Reliability Perspective Research Articles

Reliability analysis and recovery measure of an urban water network

<abstract><p>Urban water networks are important infrastructures for cities. However, urban water networks are vulnerable to natural disasters, causing interruptions in water. A timely analysis of the reliability of urban water networks to natural disasters can reduce the impact of natural disasters. In this paper, from the perspective of network reliability, the reliability analysis method of urban water networks under disaster is proposed. First, a reliability model is established with the flow rate of nodes in the water network as the index. Second, the user's demand is considered, as well as the impact of water pressure on water use. Therefore, a node failure model considering node water pressure and flow rate is established. The performance degradation of the urban water network is analyzed by analyzing the cascading failure process of the network. Third, the recovery process of the urban water network is analyzed, and the changes in the reliability of the urban water network before and after the disaster are analyzed to assess the ability of the urban water network to resist the disaster. Finally, an urban water network consisting of 28 nodes, 42 edges and 4 reservoirs is used to verify the effectiveness of the proposed method.</p></abstract>

Photovoltaic-based Distributed Generation Allocation in Distribution Network for Energy Loss Minimization

Nowadays, there is a global consensus that integrating renewable energy sources (RESs) is highly needed to meet the increasing electricity demand and reduce the overall carbon footprint of energy production. However, large-scale integration of RES-based distributed generation (DG) units often poses several technical challenges in the system from stability, reliability, and power quality perspectives. However, these problems are usually mitigated by the optimal integration of DG units in the distribution networks (DNs). In this regard, the optimal sizing and placement of the DGs are crucial. Otherwise, network performance will deteriorate. This paper proposes to apply a novel population-based technique called the dung beetle optimization (DBO) algorithm for the optimal allocation of Photovoltaic (PV) based DG units to minimize total active energy loss subject to equality and inequality constraints in the DN. A DBO is inspired by the behaviours of dung beetles, including ball-rolling, dancing, foraging, stealing, and reproducing. A standard 33-bus system has been used to demonstrate the proposed method's effectiveness. The simulation results and comparison with other techniques demonstrate our proposed approach's significant energy loss reduction and a suitable voltage profile.

Editorial Special Issue on Application of Advanced Intelligent Methods in Vehicle to Smart Grid Communications: Security, Reliability, and Resiliency

This Special Issue was organized on the application of advanced intelligent methods in vehicle-to-smart grid communications considering the security, reliability, and resiliency perspectives. We tried to bring together the ideas from researchers and experts on both transportation and smart grid areas to tackle the technological challenges in future power systems with more electric vehicles and intelligent systems. Theoretically, vehicles consist of different electrical and electronic hardware devices, which are connected with each other through the so-called ECUs being controlled by different software tools. As a well-perceived technology, all sensing instruments located at different points in an electric vehicle will direct their data to the ECU, wherein these data are analyzed and processed, and the demanding orders are sent to the pertinent actuators. With the advance of automobile technology, the electric vehicles are not only an electric load consumer anymore, but are appearing at different parts of human life, ranging from the smart homes and smart buildings to smart grid and smart cities. Owing to the complex and interconnected cyber-physical nature of electric vehicles, they can are getting a more appealing and accessible target for cyber hackers to penetrate the entire system through car hacking. This can result in long-term effects on the security and privacy of the electric vehicle owners, smart buildings, smart grids, and smart cities of the future. Be on that, this Special Issue scope includes methods, tools, applications, and solutions for analyzing, processing, and improving the electric vehicles as a complex cyber-physical system considering its direct or indirect effects on the modern human life factors. Among the high number of submissions received, 13 articles were finally chosen to be published in this Special Issue. The core ideas and concepts of the works are summarized in the rest.

