Different Levels Of Reliability Research Articles

Reliability-based ordinal consensus adjustment model for large scale group decision making

In large scale group decision-making (LSGDM), there are the substantial number of decision makers (DMs) with diverse knowledge, backgrounds, and interests related to the decision-making problem, and it is not possible to assure that all DMs are completely reliable. Thus, in order to enhance the quality of decision-making, it is necessary to analyze the reliabilities of DMs in LSGDM. This paper proposes the method to evaluate the reliabilities of DMs, sorts these DMs according to their degree of reliability, and investigates the consensus reaching process based on categories and an ordinal consensus measure. Considering the DMs' trust network, the uncertainty of a DM's evaluation information represented by a fuzzy preference relation (FPR), the deviation between a DM's FPR and those of the other DMs, and additive consistency of FPRs, the reliability of a DM is assessed using four criteria: PageRank centrality, professional competence, collaborative competence, and additive consistency. Following these reliability assessment criteria, ELECTRE-TRI is employed to sort DMs into three ordered categories according to DMs' different levels of reliability under the four assessment criteria. Furthermore, an improved ordinal consensus measure is designed to consider both the importance weights of positions and the deviation of Borda counts of the same alternative in two rankings. As for the consensus reaching process, due to the varied reliabilities of DMs in different categories, we propose a multiple strategies feedback mechanism for DMs in different categories. Finally, a numerical example is provided to illustrate the rationality and validity of the proposed model.

Designing an optimal multi-energy system with fast charging and hydrogen refueling station under uncertainties

As the demand for battery-powered and hydrogen-based electric vehicles continues to rise, the need for integrated charging and refueling systems with energy systems becomes more critical. Therefore, it is crucial to consider the stations serving diverse vehicle users during the system design process. This paper presents an optimal sizing strategy for a multi-energy system that covers clean energy sources and two energy storage technologies under the presence of a fast-charging station and a hydrogen refueling station for various types of car users. For the considered system, the optimal sizing problem aims to minimize the loss of power supply probability (LPSP) and annualized total life cycle cost (TLCC) through a two-stage stochastic programming-based multi-objective optimization approach. Using a scenario-based approach, the study considers the uncertainties associated with renewables, homeowner’s vehicle demands, and energy demands from homes and stations. Different cases are produced to evaluate the impacts of the different stations with the availability of various electric vehicle profiles under different levels of reliability. The TLCC decreases if LPSP increases in each case. Also, the cost of installing a fast charging station is significantly lower than that of a hydrogen refueling station for all LPSP limits. Moreover, the overall cost of the system design is at its lowest when homeowners’ vehicles provide vehicle-to-grid services. It is worth noting that when the station loads which come from the customers’ vehicle increase by 10%, the TLCC increases by 1.19%. Additionally, the revenue from hydrogen refueling station is approximately 70% less than the fast charging station.

Power Envelope Analyses of Chiplet Module and System-on-Chip

A novel power management method was developed to predict the reliability of silicon, and the method is applicable to both multichip and System-on-Chip packages. The System-on-Chip here refers to a single die which has many functional blocks and each functional block can be treated as an individual die. With power envelope analysis, the risk values of die powers are determined. An effective risk value considerig all the powers of dies may be defined to determine the overall impact. As circuit design engineers select and define the power magnitudes of dies, the distances to the threshold planes on the power envelope plots are calculated to determine the thermal reliability. The method also allows reliability engineers to define a weight scale value to reflect the ruling of each die, and this is very impportant for practical design and assembly because different dies may have different levels of reliability concerns. An advanced histogram method was used to compare the impact of power magnitudes of dies on the thermal reliability. We have implemented the approach to study the thermal reliability of a chiplet module and a System-on-Chip. In conclusion, this paper implements a power envelope analysis to help determine the allowed and optimized powers of the dies on a chiplet module or the powers of the functional blocks on an SoC package.

