Probabilistic Risk Assessment Research Articles

Prepare for the sustainability era: A quantitative risk analysis model for container shipping sustainability-related risks

Environmental, social, and governance (ESG) issues have attracted global stakeholders' attention, reflecting the focus of sustainability development in this sustainability era. Container shipping is confronted with a wide spectrum of sustainability-related risks during the ESG transformation. Theoretically, this research identifies 36 sustainability risks of container shipping, establishes a customised evaluation framework for container shipping sustainability risks, and quantifies the risks regarding their threatening levels. The five most threatening risks are ‘reinforcement of international emission control policy’, ‘global climate change’, ‘shipping equipment failure’, ‘fuel price volatility’, and ‘ship violates the emission control policy in port area’. The results show that the long-term likelihood as well as environmental and profit impacts of sustainability risks are the most important criteria. Managerially, this research shows that environmental risks are generally the most prioritised risks, while social risks are not significantly impactful to container shipping companies. However, among the social risks, seafarer-related risks are worth paying attention.

Perancangan Risk Assessment dengan Metode Kualitatif dan Kuantitatif pada Proyek Pembangunan Ruko di PT XYZ

PT XYZ, a contractor company in the construction sector, is currently working on a project to build 24 shop houses on Jl. Hospital, Bandung City, with a duration of 21 weeks from June to November 2024. This project is divided into several works, including preparation, structure, installation, plumber installation, electrical installation, and wall painting. The project faced challenges such as work accidents, material delays, and conflicts between foremen and subcontractor workers. Due to the lack of effective risk assessment, PT XYZ has difficulty providing a significant response to this problem. Research was conducted to design a risk assessment that includes qualitative and quantitative risk analysis. Qualitative methods are used to create probability impact matrices, risk watch lists and priority risks, while quantitative methods are used to calculate sensitivity analysis related to risk costs. From the research, 186 negative risks and 5 positive risks were found with classifications ranging from insignificant to catastrophic, with the largest risk cost reaching IDR 851,529,000. Researchers also designed contingency plans, checklist forms, material quality checks, and risk reporting to assist PT XYZ in handling project risks.

Quantitative assessment of well leakage, part I: Cement stress evolution

A damaged cement sheath in wells can open a leakage pathway to shallow freshwater aquifers and atmosphere. Quantitative assessment of leakage along wells has become an area of interest for both the industry and the regulatory bodies. The well leakage can be of importance in both active and legacy wells. In order to estimate leakage through cement sheaths, the size of the leakage pathway and the damage in the cement sheath must be estimated. In this work, we have developed a hydro-thermo-mechanically coupled near-well model that aims to calculate the evolution of cement’s stress as it cures. This process takes into account the cement’s gradual increase in stiffness, chemical shrinkage, and the heat of hydration. The results are verified using lab measured cement stress and pore pressure data from the literature. A case study was developed based on a low-enthalpy geothermal doublet in the Netherlands. The results show that during the cold water injection, an outer microannulus may open to 60 µm. The presence of an external source of water and formation stiffness are of significant importance in determining the damage to the cement sheath. The heat of hydration in cement increases the temperature of cement during curing. The subsequent drop in temperature due to drilling or completion reduces the cement stress and exacerbates the damage to the cement sheath. The producer well may not form a microannuli, however shear and cyclical failure may be of higher likelihood. The modelling framework presented here allows for estimation of annular cement stress in the well. The analysis provides quantitative estimates of the size of the leakage pathway along a well that can be used to estimate well leakge. Quantitative estimate of well leakage provides crucial information for quantitative risk analysis and provides a framework to optimize well operations to minimize leakage risk.

S15-04 The use of artificial intelligence in risk characterization through probabilistic risk assessment

S15-04 The use of artificial intelligence in risk characterization through probabilistic risk assessment

Computationally efficient Complete-Sampling-based fault tree analyses for seismic probabilistic safety assessment of nuclear facilities

The seismic risk of nuclear power plants (NPPs) can be assessed through seismic probabilistic safety assessment (PSA) based on fault tree analyses (FT). The conventional FT-based approach has limitations for handling the correlated relation of basic events and utilizing the sampling-based FT analysis for addressing such issues demands considerable computational cost. In particular, accurate consideration of the partial dependences between the failure probabilities of NPP components in seismic hazard events can further increase the computational cost of risk quantification. Therefore, this paper presents an improved complete-sampling-based seismic PSA risk quantification method. The novelty of this method is that it increases the efficiency of the risk quantification by introducing sequential sampling and truncation to the conventional fault tree analysis. In addition, as sub-concepts, we eliminate unrequired sampling extraction steps via integrated multivariate response distribution-based sampling for components and continual evaluation of the convergence of system failure probabilities. On three considered examples, including an actual NPP, the proposed method requires 91%–96% fewer samples than the conventional method, without sacrificing accuracy. These results indicate the efficiency of the proposed method, which is expected to become a useful tool in the future.