Modalities of Fictionality in the Arabic Tradition: Kalīla wa-Dimna’s Readers from the Third/Ninth to the Sixth/Twelfth Century

Abstract This study interrogates the concept of fictionality in the premodern Arabic tradition through probing into different readings of Ibn al-Muqaffaʿ’s Book of Kalīla and Dimna. Instead of presupposing the applicability of the modern concept of fictionality, I suggest to use the concept as a hermeneutic category that can encompass different perspectives on what exactly is fictional in a text. After identifying the challenges of defining fictionality in the pre-modern Arabic textual tradition, I shall look into some of the readers of Ibn al-Muqaffaʿ’s translation between the third/ninth and sixth/twelfth centuries to unpack different modalities. Some readers such as Ibn Qutayba in his ʿUyūn al-akhbār (Essential Accounts) and Ibn ʿAbd Rabbih in his al-ʿIqd al-farīd (The Unique Necklace) foreground the ethical function of parables and gnomic sayings and ignore the fact that most of Kalīla wa-Dimna’s stories contain animal characters. Others such as al-Yamanī in his Muḍāhāt amthāl kitāb Kalīla wa-Dimna (The Analogues of Kalīla wa-Dimna’s Parables) and al-Bīrūnī in his Geography of India tackle the ontology of fictionality from the perspective of reliability versus unreliability associated to Ibn al-Muqaffaʿ’s claim over the authenticity of his transmission of “the Indian book.” Finally, focusing on Ibn Sīnā’s and Ibn Rushd’s Commentaries to Aristotle’s Poetics, I show how Kalīla wa-Dimna as a prime example of parables (amthāl) and invented stories belongs to rhetorical discourse and has to be distinguished from poetic discourse which generates images (takhyīl). By opposing the two types of discourse — poetry and stories from Kalīla wa-Dimna — in terms of both their ontological status and their functionality, they portray, I argue, a different taxonomy of fictionality. Although all these various readers might agree that Kalīla wa-Dimna contains fictive content, the different interpretations defy a classification of Kalīla wa-Dimna within the modern dichotomy of fictional versus factual narrative but allow us to uncover different ontological and pragmatic modalities of fictionality in the premodern past.

Transit-Oriented Development in Saudi Arabia: Riyadh as a Case Study

Transit-oriented development (TOD) in Saudi Arabia is becoming a significant priority for the government and developers to create a sustainable and quality living environment. TOD is an integrated transport and urban planning method that aims to reduce car use and urban sprawl, increase the use of public transport, and enhance sustainable mobility. To meet the global goals as per the Paris Accord, Saudi Arabia’s policymakers must prioritize the integration of TOD in urban planning. This study was carried out with the main aim of identifying the environmental, social, and economic benefits of implementing TOD in Riyadh, Saudi Arabia. A mixed-study research method was used, and data were collected using a questionnaire survey and semi-structured interviews. The quantitative data were analyzed using SPSS version 21, and qualitative data were analyzed using NVivo software. The findings of this study show that TOD in Riyadh City would positively impact economic, environmental, and social aspects. TOD would reduce travel time, allow its people to have an active lifestyle, and reduce congestion. TOD would help reduce mental health disorders and improve physical activity. TOD would positively impact the environment of Riyadh City and assist in reducing greenhouse gases. Overall, the study results provide a reliable perspective on the benefits of TOD. Most participants assumed that the implementation of TOD in Riyadh City would increase automobile mobility, provide more employment opportunities, and reduce travel time, positively impacting the environment and economy of Riyadh City.

Overview and prospect of information and communication technology development in virtual power plants

AbstractAs a new energy‐supply service solution to address massive, distributed energy access to the power system, a virtual power plant has higher transmission reliability and real‐time communication requirements. To achieve collaborative optimisation, distributed load and energy resources must be aggregated using new information and communication technology. This study analyses underlying communication technologies for virtual power plant interaction from the perspective of standardisation, efficiency, reliability, and security, summarises the application of blockchain, cloud‐edge collaboration, machine learning, and other new information and communication technologies in virtual power plant energy trading, interaction, and scheduling, and proposes ideas for addressing shortcomings in interaction. To improve virtual power plant interaction, performance parameter mapping between communication and business technology, and multilevel virtual power plant interaction technology are proposed.

