Search Results (280)

The integration of renewable energy sources (RESs), such as wind and solar, introduces significant uncertainties into power system operations, complicating Available Transfer Capability (ATC) assessment. A key factor in ATC determination, the Transmission Reliability Margin (TRM), accounts for uncertainties like load variations, generation fluctuations, and network dynamics. The traditional deterministic TRM methods often fail to capture the stochastic nature of modern grids, leading to inaccurate estimations. This paper reviews the TRM assessment methodologies, emphasizing probabilistic approaches that enhance accuracy in high-RES environments. It explores adaptive statistical techniques, such as rolling window analysis, for dynamic TRM computation. Key challenges, emerging trends, and potential solutions are discussed to support the development of robust ATC modeling frameworks for secure and efficient renewable energy integration. Full article

With increasing exterior temperature, steel corrosion and concrete disintegration in RC (reinforced concrete) are severe due to the increased transport of harmful ions. A durability design for the intended service life should be ensured for the changing exterior conditions. In this study, for the concrete used in a UAE (United Arab Emirates) nuclear power plant structure, the diffusion coefficient of sulfate ions affected by temperature was evaluated through a natural diffusion cell test, and the service life in the structure was calculated through deterministic and probabilistic methods. As the temperature increased from 20 °C to 50 °C, the results decreased rapidly due to an enlarged diffusion coefficient, and its variation significantly increased with unstable ion transport. In the probabilistic method, the effect of the mean and COV (coefficient of variation) for each design parameter on service life was analyzed, which suggested the importance of enough cover depth design with COV under 0.2. Full article

Ship operability diagrams are commonly defined based on the seakeeping analysis, showing which course and speed can safely be taken at the sea state to satisfy pre-defined seakeeping limiting values. Although ship operability diagrams are inherently probabilistic, because of the random nature of the environmental loads, their outcome is deterministic, showing if the seakeeping criteria are satisfied or not for a certain combination of environmental and operational parameters. In the present study, uncertainties in seakeeping predictions and limiting values, which are usually neglected, are integrated into the ship operability analysis. This results in probabilistic operability diagrams, where the seakeeping criteria are exceeded with certain probabilities. The approach is demonstrated in the example of the passenger ship on a route in the Adriatic Sea. Semi-analytical closed-form expressions are used for seakeeping analysis, while limiting values for vertical bow acceleration, pitch, slamming, roll, and propeller emergence are analyzed. The second-order reliability method is used to calculate probabilities of the exceedance of the seakeeping criteria, and the results are presented as probabilistic operability diagrams. The method enables the determination of a new probabilistic operability index applicable to the ship design and represents a prerequisite for risk-based decision making in ship operation. It is also presented how the method can be validated for the existing shipping route using numerical wave databases. Full article

In recent years, the serious damage and even collapse accidents of bridge under vehicle-to-pier collision occurred frequently and have attracted growing attention world widely. Numerous studies have been conducted to examine the structural resistance of bridge piers against vehicle-with-pier collisions. Nevertheless, most of those studies employed a deterministic approach without incorporating the inherent uncertainty in structural and loading parameters. This study proposes a probabilistic approach to investigate the vulnerability of reinforced concrete (RC) piers under collisions with trucks and tractors. To do this, a dynamic mass-spring numerical model was developed to simulate the pier–vehicle collision process, which was further validated through simulating experimental data. A total of four parameters, including concrete strength, pier diameter, stirrup yield strength, and stirrup spacing, were considered and regarded as uncertainty parameters with their probability distributions determined according to the available studies. The Monte Carlo simulation method was used to generate 1000 samples for each of the uncertainty parameters and these random samples were coupled in the simplified numerical model. Through probabilistic analysis, the collapse vulnerability of RC piers was estimated. The results revealed that a tractor with a higher mass can result in higher failure probabilities than a truck. The uncertainty of the pier diameter and concrete strength have a great impact on the vulnerability of RC piers under different damage states. Full article

