Predictive Analysis of Mission Critical Systems Dependability

This paper describes the dependability evaluation of track circuit receiver. The device is a component of railway interlocking system used in Czech Republic at conventional lines. The device is based on 2oo3 principle for high dependability. The reliability analysis, model and safety characteristics calculations of this device are described. Markov chain model is used for the reliability analysis.

[1] Streamflows often vary strongly with season, and this leads to seasonal dependence in hydrological model errors and prediction uncertainty. In this study, we introduce three error models to describe errors from a monthly rainfall-runoff model: a seasonally invariant model, a seasonally variant model, and a hierarchical error model. The seasonally variant model and the hierarchical error model use month-specific parameters to explicitly account for seasonal dependence, while the seasonally invariant model does not. A Bayesian prior is used in the hierarchical error model to account for potential variation and connection among model parameters of different months. The three error models are applied to predicting streamflows for five Australian catchments and are compared by various performance scores and diagnostic plots. The seasonally variant model and the hierarchical model both perform substantially better than the seasonally invariant model. From a cross-validation analysis, the hierarchical error model provides both the most accurate prediction mean and the most reliable prediction uncertainty distribution in most situations. The use of the prior to constrain the model parameters in the hierarchical model produces more robust parameter estimation than the other two models.

Reliability prediction and modeling of 30 V-12 V to 5 V voltage regulator for automotive application using IEC-62380 reliability prediction standard

Human immunodeficiency virus (HIV) progressively impairs immune function. If the infection is detected late or left untreated, it leads to the development of AIDS. Therefore, from a public health perspective, it is necessary to monitor the occurrence of infection in the population, as well as trends overall and in specific subgroups. This is achieved through a national HIV surveillance system, whose outputs can be used not only to describe the epidemiological situation but also to guide preventive activities. The text outlines the organizational components of the surveillance system developed since 1986 and presents the key epidemiological data describing the HIV epidemic in the Czech Republic. Between 1985 and 2024, a total of 4888 cases of HIV infection were detected among Czech citizens and foreigners with long-term or permanent residence. Of those, 926 were diagnosed with AIDS, and 654 died. The basic characteristics of the HIV epidemic in the Czech Republic are the predominance of sexual transmission, especially among men who have sex with men, but with increasing numbers of heterosexually transmitted infections, a low proportion of women (approximately 15%), and an increasing proportion of foreigners (48% in the last five years). The annual number of new cases initially hovered around a few dozen, then steadily increased from 2003 until reaching 286 in 2016. After a slight decline, the numbers peaked at 292 in 2022. Recent trends have been affected by the COVID-19 pandemic and the war in Ukraine. In addition to the above figures, 856 HIV-positive refugees from Ukraine were registered in 2022-2024. Despite these facts, the Czech Republic continues to be classified as a low-prevalence country in both the European and global contexts. However, the trend in recent years has not been favorable, with the number of new cases showing a slight increase. Keywords: HIV, AIDS, surveillance, HIV transmission, foreigners.

Fatigue reliability analysis of the jacket support structure for offshore wind turbine considering the effect of corrosion and inspection

Hierarchical Bayesian modelling of quasi-region-specific soil porosity

Reliability analysis and initial requirements for FC systems and stacks

The assessment of geothermal potential has gained prominence among scholars, with a focus on establishing a reliable prediction model to reduce development risks. However, little attention has been given to predicting and evaluating the geothermal potential in Dali’s Eryuan area. This study introduces a novel hierarchical model integrating remote sensing, a Geographic Information System (GIS), and geophysics for the first-ever effective prediction of geothermal potential in Eryuan. The dataset includes lithology, seismic epicenter data, fault distribution, Bouguer gravity anomalies, SRTM-DEM images, and Landsat 8 remote sensing images. These datasets are converted into evidence maps and normalized to generate distinct evidence factor layers. Using the Analytic Hierarchy Process (AHP), a hierarchical model establishes weights for each evidence factor, resulting in a comprehensive prediction map. The results reveal the overall favorable geothermal potential in Eryuan, except the central area. Key hotspots include the Niujie–Sanying–Gromwell Lake and Liantie–Qiaohou, followed by the Youshou, Dengchuan, and Xixiang towns. Validation against known hot springs confirms the model’s accuracy and reliability.

The integration of product assurance engineering into the design process is discussed. A simple desktop approach that uses the design's indented bill of materials as its foundation is presented. The relational database structure presented supports typical reliability and maintainability analysis tasks. The author covers the indented bill of materials; reliability prediction (parts count technique); reliability prediction (stress-analysis technique conforming to MIL-HDBK-217E); failure mode, effects, and criticality analysis; maintainability prediction; and program parts selection list and generation of nonstandard part-approval requests. >

\n Nowadays, Dynamically Positioned (DP) units are responsible for most of offshore oil exploitation operations, including drilling and maintenance campaigns. Due to the larger congestion of the oil fields, keep the vessel position, despite the environmental forces, is a critical issue. This study aims to propose a methodology and apply it for a RAM analysis (Reliability, Availability & Maintainability) of DP System of two different generations (DP class 2 and DP class 3) in order to obtain accurate information that allows subsequently define their restriction diagrams. The DP system, including various subsystems, DP classes and applications, are introduced and discussed. In addition, the necessary concept and techniques to analyze the Reliability, Availability and Maintainability of DP system are explained. In the reliability analysis, two interest events (free drift and controlled drift) are evaluated for different operation times (12, 9, 6 and 3 months); and, as expected, the DP3 system is more reliable than DP2 system in all scenarios. Regarding maintainability, the Monte Carlo Simulation exposed that in more than 90% of the free drift, the maintenance teams of the DP systems under study are able to recover the positioning of the units in the first 6 hours; while the recovery times lower than 3 hours, represent 43% of simulated free drifts. The asymptotic availability analysis of DP2 and DP3 systems shows availability greater than 0.9998 even for operational times greater than 15 years. The study concludes with an evaluation of the impact of the uncertainty in the failure rates of critical components of DP systems and the use of a non-parametric method for the design of probability density function of repair times. Finally, it is suggested that future studies take into consideration the impact of human factors in the DP system RAM analysis.\n