Evaluation of fatigue life of fiberglass reinforced polyester composite materials using Weibull analysis methods

A composite material based on a polyester resin and fiberglass reinforcement was fabricated by the contact molding process with a fiber percentage of 40%. This material underwent a cyclic fatigue loading and 3-point bending at slow speed. The experimental results were used to plot the S–N curve based on a linear function, Hwang & Han’s relation and Basquin’s hypothesis. A probabilistic analysis based on the Weibull distribution with two and three parameters was used in order to adjust and predict the fatigue behavior of the material used in the study. This analysis made it possible to plot the fatigue curve for different levels of reliability (Ps = 99%, Ps = 90%, Ps = 50%, Ps = 36.8% and Ps = 10%), in order to identify first time to failure for material reliability and safety limits.

FAILURE MODEL OF NON-RESTORABLE COMPLEX TECHNICAL OBJECT OF MILITARY EQUIPMENT

Maintenance (MT) is a necessary component the process of operating a complex technical object of military equipment, intended for long-term operation in wartime and harsh operating conditions. The volume, content and timing of maintenance must be completely determined by the reliability properties of the object, conditions and modes of its use. Effective implementation of any maintenance operation is possible only if the design of the object provides special means for this purpose (for measuring the defining parameters) and ensures the accessibility and convenience of performing the operation. Complex technical objects in modern society are extremely important. Such objects belong to the class of restored objects long-term repeated use. They are usually expensive and require significant operating costs. To ensure the required level of failure-free operation during their operation, maintenance is usually carried out, the essence of which is the timely preventive replacement of elements that are in a pre-failure state, which is very important for military equipment. A characteristic feature of complex technical objects for special purposes (military equipment) is the presence in their composition of a large number (tens, hundreds of thousands) different types of components that have different levels of reliability, different patterns of their wear and aging processes. This feature requires a more subtle approach to organizing and planning maintenance during operation (of military equipment). The above statements fully justify the conclusion about need to determine the main characteristics of the maintenance system in early stages of its design, when it is still possible to make changes to design of the object. In this work, a model of failure-free operation non-repairable complex technical object of military equipment is developed. The work also confirms the general idea that data obtained fully confirm the assumption that a maintenance strategy that is not restored is more preferable in the case of unreliable (inaccurate) information about the reliability indicators of elements of a military equipment object.

Energy storage system based on hybrid wind and photovoltaic technologies

Clean energy sources like wind and solar have a huge potential to lessen reliance on fossil fuels. Due to the stochastic nature of various energy sources, dependable hybrid systems have recently been developed. This paper's major goal is to use the existing wind and solar resources to provide electricity. A 6 kWp solar-wind hybrid system installed on the roof of an educational building is studied and optimized using HOMER (Hybrid Optimization of Multiple Energy Resources) software at different levels of reliability. At an average annual Cost of Energy (COE) of $1.156 per kWh, the system generates 1996 kWh of power overall. Investigations are made on the techno-economic characteristics of real and ideal hybrid system topologies with maximum capacity shortfalls of 0 %, 5 %, 10 %, and 20 %. The hybrid system's sensitivity analysis looks at how a capacity gap affects overall net present costs and excess power generation. A 2 kWp PV system with one string of ten 12V batteries is shown to be more cost-effective than the existing system with a COE of $0.575/kWh. The most effective configuration for utilizing the site's solar and wind resources is demonstrated to be a 5 kWp wind turbine, a 2 kWp PV system, and battery storage. A wind-solar hybrid system is more expensive than the current system. Despite this, an additional 1 kWp solar PV system may be added to the current system due to the reduction in the limit deficit from 22.3 % to 3.1 %. The findings show that solar-wind hybrid energy systems may efficiently use renewable energy sources for dispersed applications. Additionally, new research directions are noted.