Background: The aim of this study was to assess the cost effectiveness of a screening and treatment intervention approach for chronic HCV infection in Zimbabwe. Methods: Using a decision tree and a validated Markov model, we estimated the lifetime costs and health effects of screening for and treating HCV infections from a healthcare perspective. We evaluated three screening strategies, namely the following: i. no screening; ii. screening among the general population; and iii. screening among high-risk groups. Incremental cost effectiveness ratios were calculated for the strategies that were not dominated. We used deterministic and probabilistic sensitivity analyses to explore the impacts of parameter uncertainty on cost effectiveness outcomes. Results: The strategy of screening among high-risk groups and treating with sofosbuvir/velpatasvir had an incremental cost of USD 1201 and incremental quality-adjusted life years (QALY) of 2.01, yielding an incremental cost effectiveness ratio (ICER) of USD 604 per QALY gained as compared to no screening. The ICER was below the 0.5 times the gross domestic product per capita parameter (USD 796), making the intervention potentially cost effective. The strategy to screen among the general population was dominated, because it costed more and resulted in fewer QALYs than its comparators. Conclusions: Screening for HCV among high-risk populations followed by treatment using sofosbuvir/velpatasvir is cost effective under the assumptions made in this study. Full article

Rainfall is one of the major causes of geological hazards such as landslides and slope failures because it decreases shear strength along the failure surface and increases the driving force of the sliding mass due to the movement of the wetting front in the geological media. Deterministic limit equilibrium methods are typically used to evaluate the stability of slopes in terms of Factor of Safety (FoS), considering the worst-case scenario. However, a coupled flow deformation analysis procedure combined with a probabilistic method is required to consider the temporal and spatial variations in the soil properties due to water infiltration and to evaluate the probability of slope failure. The study aims to develop a probabilistic framework for evaluating the probability of failure of an earth slope using the response surface derived from sample data generated from a coupled flow–deformation finite element (FE) program considering uncertain rainfall characteristics. Finite slopes with 1.5H:1V and 2H:1V slope ratios composed of sandy soil were analyzed considering the possible variations in soil and rainfall parameters. Based on the FE results, a response surface was developed for the FoS as a function of soil and rainfall parameters. The response surface was utilized to generate random scenarios and calculate the failure probability using Monte Carlo Simulation (MCS). The results obtained from the MCS were compared using the First-Order Reliability Method (FORM). The results indicated that the total probability of failure predicted by MCS was closer to the probability of failure by FORM. The total probability of failure predicted from MSC and FORM were 0.0633 and 0.0640 for the 1.5:1 slope and 0.0249 and 0.0229 for the 2:1 slope, respectively. This level of probability of failure was deemed unsatisfactory to poor based on the criteria by the US Army Corps of Engineers. Therefore, the proposed framework provides a valuable tool from the probabilistic perspective for assessing the performance level of slopes subjected to uncertain rainfall conditions. Full article

Accurate forecasting is crucial for enhancing the flexibility and controllability of power grids. Traditional forecasting methods mainly focus on modeling based on a single data source, which leads to an inability to fully capture the underlying relationships in wind power data. In addition, current models often lack dynamic adaptability to data characteristics, resulting in lower prediction accuracy and reliability under different time periods or weather conditions. To address the aforementioned issues, an ultra-short-term hybrid probabilistic prediction model based on MultiFusion, ChronoNet, and adaptive Monte Carlo (AMC) is proposed in this paper. By combining multi-source data fusion and a multiple-gated structure, the nonlinear characteristics and uncertainties of wind power under various input conditions are effectively captured by this model. Additionally, the AMC method is applied in this paper to provide comprehensive, accurate, and flexible ultra-short-term probabilistic predictions. Ultimately, experiments are conducted on multiple datasets, and the results show that the proposed model not only improves the accuracy of deterministic prediction but also enhances the reliability of probabilistic prediction intervals. Full article