Techno-economic comparison of different hybrid energy storage systems for off-grid renewable energy applications based on a novel probabilistic reliability index

The application of energy storage technologies is crucial to the extensive exploitation of renewable energy for power generation in off-grid areas because energy storage can mitigate the intermittency of renewables and balance the supply–demand mismatch. A hybrid energy storage system (HESS) with two or more heterogenous and supplementary energy storages outperforms single energy storage from the perspective of reliability and cost-effectiveness, but how to select the optimal HESS configuration is still unknown. To this end, this paper investigates the techno-economic comparison of ten HESSs in off-grid renewable energy system applications, including all pairwise combinations of thermal energy storage, pumped hydro storage, hydrogen storage, battery, and supercapacitor. Moreover, a novel probabilistic reliability index called loss of power supply probability with probability of exceedance (LPSP-PoE) is proposed to quantitatively handle the long-term uncertainties of renewable energy resources. The rule-based coordinated energy management strategies considering the charging/discharging priority and optimized operating thresholds are established for different HESSs, and then the multi-objective optimization models aiming to minimize net present cost and LPSP-PoE are developed to search the optimal components sizing and operating thresholds simultaneously. Finally, the results of case studies show that: (1) the optimal net present cost of thermal energy storage-battery at the highest reliability level is 3.3472 billion USD, which is 6.98 %∼69.85 % lower than the figure for other HESSs, indicating that thermal energy storage-battery is the most cost-effective HESS configuration; (2) The optimal charging/discharging priority can lead to 29.6 %∼75.2 % cost reduction, and the optimal operating thresholds can always achieve the lowest LPSP, illustrating the superiority of the proposed operation strategies; (3) the techno-economic performance of all HESSs varies significantly with the PoE level and load profile, while their rankings remain basically unchanged, showing the robustness of the comparison results.

A system dynamics investigation on the long-term impacts of demand response in generation investment planning incorporating renewables

By exchanging demand and price data between demand and supply sides, demand response (DR) exerts a substantial impact on the power system planning. This study proposes a novel dynamic model for long-term generation capacity investment planning with DR implementation. The relation between price and responsive loads is modeled regarding a two-way market-based relevance. Renewable energy resources alongside common thermal technologies are considered in the proposed investment process. Further, uncertainty of power generation in the thermal units, renewables' availability, and participation in the DR programs are modeled. Different levels of DR, penetration of renewables, and capacity payment are investigated to obtain the most advantageous supply by simulating several cases. Special attention is drawn to quantifying the results of DR implementation in long-term planning. The results identify that, from an environmental point of view, DR can contribute to enhancing renewables penetration and diminishing CO2 emissions. From the economic viewpoint, by postponement or preventing the new power plants construction and mitigating price spikes, DR causes more economic power system. Furthermore, from the reliability perspective, with the participation of responsive consumers, DR improves the power system's reliability and security. The proposed model allows the regulatory body to analyze the economical, technical, and environmental effects of DR in the long-term.

A Critical Discourse Analysis of the Attitudinal Resources in Modern English Poetry: The Appraisal System

Languages are means by which speakers and writers communicate their common beliefs and personal attitudes. This study thus sought to analyze the attitudinal resources in four modern English poems written by the international poetess Lang Leav. The main aim was to find out the kind of worldview the poetess attempted to share with her readers from the perspective of the attitudinal system. This system is divided into three sub-systems: Affect, judgment, and appreciation. After the attitudinal resources were collected and classified, the results indicated that both affect and appreciation resources were frequently used in the comprised corpus, followed by judgment resources. Moreover, the study found that Leav mostly shared a pessimistic view of love and romantic relationships. Therefore, the poetess utilized negative attributes more than positive ones throughout her compositions. Finally, this study may give useful implications about how modern English poetry is constructed based on a reliable perspective.