Analyzing the changing landscape of the Covid-19 vaccine debate on Twitter

The issue of vaccine hesitancy has posed a significant challenge during the Covid-19 pandemic, as it increases the risk of undermining public health interventions aimed at mitigating the spread of the virus. While the swift development of vaccines represents a remarkable scientific achievement, it has also contributed to skepticism and apprehension among some populations. Against this backdrop, the suspension of the AstraZeneca vaccine by the European Medicines Agency further exacerbated an already contentious debate around vaccine safety. This paper examines the Twitter discourse surrounding Covid-19 vaccines, focusing on the temporal and geographical dimensions of the discussion. Using over a year’s worth of data, we study the public debate in five countries (Germany, France, UK, Italy, and the USA), revealing differences in the interaction structure and in the production volume of questionable and reliable sources. Topic modeling highlights variations in the perspectives of reliable and questionable sources, but some similarities across nations. Also, we quantify the effect of vaccine announcement and suspension, finding that only the former had a significant impact in all countries. Finally, we analyze the evolution of the communities in the interaction network, revealing a relatively stable scenario with a few considerable shifts between communities with different levels of reliability. Our results suggest that major external events can be associated with changes in the online debate in terms of content production and interaction patterns. However, despite the AZ suspension, we do not observe any noticeable changes in the production and consumption of misinformation related to Covid-19 vaccines.

Experimental Study of the Sleeve Material Mechanical Properties during the Sample Tensile Test

Composite materials are widely used in various industries. Both ordinary household items and specialized equipment used, in particular, in emergency and rescue formations, are made from them. Each equipment has a different level of reliability. One of the types of such equipment with the lowest level of reliability is fire hoses. Fire hoses work under different internal working pressures, and depending on this indicator, during their manufacture, such materials are chosen that are able to withstand it. High-pressure fire hoses are a separate type of fire hoses. In order to ensure the necessary strength of the material, it includes an internal reinforcing layer, which is a weaving of textile threads or metal wire. The composite structure of the material greatly complicates the process of checking the technical condition of high-pressure fire hoses, which may have hidden defects. These defects can cause their destruction during operation and lead to non-fulfillment of the tasks assigned by units of emergency and rescue formations. Therefore, the study of changes in the properties of the composite material from which high-pressure fire hoses are made due to the influence of various factors on it is relevant.

Repeated impact resistance of steel fibre-reinforced dry UHPC: Effects of fibre length, mixing method, fly ash content and crumb rubber

Dry concrete exhibits significantly different mechanical properties and failure patterns under dynamic loads from those under static conditions. Considering the practical applications of dry concrete, the flexural impact load renders its units/structures susceptible to unpredictable damage or even failure. In this study, the modified low-velocity drop-weight impact test was conducted on steel fibre-reinforced dry UHPC (FR-DUHPC) beam samples to simulate the frequent and multiple impact loads. The effects of steel fibre length, mixing method, fly ash content and crumb rubber addition on the impact resistance of FR-DUHPC were evaluated based on dynamic responses. Weibull distribution was then conducted to analyse the failure hit number of concrete samples in consideration of the large value variation. Test results indicated that the flexural impact performance was markedly improved with longer steel fibres, but deteriorated with increased fly ash content (especially at early ages) and considerably degraded with the inclusion of rubber aggregate. Hybrid medium/long fibre reinforcement was proposed for DUHPC that were mainly subjected to impact loads during service, while the fly ash content utilized to partially replace cement was not recommended to exceed 40%. Rubber aggregate was not proposed to be added to dry concrete mixtures since the impact load would greatly accentuate the initial matrix defects caused by the weak bonding. Additionally, the two-parameter Weibull distribution was verified to be a desirable statistical method for analysing the failure blow number of FR-DUHPC under repeated low-speed drop-weight impacts. The impact energy for the practical structural design could be preliminarily computed utilizing the derived Weibull parameters at different levels of reliability.

