Probabilistic Assessment Research Articles

Construction of statistical recognition algorithms based on two-dimensional threshold functions

The recognition problem often rises in the classification of multidimensional data and is an integral part of artificial intelligence. Currently, there are many well-known methods and algorithms for solving the recognition problem. However, these methods are mainly aimed at solving such problems where objects are described by a set of independent features. A large number of features describe recognition problems in various fields of human activity. In such problems, the probability of violating the assumption of feature independence is quite high and this determines the relevance of this study.The purpose of this study is to develop a model of recognition algorithms based on the method of making statistical decisions, taking into account the high dimensionality of feature space.A statistical approach to solving the problem of recognition under the conditions of the high dimensionality of feature space is proposed. On the basis of this approach, a model of statistical recognition algorithms based on the construction of two-dimensional threshold rule is proposed. The main advantage of the proposed model is the reduction in the volume of computational operations when recognizing objects in the test set. At that, the reduction of the volume of computational operations is ensured using a number of procedures: selection of representative features; building a two-dimensional threshold rule; determination of a set of reference two-dimensional threshold rules; determination of basic two-dimensional threshold rules and calculation of a probabilistic assessment of the object belonging. This characteristic is very important for real-time recognition systems.The operability of the proposed model of recognition algorithms was investigated in the course of experiments in solving a model problem and the problem of recognizing a person's identity from a signature image. The results of the computational experiment confirm the operability of the proposed approach in solving the recognition problem under conditions when the assumption of feature independence is not satisfied. The results of experimental studies show that the proposed statistical algorithms increase the accuracy of recognition and significantly reduce the volume of computational operations by recognizing an unknown object specified in the space of interrelated features. These algorithms can be used in the compilation of various software systems focused on solving applied recognition problems in the conditions of the high dimensionality of feature space.

Multivariate probabilistic assessment of a regional database in Copenhagen

Extensive research has been carried out to establish empirical equations between two geotechnical properties and in spite of the increase in correlation studies, a construction of a multivariate distribution function of more than two parameters is still rare. The objective of this study is to investigate the possibility of constructing two multivariate distribution functions, each consisting of 5 geotechnical parameters based on a) triaxial and soil classification tests and b) oedometer and soil classification tests in stiff over-consolidated clay till from Copenhagen. For this purpose, laboratory measurements from twenty-six sites in Copenhagen are utilized and two multivariate databases are constructed. The correlations among the ratio of deviatoric and mean effective stresses (q/p´), over-consolidation ratio (OCR), secant modulus at reference stress 100 kPa (E50ref), initial void ratio (eo) and liquid limit (LL) are investigated in multivariate model A, while multivariate model B demonstrates the correlations among oedometer modulus at 100 kPa reference stress (Eoed(ur)ref), over-consolidation ratio (OCR), permeability change index (Ck), initial void ratio (eo) and liquid limit (LL). The Nataf transformation model is used for the construction of the multivariate distributions, which are then used to simulate the correlations between geotechnical properties by generating artificial samples. Finally, the artificial samples are compared with the original database for an initial validation of the model. The constructed multivariate models obtained as a result of this study can act as prior for Bayesian updating in multivariate distribution functions when additional geotechnical tests are carried out.

Improving Reliability of Active Distribution Networks Using Probabilistic Assessment of Renewable Resource Units

Improving Reliability of Active Distribution Networks Using Probabilistic Assessment of Renewable Resource Units

Good Seamanship Score Quantification in Complex and Congested Waterways

This paper presents a novel method to quantify seafarers’ good seamanship during navigation scenarios with multi-vessel encounters, in open and confined waters, and to compute COLREG's-compliant path deviations for avoiding collision and grounding. Accurate quantification of good seamanship necessitates comprehensive information about the vessels state and the surrounding environment, obtainable through the AIS system and electronic nautical charts. Our work advances the current state-of-the-art by: (1) incorporating a normalized grounding risk for navigating confined waters, (2) factoring in speed changes for a probabilistic assessment of collision risk, and (3) considering the minimum possible scenario risk based on vessel kinodynamic constraints. The proposed method is evaluated using historical AIS data and sea charts of Danish waters. The evaluation results demonstrate improved fairness scoring by acknowledging that navigators may lack risk-free options.

