Probabilistic Evaluation Method Research Articles

A Method for Threshold Setting and False Alarm Probability Evaluation for Radar Detectors

A threshold setting and false alarm probability evaluation method is proposed for radar detectors for which an analytical relationship between thresholds and false alarm probabilities is impossible or difficult to obtain due to complicated detection schemes or non-Gaussian noise and clutter. Importance sampling is performed to increase the sampling efficiency of low-probability samples. Then, the weighted piecewise parabolic (P2) interpolation method is used to rapidly plot the relationship curve between the threshold and the false alarm of the detector, with a low storage requirement and high accuracy. The proposed method effectively enhances the detector threshold computing scale and addresses the statistical verification of the false alarm probability for radar detectors with a low false alarm rate.

浮体式洋上風車の風と波による応答および構造損傷発生確率評価に関する研究

An evaluation method of structural damage probability of floating offshore wind turbines under wind and wave actions is presented. The structural damage probability of the floating wind turbines is analyzed by using the first order reliability method in the structural reliability evaluation. In the evaluation of the probability, the response analysis results of the floating wind turbine for the wind and wave actions are used. The response for the action by the mean wind speed is analyzed by using the statically equation of equilibrium. On the other hand, the response for the dynamic actions by the variable wind speed and the wave is analyzed by using a mode superposition method and a stationary random vibration theory. Numerical model of the floating wind turbine is discretized by finite elements, whereas interface of the floating wind turbine and the sea water is discretized by boundary elements. Moreover, variation of the damage probability of the floating wind turbine for different wind speed is discussed by using the proposed method.

Effective physical protection system design and implementation at a radiological facility: an integrated and risk management approach

Abstract Lives are threatened whenever there is an act of theft or destruction against a nuclear and radiological facility thus, physical protection systems are effectively employed to prevent or mitigate loss of valuable assets. Health facilities that provide radiotherapy services have in their facility a temporary storage unit where disused radioactive sources 60Co, 137Cs and 192Ir are kept and this raises concerns for effective physical protection. An integrated physical protection System was considered to consolidate of all sub systems, sensors and elements related to protection system for an effectively secured environment at a radiological facility. Sequence adversary diagram (ASD) was developed to depict the paths that enemies can take to achieve sabotage or stealing objectives and analyze flews in the paths. The approach to this security system effectiveness focuses on using probabilistic statistical methods for risk evaluation considering detection, delays and response. This paper considers the basic and effective elements required for physical protection system for a radiological center and makes risk evaluation as an approach of security system effectiveness which can serve as fundamental guiding principle for decision makers in the establishment of an effective physical protection for a radiological center.

Comprehensive reliability evaluation of water-energy nexus systems

• New reliability model is developed for integrated Water-Energy Nexus (WEN). • An augmented probabilistic algorithm is devised to evaluate the reliability of WEN. • Renewable energy sources and energy storage are considered in reliability analysis. • Both mechanical failures and hydraulic analysis of the water system are considered. • Three reliability indices for water system considering power reliability are devised. • Power supply reliability is an unneglectable factor as three overall reliability indices of water system increase by 19.7%, 32.6%, and 26.9% respectively when it is considered. Water and power systems are two national critical infrastructures which support our daily life and economic growth. Both are highly interconnected and complex networks, which consist of various system elements. The core functions of water and power distribution systems are to deliver satisfactory water and electric services to consumers by satisfying the demands at all load points. Besides the factors in the water distribution system itself, power supply may affect the performance of the water distribution system. Therefore, the two systems are in fact physically connected and coupled. The purpose of this study is to develop an appropriate model and an efficient evaluation algorithm to quantify the reliability of the water distribution and power supply system as an integrated Water-Energy Nexus (WEN). This paper proposes a probabilistic reliability evaluation method for the micro-WEN model based on the sequential Monte Carlo Simulation (MCS) procedure. In the proposed evaluation procedure, both mechanical failures and hydraulic analysis are taken into consideration. Case studies are performed based on a representative water-energy nexus system to demonstrate the effectiveness of the proposed method.

A hybrid probabilistic linguistic term set decision-making evaluation method and its application in the site selection of offshore wind power station

In the context of carbon neutrality, China vigorously develops clean energy and renewable energy. As a result, offshore wind power projects have grown rapidly. The success of offshore wind power projects depends on the location of offshore wind power station(OWPS), and this paper aims to develop a hybrid decision-making framework to address the location of offshore wind power stations. Firstly, a comprehensive evaluation attribute system of offshore wind power station site selection is innovatively constructed, including wind resources, construction conditions, economy, environment and risks. Secondly, probabilistic linguistic term set(PLTS) is used to describe uncertain information, which improves the reliability of decision information. Thirdly, The Best-worst method (BWM) based on probabilistic language term sets determines the weights of attributes, which ensures the accuracy of the attribute weight. Finally, an extended TODIM (an acronym in Portuguese of Interactive and Multicriteria Decision Making) method is proposed to rank the alternatives. The proposed method is applied to the location selection of offshore wind power station in Jiangsu Province, China. Through sensitivity analysis and comparative analysis, it is verified that the proposed model has good stability and applicability.