A Risk-Based Framework to Evaluate Infrastructure Investment Options for a Water Supply System

Increasing water demand due to socio-economic development often requires structure-level interventions, e.g., infrastructure expansion of water supply systems to bridge the gap between demand and water supply. Evaluating different expansion options is critical to making informed decisions. This study focuses on evaluating infrastructure investment options from the reliability perspectives of a water supply system. The evaluation framework is comprised of probabilistic demand projections, stochastic streamflow generation, a mixed-integer programming, and system performance evaluation. Different “industry understood” performance metrics, e.g., annual reliability, maximum delivery capacity, the probability of unsuccessful status, and the magnitude of potential water shortage, can be employed to evaluate the performance of water supply systems. This framework has been applied to Tampa Bay Water, a regional supply agency on the west coast of Florida, United States. The probabilistic demand projections for the future (2021–2040) consider socio-economic projections and climate conditions based on the statistics of historical observations. The Latin Hypercube Sampling algorithm is used to capture the bivariate distribution of supply and demand. This mixed-integer programming is a daily system optimization that minimizes operational cost and considers operational constraints and preferences, e.g., water withdrawal permits, facility production capacity, and water production preferences. Current infrastructure capacity and operational conditions are defined as the baseline scenario. Two additional planning scenarios of expanding the treatment capacity of a surface water treatment plant by 75,708 m3/day [20 million gallons per day (mgd)] and 113,562 m3/day (30 mgd) in the year 2028 are investigated. Results reveal that annual reliability would increase with the expansion of surface water treatment plant capacity. The spatio-temporal supply and demand variability determines that the firm yield from the surface water treatment is less than its expanded production capacity. Except for low demand realizations in the future, the duration and magnitude of potential water shortage could be reduced in both scenarios with engineering intervention. Although this framework is demonstrated for a regional water utility in Florida, it can be applied to other water supply systems around the world.

Optimal cropping patterns can be conducive to sustainable irrigation: Evidence from the drylands of Northwest China

The pressures of frequent extreme weather, water shortages and increasing food demand pose a continued challenge of maintaining the sustainable development of irrigated agricultural systems. Although rational arable land management is fundamental to alleviating these pressures, the relationship between cropping patterns and irrigation sustainability is understudied. Using the Hexi Corridor as an example, a maximum entropy machine learning model was used to determine the optimal cropping pattern based on crop suitability and to explore the impact mechanism of the optimal cropping pattern on the irrigation sustainability index (SI) from the perspective of reliability, resilience, and vulnerability. An optimal cropping pattern was conducive to sustainable irrigation and reduced irrigation water use by 21.03% from 1960 s to 2010 s with no continued agricultural expansion. Thus, the challenges of food security and sustainability for similar regions, and globally, can be met but will require major changes in cropping planning and management.

SERS of cylindrospermopsin cyanotoxin: Prospects for quantitative analysis in solution and in fish tissue

Cylindrospermopsin (CYN), a cyanotoxin occurring in environmental waters as a cyanobacteria metabolite, has recently raised increased interest both in the scientific community and the environmental, food control and health care bodies due to the incidence of poisoning reports and the lack of prompt, effective detection and monitoring techniques. Here we report comprehensive Raman and SERS spectroscopy data on CYN cyanotoxin and provide a detailed characterization of the vibrational Raman signal based on DFT calculation as well as the adsorption properties with respect to the silver nanoparticles surface.Quantitative SERS analysis was achieved for concentrations range from 0.218 nM to 2.18 µM in aqueous solution. We further investigated the SERS discrimination of artificially intoxicated fish tissue from normal one, using linear discriminant analysis. Significant changes in SERS signal of toxic tissue compared to normal one allowed clear and fast differentiation of toxic tissue with 100% specificity/sensitivity. The cross-validation procedure provided 100% clear separation based on the SERS data. The results open reliable perspectives for SERS monitoring the environmental water bodies.