SAFETY ASSESSMENT OF CONTINUOUS CONCRETE GIRDER BRIDGES SUBJECTED TO RANDOM TRAFFIC LOADS CONSIDERING FLEXURAL-SHEAR COUPLED FAILURE

Bridges generally perform complicated mechanical behaviors under external loads, such as flexural-shear coupling, compression-bending coupling, and flexural-shear-torsion coupling. In the context of deterministic design approaches such as design codes, these complicated coupled issues are generally simplified to the safety verification of bridge components under a single mechanical state (i.e. flexural, shear, torsion). At present, the rapid development of sensor and information technologies makes it possible to collect the external loads acted on bridges and understand bridge performance under these stochastic external loads. In this manner, the reliability-based full probabilistic approach could be applied to investigate the performance of bridges over their lifetime. However, the current bridge reliability assessment incorporating realistic traffic load measurements mainly focuses on the analysis of bridge components under a single mechanical state. In this paper, a reliability-based probabilistic analytical framework of the flexural-shear performance of girder bridges under random traffic loading is established. The flexural-shear coupled failure path of bridge girders under random traffic loading is characterized for the first time, where the bivariate extreme value theory is incorporated to develop the extreme value distribution of combined flexural and shear load effects. The modified compression field theory recommended by AASHTO is employed to establish the coupled flexural-shear coupling resistances. Finally, the reliability of the flexural-shear performance of bridge girders is evaluated by solving the multivariate ultimate limit state equation. The proposed analytical framework is applied to a realistic bridge. The results show that the reliability index of the flexural-shear coupling evaluation is lower than that of the flexural or shear evaluation, which highlights the importance of the flexural-shear performance checking in the reliability assessment of bridges under random traffic loading. The proposed analytical framework could be further applied to the probabilistic assessment of bridge components subjected to combined loading mechanisms under random loadings.

Detailed seismic zoning of the East Kazakhstan region in the Republic of Kazakhstan

Kazakhstan is currently drafting new construction regulations that comply with the major provisions of the Eurocodes. Such regulations are created on the basis of seismic zoning maps of various degrees of detail, developed by our Institute of Seismology using a new methodological approach for Kazakhstan. The article is about creating the first normative map of the Detailed Seismic Zoning on a probabilistic foundation for the Republic of Kazakhstan's East Kazakhstan region. We carried out the probabilistic assessment of seismic hazard using a methodology consistent with the main provisions of Eurocode 8 and updated compared with that used in developing maps of Kazakhstan's General Seismic Zoning and seismic microzoning of Almaty. The most thorough and current data accessible for the area under consideration were combined with contemporary analytical techniques. Updates have been done to not only the databases being used but also the way seismic sources were shown, including active faults now. On a scale of 1:1000000, precise seismic zoning maps of the East Kazakhstan region were created for two probabilities of exceedance: 10 % and 2 % in 50 years in terms of peak ground accelerations and macroseismic intensities. The obtained seismic hazard distribution is generally consistent with the General Seismic Zoning of Kazakhstan's previous findings. However, because active faults were included and a thoroughly revised catalog was used, there are more pronounced zones of increased danger along the fault in the western part of the region. In the west of the territory, acceleration values also increased due to a more accurate consideration of seismotectonic conditions. Zoning maps are the basis for developing new state building regulations of the Republic of Kazakhstan.

Increasing the reliability of the probabilistic assessment of the forecast for identifying oil- and gas-bearing local structures during geological exploration work on a geodynamic basis

On the basis of tectonophysical models at the regional and local levels, the paper provides an analysis of the role of geodynamic factors that increase the likelihood of assessing the detection of oil- and gas-bearing structures at geological exploration stages. It proposes a consideration of geodynamic criteria during prospecting works to develop and substantiate scientific and methodological approaches to the possibility of accumulation and preservation of hydrocarbon components in the sedimentary cover structures. The obtained results allow to correct the geological model of the proposed field in the area of structural heterogeneity, to reveal the connection between productive formations, as well as the other factors, for the successful discovery of economically viable development targets.

Probabilistic fatigue strength assessment of cross-ply laminates: Exploring effects of manufacturing defects through a two-scale modeling approach

The study presents a two-scale modeling approach allowing for an efficient fatigue strength evaluation on a macro scale considering a micro-mechanical defect characterization of a Carbon Fiber Reinforced Polymer (CFRP) material. The modeling approach integrates a macro model with the effective elastic properties from micro-mechanical simulations considering voids. This enables the analysis of defects’ influence on material fatigue strength using a probabilistic weakest link approach. A CFRP laminate with a cross-ply layup was investigated. Two simulation case studies demonstrate the effect of void content and size on the characteristic fatigue strength. An experimental investigation was conducted testing the laminates in tension–tension fatigue verifying the predicted numerical behavior. The numerical models identify a difference in the characteristic fatigue strength consistent with the fatigue test results. It is numerically concluded that the investigated CFRP material’s fatigue strength is affected by the presence of voids and even with only a slight difference in the global void volume fraction a scatter in fatigue strength is identified.

