Probability Calculation Model Research Articles

Research on the Quantitative Assessment Method of HVDC Transmission Line Failure Risk during Wildfire Disaster

It is increasingly important to effectively predict the failure of HVDC transmission lines caused by wildfire disasters. On the basis of comprehensively considering the distribution of fire points, the characteristics of wildfire propagation, and the failure factors of the transmission line, a method for calculating the probability of failure in HVDC transmission lines during wildfire disasters is proposed to quantify the risk of HVDC transmission line failures caused by wildfire disasters. Using the ArcGIS 10.7. platform, the study examined the quantity of fire points within the buffer zone of each HVDC transmission line from 2001 to 2022. The results indicate significant variations in the number of fire incidents in the buffer zones of various transmission lines. Notably, there has been a noticeable increase in the number of fire incidents along several HVDC transmission lines, including Xizhe, Baihetan-Jiangsu, Baihetan-Zhejiang, and Fufeng, in recent years. Based on the number of fire points in the buffer zone obtained through ArcGIS processing and the proposed failure probability calculation model, six HVDC hydropower transmission channels in the Sichuan Province were analyzed. At the same time, the proposed probability calculation model was simplified, and a corresponding linear evaluation index was introduced. The regression analysis results indicate that the proposed index can effectively assess the failure risk of HVDC transmission lines during wildfire disasters.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept, this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory. Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion, we divide into a finite number of fragments distribution planes based on the time series in space, set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target. Building on the precondition that the multilayer fragments of the time series effectively assail the target, we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model. Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable, we introduce cloud model theory to research the target damage assessment method. Combining the equivalent simulation experiment, the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

RISK ASSESSMENT OF SUBWAY STATION FIRE BY USING A BAYESIAN NETWORK-BASED SCENARIO EVOLUTION MODEL

Subway station fires frequently result in massive casualties, economic losses and even social panic due to the massive passenger flow, semiconfined space and limited conditions for escape and smoke emissions. The combination of different states of fire hazard factors increases the uncertainty and complexity of the evolution path of subway station fires and causes difficulty in assessing fire risk. Traditional methods cannot describe the development process of subway station fires, and thus, cannot assess fire risk under different fire scenarios. To realise scenario-based fire risk assessment, the elements that correspond to each scenario state during fire development in subway stations are identified in this study to explore the intrinsic driving force of fire evolution. Accordingly, a fire scenario evolution model of subway stations is constructed. Then, a Bayesian network is adopted to construct a scenario evolution probability calculation model for calculating the occurrence probability of each scenario state during subway station fire development and identifying critical scenario elements that promote fire evolution. Xi’an subway station system is used as a case to illustrate the application of Bayesian network-based scenario evolution model, providing a practical management tool for fire safety managers. The method adopted in this study enables managers to predict fire risk in each scenario and understand the evolution path of subway station fire, supporting the establishment of fire response strategies based on “scenario–response” planning.

Multiple Factors Coupling Probability Calculation Model of Transmission Line Ice-Shedding

After a transmission line is covered by ice in winter, ice-shedding and vibration occurs under special meteorological and external dynamic conditions, which leads to intense transmission line shaking. Transmission line ice-shedding and vibration often cause line flashover trips and outages. In January 2018, three 500 kV transmission lines, namely, the 500 kV Guanli line, the 500 kV Dushan line, and the 500 kV Guanqiao line, tripped and cut off due to ice-shedding and vibration in Anhui province, seriously threatening the safe operation of a large power grid. Current studies mainly focus on analyzing the influence factors and characteristics of line ice-shedding and investigating suppression measures, but they only analyze the correlation between each influencing factor and icing or shedding, and do not consider the coupling effects between multiple factors. In this paper, the key influencing factors and the probability distribution of transmission line ice-shedding were analyzed, and a multiple-factor coupling fault probability calculation model of line ice-shedding based on Copula function was proposed. The fault probability was calculated directly by considering multiple influence factors at the same time, which effectively overcame the error caused by multi-factor transformation in fuzzy membership degree and other methods. It provided an important decision-making basis for preventing and controlling transmission line ice-shedding faults.