Development of an integrated framework for dissecting source-oriented ecological and health risks of heavy metals in soils

Heavy metals (HMs) in soils pose significant risks on ecosystem and human health. To design targeted regulatory measures for mitigating and controlling the risk, it is necessary to accurately identify the pollution sources and environmental risks of soil HMs, as well as to reveal the linkages between them. To date, yet systematic investigation aimed at deciphering the links between source apportionment of soil HMs and their associated environmental risks is still lacking. To fill the gap, an integrated framework has been developed in this study and applied for dissecting the source-sink relationship and source-oriented ecological and health risks of soil HMs in Shanxi, a province with rich coal resource, in which long-term coal mining activities in history has resulted in soil HMs pollution and unavoidably posed environmental risks. Two advanced receptor models, multivariate curve resolution alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA) and multilinear engine 2 (ME2), have been employed for apportioning the potential sources, and their apportionment results are jointly incorporated into a modified ecological risk index and a probabilistic health risk assessment model for identifying the source-oriented ecological and health risks posed by soil metals. The results show that the soils in study area have been polluted by HMs (i.e., Cd, Cr, Hg and As) to varying degrees. Industrial activities (35%–35.8%), agricultural activities (11.1%–20.5%), atmospheric deposition (10.5%–13%) and mix source (31.5%–42.6%) are apportioned as the main contributors of soil HMs in the area. The source-oriented ecological risk assessment suggests Hg has presented significant ecological risk and largely contributed by the sources from atmospheric deposition and industrial activities. The source-oriented health risk assessment shows the non-carcinogenic hazard level and carcinogenic risk posed by soil HMs in the study area are acceptable. Relatively, industrial activities and mix source have contributed more on the health risks.

Seismic correlation coefficient evaluation for the application of separation of variables approach in fragility assessment

Seismic correlation can affect seismic probabilistic risk assessment results when components within the system have similar dynamic characteristics. While the fragility assessment methodology is well established, researches to evaluate and apply seismic correlation in fragility are still in progress. In this study, the seismic correlation coefficient (SCC) was quantitatively analyzed based on fragility assessment methods. In order to evaluate the SCC of several random variables associated with structure response in fragility assessment, a numerical analysis model of the structure was constructed and statistical analysis of the numerical results was performed. The SCC of the floor responses of the structural model considering random variables was evaluated from two perspectives. The first perspective involved applying variables individually or simultaneously when performing probabilistic structural analysis. The second perspective aimed to assess whether simplification of the structural analysis model affects the SCC. For this purpose, SCCs were calculated for each method and applied to a simplified failure sequence model to compare the combined fragility curves. The results of this study demonstrate the applicability of separation of variables method to the evaluation and generalization of the SCC for random variables of the fragility curve.

Quantitative risk analysis of road transportation of hazardous materials in coastal areas

Given the complex climate conditions in coastal areas and their role as key transportation hubs for hazardous chemicals, this study proposes a method to quantitatively and comprehensively evaluate transportation risks. Initially, accident data were analyzed to identify risk factors from five aspects: human, vehicle, materials, environment, and management, based on system safety theory. Subsequently, a risk analysis model was developed using Decision-making Trial and Evaluation Laboratory, interpretive structural model theory, and Bayesian theory to quantitatively assess accident risk levels. The model was applied to a case involving a hazardous chemical accident on a cross-sea bridge, where Bayesian backward reasoning was used to analyze the sensitivity and importance of risk factors. This approach facilitated the key risk factors affecting the safety of hazardous chemical transportation systems. Notably, the study incorporated scenarios involving hazardous material transport vehicles crossing sea bridges into the risk assessment framework, offering valuable insights for management authorities. It also considered the impact of strong side winds-a factor often overlooked-in hazardous material transport. The validation process demonstrated that the method accurately quantifies the risk of hazardous chemical transportation and identifies the key factors influencing accident occurrence. The research highlights that strong gusts of wind significantly impact safety, and human factors are crucial in the overall risk system.