Pluvial flash floods are among the most dangerous weather-triggered disasters, usually affecting watersheds smaller than 100 km2, with a short time to peak discharge (from a few minutes to a few hours) after causative rainfall. Several warning systems in the world try to use this time lag to predict the location, extent, intensity, and time of flash flooding. They are based on numerical hydrological models processing data collected by on-ground monitoring networks, weather radars, and precipitation nowcasting. However, there may be areas covered by weather radar data, in which the network of ground-based precipitation stations is not sufficiently developed or does not even exist (e.g., in an area covered by portable weather radar). We developed a method usable for designing an early warning system based on a different philosophy for such a situation. This method uses weather radar data as a 2D signal carrying information on the current precipitation distribution over the monitored area, and data on the watershed and drainage network in the area. The method transforms (concentrates) the 2D signal on precipitation distribution into a 1D signal carrying information on potential runoff distribution along the drainage network. For sections of watercourses where a significant increase in potential runoff can be expected (i.e., a significant increase of the 1D signal strength is detected), a warning against imminent flash floods can be possibly issued. The whole curve of the potential runoff development is not essential for issuing the alarm, but only the significant leading edge of the 1D signal is important. The advantage of this procedure is that results are obtained quickly and independent of any on-ground monitoring system; the disadvantage is that it does not provide the exact time of the onset of a flash flooding or its extent and intensity. The generated alert only warns that there is a higher flash flooding hazard in a specific section of the watercourse in the coming hours. The forecast is presented as a dynamic map of the flash flooding hazard distribution along the segments of watercourses. Relaying this hazard to segments of watercourses permits a substantial reduction in false alarms issued to not-endangered municipalities, which lie in safe areas far away from the watercourses. The method was tested at the local level (pluvial flash floods in two small regions of the Czech Republic) and the national level for rainfall episodes covering large areas in the Czech Republic. The conclusion was that the method is applicable at both levels. The results were compared mainly with data related to the Fire and Rescue Service interventions during floods. Finally, the increase in the reliability of hazard prediction using the information on soil saturation is demonstrated. The method is applicable in any region covered by a weather radar (e.g., a portable one), even if there are undeveloped networks of rain and hydrometric gauge stations. Further improvement could be achieved by processing more extended time series and using computational intelligence methods for classifying the degree of flash flooding hazard on individual sections of the watercourse network.

Purpose– While increased mechanization and automation make considerable contributions to mine productivity, unexpected equipment failures and imperfect planned or routine maintenance prohibit the maximum possible utilization of sophisticated mining equipment and require significant amount of extra capital investment. Traditional preventive/planned maintenance is usually scheduled at a fixed interval based on maintenance personnel's experience and it can result in decreasing reliability. This paper deals with reliability analysis and prediction for mining machinery. A software tool called GenRel is discussed with its theoretical background, applied algorithms and its current improvements. In GenRel, it is assumed that failures of mining equipment caused by an array of factors (e.g. age of equipment, operating environment) follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest based on Genetic Algorithms (GAs) combined with a number of statistical procedures. The paper also discusses a case study of two mine hoists. The purpose of this paper is to investigate whether or not GenRel can be applied for reliability analysis of mine hoists in real life.Design/methodology/approach– Statistical testing methods are applied to examine the similarity between the predicted data set with the real-life data set in the same time period. The data employed in this case study is compiled from two mine hoists from the Sudbury area in Ontario, Canada. Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation.Findings– The case studies shown in this paper demonstrate successful applications of a GAs-based software, GenRel, to analyze and predict dynamic reliability characteristics of two hoist systems. Two separate case studies in Mine A and Mine B at a time interval of three months both present acceptable prediction results at a given level of confidence, 5 percent.Practical implications– Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation.Originality/value– Compared to conventional mathematical models, GAs offer several key advantages. To the best of the authors’ knowledge, there has not been a wide application of GAs in hoist reliability assessment and prediction. In addition, the authors bring discrete distribution functions to the software tool (GenRel) for the first time and significantly improve computing efficiency. The results of the case studies demonstrate successful application of GenRel in assessing and predicting hoist reliability, and this may lead to better preventative maintenance management in the industry.

<div class="htmlview paragraph">This paper discusses reliability prediction, modeling and analysis activities which are taking place in the Apollo program, after first giving a brief summary of the program itself. Reliability modeling and analysis of a typical manned Apollo mission are discussed through an example, the switch selector in the S-IVB stage of the Saturn V launch vehicle. Benefits and limitations of the analytical approach are given. It is concluded that prediction activities have benefited the Apollo program, and they have been most useful as consistent tools for designers where complete communication is maintained between engineers performing the analyses and those engaged in designing and testing the hardware.</div>

Reliability is importance property of a healthcare system. Methods for this system reliability analysis are considered in the paper. These methods have to include reliability analysis of technical part, and organization and human components of a health care system. Importance reliability analysis is proposed for this reliability analysis. The importance reliability analysis allows to estimate the influence of every healthcare system component to the system reliability and functioning.

The importance of raw material equivalents in economy-wide material flow accounting and its policy dimension