Design method of high transport performance biochar-cement based materials based on particle size distribution and permeation probability calculation model

Cement-based materials are the most widely used and largest quantity of engineering materials. Enhancing carbon fixation efficiency and reducing carbon emissions in cement-based materials is an active method of coping with climate change, which has important environmental and social benefits. The amount of carbon dioxide transported into the cement-based material represents the maximum carbon fixation capacity. Enhancing the carbon transport performance of cement-based materials is the material guarantee and basic premise for improving their carbon fixation levels. Considering the impact of particle connections on the maximum cluster, a permeation probability calculation model of porous media system was established, providing the changing rule of the permeation probability with the mathematical expectation of the Poisson distribution, which was verified to be reasonable through experimental studies. The experimental results showed that under the same cement-based conditions, the water transport properties of biochar cement-based materials increased as the mathematical expectation increased. The carbon dioxide transport properties were influenced by the surface area of the biochar particles and exhibited a trend of first decreasing and then increasing with an increase in the mathematical expectation. When the water-cement ratio decreased, the differences in the microstructure of cement-based materials with different biochar particle size distributions increased, the change rate of permeation probability therefore was more sensitive, resulting that the differential effects of different particle size distributions on the transport properties were amplified, and the influence of the particle size distribution of biochar on the transport properties of cement-based materials was more significant.

Threat assessment for air-to-ground combat of UAVs using improved Bayesian networks

Aiming at the problems of information uncertainty and real-time faced by ground threat assessment during UAV air-to-ground combat, the limitations of existing threat assessment methods are analyzed, and a new threat assessment method based on improved Bayesian network is proposed in this paper. In this method, a hybrid-driven approach of threat data and expert knowledge is used to improve the rationality of threat assessment model, and a layered threat assessment architecture is constructed. Threat levels are classified based on the relationship between carrier aircraft and threat envelope, threat radiation, etc. In order to improve the rationality of the ground threat assessment model, a calculation model of ground threat intervisibility probability is established, and the intervisibility probability is taken as the input of Bayesian network threat assessment model. Simulation results show that the model has less computation and good real-time performance, and the introduction of threat intervisibility probability improves the rationality of ground threat assessment.

A Refined Analysis Method for Flight Safety Based on a Multi-stage Reliability Model

Flight verification is an indispensable key step in the process of aircraft development. Due to the inevitable existence of protected targets in and around the flight area, the accidental crash of aircraft during flight will pose a threat to the protected targets, so it is necessary to carry out a quantitative analysis of flight safety risks. To meet the requirements of flight safety risk quantitative analysis and improve the refinement degree of risk quantification, this paper proposes a flight safety refinement analysis method based on a multi-stage reliability model. Firstly, the failure modes of the aircraft flight process are summarized, and then the stage distribution logic analysis method and quantitative calculation method of failure modes are proposed. Finally, the target threat probability calculation model is given, which realizes the quantitative evaluation of the safety risk of the flight area and provides support for the optimization design of the flight safety control area.

Reliability Analysis of Nuclear Power Plant Electrical System Considering Common Cause Failure Based on GO-FLOW

The reliability of nuclear power plant electrical systems is an important guarantee of nuclear safety, and the common fault failure problem arising from redundant design and intelligent control may greatly affect reliability assessment results. Combined with the features of repairability, multi-state characteristics, and common fault failure of nuclear power plant electrical systems, a reliability analysis method of nuclear power plant electrical systems based on the GO-FLOW method considering common fault failure is proposed. This study firstly constructs the algorithmic model of combining operators of repairable components and the equivalent model of reliability parameters of multi-mode repairable components, then establishes a probability calculation model of common fault failure for repairable systems by considering the quantitative computation of the common signaling system model, and finally, quantitatively calculates the reliability of nuclear power plant electrical systems and their influencing factors. The example simulation calculates the reliability of the external power supply system and the electrical system of the nuclear power plant, analyzes the influence of the common signal processing and the common fault failure factors on the reliability of the electrical system of the nuclear power plant, and verifies the validity of the proposed method. The results show that the common fault failure factors have a large impact on the system reliability analysis; the common fault failure of the standby diesel generator set will seriously reduce the reliability of the electrical system, which can be improved by installing additional standby diesel generators.