Methodology of creation and development of information systems for technological safety of mining facilities

Purpose. To develop methodological approaches to the process of informatization of technological security (TS) and to propose a project of step-by-step development of the architecture of information system (IS) of TS, which will contribute to effective integration of digital and mining technologies. To develop a mathematical model for finding the number of sensors required for probabilistic assessment of the concentration gradients of hazardous gases. Methodology. General and special methods of knowledge are used: structural analysis – to establish the structure and tasks of IS of TS; logical generalization – for formation of methodological system of directions of TS information measures; system analysis – to establish synergistic effect of complex implementation of the indicated directions; scientific abstraction – for development of a project for IS architecture derivation; mathematical formalization – for development of mathematical model for estimating gradients of concentration gases and the number of sensors. Findings. A project for the phased development of IS architecture of mining facilities based on the implementation of diffusion principle is developed, which will allow solving a complex of issues: integrated monitoring of danger of gas environment of underground structure for detection of gas traps and permanent determination of concentration gradients of hazardous gases, implementation of intelligent safety loops using analytical resources of technological mining process. A methodological system of directions for diffusion implementation of TS information measures is formed. The use of the method of system analysis made it possible to point out the synergistic effect of the complex implementation of the directions of implementation of TS information measures. Originality. A project for the phased development of the information system architecture of the technological safety of mining enterprises has been developed. A mathematical model has been developed to estimate the concentration gradients of hazardous gases and the number of sensors to ensure the appropriate level of probability of finding a sensor in each cell of the underground mine. Practical value. The methodological approach makes it possible to form an IS that implements a comprehensive approach to ensuring the appropriate level of technological safety of mining facilities.

Feature selection of ground motion intensity measures for data‐driven surrogate modeling of structures

AbstractIn the probabilistic seismic performance assessment of structures, intensity measures (IMs) represent seismic characteristics and variations. Traditional fragility analysis method based on the assumption of linear regression requires selecting an optimal IM as input variable. By introducing machine learning (ML) techniques, nonparametric fragility analysis theoretically allows for considering all potential IMs as inputs. Nevertheless, to reduce input dimensionality and improve training efficiency, the feature selection of IMs remains imperative. This paper proposes a method to select optimal ground motion IMs for data‐driven surrogate modeling of structures. Specifically, the elastic net algorithm is employed to select the optimal multiple IMs based on the coefficient of determination and regression coefficient, differing from the efficiency and practicality emphasized in the traditional method. Using the optimal multiple IMs as input variables, several ML techniques are employed to construct surrogate models for seismic damage assessment of structures, thereby developing fragility functions, that is, the conditional probability of exceeding a damaged state given seismic intensity. A 3‐span, 6‐storey, reinforced concrete frame is utilized to illustrate the proposed methodology. The predictive performance of all ML models with the optimal multiple IMs outperforms that of the models with the commonly used IM (e.g., peak ground acceleration, PGA) as sole input and all candidate IMs as inputs. Additionally, the surrogate models with the optimal multiple IMs enable a more comprehensive seismic fragility modeling of structures under two or more IMs simultaneously, such as the fragility surface under spectral acceleration at 1.0s (Sa‐1.0s) and velocity spectrum intensity (VSI).

Probabilistic seismic assessment of multispan RC highway bridges considering soil-structure interaction and chloride-induced corrosion

