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Lately, transformer-less Researchers in the fields of power electronics and renewable energy have taken notice of photovoltaic inverters because of their great efficiency, low cost, and small size. However, higher efficiency typically results in more components, making the inverter costly and bulky. This article proposes a single-phase seven-level transformer-less with common ground topology. The proposed topology utilizes 10 switches, 4 capacitors and 1 diode. This article also suggests an improved Phase Shift (PS) Modulation Technique which reduces overall losses. When implemented with improved Phase Shift (PS), the total highest attainable efficiency of the proposed topology is 98.05% at 15 W. The THD% of voltage harmonics is reduced to 15.29% from 17.20% and for current harmonics is reduced to 5.07% from 10.15%. The reliability of the proposed inverter has also been analyzed. The simulation as well as hardware results have been presented to validate the performance of the proposed inverter.

PurposeThe purpose of this study is to develop Markovian model to obtain the transient probabilities to determine mean-time-to-failure and reliability function and further steady state availability of the repairable system. As the system parameters are uncontrollable factors; thus the life times, repair times and recovery/reboot time are assumed to be as uncertain or fuzzified distributions.Design/methodology/approachThe fuzzy approach is introduced to investigate the reliability measures of load sharing repairable system which consists of two operating units and one standby unit. On the failure of an operating component, it is instantly spotted, located and sent for recovery procedures with coverage probability. In case of imperfect recovery, reboot takes place.FindingsOn the basis of extension principle and mathematical programming approach, the authors establish membership functions for system characteristics with the help of α-cuts. To demonstrate the practical validity of the proposed fuzzified model, numerical illustrations are performed.Originality/valueThe model proposed for reliability analysis may cheer up the continuance of the work towards more applications in repairable systems. Therefore, the reader is provided with useful intuition into the nature of fuzzy computations and practical amendments while measuring ambiguous data.

Purpose The purpose of this paper is to evaluate various reliability measures like availability, reliability, mean time to failure and profit function. Design/methodology/approach The authors present a novel method for availability analysis of an engineering system incorporating waiting time to repair. The considered system consists of two subsystems, namely, A and B connected in series. The subsystem B has two identical units in standby arrangement. Each unit of the subsystem has two modes, i.e. normal efficiency or failed. The two standby units of the subsystem B are connected by an imperfect switching. The system is analyzed by supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula. Findings Numerical examples with a way to highlight the important results have been appended at last. Numerical calculation shows that availability and reliability of the system is decreasing with respect to time when failure rates are fixed at different values. Finally, cost analysis of system reveals that the expected profit decreases with increase in service cost. Originality/value This paper presents a mathematical model in which an important aspect of switching has been taken into consideration, which is consistent with actual failures of switching by assuming two different types of failure between adjacent transition. It is evaluated with the help of the Gumbel-Hougaard family of copula.

The paper deals with the comparison of reliability function, mean time to failure, and hazard rate function for simple mixed systems. Simple systems are those that can be divided into a sequence of series and/or parallel subsystems. The paper compares systems consisting of four subsystems; a total of seven systems are compared. A system with four parallel arranged subsystems is also included in the paper, for which the mean time to failure has the largest value. A system with four series-arranged subsystems is also included in the paper, for which the mean time to failure has the smallest value. The MATLAB program was used for the solution.

This paper presents a case study describing reliability analysis comparisons due to different maintenance decisions for punching tool sets that are used for perforating in a line-making process. Field maintenance data for punching tools are classified according to different maintenance decisions. The data were analyzed further to identify the best fit distribution models. The related reliability characteristics are then revealed and discussed. The reliability analysis results of four different major maintenance decisions shows that the short-term view indicates no significant differences of mean-time-to-failure (MTTF) for the equipment. However, the range (lower and upper limit values) for MTTF for each replacement decision package can be used by a maintenance engineer for equipment spare parts planning. The results found that the failure rate of the equipment was due to replacement decisions packages that are in a deteriorating state. Thus, the maintenance engineering team noticed that the determination of optimum preventive maintenance time is beneficial and cost effective. This study concludes the importance of reliability analysis to better understand the probability nature of the subject under consideration, i.e., it helps a technical team to utilize proper preventive maintenance and spare parts planning.

We present the mean-time-to-failure (MTTF) calculations for AlGaN/GaN high-electron-mobility transistors (HEMTs) using two independent acceleration factors. MTTF predictions are generally calculated through the Arrhenius relationship, based on channel temperature and acceleration, depend only on one parameter. Although the failure modes of the AlGaN/GaN HEMTs depend largely on the applied electric fields, the Eyring model is introduced to investigate both voltage and temperature dependent degradation of AlGaN/GaN devices. In anticipation of adequate MTTF values, studies were conducted on non-commercial devices. Further, we distinguished the cumulative failure percentages through the Weibull and log-normal distributions. We also explored the increase in gate leakage current at high temperatures for early device deterioration.