Determination of the optimal connected and automated vehicles platoon size based on the merging success rate

ABSTRACT The platoon size is a critical parameter in connected and automated vehicle (CAV) platoon configuration. However, the optimal platoon size configuration for the mixed human-driven vehicles (HVs) and CAVs traffic has not been well-studied, especially in merging areas. This paper aims to determine the optimal platoon size in the merge area through numerical analysis. Specifically, the existing merge probability calculation model is improved considering the impact of mainline random platoon size on on-ramp vehicles. In the improved model, the CAV platoon is treated as a vehicle with different lengths, and the headway between the platoon and single vehicle and the headway between the platoons are related to the maximum platoon size and CAV penetration rate. Three key parameters, namely the CAV penetration rate, acceleration lane length, and mainline traffic volume, were combined at various values. Based on this input, the relationship between the success rate and the platoon size was analyzed. The numerical analysis results indicate that: (1) when the CAV penetration rate is 10% ~30%, the merge success rate increases and stabilizes as the platoon size increases, and the optimal platoon size is 4 ~ 6. (2) When the CAV penetration rate is 40% ~70%, the trend of merge success rate varies with increasing platoon size under different mainline traffic volumes and acceleration lane lengths. Under the situation with lower traffic and longer acceleration length, the merge success rate tends to decline easier with larger platoon sizes, with 3 ~ 8 being the optimal platoon size. (3) When the CAV penetration rate is 80% ~90%, as the platoon size increases, the merging success rate tends to increase to the highest point and decrease. The optimal platoon size is 3 ~ 5. Finally, the validity of the theoretical model is confirmed through simulation experiments, and its limitations are discussed.

Adaptability evaluation of conceptual design for smart product-service system: An integrated rough DEMATEL and Bayesian network model

Smart product service system (PSS) design evaluation plays a crucial role in the early design stage of Smart PSS development. It aims at considering the user's value proposition for Smart PSS in the dimensions of intelligence, sustainability, and society, while also ranking Smart PSS to support delivery risk management under uncertainty. However, related Smart PSS evaluation models advocate the use of multi-criteria decision models for obtaining the intrinsic value of PSS by ignoring the influence of the causality of criteria on Smart PSS design, which results in an unstable evaluation process. Additionally, the adaptiveness of Smart PSS has not been thoroughly explored, and determining the adoption intentions of Smart PSS can be challenging. To fill these gaps, a Smart PSS evaluation model that integrates a rough decision-making trial and evaluation laboratory (DEMATEL) and a Bayesian network (BN) is proposed to support probabilistic reasoning for Smart PSS adaptiveness and reduce the risk of Smart PSS development. First, a set of 17 evaluation criteria is identified, and their causal relationships and weights of the criteria were identified using a rough DEMATEL under uncertainty. Second, a BN-based reasoning model for Smart PSS criteria is developed to evaluate the adaptability of smart PSS by constructing a conditional probability calculation model based on criterion weights. Finally, a multifunctional smart cooking center (MFSCC) case study is presented to demonstrate the applicability of the proposed approach. The belief propagation analysis results revealed the key criteria affecting the MFSCC service system development and provided design strategies to improve the adaptiveness of the Smart PSS.

Probability Calculation Model for 1 + n-Type Multistage Gas Spark Switch With High Reliability and Compactness

By describing the gas breakdown phenomenon from the view of probability density function (pdf) estimation, a numerical calculation model is proposed to apply for the design of a 1 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$+$</tex-math> </inline-formula> n-type multistage gas spark switch (GSS). The physical principle, numerical calculation model, design procedures, and experimental test for GSS are hence described in considerable detail in the text. Various key operating parameters for GSS, that is, nontrigger rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\xi $</tex-math> </inline-formula> , error breakdown rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\chi $</tex-math> </inline-formula> , mean breakdown voltage, and breakdown voltage jitter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sigma $</tex-math> </inline-formula> , are deduced from the calculation model. Optimization of operation parameters helps to design reliable compact GSS for pulsed power systems. The validity of the calculation model is verified and its suitability to a more general switch design is discussed.

Life-cycle maintenance strategy of bridges considering reliability, environment, cost and failure probability CO2 emission reduction: A bridge study with climate scenarios

Climate change significantly affects existing infrastructure by enhancing the deterioration of concrete structures. As the number of repairs and strengthening increases during the service life of a bridge, the cost and environmental impact gradually increase as well. This study aims to propose a framework with climate adaptability considering reliability, environment, and cost, to realize the optimization of the life-cycle maintenance strategy of bridges under climate change. In this study, four preventive maintenance and four essential maintenance of bridges were comprehensively considered, and the reliability, environmental impacts and cost of the bridge at the maintenance stage were quantitatively analyzed. By using the decision tree method, the optimal strategy of bridge life cycle maintenance and reinforcement under climate change scenario was proposed, with the environmental impacts, environmental cost, economic cost and comprehensive cost as the optimization objectives, respectively. Finally, a failure probability calculation model of emission reduction target of bridges was estimated, based on the CO2 emission reduction targets by China in the Paris agreement. To demonstrate the applicability of the proposed framework, a typical highway bridge was taken as an example. It can be observed from the results that the maintenance strategies determined with different optimization objectives show great differences in environmental and economic costs. With the deepening of climate scenario, the failure probability of bridge emission reduction of maintenance strategies with diverse optimization objectives will increase by 10%–20%. The findings highlight the climate adaptability assessment framework is of significant for optimizing the maintenance budget and environmental impact of aging bridge structures in China, and is expected to support decision-making for bridge maintenance under the influence of climate change.