Deterioration mechanisms, such as chloride-induced corrosion, affect bridges in aggressive environments, making them more vulnerable to extreme events like earthquakes. Although many studies have assessed the impact of chloride-induced corrosion on the seismic vulnerability of reinforced concrete (RC) highway bridges, several gaps still need to be addressed. Accordingly, this research primarily focuses on evaluating the seismic performance of RC highway bridges in aggressive environments susceptible to chloride-induced corrosion and earthquakes. To achieve this, a probabilistic framework is employed, which incorporates uncertainties associated with corrosion progression, seismic events, and the impact of different modeling approaches for boundary condition. The framework considers the time-dependent effects of corrosion on the physical and material properties of steel and concrete in bridge columns. Monte Carlo Simulations (MCS), probabilistic seismic hazard analysis (PSHA), and record selection strategies are utilized to address the uncertainties in corrosion and seismic demand. Nonlinear dynamic models and multiple stripe analysis (MSA) are employed to obtain fragility surfaces and curves for main bridge components and the entire system under different boundary conditions. The study focuses on a five-span highway bridge with simply-supported prestressed concrete I-girder and RC multi-column bents located in Chile. The results reveal that elastomeric bearings are the most vulnerable components, exhibiting varying vulnerability levels under different corrosion exposure and boundary conditions. Abutments, although the second most susceptible, are unaffected by corrosion uncertainty in terms of seismic fragility. Bridge columns are identified as the third most vulnerable components, with the probability of exceeding slight damage state consistently increasing with more prolonged corrosion exposure. It is noted that only flexure failure mode in column is analyzed and possible shifting to shear or flexure-shear modes is not accounted for. The findings of this study underscore the exceptional resilience of Chilean highway bridge columns to seismic demand and corrosion uncertainties, contrasting with the situation in US regions where columns are more vunerable. Additionally, the study indicates that Soil-Structure Interaction (SSI) tends to reduce bridge vulnerability under combined corrosion and earthquake effects. The insights obtained from this study and the proposed framework can inform the development of maintenance programs based on bridge performance expectations and enhance the seismic resilience of bridge systems worldwide.

“Practical elimination” principle in the Akkuyu Nuclear Power Plant design

The paper considers the implementation of the “practical elimination” principle in the design of the Akkuyu NPP with VVER1200 reactors being under construction in Turkey. The “practical elimination” principle is defined as follows: for accident sequences or phenomena that contribute or lead to unacceptable radiological consequences for the public or the environment, it shall be shown with a high level of confidence that their occurrence is highly unlikely. “Practical elimination” is proved predominantly by results of a Level 2 probabilistic safety assessment. The implementation of the “practical elimination” principle was considered at the level of accident sequences leading to a large radioactive release. It has been shown that each accident sequence leading to an unacceptable release has the probability of occurrence below 4.45Е–8 per reactor per year, while their total probability not exceeding the value of 6.17Е–7 per reactor per year. For the phenomena inside the containment area during severe accidents, including hydrogen detonation, a large thermal explosion, direct containment heating, overpressure in the containment volume, and the containment damage at later stages due to the basement melting through, their “practical elimination” has been demonstrated. The paper also considers specific hard-to-assess scenarios of beyond design basis accidents, for which the applicability of the “practical elimination” principle is assessed as well: a major positive reactivity insertion, a rupture of the reactor pressure vessel and other largescale components, damage of fuel elements in the spent fuel pool, severe accidents with the containment bypass or containment failure, and severe accidents accompanied the means for mitigating with their consequences being unavailable. Criteria have been developed and used for the “practical elimination” assessment. A sensitivity analysis was undertaken as part of the Level 2 probabilistic safety assessment which has shown that estimated values slightly depend on the analytical assumptions, as well as on the random change in the parameters that the affect the progression of severe accidents.

Probabilistic autoencoder-based bridge damage assessment using train-induced responses

Structural health monitoring (SHM) systems have been increasingly employed to continually assess the current state of bridges. However, the vast amounts of sensor data generated by SHM systems, along with constantly changing environmental and operational conditions, make structural damage assessment a computationally demanding and challenging task. Traditional data-driven approaches primarily utilise machine learning methods for pattern recognition and feature extraction to address this issue. This paper introduces a methodology for assessing bridge conditions using a probabilistic temporal autoencoder (PTAE). The proposed approach effectively extracts features and captures temporal relationships in multi-sensor data collected only during train crossings. By calculating the reconstruction loss and KL divergence-based of damage features, the methodology enables the identification of potential damage of a monitored bridge. An Exponentially Weighted Moving Average (EWMA) filter and a control chart-based threshold mechanism are applied to further refine the damage assessment process, facilitating the distinction between healthy and progressively deteriorating damage cases. The proposed method is adaptable to various monitoring scenarios and sensor configurations, and robust to varying operational and environmental conditions. The effectiveness of the methodology is assessed using numerically generated data and validated with real-world data from the KW51 bridge. The results demonstrate that the proposed method can detect damage with a limited number of sensors, making it a valuable approach to enhance bridge safety.