Routing and Resource Allocation for IAB Multi-Hop Network in 5G Advanced

Integrated access and backhaul (IAB) is a novel feature for extending the network coverage in 5G cellular networks, based on sharing/efficient allocation of owner’s spectrum traditionally reserved for access. However, since ultra-reliability and low latency (URLLC) requirements are a key component of 5G advanced services, provisioning such services present stringent challenges for IAB multi-hop network design. To fulfill the URLLC requirements in the IAB network, we propose a cross-layer design on routing and resource allocation under the current 3rd Generation Partnership Project (3GPP) 5G standards. We first formulate a routing problem for the IAB multi-hop network, which minimizes the latency while satisfying the reliability requirement. Subsequently, we present a reinforcement learning (RL) framework to solve the resource allocation and routing problem based on the local information of each agent (IAB node) in the environment. Afterward, we propose a novel entropy-based RL algorithm with federated learning (FL) mechanism to improve the overall performance as well as accelerate the convergence speed. Via the simulation, the proposed algorithm outperforms baseline algorithms from the latency and reliability perspective, respectively. Meanwhile, the convergence speed with the proposed algorithm also improves by using FL.

Impact of Negotiation Strategies on the Effectiveness of Communication: A Mediating Approach from Digital Public Relation

Recently, negotiation, as an integrated management and communication discipline, has obtained a huge influence on communication effectiveness that ultimately prompt the public relations in government organizations. The current study prime goal is to fill in the research gap by examining the impact of negotiating strategies on the effectiveness of communication among e-Government users in Oman. In addition to that another prime goal of this study is to investigate the mediating role of digital public relations between negotiating strategies and effectiveness of communication. This proposed theoretical framework is based on the negotiation theory. This study was based as quantitative. The GPOWER analysis was conducted to determine the sample size, which was 153 and however, to avoid any complication related to data analysis arising from a small sample size, this study intended to collect data from 250 representatives of government services in Oman. After collecting the data, preliminary several tests were conducted such as reliability and validity perspectives before conducting PLS-SEM approach using SPSS AMOS. This study has found negotiation strategies (structural negotiation strategies, behavioural negotiation strategies, concession exchange negotiation strategies and integrative negotiation strategies) have a direct and significant positive effect on digital public relations and communication effectiveness among the government services in Oman. This study also confirmed a direct, positive and significant effect of digital public relations on the effectiveness of communication among the government services in Oman. However, digital public relation is found to not significantly mediate the relationship between a dimension of negotiation strategies (strategic negotiation strategies) and communication effectiveness of the Omani government services. The results of this study could be used to promote the development of significant policies by the national and state governments in Oman and other comparable nations about the use of successful negotiation strategies that generate positive and effective communication. The prime contribution of this study is to add literature to the existing domain by further developing the theory of social presence and negotiation theory. By creating a theoretical framework linking negotiation strategies, digital public relations, and communication effectiveness within the premises of the theory of social presence and negotiation theory, supported and validated by data, and supported by robust statistical analyses, the study has achieved its objectives that will accelerate the Omani governmental communication policy.

System analysis of internal and external impacts on overhaul repair frequency of vertical split casing pumps

ALROSA is currently starting transition from surface to underground mining of kimberlite pipes. Underground mining promotes with various-nature rushes of water in underground openings. These inflows of water are finally collected in drain sumps of the main water-removal plant, and then are pumped out to ground surface by vertical split casing pumps. The practice shows that frequent overhaul repairs are typical of the domestic-manufacture split casing pumps operated in underground kimberlite mines. The overhaul repair frequency of the vertical split casing pumps is largely governed by the radial clearance between the inside faces of the gasket rings and the outside surfaces of the seal bands of the impellers. It is found that the dominant impact on the multifactor damage pattern of impeller sealers in vertical split casing pumps operated in underground kimberlite mines in Russia is exerted by hydro-abrasive wear, especially at the sites of corrosive filming. The integrated research finds out that the average service life between the overhaul repairs of the vertical split casing pumps in use in the underground kimberlite mines in Russia greatly depends on such external and internal impacts as the pump head, error-free running time of the balancing ring and concentration of mechanical impurities in mine water. The implemented regression analysis has yielded a prognostic model which allows a sufficiently reliable perspective forecast of average service life of the vertical split casing pumps between overhaul repairs for the underground kimberlite mines in Yakutia.

