Reliability Implications Research Articles

Post‐Mortem Analysis of Building‐Integrated Flexible Thin Film Modules

ABSTRACTFlexible, lightweight thin film (TF) photovoltaic (PV) modules offer a unique opportunity for integration into non‐planar surfaces unable to support heavy weights. While such applications increase the potential for PV in urban areas, the reliability implications are yet to be investigated. Here, prototypes of corrugated rooftiles with integrated Cu (In,Ga)Se2 (CIGS) modules were investigated after 3 years of outdoor operation. Their performance before and after the outdoor exposure was compared and defects were localized. An unpackaging method was developed, allowing access to the solar cells for more detailed characterization of present defects without causing additional damage or changes to existing defects. To our knowledge, this was the first time such an unpackaging method was successfully applied to flexible TF PV modules. The relative efficiency loss ranged from 17% to 43%, mostly due to short‐circuit current (ISC) loss and series resistance (RS) increase. The predominant cause of the RS increase was the delamination at the interconnects, ascribed to thermomechanical stresses caused by outdoor temperature fluctuations. The ISC loss was mainly caused by localized delamination of CIGS from the molybdenum (Mo) back‐contact. The occurrence of such delaminated areas pointed to presence of high local stresses during outdoor operation, possibly due to thermal fluctuations, applied deformation and/or mechanical impact. Two other types of delamination defects were found with no observable impact on performance. These results show the necessity for further optimization in the material choice and processing of TF flexible modules, to avoid mechanical stress related failures upon integration into curved surfaces.

Insights into oxygen vacancy dynamics in HfO2–ZrO2 superlattice ferroelectric films: Implications for device reliability

Compared with solid solution (SS) Hf0.5Zr0.5O2, HfO2–ZrO2 superlattice (SL) ferroelectric films exhibit enhanced endurance and reduced leakage. However, so far, the underlying physical mechanism is still missing. In this work, first-principle calculations reveal that the superior reliability arises from the precise control in the spatial profile of oxygen vacancy with the stacked structure in SL in which oxygen vacancies (Vo) exhibit different formation energies and different energy profiles in Zr- and Hf-layers. However, Vo have the tendency to migrate and its suppression become critical to maintain the superiority of SL. A low annealing temperature is, therefore, suggested and validated with our fabricated SL- and SS-ferroelectric films with different annealing temperatures. This understanding can pave ways for the optimization in SL ferroelectric films.

The influence of pin inclination on frictional behaviour in pin-on-disc sliding and its implications for test reliability

The pin-on-disc test is a widely employed method for investigating the friction and wear performance of materials in conformal contact. In a typical pin-on-disc system, self-aligning pin holders are frequently utilized to ensure proper surface contact. This study reveals that in such a setup, pin inclination has a significant impact on test reliability, particularly under oil-lubricated conditions, which may overweight the influence of other parameters such as roughness or texture elements. Utilizing in-situ measurements, we captured the dynamic changes in pin inclination during rotational sliding. Our findings indicate that the pin inclination varies with sliding speed, showing a pitch angle difference of approximately 0.01°as the speed decreases from 2 m/s to 0.04 m/s in our test setup. Importantly, a robust correlation was identified between the friction coefficient and pin inclination, which is supported by the numerical investigation. This study underscores concerns regarding the test reliability of pin-on-disc tribometers, prompting a reconsideration of the assumptions associated with self-aligning pin holders in such experimental configurations.

Offline Payments: Implications for Reliability and Resiliency in Digital Payment Systems

With the proliferation of digital payments, internet-based technology has been integral in supporting the delivery of these transactions. Traditional digital payments, such as those made with credit cards, debit cards, and mobile wallets, often require an internet connection to settle transactions. Processors must communicate between banks to carry out a payment, relying on internet connectivity to do so.