Parameters of the Lyman Model for Calculation of Normal-Tissue Complication Probability: A Systematic Literature Review

The Lyman model is one of the most used radiobiological models for calculation of normal-tissue complication probability (NTCP). Since its introduction in 1985, many authors have published parameter values for the model based on clinical data of different radiotherapeutic situations. This study attempted to collect the entirety of radiobiological parameter sets published to date and provide an overview of the data basis for different variations of the model. Furthermore, it sought to compare the parameter values and calculated NTCPs for selected endpoints with sufficient data available. A systematic literature analysis was performed, searching for publications that provided parameters for the different variations of the Lyman model in the Medline database using PubMed. Parameter sets were grouped into 13 toxicity-related endpoint groups. For 3 selected endpoint groups (≤25% reduction of saliva 12 months after irradiation of the parotid, symptomatic pneumonitis after irradiation of the lung, and bleeding of grade 2 or less after irradiation of the rectum), parameter values were compared and differences in calculated NTCP values were analyzed. A total of 509 parameter sets from 130 publications were identified. Considerable heterogeneities were detected regarding the number of parameters available for different radio-oncological situations. Furthermore, for the 3 selected endpoints, large differences in published parameter values were found. These translated into great variations of calculated NTCPs, with maximum ranges of 35.2% to 93.4% for the saliva endpoint, of 39.4% to 90.4% for the pneumonitis endpoint, and of 5.4% to 99.3% for the rectal bleeding endpoint. The detected heterogeneity of the data as well as the large variations of published radiobiological parameters underline the necessity for careful interpretation when using such parameters for NTCP calculations. Appropriate selection of parameters and validation of values are essential when using the Lyman model.

Analysis of an empirical seismic fragility prediction model of wooden roof truss buildings

To explore the vulnerability of wood roof truss buildings (WRTBs) under earthquake action, the empirical damage typical characteristics of 12,343.4 × 104 m2 and 21,490 buildings of this type of building that suffered different degrees of loss in 22 typical destructive earthquakes in China from 1993 to 2013 were observed and analysed. Based on the analysis methods of the nonlinear vulnerability model, probability statistics, and prediction model, a novel fragility probability matrix, plane, surface, nonlinear regression curve, and function model of different intensity zones under the latest Chinese macrointensity standard (GB/T 17742–2020, CMS-20) assessment were established, and vulnerability curve models were employed based on the damage ratio (DR) and actual cumulative damage probability (ACDP) parameters. According to 1993–1999, 2000–2010, and after 2011, the time-varying fragility specimen data were classified and censusly analysed. The fragility prediction curve models of DR and ACDP were performed using the probabilistic demand modal analysis method. Combined with the matrix probability and confidence interval calculation model, a novel regional mean fragility index domain model for typical structural (WRTB) vulnerability assessment was developed.

Geostationary Orbital Debris Collision Hazard after a Collision

Many space objects are densely distributed in the geostationary (GEO) band, and the long-term impact of the collision of GEO spacecraft and space debris on the GEO environment has attracted more and more attention. After summarizing the advantages and disadvantages of the long-term evolution model based on the “Cube” collision probability calculation model, the “Grid” model, a long-term evolution model especially suitable for GEO band, was established. For four types of collision and disintegration events, the “Grid” model was used to study the space environment in the GEO band after collisions between GEO spacecraft and space debris. Future collisions were simulated, and the number of space objects in the next 100 years was counted. Once space debris and massive spacecraft were completely disintegrated after collision, the number of space objects and the collision probability increased sharply, and this caused a collision cascading syndrome. Even if there was no initial disintegration event, collision and disintegration events occurred in the long-term evolution of the GEO band, which led to an increase in the number of space objects. However, the collision probability was much lower, and the number of space objects grew much more slowly without the initial collision.