Dietary Exposure to Polycyclic Aromatic Hydrocarbons and the Probabilistic Health Risk Assessment of Eating Roasted Yams (Dioscorea Species) by African Population

The roasting of food is one of the oldest food preparation and preservation technologies. Although roasted foods have been associated with potential health hazards, this processing method is still used in many foods. This study was carried out to ascertain the health risks of ingesting white (Dioscorea rotundata), and bitter yam (Dioscorea dumetorum) roasted with firewood, charcoal, and charcoal augmented with PET bottles. The PAH content in all the roasted yam samples was identified and analyzed using gas chromatography-mass spectroscopy (GC-MS). A total of 8 PAHs were identified in both yam species; however, bitter yam roasted with augmented charcoal contained 9 PAHs. The total EDI showed that bitter yam roasted with augmented charcoal (6.59E-1) had the highest PAH content while white yam roasted with only charcoal contained the lowest (1.27E-1). The hazard quotients and indexes revealed that bitter yam had the highest HQ in all the roasting methods except for napathalene, fluoranthene and benzo (a) pyrene in samples roasted with charcoal. The HI for both species in all the roasting methods was above 1 (>1), while firewood produced the highest HI. Benzo (a) anthracene was the most potent PAH identified across the yam species and the roasting techniques. The evaluated ILCR showed that dibenzo (a, h) anthracene identified in white yam smoked with charcoal had the highest tendency to cause cancer (6.38E-1) while the least PAH was acenaphthylene (3.35E-6) which was seen in bitter yam roasted with charcoal. Therefore, it is necessary to inform the consumers of the possible health implications associated with consuming roasted yams and especially yam roasted with augmented charcoal

Основные расчетные гидрологические характеристики систем очистки поверхностного стока в северо-западной зоне России

Purpose: The normative and methodological documents in Russia regarding the treatment of surface runoff from residential areas do not provide explanations on the effectiveness of the treatment system from the point of view of the possibility of pollution of water bodies they allow. The probability of pollution and the dilution ratio of untreated wastewater have not been studied. The goal is to develop a method for determining the hydrological characteristics of the runoff necessary for the probabilistic assessment of dilution factors, permissible concentrations and discharges of contaminated surface waters. Methods: Based on observational data from fourteen weather stations in the North-West of Russia, the probabilistic relationship between the characteristics of runoff from built-up areas and the receiving river has been studied, taking into account the basics of probability theory and hydrological calculations of minimum runoff. Calculations have been carried out and the dependence of the number of days with precipitation and their relative amount in the warm period of the year on the maximum daily precipitation layer has been established. A mathematical relationship has been found between the frequency of rain and the number of possible cases of pollution of a water body. Results: A method has been developed for calculating the probable values of precipitation characteristics, minimum water runoff in the receiving river and the dilution factor of pollutants depending on the permissible frequency of negative consequences from river water pollution and the correlation coefficient of the probability of minimum water flow from built-up areas and in the receiving river. Practical significance: The method for calculating the hydrological characteristics of runoff will make it possible to more reasonably and accurately determine the required degree of wastewater treatment, the productivity and parameters of treatment facilities, and in some cases, to reduce the degree of pollution of watercourses.

Fluoride in Raw Rice (Oryza sativa): a Global Systematic Review and Probabilistic Health Risk Assessment.

Rice (Oryza sativa) is one of the essential staple foods highly consumed globally, with nearly 40% to 45% of the global population estimated to consume rice. Therefore, consumable rice should have low levels of harmful elements. This study investigates fluoride (F¯) content in raw rice (uncooked rice) and evaluates Probabilistic Health Risk Assessment (PHRA) through Monte Carlo simulation (MCS) due to the consumption of F¯ enriched rice. The literature review reveals that limited studies have been conducted on the investigation of F¯ in raw rice. The fluoride (F¯) concentration in raw rice varies across the studied countries, indicating the need for additional studies to facilitate a more accurate comparison. The F¯ content in raw rice varied among the studied countries, making it difficult to definitively state that the concentration of F¯ in one country is higher. However, the concentration of F¯ in raw rice in India is notably elevated. This study also highlighted the importance of investigating the F¯ content in raw rice. The study will be highly helpful for policymakers to formulate guidelines for water used for irrigation.