Enhanced Thermal Study in Hybrid Nanofluid Flow through a Channel Motivated by Water/Cu+Al2o3 and Entropy Generation

This study examines the analysis of entropy generation in the magnetohydrodynamic oscillatory convective flow of hybrid nanofluid through a porous horizontal channel with velocity slip. The analysis incorporates suction at the cold wall and injection at the hot wall. Variable viscosity, thermal radiation, and viscous dissipation are also considered. Utilizing similarity transformations, the governing nonlinear partial differential equations are converted into ordinary differential equations, and exact solutions are obtained using Mathematica. Graphs are used to illustrate the impact that a variety of physical factors have on velocity, temperature, entropy generation, the Bejan number, skin friction, and the Nusselt number. The graphic results demonstrate that the fluid velocity is positively correlated with the cold wall slip parameter and negatively correlated with the hot wall slip parameter. There is an opposite relationship between fluid temperature and thermal radiation and an ascending relationship between fluid temperature and the Brinkman number. Findings from this study have important implications for better thermal management, device performance, and reliability as well as for optimizing microelectronic cooling systems.

Analyzing Aging Effects on SRAM PUFs: Implications for Security and Reliability

The aging effects on Static Random-Access Memory Physical Unclonable Functions (SRAM PUFs) pose significant security and reliability challenges for current hardware systems. SRAM PUFs utilize process variations in integrated circuits for secure key generation and device authentication. However, aging effects such as bias temperature instability (BTI) and hot carrier injection (HCI) may change SRAM cell characteristics and affect PUF responses. This study addresses various aging-induced variation challenges, identifies security vulnerabilities, and provides innovative approaches to risk reduction. Furthermore, this study focuses on concerns about SRAM PUF reliability. In this regard, mitigation approaches like adaptive reconfiguration, error correction codes, and multi-modal PUFs are introduced to enhance the resilience of SRAM PUFs. This study concludes by outlining future research directions and prospects for improving SRAM PUF-based security solutions by several orders of magnitude. This is carried out with various complexities related to semiconductor device aging.

Leveraging Stacking Framework for Fake Review Detection in the Hospitality Sector

Driven by motives of profit and competition, fake reviews are increasingly used to manipulate product ratings. This trend has caught the attention of academic researchers and international regulatory bodies. Current methods for spotting fake reviews suffer from scalability and interpretability issues. This study focuses on identifying suspected fake reviews in the hospitality sector using a review aggregator platform. By combining features and leveraging various classifiers through a stacking architecture, we improve training outcomes. User-centric traits emerge as crucial in spotting fake reviews. Incorporating SHAP (Shapley Additive Explanations) enhances model interpretability. Our model consistently outperforms existing methods across diverse dataset sizes, proving its adaptable, explainable, and scalable nature. These findings hold implications for review platforms, decision-makers, and users, promoting transparency and reliability in reviews and decisions.

Reliability Assessment for a Stochastic Air Transport Network with Multiple Demands

Air transport networks play a significant role in the modern tourism industry, and their operational performance and stability can be measured by reliability analysis. This study, from the perspective of a travel agency, attempts to assess the reliability of a stochastic air transport network (SATN) by considering multiple passenger demands generated by both the starting airport and several connection airports. The SATN is modeled as a stochastic flow network comprised of several nodes and arcs where nodes represent airports, and arcs represent flights connecting two airports. Each flight is associated with a predetermined stochastic capacity following a specific probability distribution, departure time, arrival time, and discount fare. Accordingly, network reliability refers to the probability that the network can successfully transport passengers from their respective source airports to the destination airport within the given travel time and travel cost limit. An algorithm in terms of the concept of lower boundary point is developed to compute network reliability. Furthermore, a simple example and a case study are presented to demonstrate the proposed reliability method and the managerial implications of reliability for travel agencies.