OPTIMIZATION METHOD FOR THE STRATEGY OF REGULATED MAINTENANCE OF MILITARY EQUIPMENT

Complex technical objects in modern society are extremely important. Such objects belong to the class of recoverable objects of long-term multiple used. They tend to be expensive and require significant maintenance costs. To ensure the required level of reliability during their operation, maintenance is usually carried out, the essence of which is the timely preventive replacement of elements that are in a pre-failure state, which is very important for military equipment. A characteristic feature of complex technical objects for special purposes (military equipment) is the presence in their composition of a large number (tens, hundreds of thousands) of different types components that have different levels of reliability, different patterns of their wear and aging processes. This feature requires a more subtle approach to the organization and planning of maintenance during operation (military equipment). The problem is that when developing such objects of military equipment, all issues related to maintainability and maintenance should be addressed already at the early stages of designing an object. If you do not provide in advance the necessary hardware and software for the built-in monitoring of the technical condition (TC) of the object, do not develop and “embed” the maintenance technology into the object, then it will not be possible to realize in the future a possible gain in the reliability of the object due to the maintenance. Since all these issues must be resolved at the stage of creating an object (when the object does not yet exist), mathematical models of the maintenance process are needed, with the help of which it would be possible to calculate the possible gain in the level of reliability the object due to maintenance, to estimate the cost costs required for this. Then, based on such calculations, make a decision on the need for maintenance for this type of objects and, if such a decision is made, develop the structure of the maintenance system, choose the most appropriate maintenance strategy, and determine its optimal parameters. In this paper, we develop a methodology for optimizing the parameters of the strategy for regulated maintenance of military equipment. The paper also confirms the general idea that the data obtained fully confirm assumption that the “adaptive maintenance” strategy is more preferable in the case of unreliable (inaccurate) information about the reliability indicators of the object’s elements.

Resistance factors for design of slopes in a homogenous soil layer

Traditionally, the factor of safety (FOS) is widely used to account for uncertainties in the design of slopes within the framework of working stress design. As the uncertainties involved in the design of slopes vary, the same FOS may correspond to the different levels of reliability. In this study, the advanced first order reliability method is used to determine the resistance factors for design of slopes in a homogenous soil layer. It is found that the resistance factors depend on the target reliability index, the height of the slope, and the variability of the soil strength parameters. It is difficult to suggest a unique set of resistance factors for design of slopes. Analytic solutions are developed to determine the resistance factors for design of slopes assuming the random variables are normally distributed. An approximate method based on the concept of equivalent target reliability index is also suggested to determine the resistance factors for design of the slope when the soil strength parameters are lognormally distributed. The method suggested in this paper provides a practical way to perform load and resistance factors design of slopes.

Aristotle on the Truth and Falsity of Three Sorts of Perception

AbstractAristotle's theory of perception is complicated by the fact that he recognizes three kinds of perceptible object: special, common, and incidental, all of which have different levels of reliability. Focusing on De Anima 3.3, 428b17–25, this paper discusses why these three sorts of perception are true and false. It argues that perceptions of special objects can be false because of the blind-spot phenomenon and that common objects are typically perceived as predicated of an incidental object. This helps explain why perceptions of common objects are the most error prone. The paper ends with a suggestion about the importance of predicational perception for Aristotle's epistemology.

Reliability modelling of wheel wear deterioration using conditional bivariate gamma processes and Bayesian hierarchical models

Wear of wheel profiles is a common degradation process that significantly impacts the reliability of wheelsets. In this study, a conditional bivariate Gamma process is constructed to characterize wheel wear, and hierarchical Bayesian models are employed to identify the differences in wear between each vehicle within a train. Before computation, the field data are modified by isotonic regression and monotone cubic Hermite interpolants. Due to the failure modes involving flange thickness and wheel diameter difference, the distributions of first-passage times are calculated using an analytical approach and kernel density estimation, respectively. The proposed model is validated with a real-world case study of a train consisting of eight vehicles. The results indicate that the laws of wear vary throughout the train, besides left and right wheels. Based on the results, conclusions can be drawn that the first and last vehicles in a train have higher mean wear rates than others, and that different vehicles have different levels of reliability during different stages; the early failure rates are close to zero, but they rapidly increase in the late stage.