Minimizing mission cost for production system with unreliable storage

Considerable research efforts have recently been devoted to the reliability analysis and optimization of production systems with product storage. The existing models, however, failed to address a crucial design factor of cost. This paper makes contributions by modeling the expected mission cost (EMC) of an imperfect production system with storage subject to failures during uploading and downloading processes. To perform a successful mission, the system must meet a certain demand during a specified mission time. The EMC modeled encompasses operation and standby cost of the production unit, downloading and uploading cost of the storage, cost of losses associated with the failure of the production unit and storage, as well as penalty cost associated with the mission failure. The optimal EMC problem is formulated and solved, which determines the scheduled storage uploading time to minimize the EMC. A detailed case study of a coal feeding system is conducted to demonstrate the proposed probabilistic evaluation method and influences of different model parameters on the mission success probability and EMC as well as on the optimization solutions. The advantage of using the production storage is also illustrated through a comparison to a dual-production unit system without storage.

Probabilistic fatigue life analysis considering mean stress effects of fiber reinforced polymer (FRP) composites

In general, the S-N curve, which describes the relationship between fatigue life and stress level with a typical guarantee rate, is employed during the design of FRP structures. However, the effect of mean stress on fatigue life is typically ignored. In this paper, a revision term is proposed to consider the mean stress effects on the basis of the common S-N equation. The third material parameter of the revised S-N-R equation increased the difficulty to predict the probabilistic fatigue life with the traditional analysis method during the design of FRP structures. Hence, a failure probability evaluation method is proposed to obtain the probabilistic fatigue life with three material parameters by using Markov chain Monte Carlo (MCMC) and Bayesian inference. The results show the applicability and effectiveness of the method in evaluating failure probabilities.

A Failure Probability Evaluation Method for the Collapse of Drill-Blast Tunnels Based on a Multistate Cloud Bayesian Network

Collapse is one of the main dangers of tunnel construction using the drill-blast method. To assess the risk of collapse and provide a basis for risk control, a failure probability evaluation method for tunnel collapse based on a Bayesian network (BN) and normal cloud theory is proposed in this paper. First, typical tunnel collapse cases are analysed statistically based on the risk breakdown structure method, a Bayesian network model is built for drill-blast tunnel collapse and the causal relationships between the tunnel collapse and influential factors, such as geological factors and construction management factors, are revealed. Second, the multiple fault states of the risk factors are described using fuzzy numbers. A multi-state fuzzy conditional probability table of uncertain logical relationships between nodes is established using normal cloud theory to describe node failure probabilities. Finally, this paper will consider the entire life cycle of risk-prone events, including pre-incident, dynamic evaluation of the construction process and post-incident control. A typical tunnel collapse incident encountered during the construction of the Jinzuba Tunnel in Fujian was used as an example to verify the applicability of the method.

RC structures life-cycle probabilistic evaluation method considering mesoscopic material uncertainty with chloride ingress

Due to the attack of harmful environmental substances, the reinforcements in concrete can be corroded. The corrosion of reinforcements induces the concrete crack and the reduction in structural capacity. The complex durability deterioration at the material scale is commonly oversimplified in the structural analysis, and the influence of reinforcement corrosion distribution can hardly be evaluated in traditional methods. Benefitted from the accurate material model and efficient solution technologies, a structural life-cycle probabilistic evaluation method is proposed based on the material uncertainty influence. The computational framework consists of three steps. First, the simulation of chloride ingress in structural cross-section considering mesoscopic variation; second, the finite element analysis of structural response with modifying reinforcement corrosion states; third, the structural life-cycle performances are evaluated probabilistically with the trained Artificial Neural Network model. Focussed on the life-cycle hysteretic performance of the reinforced concrete column, the whole procedure is operated for illustration, and the time-dependent decreasing structural performance are investigated. Compared with widely used macroscopic methods, the model precision can be refined over 90%. By discussion effects of different measures to improve structural performance are studied, including increasing concrete strength and concrete cover. The results show that the thicker concrete cover can postpone the initial deterioration and significantly increase structural life-cycle performance probabilistically, and with the same designed action effect, the structural service life can be extended over 85% to reach same reliability.