Economic Consequences Based on Reversible and Irreversible Degradation of PV Park in the Harsh Climate Conditions of Iraq

Photovoltaic (PV) system reliability and durability investigations are essential for industrial maturity and economic success. Recently, PV systems received much interest in Iraq due to many reasons—for instance, power shortage, global warming and pollution. Despite this interest, the precise economic implications of PV system reliability in harsh climates like Iraq remain uncertain. This work assesses the economic implications of PV system component reliability and soiling in Iraq using field experience and historical data. This study identifies the most common failure modes of PV systems installed in Iraq and similar climatic regions, and also ranks their severity. Simulations explore scenarios of PV module degradation rates, inverter lifetimes, soiling rates, and cleaning intervals, revealing that soiling has the most detrimental effect, with cleaning frequency leading to Levelized Cost of Electricity (LCOE) losses of over 30%, depending on the location. Inverter lifetime contributes to LCOE losses between 4 and 6%, depending on the PV system’s location. This study also evaluates the impact of tilt angle as a mitigation strategy for reducing soiling loss and its economic implications, finding that installing PV modules at higher tilt angles could reduce the economic impact of soiling by approximately 4.4%. Additionally, the optimal cleaning strategy identified is fully automated dry cleaning with robots, outperforming other strategies economically. Overall, the findings highlight that the LCOE in Iraq is relatively high compared to the global weighted average for utility-scale PV systems, primarily due to high soiling and degradation rates. The LCOE varies within the country, influenced by different degradation rates. This study aims to assist PV stakeholders in Iraq and the Middle East and North Africa (MENA) region in accurately estimating solar bankability; moreover, increasing reliability by minimizing the technical and financial risks by considering key parameters specific to these regions.

Minimizing the impact of electric vehicle charging station with distributed generation and distribution static synchronous compensator using PSR index and spotted hyena optimizer algorithm on the radial distribution system

This research investigates the impact of electric vehicle charging station on power loss, voltage stability, and reliability within radial distribution systems. With the escalating use of electric vehicles, understanding these effects is crucial for ensuring the stability and efficiency of radial distribution systems infrastructure. The study formulates the electric vehicle charging station allocation problem as a multi-objective function, integrating power loss, voltage stability, and reliability metrics expressed as the PSR index. Using the IEEE 69-bus system as a test system, the research explores the ramifications of electric vehicle charging station integration and proposes strategies to mitigate their effects. An innovative combination of distributed generation and distribution static compensator are employed to alleviate the impact of electric vehicle charging station on radial distribution systems. A recent optimization methodology called spotted hyena optimizer algorithm is introduced to determine optimal electric vehicle charging station locations, with results compared to other existing algorithms. The study assesses potential power losses induced by additional electric vehicle loads, explores strategies to optimize charging rates for minimizing resistive losses, and evaluates voltage stability and reliability implications. The important results include objective function values obtained using various algorithms: Spotted hyena optimizer algorithm (0.7683), cuckoo search algorithm (0.7709), bat algorithm (0.8035), and African vultures optimization algorithm (0.7856). The findings demonstrate that the proposed algorithm outperforms other algorithms in minimizing the objective function value, indicating its efficacy in optimizing electric vehicle charging station placement within radial distribution systems. In conclusion, this research contributes valuable insights into the challenges associated with integrating electric vehicle charging station into radial distribution systems and provides innovative solutions for optimizing electric vehicle charging station placement, thereby advancing the understanding and management of distribution systems in the context of electric vehicle adoption.

Bifurcation and chaos analysis of a fractional-order delay financial risk system using dynamic system approach and persistent homology

A comprehensive theoretical and numerical analysis of the dynamical features of a fractional-order delay financial risk system(FDRS) is presented in this paper. Applying the linearization method and Laplace transform, the critical value of delay when Hopf bifurcation first appears near the equilibrium is firstly derived in an explicit formula. Comparison simulations clarify the reasonableness of fractional-order derivative and delay in describing the financial risk management processes. Then we employ persistent homology and six topological indicators to reveal the geometric and topological structures of FDRS in delay interval. Persistence barcodes, diagrams, and landscapes are utilized for visualizing the simplicial complex’s information. The approximate values of delay when FDRS undergoes different periodic oscillations and even chaos are determined. The existence of periodic windows within the chaotic interval is correctly decided. The results of this paper contribute to capturing intricate information of underlying financial activities and detecting the critical transition of FDRS, which has promising and reliable implications for a deeper comprehension of complex behaviors in financial markets.