Integrating Reliability in Conceptual Design Trade‐Off Analysis: A look at the Literature

AbstractThis research focuses on developing models to estimate the system reliability of Unmanned Ground Vehicles using knowledge and data from similar systems. Reliability is often a stand‐alone requirement and not always fully included in performance and life cycle cost models. Traditional reliability approaches require detailed knowledge of a system and are used in later design sta ges as well as development, operational test and evaluation, and operations. The critical role of reliability and its impact on acquisition program performance, cost, and schedule motivates the need for improved system reliability models in the early design stages. This research seeks to integrate reliability, performance, and cost models in a trade‐off analysis framework in the early acquisition stages. This research uses functional analysis methods to estimate reliability Pre‐Milestone A and assess the impact of reliability on performance and cost models of early system concepts. This research us es technology readiness level (TRL), which is indexed, to assess different levels of reliability for design. An integrated cost and performance model will inform decision ‐makers on the impact of reliability before choosing a system concept for further development.

Size optimization of a stand‐alone hybrid photovoltaic/wind/battery renewable energy system using a heuristic optimization algorithm

Today, it has become imperative to design these systems at optimum size to make reliable and minimize the total costs of renewable energy systems. There are many studies about size optimization in the literature. However, few studies have approached the problem with a heuristic method at different levels of reliability and compared the results with commercial software. This paper aims to fill this gap by proposing an artificial bee colony (ABC) algorithm with different reliability ratios for renewable energy systems size optimization and comparing the results of the proposed method with the results of the HOMER Pro software. The current methodology is validated with a real case study on the load demand of a school building (latitude 41.37, longitude 27.3) in Turkey. The peak and average load per day for the school building are 7.4 kW and 51.8 kW, respectively. The proposed method has presented 14.71%, 14.36%, and 6.23%, respectively, more economical solutions than HOMER Pro software for hybrid photovoltaic (PV)/wind/battery, PV/battery, and wind/battery renewable energy system scenarios. In addition, the ABC algorithms with different reliability ratios (%0, %0.2, %1, and %3) are used to analyze the effect on the system cost of the loss of power supply probability. According to the results, the hybrid renewable energy system consisting of 230 PV panels, 6 wind turbines, and 34 batteries is the most economical option with a total annual cost of $42 717.58 compared to stand-alone systems with a reliability %0 ratio. It has been seen that increasing the loss of power supply probability reduces system costs. Consequently, this study shows that using the ABC algorithm in size optimization of renewable energy systems yields accelerates the decision-making process and more optimized solutions.

On the Reliability and Treatment Utility of the Practical Functional Assessment Process.

Saini et al. (2019) urged caution with respect to the use of practical functional assessment (PFA) procedures to inform behavioral treatment when they found that responses to an open-ended caregiver interview were only somewhat reliable and showed moderate to weak correspondence with analog functional analyses. Because the practitioner's goal in conducting any functional assessment process is to inform the successful treatment of problem behavior, we replicated and extended Saini et al. by (a) evaluating the reliability of hypotheses gleaned from two independent PFA processes for each of four children, (b) conducting treatment informed by a randomly assigned PFA, and (c) determining the extent to which potentially different levels of reliability impacted the treatment utility of the PFA process. Results indicated that the reliability of the PFA process varied depending on the stringency with which it was evaluated. However, treatments developed from randomly determined PFA processes produced efficacious outcomes on problem behavior and targeted social skills that transferred to the context designed from the other PFA process in all evaluations, suggesting that the PFA has strong treatment utility despite parts of the process having ambiguous levels of reliability. We discuss implications for practitioners tasked with treating severe problem behavior.

A Closer Look at Warning Cues on the Sustained Attention to Response Task Performance.