Airborne concentrations of bacteria and mold in Korean public-use facilities: measurement, systematic review, meta-analysis, and probabilistic human inhalation risk assessment.

Bioaerosols adversely affect human health posing risk to users of public facilities in Korea. Between October 2021 and May 2022, airborne bacteria and mold were measured in 1,243 public-use facilities across 23 categories. A systematic review and meta-analysis were performed on these and other studies from June 2004 to May 2021, and the non-carcinogenic risks to humans were assessed using Monte Carlo simulations. For bacteria, the maximum 95th percentile concentration was 584.4cfu/m3 and 1384.8cfu/m3 for mold. The heterogeneity statistic I2 was over 50% in all facilities, and for subway station bacteria, there was a significant difference according to the measurement method. The 95th percentile of hazard by population group was 8.83 × 10-2 to 3.42 × 10-1 for bacteria, and 1.31 × 10-1 to 3.55 × 10-1 for mold. The probability of a hazard quotient exceeding 1 for some population groups was derived from exposure to bacteria and mold in the air resulting from the use of all public facilities. The most powerful explanatory factor for risk was exposure time to the facility, both within (up to 0.922 for bacteria and up to 0.960 for mold) and between populations (up to 0.543 for bacteria and 0.483 for mold). This study identified populations at risk of bioaerosol exposure in Korean public-use facilities and estimated the influencing factors, highlighting the need for comprehensive improvement in bioaerosol control in public-use facilities.

Analysis of 3-MCPD and 1,3-DCP occurrence in mayonnaise: A probabilistic risk assessment of dietary exposure for Iranians

Mayonnaise is a commonly used oil-in-water emulsion food product. Due to their toxicological properties/genotoxicity and carcinogenicity, chloropropanols’ oral exposure has raised concerns over the past decade. The present study reports the occurrence level of free forms of 3-chloropropane-1,2-diol (3-MCPD) and 1,3-dichloro-2-propanol (1,3-DCP) in mayonnaise samples and the risk of oral exposure to these chemicals through consumption of the analyzed samples. Mayonnaise (low- and high-fat, from 6 brands, totally 120 samples) were analyzed for 1,3-DCP and 3-MCPD by gas chromatography-mass spectrometry. The mean level of chemicals was higher in the high-fat samples, with no significant difference among the brands. Generally, 1,3-DCP level was significantly lower in both high-fat and low-fat samples compared to 3-MCPD. Hazard Index (HI) values calculated for oral exposure to 3-MCPD for Iranian adults using probabilistic methods, were less than 1.0, reflecting no major risk. In the Margin of Exposure scenario, low- and high-fat mayonnaise samples were of de minimis health concern at the 50th, 80th, and 95th centiles. Nevertheless, in order to safeguard consumer interests, it is imperative to implement online real-time methodologies for monitoring reactions that result in generation of thermal process contaminants such as 3-MCPD and 1,3-DCP, and to innovate novel technologies to minimize the occurrence of such chemicals while preserving both safety and sensory attributes.

Geographical analysis of fluoride and nitrate and its probabilistic health risk assessment utilizing Monte Carlo simulation and GIS in potable water in rural areas of Mathura region, Uttar Pradesh, northern India

Human health is being increasingly exposed to fluoride and nitrate ingestion globally due to anthropogenic alternations in groundwater resources. In the present research work, a hazard quotient (HQ), Monte Carlo simulation (MCS), and geographic information systems (GIS) have been used to estimate the non-carcinogenic health risk of nitrate and fluoride in vulnerable adults, teenagers, and children living in far-flung areas of Uttar Pradesh, Northern India. About 110 samples from some nearby populations were collected and analyzed for nitrates by ion chromatography and fluoride by a fluoride-selective electrode. The results indicated that the concentrations of fluoride and nitrate in the sampling areas ranged from 0.21 to 1.71 mg/L and 0.4–183.54 mg/L, respectively, with mean concentrations of about 1.20 mg/L and 51.52 mg/L for fluoride and nitrate, respectively. The results indicated that 27.27 % of the fluoride samples (27 out of 110) and 45.45 % of the nitrate samples (44 out of 110) were above the standard limits set by WHO. The calculated average HQ values fluoride and Nitrate for children, teenagers and adults were 1.88, 0.98, 0.90 and 3.02, 1.57, 1.45 respectively The 95th percentile HQ values for fluoride were 2.87 for children and 1.03 for adults, while those for nitrate were 4.10 for children and 1.98 for adults. Results of the health risk assessment show that there is a high potential for both non-carcinogenic and cancer risks from fluoride and nitrate through the consumption of groundwater. The Monte Carlo simulation showed the uncertainties and increased risks for children; therefore, one can infer that rural groundwater of the Mathura region, Uttar Pradesh, India, must be treated to make it potable for consumption.