Efficient seismic fragility analysis of structures from dynamic reliability perspective

Seismic fragility analysis of structures quantitatively describes the relationship between the failure probabilities of structures and ground motion Intensity Measures (IMs). Generally, two steps are involved: (1). calculating the failure probabilities of the structure under consideration at a set of IM levels; (2). regressing the IM levels and the corresponding failure probabilities to obtain a bunch of fragility curves. In this paper, a new method is proposed for seismic fragility analysis of structures from a dynamic reliability perspective, where efficiency and accuracy are emphasized. First, the dynamic reliability of structures under fully non-stationary ground motions is presented, where the Fractional Exponential Moments-based Maximum Entropy Method (FEM-MEM) is applied to derive the extreme value distribution with high efficiency. In this method, only a total of 89 samples of fully non-stationary ground motions generated by the spectral representation method and consistent with the design response spectrum that are sufficient in the FEM-MEM for efficient dynamic reliability computations are required. Then, a four-parameter distribution model, which exhibits high flexibility, is used to recover the fragility curves. A two-step strategy is developed for parameter estimation based on four failure probabilities at four different IM levels. In addition, a strategy for selecting a small number of IM levels for all damage states is also suggested, which improves the computational efficiency. Two numerical examples, including a seven-story nonlinear shear frame structure and a five-story three-span frame structure designed according to Chinese codes, are investigated to verify the effectiveness of the proposed method, where the results obtained from the traditional lognormal distribution are also compared.

A Survey on UAV Computing Platforms: A Hardware Reliability Perspective

This study describes the Computing Platforms (CPs) and the hardware reliability issues of Unmanned Aerial Vehicles (UAVs), or drones, which recently attracted significant attention in mission and safety-critical applications demanding a failure-free operation. While the rapid development of the UAV technologies was recently reviewed by survey reports focusing on the architecture, cost, energy efficiency, communication, and civil application aspects, the computing platforms’ reliability perspective was overlooked. Moreover, due to the rising complexity and diversity of today’s UAV CPs, their reliability is becoming a prominent issue demanding up-to-date solutions tailored to the UAV specifics. The objective of this work is to address this gap, focusing on the hardware reliability aspect. This research studies the UAV CPs deployed for representative applications, specific fault and failure modes, and existing approaches for reliability assessment and enhancement in CPs for failure-free UAV operation. This study indicates how faults and failures occur in the various system layers of UAVs and analyzes open challenges. We advocate a concept of a cross-layer reliability model tailored to UAVs’ onboard intelligence and identify directions for future research in this area.

RPL routing protocol over IoT: A comprehensive survey, recent advances, insights, bibliometric analysis, recommendations, and future directions

In the course of time, the Internet of Things (IoT) has attracted significant research interest. However, IoT devices have limited resources available in terms of battery power, processing capacity, memory, bandwidth, etc. In an attempt to provide connectivity and Internet Protocol version 6 (IPv6) support to IoT devices, the IPv6 routing protocol for Low-Power and Lossy Networks (RPL) was officially launched as the standard routing protocol for IoT in 2012. Despite being reputed and used in diverse applications, several recent studies have revealed RPL's drawbacks and limitations. The main objective of this work is to help the IoT research community understand all aspects of RPL. The paper also provides a detailed description of the operation of the RPL protocol. What is more, this work includes novel and thorough examples, thereby gaining practical knowledge of the pros and cons of this protocol. In addition, this paper reviews and summarizes relevant RPL-based protocols and conducts comprehensive comparisons among them from the perspectives of reliability, robustness, energy efficiency, and flexibility. Technically speaking, after studying and reviewing the majority of the proposed RPL solutions, we are ultimately capable, in this work, of highlighting all the challenges faced by IoT researchers while enhancing RPL and providing what is expected to be dealt with professionally. The present work also gives more details about RPL simulation platforms and RPL applications. Not only to this extent, but rather the historical bibliometric analysis of RPL, which shows the trends in the area of research to be focused on, has been professionally analyzed based on RPL challenges over the years 2010 through 2021. To this end, the conclusions and recommendations of this study are presented along with the effective directions for future RPL, and their applicability. As a result, the authors believe that this work will be a valuable reference for all RPL researchers and designers.