Oblique Collision Experiment and Probability Calculation Model of Collision Coefficient Between Micron Particles and Silicone Rubber Insulators

Studying the collision and rebound characteristics between particles and silicone rubber surfaces is the basis of establishing a scientific contamination deposition model for silicone rubber insulators. In this article, high-speed and microscopic imaging techniques are used to set up an experimental platform for tracking and filming the collision and rebound motion of micrometer particles. Key parameters in the semiempirical calculation formula of critical adhesion velocity and tangential and normal rebound coefficients of particles in the collision issue between particles and silicone rubber surface are also obtained in this article by the parameter optimization method based on experimental measurement results. In addition, a probability calculation model for tangent and normal rebound coefficients of particles is proposed based on the statistical analysis method. Findings show that the critical adhesion velocity of particles decreases with the increase of the particle diameter. Influenced by the roughness distribution of the silicone rubber surface, the tangent rebound coefficient and the ratio between the measurement results and the theoretical calculated values of normal rebound coefficients of particles in the oblique collisions obeys normal distributions. This article is valuable for studying the contamination mechanism of silicone rubber insulators.

A Probabilistic Calculation Method of Transformer Temperature Fault Based on Photoelectric Infrared Sensor

Aiming at the defect of the lack of quantitative detection probability evaluation method, we design two models which affect the detection probability of image fusion system. They are spectral contrast modeling of target and background and probability model of transformer fault detection and recognition under the influence of multiple factors. Based on the infrared optical imaging method, we established the fault identification model of multi-mode transformer or its connected parts; Studied several infrared optical imaging fusion test systems, and deduced the calculation method of transformer fault detection based on false alarm probability; Analyzed the correlation between the detection ability of the detection system and the characteristics of the target itself, environmental illumination, detection distance and so on. According to the relationship among SNR, detection range and detection probability, we derived the calculation model of target detection probability of optical imaging system under complex background. Through calculation and experimental analysis, the results show that the proposed method can effectively evaluate the detection probability of photoelectric detection imaging system under different background in practical application.

Aging-Aware Gate-Level Modeling for Circuit Reliability Analysis

Due to severer transistor aging at nanoscale, circuit design margin becomes extremely tight for advanced technology nodes. Thus, reliability-aware circuit design is urgently needed. In this article, a new framework to perform aging-aware static timing analysis (STA) is presented for reliability analysis. The key parts of aging-aware STA flows are workload analysis and aged delay/transition calculation. For the workload analysis, a new analytical stress probability (SP) calculation model is proposed, which considers the floating effect and signal correlations. For aged delay/transition calculation, a new aging-aware model is developed, which is accessible to large industrial libraries. The results show that the proposed model achieves high accuracy in the degradation estimation and aged-path-delay calculation. Due to its high accuracy and scalability, the proposed framework is a promising solution that is compatible with commercial Electronic Design Automation (EDA) tools.

Study on damage effect of behind-armor debris on internal parts in tanks based on the experiments

PurposeIn order to explore the damaging effect of behind-armor debris of explosively formed projectile (EFP) attack on the top armor of tank and the internal parts of vehicles, a method of damage probability calculation based on experiments is proposed.Design/methodology/approachThe equivalent target structure of rear-effect damage of the equipment and personnel in the vehicle is determined based on the analysis of the vulnerability of internal equipment and personnel in the tank. The experimental scheme to obtain the density distribution of behind-armor debris is designed, and the calculation model of the damage probability of cavitating antipersonnel debris to the key components of the vehicle is given in the range of scattering angles and different broken pieces.FindingsThe examples show that the damage probability calculation model can be used in the process of evaluating the damage of the equipment and personnel in the tank by behind-armor debris.Originality/valueAn experimental model based on the analysis of the vulnerability of the equipment and personnel is proposed to calculate the damage probability from debris falling on the equipment and personnel in the vehicle. The results are of great value to the calculation of damage evaluation of the equipment and personnel in the tank.

Laser reflection echo signal detection and calculation under multi-attitude intersection

To improve the detection capability of laser fuze, this paper researches the laser echo signal detection method and echo power calculation method on laser fuze. From the multi-attitude intersection relation of projectile and target, we analyze the laser echo characteristics of target, set up the modeling of laser echo power by using the finite element meshing method. Taking into account the parameters of yaw angle and pitch angle and roll angle, we derive the target reflection laser echo power calculation function by combining the non-Lambertian and bidirectional reflection function of target's surface, establish the target detection probability calculation model. According to the established laser echo signal and echo power calculation function, we calculate the laser echo power and detection probability under the multi-attitude intersection conditions and different detection distances. Through simulation tests, the test result accords with the theoretical model.