New methods for comparing embryo selection methods by applying artificial intelligence

Purpose To develop a process for comparing embryo selection methods by applying artificial intelligence (AI) for live births retrospectively with historical individual embryo sequence data from live births. Methods We sought to predict the results for live birth outcomes with the sequences of embryos from patient data. To do so, we developed two functions. For the first (ranking evaluation) method, we summed the weighted order number of the embryo sequence to determine the order number of embryos that became a live birth. For the second (probability evaluation) method, we calculated the AI-derived confidence scores of the embryo for predicting a live birth via the result of the embryo sequence. Results We used both methods to evaluate the embryo sequence for empirical samples. With the assumed known result of becoming a live birth in a sequence of blastocysts, any methods for creating sequences could now be quantitatively evaluated, regardless of whether AI is used. Conclusions Through use of AI, we could, to a certain extent, expect to evaluate the superiority or inferiority of past, current, or future methods. The accuracy of AI-based diagnosis for predicting a live birth should improve, meaning the methods presented herein will become increasingly useful.

A probabilistic uncertainty evaluation method for turbomachinery probe measurements

The paper presents a probabilistic uncertainty evaluation method described in the Guide to the Expression of Uncertainty in Measurement (GUM) [1] and its application to the field of Turbomachinery probe measurement techniques. All sources of uncertainties contributing to a measurement result are expressed in terms of probability distributions. Consequently, the overall standard uncertainty of the result can be calculated using the Gaussian error propagation formula. The result of the uncertainty evaluation yields the most probable value of the measurand and describes its distribution in terms of standard or extended uncertainties. A pneumatic five-hole-probe measurement technique has been chosen to show the principle of the probabilistic uncertainty evaluation method. The complete signal chain including the probe calibration, the modeling and the application in the turbine has been included in the analysis. The overall uncertainties of the measured flow angles and flow total and static pressures are presented as a function of the flow Mach number. In addition, the contribution of the individual sources of uncertainty to the overall standard uncertainty is shown. Based on this break down of uncertainties optimization options of the measurement chain are suggested.

Evaluation of pressure and species concentration measurement using uncertainty propagation

This paper presents a probabilistic uncertainity evaluation method as described in the Guide to the Expression of Uncertainty in Measurements (GUM) and its application to probe measurements on pressure and fuel concentration. All sources of unceratinties are expressed as probability distributions. Consequently, the overall standard uncertainty of the quantity can be calculated using the Gaussian error propagation formula. The result of the uncertainty evaluation yields the most probable value of the measurand and describes its distribution in terms of rectangular (standard uncertainty) or gaussian (“expanded” uncertainty) distribution. A pitot-static probe and a fuel-concentration stem probe are used in order to demonstrate the principle of the probabilistic uncertainty evaluation method. The uncertainty induced by the pressure and concentration data acquisition system as well as the calibration of the fuel-concentration probe are included in the analysis. The overall “expanded” uncertainties for the measured and calculated values are presented as a function of different inlet fuel flows. In addition to this, the individual sources of uncertainty to the overall standard uncertainty are presented and discussed. Moreover, the transformation of standard uncertainty to “expanded” uncertainty will provide the deviation of the measurement in a 95% or 99% normal distributed interval instead of a 67% rectangular distributed interval.

Fundamental study on failure probability assessment method during vibration

The various vibration tests have been conducted, depending on the specification and shape of the structure. However, the data, which was obtained from these vibration tests, are underutilized in the failure evaluation caused by vibration. In this study, the failure probability evaluation method of the similar structure is investigated based on these test data. In previous studies, cabinets and underfloor equipment on railroad vehicles were investigated based on the PRA (Probabilistic Risk Assessment) method used in nuclear facilities. As a result, the failure probability could be evaluated at classifying these sample appropriately before the vibration test. Furthermore, in order to adapt this method to more structures and equipment, an evaluation indicator, which can be evaluated regardless of differences in input waves, is necessary. Accordingly, in this report, the vibration tests with the simple examination specimens were carried out in order to investigate the vibration energy which input to the equipment and accumulated. The natural frequency of the simple examination specimen is 112Hz. The sine wave test was carried out at the resonant frequency. The accumulated energy to failure, was investigated for each vibration test. As a result, the accumulated energy increased with increasing input acceleration, furthermore, the average value of the accumulated energy to failure was approximately 3750 [J] on this test condition.

Cross-Efficiency Evaluation under Probabilistic Hesitant Fuzzy Environment and Its Application to the Portfolio Selection Process

In the case of insufficient quantitative data, qualitative evaluation information is very important for investment decision-making. However, if it is completely based on qualitative evaluation information, the results may be subjective. In response to this problem, this paper proposes a method, namely, probabilistic hesitant fuzzy cross-efficiency evaluation (PHFCEE) method, based on probabilistic hesitant fuzzy theory, cross-efficiency data envelopment analysis (CEDEA). This method uses probabilistic hesitant fuzzy sets to collect qualitative evaluation information and then uses the cross-efficiency DEA model to fuse quantitative data and qualitative information. And finally, an investment portfolio is built based on the cross-efficiency value and its variance. In addition, this article gives the specific operating steps of the PHFCEE method and uses the construction of a portfolio of 10 stocks in the China CSI 300 Index as an example to illustrate the effectiveness of this method.