Failure behavior and probabilistic safety assessment of containment structure under internal pressure considering time-varying prestress loss

This paper adopts a refined method to calculate the prestress loss of containment and evaluates the impact of time-varying effects on the mechanical properties and safety of containment under accident pressure. Firstly, a new method for converting the commonly used creep model into the Kelvin chain creep model is proposed, and rate-type constitutive relationships considering time-varying factors are established. Utilizing the developed subroutine scripts, these constitutive relationships are incorporated into the ABAQUS platform. Subsequently, the prestress losses of containment at different service times are calculated. Finally, the failure behavior and the probabilistic performance of containment under prestress loss and internal pressure conditions are systematically discussed. Results show that the proposed method exhibits high applicability, and the fitted creep compliance function based on the Kelvin chain model agrees well with the original creep compliance function. For the investigated containment, the time-varying prestress loss is most pronounced in the horizontal tendons near penetrations. Under design pressure, the containment remains elastic for all investigated prestress loss conditions, but the structural deformation, steel liner strains, and principal tensile stresses in concrete increase with the increase in time-varying prestress losses. At the limit state, greater time-varying prestress loss makes the containment more prone to functional failure at lower internal pressures. The time-varying prestress loss has a significant impact on the fragility and reliability of the penetrations in containment, while its impact on regular segments is relatively small.

Quantitative risk analysis of industrial incidents occurring on overseas tuna fishing vessels

Quantitative risk analysis of industrial incidents occurring on overseas tuna fishing vessels

Determining priority control factors for heavy metal management in urban road dust based on source-oriented probabilistic ecological-health risk assessment: A study in Xi'an during peak pollution season

Urban road dust (URD) is essential for transporting heavy metals (HMs), which can be a major danger to both the environment and human health. Moreover, URD has the potential to be carried into bodies of water, leading to contamination of the aquatic ecosystem. A study was conducted in Xi'an, a city in northwestern China known for high air pollution levels, during January 2024 - a period characterized by peak pollution due to frequent low wind speeds and temperature inversions. The research investigated the presence of 10 types of HMs (Cu, Zn, Cd, Cr, Pb, As, Ni, Hg, Co, and Mn) in URD. Findings revealed elevated levels of Cu, Zn, Cd, Cr, Pb, As, and Hg in URD compared to background levels. Hg showed the most significant contamination (moderate to heavy), followed by moderate contamination of Cd, and lower levels of As, Zn, and Cu. The main sources of HMs were traffic (58.2%), mixed natural and industrial (30.3%), and industrial (11.5%). The ecological risk in the area was deemed to be very high, primarily because of Hg and Cd. Based on probabilistic health risk assessments, it was determined that non-carcinogenic risks were deemed acceptable for all groups. Nevertheless, the possibility of carcinogenic risks should not be disregarded. Strategies for controlling ecological-health risks prioritize mixed natural and industrial sources, with a focus on Hg, Cd, and As in URD. The results offer a foundation for policymakers to create specific control strategies.

Auto-WoodSDA: A scalable end-to-end automation framework to perform probabilistic seismic risk and recovery assessment of new residential woodframe buildings

The seismic performance of residential woodframe buildings has a widespread and lasting impact on the socioeconomic vitality of a community. To enable efficient seismic risk and resilience assessment, a comprehensive framework that is rooted in performance-based earthquake engineering (PBEE) methodology is proposed. The framework is formulated as a computational workflow which is operationalized as an automation program dubbed “Auto-WoodSDA”. The end-to-end platform is developed to perform four major tasks: (1) generate code-compliant seismic design, (2) create numerical models, (3) perform nonlinear analyses, and (4) assess earthquake-induced financial losses and functional recovery time. Given the user inputs, Auto-WoodSDA sequentially executes the four tasks without intermediate human intervention to produce seismic performance metrics such as the expected annual loss. It is presented as a ready-to-implement platform that is computationally efficient and scalable in performing large-scale seismic risk and resilience assessment. An example building from the existing literature is used to demonstrate the key features of the automation framework and verify the results. The results underscore the ability of the AutoWoodSDA computational workflow to automate the generation of reliable new code-compliant woodframe building designs, perform nonlinear analysis, and assess the earthquake-induced impacts using PBEE principles.