Tracking the spatial footprints of extreme storm surges around the coastline of the UK and Ireland

Storm surges are the most important driver of flooding in many coastal areas. Understanding the spatial extent of storm surge events has important financial and practical implications for flood risk management, reinsurance, infrastructure reliability and emergency response. In this paper, we apply a new tracking algorithm to a high-resolution surge hindcast (CODEC, 1980–2017) to characterize the spatial dependence and temporal evolution of extreme surge events along the coastline of the UK and Ireland. We quantify the severity of each spatial event based on its footprint extremity to select and rank the collection of events. Several surge footprint types are obtained based on the most impacted coastal stretch from each particular event, and these are linked to the driving storm tracks. Using the collection of the extreme surge events, we assess the spatial distribution and interannual variability of the duration, size, severity, and type. We find that the northeast coastline is most impacted by the longest and largest storm surge events, while the English Channel experiences the shortest and smallest storm surge events. The interannual variability indicates that the winter seasons of 1989-90 and 2013–14 were the most serious in terms of the number of events and their severity, based on the return period along the affected coastlines. The most extreme surge event and the highest number of events occurred in the winter season 1989–90, while the proportion of events with larger severities was higher during the winter season 2013–14. This new spatial analysis approach of surge extremes allows us to distinguish several categories of spatial footprints of events around the UK/Ireland coast and link these to distinct storm tracks. The spatial dependence structures detected can improve multivariate statistical methods which are crucial inputs to coastal flooding assessments.

The Role of Artificial Intelligence in Formal and Informal Education for Students

Abstract: Artificial Intelligence (AI) is transforming the field of online learning by providing personalized and efficient learning experiences for students. AI-powered online learning platforms can analyze data on students’ learning styles, preferences, progress, and performance, and use this information to tailor the curriculum, content, feedback, and support for each student. AI can also enhance the engagement and interaction of online learners by using chat bots, virtual assistants, and intelligent content recommendations. According to a report by eLearning Industry 1 , AI is expected to grow by 48% in the eLearning market by 2024, reaching a value of $3.68 billion. Some of the factors driving this growth are the increasing demand for personalized learning, the availability of big data and cloud computing, and the advancement of AI technologies. However, there are also some challenges and limitations that need to be addressed, such as the ethical, legal, and social implications of AI, the quality and reliability of AI systems, and the need for human oversight and intervention. Artificial Intelligence (AI) has the potential to revolutionize the way we teach and learn, making education more personalized, efficient, and effective. In this paper, we explore the role of AI in both formal and informal education for students. The fundamental goal of AI research includes the representation of knowledge, reasoning, planning, learning and processing, and the capability to use objects [2].We discuss the benefits and challenges of implementing AI in education and provide examples of how AI is being used in education today

A Review of Uncertainties in Power Systems—Modeling, Impact, and Mitigation

A comprehensive review of uncertainties in power systems, covering modeling, impact, and mitigation, is essential to understand and manage the challenges faced by the electric grid. Uncertainties in power systems can arise from various sources and can have significant implications for grid reliability, stability, and economic efficiency. Australia, susceptible to extreme weather such as wildfires and heavy rainfall, faces vulnerabilities in its power network assets. The decentralized distribution of population centers poses economic challenges in supplying power to remote areas, which is a crucial consideration for the emerging technologies emphasized in this paper. In addition, the evolution of modern power grids, facilitated by deploying the advanced metering infrastructure (AMI), has also brought new challenges to the system due to the risk of cyber-attacks via communication links. However, the existing literature lacks a comprehensive review and analysis of uncertainties in modern power systems, encompassing uncertainties related to weather events, cyber-attacks, and asset management, as well as the advantages and limitations of various mitigation approaches. To fill this void, this review covers a broad spectrum of uncertainties considering their impacts on the power system and explores conventional robust control as well as modern probabilistic and data-driven approaches for modeling and correlating the uncertainty events to the state of the grid for optimal decision making. This article also investigates the development of robust and scenario-based operations, control technologies for microgrids (MGs) and energy storage systems (ESSs), and demand-side frequency control ancillary service (D-FCAS) and reserve provision for frequency regulation to ensure a design of uncertainty-tolerance power system. This review delves into the trade-offs linked with the implementation of mitigation strategies, such as reliability, computational speed, and economic efficiency. It also explores how these strategies may influence the planning and operation of future power grids.