Reliability-based multi-attribute large group decision making under probabilistic linguistic environment

This study proposes a more rational and effective multi-attribute large group decision making (MALGDM) method with probabilistic linguistic term set (PLTS) from reliability perspective. A reliability measure method is first proposed to compute the reliability degree of the PLTS, and then a normalization method is presented to normalize the ignorant PLTSs with respect to maximizing their reliability degrees. An efficient clustering method combining the opinion similarity of experts and the reliability degrees of the clusters formed is introduced. Moreover, an objective method of determining the similarity and reliability thresholds is presented. After classifying the large-scale experts, the consensus levels of clusters and the global consensus level are measured and the cluster that need to adjust information is identified based on its consensus level and reliability degree. Then, an optimization model to maximize the global consensus level and the global reliability degree is then built to obtain the evaluation values for improving the consensus levels and reliability degrees. The deviation between the expectation values of the evaluation values before and after adjustment is constrained by the parameter provided by the experts within the cluster that need adjustment. Finally, an application example of the selection of the hotel for isolating the entry personnel during the Covid-19 pandemic and some comparative analyses are provided to validate the proposed method.

Stability in time and consistency between atmospheric corrections: Assessing the reliability of Sentinel-2 products for biodiversity monitoring in tropical forests

Earth observation satellite imagery is increasingly accessible, and has become a key component for vegetation mapping and monitoring. Sentinel-2 satellites acquire optical images with five days’ revisit frequency, which is an important feature to increase the probability of acquisition with reasonable cloud cover in tropical regions. Regular and reliable satellite observations open perspectives for the monitoring of vegetation properties and biodiversity. Atmospheric correction methods (ACMs) producing bottom-of-atmosphere (BOA) reflectance are critical to ensure temporal consistency of higher-level products and optimal sensitivity to changes in vegetation properties. Still their application in tropical regions remains challenging due to complex atmospheric issues. This study aims at performing ACM inter-comparison in the context of tropical forest monitoring. We produced BOA reflectance for a set of Sentinel-2 acquisitions corresponding to a forested area in Cameroon, using four atmospheric correction methods: Sen2cor, MAJA, Overland and LaSRC. We selected five successive acquisitions with moderate to no cloud cover, and computed a set of spectral indices and spectral diversity metrics in order to compare the consistency of these products through time, under the hypothesis that they should remain stable over a short period. We also assessed the agreement between atmospheric correction methods. Two spatial extents were used for the computation of spectral diversity metrics to assess the robustness of the data-driven processes applied to compute spectral diversity. We found that the choice of an ACM did have a significant impact on BOA reflectance and higher-level products. In the visible domain, Overland and LaSRC produced consistent BOA reflectance values, while MAJA and Sen2Cor showed strong variability which could not be explained by changes in surface properties. This directly influenced the temporal consistency of NDVI. Yet, the influence on the temporal consistency for EVI and NDWI was moderate. Spectral diversity metrics were consistent through time for all methods, but to a lesser degree than vegetation indices. When comparing the mean values over the period considered, vegetation indices were stable across methods, but not diversity metrics. Spatial context changes had an impact on the Shannon index, but not on Bray-Curtis dissimilarity. These results suggest that the choice of ACM has major potential implications for tropical forest monitoring.