Background: The prevalence of chronic conditions that increase the risk of influenza complications is high among individuals aged ≥50 years, and evidence suggests age-related changes in immune responses to vaccines begin to decline at this age. Persons aged 50–59 years have high rates of influenza infections and are also the most likely age group to be employed. Thus, the burden of influenza is high in this age group. Methods: We investigated the cost-effectiveness of vaccination with an adjuvanted quadrivalent influenza vaccine (aQIV) in a Spanish population aged ≥50 years at high risk of influenza complications. Using a static decision-tree model specifically designed to analyze Spanish data, we calculated incremental cost-effectiveness ratios (ICERs) for aQIV vs. egg-based QIV (QIVe; indicated for any age) and aQIV vs. high-dose QIV (HD-QIV; indicated for persons aged ≥60 years) from payer and societal perspectives. We compared ICERs against a willingness-to-pay threshold of EUR 25,000 per quality-adjusted life year (QALY) gained. The impact of input uncertainty on ICER was evaluated through a probabilistic sensitivity analysis (PSA) and a one-way deterministic sensitivity analysis (DSA). Results: The total incremental cost of vaccination with aQIV was EUR –86,591,967.67, which was associated with gains of 241.02 in QALY (EUR –359,268.05 per QALY gained) and 318.04 in life years (EUR −272,271.37 per life year gain). Compared with the willingness-to-pay threshold of EUR 25,000 per QALY gained, aQIV was the most cost-effective influenza vaccine relative to the combination of QIVe or HD-QIV. These findings were supported by PSA and DSA analyses. Conclusions: In the model, aQIV dominated QIVe and HD-QIV, demonstrating that aQIV use would be cost-saving for persons aged ≥50 years who are at high risk of influenza complications. Full article

The excessive vibration or collapse of a transmission tower-line (TTL) system under seismic excitation can result in significant losses. Viscoelastic material dampers (VMDs) have been recognized as an effective method for structural vibration mitigation. Most existing studies have focused solely on the dynamic analysis of TTL systems with control devices under deterministic seismic excitations. Studies focusing on the nonstationary stochastic control of TTL systems with VMDs have not been reported. To this end, this study proposes a comprehensive analytical framework for the nonstationary stochastic responses of TTL systems with VMDs under stochastic seismic excitations. The analytical model of the TTL system is formulated using the Lagrange equation. The six-parameter model of VMDs and the vibration control method are established. Following this, the pseudo-excitation method (PEM) is applied to compute the stochastic response of the controlled TTL system under nonstationary seismic excitations, and a probabilistic framework for analyzing extreme value responses is developed. A real TTL system in China is selected to verify the validity of the proposed method. The accuracy of the proposed framework is validated based on the Monte Carlo method (MCM). A detailed parametric investigation is conducted to determine the optimal damper installation scheme and examine the effects of the service temperature and site type on stochastic seismic responses. VMDs can effectively suppress the structural dynamic responses, with particularly stable control over displacement. The temperature and site type have a notable influence on the stochastic seismic responses of the TTL system. The research findings provide important references for improving the seismic performance of VMDs in TTL systems. Full article

With the advent of large-scale electronic transportation, the construction of electric vehicle charging stations (EVCSs) has increased. The stochastic characteristic of the charging power of EVCSs leads to a risk of destabilization of the DC distribution network when there is a high degree of power electronification. Current deterministic stability analysis methods are too complicated to allow for brief descriptions of the effect of probabilistic characteristics of EVCSs on stability. This paper develops a probabilistic small-signal stability analysis method. Firstly, the probabilistic information of the system is obtained by combining the s-domain nodal impedance matrix based on the point estimation method. Then, the probability function of stability is fitted using the Cornish–Fisher expansion method. Finally, a comparison experiment using Monte Carlo simulation demonstrates that this method performs well in balancing accuracy and computational efficiency. The effects of line parameters and system control parameters on stability are investigated in the framework of probabilistic stability. This will provide a probabilistic perspective on the design of more complex power systems in the future. Full article

Nuclear power plant risk assessments rely on conservative deterministic criteria for core-damage determination despite significant advancements in plant response and system analyses. This study proposes a probabilistic approach to determine fuel rod fracture during loss-of-coolant accidents (LOCAs) in light-water reactors, addressing the need for more rational and realistic assessments. The methodology integrates a fuel rod fracture probability estimation model with best-estimate-plus-uncertainty analysis of plant response, utilizing the stress–strength model and Monte Carlo simulations. Both stress and strength distributions are estimated through Bayesian statistical modeling, with numerical integration techniques implemented to enhance accuracy for low-frequency events. The application of this approach to a virtual dataset demonstrated that while conventional deterministic methods indicated definitive rod fracture, our probabilistic analysis revealed a more realistic fracture probability of 15.1%. This significant finding highlights the potential reduction in assessment conservatism. The proposed methodology enables a transition from conservative binary evaluations to more realistic probabilistic assessments of core damage, providing more accurate risk insights for decision-making. Full article