Tooth interior fatigue fracture in automotive differential gears

Tooth Interior Fatigue Fracture (TIFF) is an emerging gear failure mode with significant implications for gear lifetime and reliability, particularly in modern mechanical transmissions subjected to higher loads, smaller sizes, and increased Noise, Vibration, and Harshness (NVH) requirements. This paper investigates fatigue cracks initiated within the interior of pinion and/or side gear teeth in transmission differentials, representing a new area of recent failure detection. Conventional modeling has suggested that TIFF cracks originate in the case/core area of gear teeth, primarily seen in idler transmission gears. However, this study challenges this notion by presenting evidence that cracks often form closer to the middle of the tooth at various heights. These findings indicate the need for a deeper understanding of TIFF, as the existing theoretical descriptions may not fully explain the observed behaviors. By focusing on this novel area of failure, the paper highlights the importance of addressing TIFF to improve the reliability and durability of gears in modern mechanical transmissions.

Tourism metaverse from the attribution theory lens: a metaverse behavioral map and future directions

Diseño/metodología/enfoqueEste estudio se basa en una exploración exhaustiva de la brecha de investigación mediante la búsqueda de revistas de primer nivel en las bases de datos Scopus y Web of Science sobre la literatura relevante para analizar los datos relevantes con el fin de proporcionar una base para futuras investigaciones transformadoras. El estudio examina la relación entre la teoría de la atribución y el metaverso turístico y explora cómo la teoría de la atribución puede facilitar la comprensión de las evaluaciones y acciones de los turistas en el contexto metaverso.PropósitoEste estudio pone de relieve la importancia de utilizar la teoría de la atribución en la investigación turística en metaverso. El estudio aborda la falta de claridad sobre las dimensiones de la teoría de la atribución (lugar de causalidad, estabilidad y, controlabilidad) y su posible aplicación en el contexto del turismo en metaverso.ConclusionesEl estudio muestra que la teoría de la atribución tiene el potencial de mejorar de forma significativa la comprensión del metaverso turístico al esclarecer los procesos de toma de decisiones de los turistas y los factores que contribuyen a dichas decisiones. El estudio destaca la importancia de aplicar la teoría de la atribución para generar implicaciones más impactantes y fiables para la industria turística.Originalidad/valorEste estudio es transformador porque proporciona una comprensión fundacional de la aplicación de la teoría de la atribución en la investigación del metaverso turístico. El estudio es significativo porque arroja luz sobre un ámbito poco explorado cuyo marco teórico es necesario para informar y orientar la investigación sobre tecnología turística. La originalidad del estudio radica en su contribución al turismo al identificar las posibilidades de mejora en la investigación del metaverso turístico y destacar los beneficios potenciales de la utilización de la teoría de la atribución.

Chance-Constrained Optimization of Photovoltaic System Allocation considering Power Loss, Voltage Level, and Line Current

Changes are emerging that will significantly alter structure and operation of this century’s distribution networks, and photovoltaic (PV) systems will play greater role in energy sector, with implications for power system reliability. Considering uncertainties in solar irradiance and electrical loads and incorporating them into the optimization problem within an appropriate methodology is becoming increasingly important in reshaping distribution networks. In this paper, uncertainty scenarios are handled with Monte Carlo Simulation (MCS) under genetic algorithm (GA) and differential evolution- (DE-) based optimization, and probability distribution functions (pdf) of bus voltages and line current are obtained to be used in chance-constrained stochastic programming. This present study focuses on investigating impact of uncertainties in PV system operating under different irradiance scenarios on power loss with probabilistic constraints in distribution networks instead of precise deterministic limits to contribute more efficient and reliable use of energy. By combining meta-heuristic optimization and MCS technique under one framework, this paper contributes to knowledge base of how to allocate PV plants within distribution networks under chance-constrained strategy. In order to show the effectiveness of the proposed methodology, obtained optimization results are tested using MCS under set of uncertainty conditions and network constraints are evaluated for limit violation probabilities. The effectiveness of this method is investigated based on comparative results of two different optimization methods through probabilistic analysis and simulation.