The long-term reliability of open-tube diffused planar InGaAs/InP APDs was investigated via accelerated life testing in this study. For the proposed life testing scheme, both thermal and electrical stresses were applied simultaneously to reduce the testing periods while maintaining statistical significance. Additionally, the Eyring model was used to extrapolate the activation energy. To determine the optimum life testing conditions, high-temperature storage tests, preliminary accelerated life tests, and main accelerated life tests were conducted. From the test results, the mean-time-to-failure was utilized to verify the suitability of the Eyring model. The proposed testing scheme, which utilizes a hybrid of accelerated stress factors, allows us to estimate the device reliability within an acceptable testing period, minimizing the time to market.

In this work, bridge network model with Rayleigh distribution lifetimes is used. Two main techniques are calculated to upgrade this model: reduction and redundancy techniques. In order to compare the effectiveness of the various approaches, the survival function, the mean time to failure and gamma-fractiles for the original and upgraded model are calculated. Finally, we analyze comprehensively a computer simulation example to distingue between the methods. The numerical simulations were done in Mathematica which indicated that the upgraded system performs better than the original one and the best technique is by cold duplication.

In recent years, there has been a growing interest in utilizing machine learning (ML) to investigate the predictability of shear-slip failures, known as laboratory quakes, in centimeter-scale rock-friction experiments. However, the applicability of ML to larger-scale laboratory quakes and natural earthquakes, where important timescales vary by orders of magnitude, remains uncertain. Here, we apply an advanced ML approach to meter-scale laboratory quake data, characterized by accelerating foreshock activity manifesting as increasing numbers of tiny acoustic emission events. We demonstrate that a trained ML model, using a network representation of the event catalog, can accurately predict the time-to-failure of meter-scale mainshocks, from tens of seconds to milliseconds before the upcoming main quakes. These timescales correspond to approximately decades down to weeks in the context of large earthquakes. By comparing our results with a dynamic model of shear failures that replicates the experimental data, we suggest that tracking the evolution of shear stress on creeping fault areas, rather than nominal shear stress, indirectly through the acoustic emission events, enables ML to predict both numerical and laboratory quakes. These findings provide critical insights into fault conditions that may facilitate short-term forecasting of earthquakes in nature. In this study, machine learning accurately predicts meter-scale laboratory quakes from tiny foreshocks, bridging the scale gap between laboratory and natural earthquakes and offering insights into short-term earthquake forecasting.

Purpose There is considerable debate regarding the optimal method of fixation for lateral meniscus allograft transplantation (MAT), with bone bridge techniques technically harder but allowing maintenance of root attachments, while soft tissue techniques are potentially more challenging for healing. The aim of this study was to compare the clinical results of the bone bridge and soft tissue techniques for lateral MAT in terms of failure, re-operation rate, complications and patient reported outcomes. Methods Retrospective analysis of prospectively collected data for patients undergoing primary lateral MAT with a minimum of 12-month follow-up. Patients following surgery utilising the bone bridge technique (BB) were compared with historical control patients who underwent MAT with the soft tissue technique (ST). Outcome was assessed by failure rate, defined as removal or revision of the meniscus transplant, survivorship by Kaplan–Meir analysis, re-operation rates, and other adverse event. Patient-reported outcome measures (PROMs) were compared using data at the 2-year point or 1 year if not reached 2 years. Results One-hundred and twelve patients following lateral meniscal transplants were included, 31 in the BB group and 81 in the ST historical control group, with no differences in demographics between both groups. Median follow-up for the BB group was 18 (12–43) months compared to 46 (15–62) months for the ST group. There were 3 failures (9.6%) in the BB group v 2 (2.4%) in the ST group (n.s.) with a mean time to failure of 9 months in both groups. 9 patients (29%) required a re-operation (all cause) in the BB group v 24 patients (29.6%) in the ST group (n.s). There was no difference in complications between both groups. There was significant improvement ( p  < 0.0001) in all PROMs (Tegner, IKDC, KOOS and Lysholm) between baseline and 2-year follow-up for both groups but no between-group differences. Conclusion Lateral MAT has a high success rate for symptomatic meniscal deficiency with significant benefits irrespective of the fixation technique. There is no advantage in performing the more technically demanding BB technique over ST fixation. Level of evidence Level 2.