Radio Frequency Identification (RFID) is a key component in automatic systems that address challenges in environment monitoring. However, tag collision continues to be an essential challenge in such applications due to high-density RFID deployments. This paper addresses the issue of RFID tag collision in large-scale intensive tags, particularly in industrial membrane contamination monitoring systems, and improves the system performance by minimizing collision rates through an innovative collision-avoiding algorithm. This research improved the Predictive Framed Slotted ALOHA–Collision Tracking Tree (PRFSCT) algorithm by cooperating probabilistic and deterministic methods through dynamic frame length adjustment and multi-branch tree processes. After simulation and validation in MATLAB R2023a, we performed a hardware test with the RFM3200 and UHFReader18 passive tags. The method’s efficiency is evaluated through collision slot reduction, delay minimization, and enhanced throughput. PRFSCT significantly reduces collision slots when the number of tags to identify is the same for PRFSCT, Framed Slotted ALOHA (FSA), and Collision Tracking Tree (CTT); the PRFSCT method needs the fewest time slots. When identifying more than 200 tags, PRFSCT has 225 collision slots for 500 tags compared to FSA and CTT, which have approximately 715 and 883 for 500 tags, respectively. It demonstrates exceptional stability and adaptability under increased density needs while improving tag reading at distances. Full article

This work aims to improve the reliability of dynamic systems by eliminating the effect of random control variables. At first, the reliability-based dynamic optimization problem (RB-DOP) is introduced and defined to account for dynamic systems with uncertainty associated with random control variables. Whereafter, in order to solve RB-DOP efficiently, the constraint function response shift scalar (CFRSS)-based RB-DOP optimization method is proposed, in which the nested RB-DOP is decoupled into an equivalent deterministic DOP and a CFRSS search problem, and the two problems are addressed iteratively until the control law converges. Specifically, the shift scalar CFRSS is calculated by the probability density function of the constraint function response and deducted for probabilistic constraints in the constraint function response space to move the violated constraints toward the reliable region, avoiding solving large-scale optimization problems in the control variable space. Finally, two numerical examples and a low-thrust orbit transfer problem are investigated to demonstrate the feasibility of the proposed approach. Full article

Accurate prediction of regional wind power generation intervals is an effective support tool for the economic and stable operation of provincial power grid. However, it involves a large amount of high-dimensional meteorological and historical power generation information related to massive wind power stations in a province. In this paper, a lightweight model is developed to directly obtain probabilistic predictions in the form of intervals. Firstly, the input features are formed through a fused image generation method of geographic and meteorological information as well as a power aggregation strategy, which avoids the extensive and tedious data processing process prior to modeling in the traditional approach. Then, in order to effectively consider the spatial meteorological distribution characteristics of regional power stations and the temporal characteristics of historical power, a parallel prediction network architecture of a convolutional neural network (CNN) and long short-term memory (LSTM) is designed. Meanwhile, an efficient channel attention (ECA) mechanism and an improved quantile regression-based loss function are introduced in the training to directly generate prediction intervals. The case study shows that the model proposed in this paper improves the interval prediction performance by at least 12.3% and reduces the deterministic prediction root mean square error (RMSE) by at least 19.4% relative to the benchmark model. Full article

In quantum communication, the concept of dense coding traditionally relies on maximally entangled states as quantum channels. Recent advancements have expanded this framework to include non-maximally entangled states within the probabilistic dense coding paradigm. However, such schemes introduce a significant limitation: the receiver cannot always retrieve the complete dense coding information sent by the sender. Consequently, the receiver must inform the sender of the amount of information successfully received. Based on this feedback, the sender determines whether retransmission is necessary, leading to inefficient use of the quantum channel and reduced communication efficiency. To address these shortcomings, we propose an alternative deterministic quantum dense coding scheme that utilizes non-maximally entangled states as the quantum channel. This deterministic approach eliminates the need for retransmissions and significantly enhances communication efficiency while maintaining compatibility with non-maximally entangled states. Our scheme represents a substantial improvement over existing probabilistic methods and paves the way for more efficient quantum communication protocols. Full article