Research on Economic Trade and Cultural Value of the China-Russia Ten Thousand Mile Tea Route by Integrating Probabilistic Assessment Models

Abstract According to the relationship between the economy and trade of the tea ceremony in foreign markets, this paper establishes the economic output model of tea in the tea ceremony in China and Russia, and at the same time, considering the spring tea frost disaster, combined with the probability model, the economic loss rate of tea frost is quantitatively evaluated. Through the analysis of social network and semantic network diagram, the semantic related high-frequency words were classified into the concept of tea culture, and the correlation between high-frequency words about tea culture was obtained. According to the comprehensive influence of domestic factors and foreign factors, the index system of influencing factors of tea export value was determined, and the prediction model of China’s tea export value based on CNN-BSO-LSTM algorithm was constructed by using big data technology, and the tea economy and culture from the perspective of Sino-Russian tea ceremony were studied and analyzed. The results showed that the three indexes of CNNBSO-LSTM were 0.9431, 8850212 and 4.112, respectively, which performed better than other models. The CNN-BSOLSTM model predicts that China’s tea exports will reach around RMB 3.5 billion in 2025, up significantly from RMB 2.3 billion in 2022. This study promotes the economic and cultural exchanges between China and Russia, and is of great significance for promoting the rise and development of urban belts along the Belt and Road.

Probabilistic Assessment of the Intake of Trace Elements by Consumption of Red Deer (Cervus elaphus) and Wild Boar (Sus scrofa) Meat

The aim of this work was to study the nutritional value of game meat through the fulfillments of Dietary Reference Intakes (DRI) for trace elements (Co, Cr, Cu, Fe, Ni, Se, and Zn). A probabilistic model (@Risk) was developed based on the consumption data of hunter-consumers obtained from a previously published survey. Two game species widely consumed in Europe were selected: red deer (Cervus elaphus) and wild boar (Sus scrofa). Red deer muscle had the highest content of Cr (0.25 mg/kg) and Zn (44.3 mg/kg) and wild boar muscle recorded the highest Cu (2.23 mg/kg), Ni (0.60 mg/kg), and Se (0.19 mg/kg), showing statistically significant differences between the two species for these elements. No statistically significant differences were found for Fe between both game species (red deer: 52.9 mg/kg and wild boar: 53.3 mg/kg). Co content in this kind of meat was negligible for both species. The results obtained from the simulation of the probabilistic model with red deer indicated that a consumption once per week of this meat fulfills Cr, Fe, and Zn DRIs for the 95th percentile in hunter-consumers. Regarding wild boar, the values obtained also fulfill the Fe DRI and were between 61 and 75% for the rest of the trace elements analyzed.

Markov chain‐assisted stochastic model of crack growth rate

AbstractOne of the most essential tasks in probabilistic damage tolerance assessment is to describe the scatter in crack growth accurately. This study proposes a stochastic model of the crack growth rate, which calculates the critical parameters of a random distribution accurately by combining the Markov chain and data fitting algorithms. The proposed method is validated by the crack growth test data of Ni‐based superalloy GH4710Li at 550°C. The validation results show that the proposed method is a robust and efficient stochastic model for the crack growth rate.

The role of risk-informed approaches for advanced reactors in Korea

Currently, various types of advanced reactors are being developed in the Republic of Korea, including (1) advanced large power reactors, (2) light water–based small and modular reactors, and (3) Generation IV reactors. While Probabilistic Safety Assessments (PSAs) have been performed for these advanced reactors in Korea, the PSAs were not conducted in detail since they were not regulatory requirements in many cases. However, the role of PSA is changing in Korea nowadays, and qualified PSA models have recently become an essential element in the licensing of operating and new reactors. In addition, PSAs for advanced reactors are essential not only to meet regulatory requirements but also to improve the safety and performance of advanced reactors. It can be said that the success of advanced reactors depends on how their safety and economics can be secured effectively and efficiently. The PSA will play an essential role in this aspect. Various risk-informed approaches (RIAs) based on PSAs are used in many countries worldwide for this purpose. A few issues remain to be resolved for the success of PSAs and RIAs for advanced reactors, such as the development of licensing frameworks for advanced reactors, the reliability assessments of passive safety systems, and so on. In this paper, we introduce the current status of PSAs and RIAs for advanced reactors, including descriptions regarding the characteristics of advanced reactors currently being developed in Korea. We also discuss some important issues to be resolved for the success of RIAs for advanced reactors. We also briefly introduce some research performed to resolve those issues.