재생에너지 발전출력의 변동성을 고려한 정적안정도의 위험도(Risk) 평가 방법에 관한 연구

In this paper, a probabilistic static stability evaluation method considering the variability of renewable energy generation output and a Well-Being Analysis (WBA) method that can evaluate the level of risk of static stability are presented. In order to apply the WBA, we analyzed the measured renewable energy generation output and variability. In addition, to prove the effectiveness of the proposed WBA method, a probabilistic stability evaluation was performed using a test system and the WBA method was applied.

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.

Method for probabilistic evaluation of post-earthquake functionality of building systems

Recent large earthquakes have caused significant building damage resulting in lengthy functional recovery times. Post-earthquake recovery time can be minimized through improved design of building systems essential for providing continuous operation. This study presents a novel method for probabilistic evaluation of the post-earthquake building’s functionality to support functionality-based seismic design. Aligned with the PBEE methodology, the proposed method utilizes FEMA P-58 damage assessment results in conjunction with fault trees of complex building systems to find the percent of building area with compromised functionality and to identify building components that impair its functionality. The primary user-defined inputs are probabilistic limit state functions of individual building components, which define the damage thresholds for partial (local) and full loss of the building functionality. The proposed method is highly flexible; it has a modular structure that allows easy extension by adding new features. A case study is conducted for an existing 13-story building to demonstrate the functionality evaluation and showcase how its results can guide the retrofit measures for improved seismic performance.

Correlated Rare Failure Analysis via Asymptotic Probability Evaluation

In this article, a novel asymptotic probability evaluation (APE) method is proposed to estimate the probability of correlated rare failure events for complex integrated systems containing a large number of replicated cells. The key idea is to approximate the failure rate of the entire system by solving a set of nonlinear equations derived from a general analytical model. An error refinement method based on look-up table is further developed to improve numerical stability and, hence, reduce estimation error. Furthermore, a statistical algorithm based on resampling is developed to accurately estimate the confidence interval of APE. Our numerical experiments demonstrate that compared to the state-of-the-art method, APE can reduce the estimation error by up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$30\times $ </tex-math></inline-formula> without increasing the computational cost.

A hybrid GMDH neural network and logistic regression framework for state parameter–based liquefaction evaluation

The cyclic stress or liquefaction behavior of granular materials is strongly affected by the relative density and confining pressure of the soil. In this study, the state parameter accounting for both relative density and effective stress was used to evaluate soil liquefaction potential. Based on case histories along with the cone penetration test (CPT) database, models for calculating the state parameter using a group method of data handling (GMDH) neural network were developed and recommended according to their performance. The state parameter was then used to develop a state parameter–based probabilistic liquefaction evaluation method using a logistic regression model. From a conservative point of view, the boundary curve of 20% probability of liquefaction was suggested as a deterministic criterion for state parameter–based liquefaction evaluation. Subsequently, a mapping function relating the calculated factor of safety (FS) to the probability of liquefaction (PL) was proposed based on the compiled CPT database. Based on the developed PL–FS function, a new risk criterion associated with the state parameter–based design chart was proposed. Finally, a flowchart of state-based probabilistic liquefaction evaluation and quality control for ground-improvement projects was presented for the benefit of practitioners.

Probabilistic double hierarchy linguistic alternative queuing method for real economy development evaluation under the perspective of economic financialization

With the development of science and technology, the new road of scientific economic and financial development has played a decisive role in supporting the financial undertaking. To accelerate the economic development, it is very important to increase the guiding role of financial undertaking in the real economy. Therefore, it is necessary to promote the development of the real economy under the perspective of economic financialization based on some actions. To judge the implementation effect of these actions, this paper develops a multiple criteria decision-making (MCDM) method to evaluate them. First, the decision-making matrices are established with the probabilistic double hierarchy linguistic term set in which the probabilities are added to all double hierarchy linguistic terms. Additionally, a weight-determining method is developed to obtain the weight vector of criteria, and we develop a MCDM method named the probabilistic double hierarchy linguistic alternative queuing method (PDHL-AQM), where the decision-making result is intuitive by a directed graph or a 0–1 precedence relationship matrix. Furthermore, we apply the PDHL-AQM to solve a practical MCDM problem involving the real economy development evaluation under the perspective of economic financialization. Finally, some comparative analyses are made to show the advantages and reasonableness of the PDHL-AQM.