We investigated the effects of auditory cues of varying reliability levels on response inhibition performance using a target detection task to determine if external cues offer performance benefits. Further, we examined how the slope of the speed accuracy trade-off changes as a function of auditory cue reliability and used the trade-off to understand where any performance gains may be realized. Researchers have proposed that the sustained attention to response task (SART) can be used to study the mechanisms causing failures of response inhibition. External cues may mitigate the results of motor inhibition failure. The extent to which external cues can effectively aid performance depends on the level of cue reliability. Ninety-one participants performed three SARTs with auditory cue assistance at three different levels of reliability (i.e. 0%, 60% and 100% reliable at cueing imminent No-Go stimuli). We observed fewer errors of commission and faster reaction time in conditions with higher cue reliability. The slope of speed-accuracy trade-off relationship was impacted by cue reliability and was not a simple linear function. Reliable auditory cues aid performance by reducing reaction time and errors of commission. Auditory cues also impact the relationship between speed and accuracy trade-off. Insights of cue effectiveness at different reliability levels help people make informed decisions in developing automation interfaces or sensors based on expected performance. Reliable cues mitigate the risk of impulsive errors; however, the reliability has to be high to have a noticeable impact on the speed-accuracy trade-off.

Production indicator models for fodder maize (Zea mays L.) in the Comarca Lagunera II

Forage corn is a crop in greatest demand in the Comarca Lagunera. The objective is to obtain the models for the production indicators of forage maize hybrids, which could improve the production systems. The variables evaluated were: leaf area index (IAF), number of leaves and dry matter (DM). The DM model as a function of the IAF was 17.13 grams plant per unit of IAF. For the days after sowing (DDS) a production of 5 grams plant / elapsed day was found. For IAF based on DDS, 0.36 units of IAF were obtained per day and the IAF increased by 0.65 units as a function of the number of leaves. It is concluded that the behavior of the evaluated variables provides results of linear and polynomial regression models, with different levels of reliability, which allow future estimates to be made to choose the hybrids that best adapt to the region.

Age-based preventive maintenance with multiple printing options

In today's economic context, production systems must be readily available and machinery downtime kept to a minimum. Maintenance and spare parts inventory management play a vital role in achieving these goals, and preventive maintenance has increasingly been considered in maintenance policies. Additive manufacturing (AM) has recently been combined with preventive maintenance, and thus represents an emerging research direction. However, few studies have as yet been conducted in this research stream, and we intend to fill this gap. Our study makes three main contributions. First, we address the main limitations of two current models (i.e., assuming that no failure occurs during the replenishment lead time of the spare parts). Second, we propose a new maintenance policy that considers two printing options with different levels of reliability and unitary purchase costs. Third, we develop a decision support system (DSS) to assist managers in deciding whether to implement a preventive maintenance policy that includes AM or conventional manufacturing (CM) parts. We take an interdisciplinary approach to conducting a parametrical analysis where we consider real data on the reliability of CM and AM parts, in addition to the impact of post-processing operations and optimization routines. We find that AM-based preventive maintenance policies are favored when the MTTF and the backorder costs are low and when the failure and maintenance costs are high. These findings have been incorporated into the DSS, which provides thresholds for every parameter to guide practitioners in choosing between AM and CM parts for preventive maintenance, without requiring time-expensive calculations.

Synthesizing Data to Classify and Risk Assess Vegetation Types for Regulations in Inland New South Wales Australia

From 1998, land-use regulations in New South Wales Australia referred to risk status of plant community types and abiotic landscapes. Lacking was a uniform vegetation classification for 77% of NSW comprising the inland arid, semi-arid and cropping agricultural zones: regions that contain patchy floristic plot data. In response, 562 plant communities, mainly at levels 8 in the IVC, were classified by synthesizing plot-based analyses, qualitative descriptions, maps, extensive field checks, new field samples and peer review. Qualitative information was vital to complete a thorough classification. Each type was assigned a risk category based on six risk assessment criteria developed prior to IUCN RLE. Occurrences in protected areas were audited and related to original extent yielding a protected area/adequacy code. Results were used in land change assessment tools and contributed to the listing of 40 threatened ecological communities under biodiversity laws. Two mapping methods attained different levels of reliability. Applying risk criteria to coarse versus fine levels in typologies can produce different results. Mid-to fine level global hierarchies best suit ecosystem risk assessment.