognition of Topological Relations Between Residential Lines in Low Voltage Station Area Based on Correlation Analysis Algorithm and Probabilistic Decision Method." Journal of Nanoelectronics and Optoelectronics 16, no. 7 (July 1, 2021): 1107–14. http://dx.doi.org/10.1166/jno.2021.3053.

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Анотація:

In order to solve the problems of low accuracy and incomprehensive recognition of the topological relationship between households in the station area and the incomplete recognition results in traditional methods, a method for identifying topological relationships between household changes in low-voltage stations based on correlation analysis algorithm and probabilistic decision method is proposed. The BIRCH method is used to cluster the topological relationship characteristics of the household line changes in the low-voltage station area, and the topological relationship characteristics are obtained through clustering parameter initialization, clustering implementation and clustering evaluation, and the user phases in the topological relationship are identified according to the feature clustering results. The correlation analysis method is used to analyze the similarity of the voltage sequence of the points to be identified and the comprehensive similarity of all the faults of the target distribution transformer and the auxiliary distribution transformer, and set a similarity threshold to determine whether the points to be identified belong to the same station area. Finally, based on the probabilistic decision-making method, the identification of the topological relationship of the low-voltage station area household line change is completed. The experimental results show that this method can not only identify the topological relationship of single distribution transformer outage, but also identify the topological relationship of multiple distribution transformer outage. The accuracy of the identification result is high, and the identification loss function is low, which indicates that the identification result of this method is reliable and comprehensive.

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Chisty, Nur Mohammad Ali, and Harshini Priya Adusumalli. "Applications of Artificial Intelligence in Quality Assurance and Assurance of Productivity." ABC Journal of Advanced Research 11, no. 1 (January 28, 2022): 23–32. http://dx.doi.org/10.18034/abcjar.v11i1.625.

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Probabilistic intelligence is vital in current management and technology. It is simpler to persuade readers when a management or engineer reports connected difficulties with objective statistical data. Statistical data support the evaluation of the true status, and cause and effect can be induced. The rationale is proven using deductive logic and statistical data verification and induction. Quality practitioners should develop statistical thinking skills and fully grasp the three quality principles: “essence of substance,” “process of business,” and “psychology.” Traditional quality data include variables, attributes, faults, internal and external failure costs, etc., obtained by data collection, data processing, statistical analysis, root cause analysis, etc. Quality practitioners used to rely on these so-called professional qualities to get a job. If quality practitioners do not keep up with the steps of times, quality data collection, organization, analysis, and monitoring will be confusing or challenging. Increasingly, precision tool machines are embedded in various IoTs, gathering machine operation data, component diagnostic and life estimation, consumables monitoring and utilization monitoring, and various data analyses. Data mining and forecasting have steadily been combined into Data Science, which is the future of quality field worth worrying about.

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