Mitigation of the Impact of Incorporating Charging Stations for Electric Vehicles Using Solar-based Renewable DG on the Electrical Distribution System

Background:: The utilization of electric vehicles (EVs) is on the rise, which has led to significant challenges for the radial distribution system (RDS). This research aimed to investigate the impact of electric vehicle charging stations (EVCS) on power loss, voltage stability, and reliability within the RDS. Solar-based renewable distributed generation (SRDG) offers a range of benefits in mitigating the impact of EVCS on the distribution system. To simulate the integration of EV charging loads and assess their effects on the RDS, the study has employed the widely used IEEE 69-bus system as a test platform. Methods:: A novel approach utilizing the cuckoo search algorithm (CSA) is presented in this article to determine the optimal locations for EVCS and SRDG. Results:: The study has examined the potential power losses resulting from additional EV loads and explored strategies to optimize charging rates and minimize resistive losses. Voltage stability has been assessed by analyzing the voltage drop caused by high charging loads, and the efficiency of voltage regulation devices and control strategies has been evaluated. Moreover, the paper has discussed the reliability implications of EV charging, including localized overloads and the possibility of outages. Conclusion:: Overall, this research has enhanced our understanding of the challenges associated with integrating EVCS into the RDS and offered potential solutions to address these challenges.

Investigation of Fracture Evolution and Failure Characteristics of Rocks under High-Temperature Liquid Nitrogen Interaction

The utilization of liquid nitrogen as a sustainable and water-free fracturing medium exhibits immense promise in engineering applications. In this investigation, Brazilian split tests and acoustic emission tests were conducted to explore the impact of liquid nitrogen cooling on the internal structure and mechanical properties of rock specimens. To examine the influence of liquid nitrogen cooling on the tensile strength of rocks, displacement-load curves were obtained from samples subjected to varying cycles of high-temperature liquid nitrogen cooling using Brazilian split tests. Acoustic emission experiments were conducted to investigate the characteristics of granite samples exposed to various cycles of high-temperature liquid nitrogen cooling. Based on these findings, the impact of liquid nitrogen cooling on the internal structure of rock masses was analyzed. The findings of this study demonstrate that high-temperature liquid nitrogen thermal treatment significantly modifies the microscopic structure and mechanical properties of rocks, with potential implications for overall stability and reliability. Notably, an observable decline in tensile strength was observed as the number of cycles of high-temperature liquid nitrogen treatment increased. These findings underscore the substantial impact of liquid nitrogen cooling on the behavior of rocks. High-temperature liquid nitrogen treatment effectively promotes the generation of microcracks within rocks, thereby increasing their permeability. During the experiment, granite specimens primarily exhibited shear-type fractures when subjected to high-temperature freeze-thaw cycles induced by liquid nitrogen.

Enhancer or stabilizer? Investigating the distinct impact of primary and secondary CSR on the level and variability of firm value

Prior research in CSR concentrates on its impact on the level of firm value, without considering the risk associated with such effect (i.e., reliability). Understanding the reliability of such an impact is important as it unpacks the risky nature of CSR investment. By classifying CSR activities as competitive-advantage-seeking and legitimacy-seeking, we develop a theoretical framework that provides a holistic understanding of CSR’s impact on firm value in terms of simultaneous implications for both level and reliability. Our results suggest that high performance in primary-stakeholder-oriented CSR increases firm value, but simultaneously increases the variability of the resulting value distribution. In contrast, secondary-stakeholder-oriented CSR does not significantly increase firm value but does reduce the variability of the resulting value distribution. That is, primary-stakeholder-oriented CSR activities demonstrate a “risky investment” property and function as a risky value enhancer, while secondary-stakeholder-oriented CSR activities demonstrate a “risk reduction” property and function as a value stabilizer.