Vibration test and fatigue test for failure probability evaluation method with integrated energy

The seismic evaluation of key components such as reactor vessel is important for the Seismic Probabilistic Risk Assessment (S-PRA) in a Sodium-Cooled Fast Reactor (SFR). Many components were fractured by integrated damage like fatigue damage during seismic ground motion. In this paper, failure probability evaluation method with integrated energy was developed by comparing the energy with vibration tests and fatigue tests. Vibration tests were performed to evaluate integrated vibration energy at failure by energy balance equation, and fatigue tests were performed to evaluate integrated vibration energy at failure based on experimental results. As results, it is shown that integrated energy at failure time by vibration tests were estimated and its values were in range the energy based on results of fatigue tests.

Enhancing safety and reliability in multistory construction: A multi-state system assessment of shoring/reshoring operations using interval-valued belief functions

Ensuring safety and reliability in multistory concrete construction necessitates rigorous assessment methodologies capable of addressing the inherent uncertainties of the construction process. This paper introduces a novel reliability assessment methodology for shoring/reshoring (S/R) operations, framed within a multi-state parallel-series system (MSS). Our approach innovatively combines concrete slab capacities, forming system strengths, and construction quality, integrating cost and time efficiencies. Central to our method is the use of Interval Universal Generating Functions (IUGF), which leverage Dempster-Shafer (D-S) theory and interval analysis to robustly estimate system reliability under uncertainty. For instance, the model considers concrete strength ranging from 0.72 × 2.1D to 0.96 × 2.1D at different curing stages, producing a system reliability index between 0.63 and 0.76, against a desired threshold of 0.8. This methodology produces interval-valued belief functions that capture a comprehensive range of potential system states and their likelihoods, offering a refined perspective on system safety. An illustrative case study demonstrates the practical application of this methodology in optimizing formwork removal and S/R schedules, significantly enhancing decision-making in construction operations. This paper aligns with the core themes of reliability engineering and system safety by addressing critical safety and reliability issues in complex technological systems through advanced probabilistic safety assessment methods. It significantly enriches the professional discourse by presenting a robust method that can be adapted across various engineering fields facing similar reliability challenges.

An integrated urban flooding risk analysis framework leveraging machine learning models: A case study of Xi'an, China

As global climate change intensifies and urbanization progresses, the frequency and extent of urban flooding have been increasing. This trend poses a significant threat to the safety and property of urban residents and severely impedes the advancement of sustainable development goals (SDGs). This study proposed an integrated urban flooding risk analysis framework to provide an essential basis for developing effective adaptation and mitigation measures. The kernel density estimation was adopted to analyze the distribution characteristics of urban flooding hotspots. The maximum entropy (MaxEnt) model was adopted for urban flooding risk probability assessment based on multi-source data. This study conducted an in-depth analysis from three perspectives including spatial analysis, risk planning and model comparison. The MaxEnt model and multiple exploratory spatial data analysis methods were combined to reveal spatial distribution patterns at grid cell scale. The MaxEnt and Zonation models were coupled to generate an urban flooding risk map. Further, six traditional machine learning models were compared with the MaxEnt model. The results indicate that rapid urbanization and intense human activities have significantly increased the number of buildings, leading to loss of previously existing blue and green spaces. These urban characteristics increase the vulnerability of cities to extreme rainfall. Compared to traditional machine learning models, the MaxEnt model has significant advantages. In the field of urban flooding risk, the MaxEnt model demonstrates significant potential for practical application. In summary, the framework empowers urban managers to comprehensively evaluate flooding risk in planning, supporting urban design and risk prevention.

Proposal of a Nonlinear Spring Model on Piping Support Structures for an Elasto-Plastic Response Analysis Method

Abstract In probabilistic risk assessment against earthquakes (seismic PRA) for nuclear power plants, the development of a realistic response analysis method for the fragility assessment of piping systems considering input seismic motions exceeding design assumptions is one of the important issues. Usually, piping systems exhibit complex three-dimensional shapes. The arrangement and stiffness of the piping support structures significantly affect the response characteristics of the entire piping system. Therefore, it is necessary to develop a realistic response analysis method of piping systems including piping support structures. In this study, a method for modeling the elasto-plastic hysteresis characteristics of piping support structures is developed to establish a seismic response analysis method of piping systems including piping support structures. First, we formulate an elatsto-plastic spring model that can express the elasto-plastic hysteresis characteristics of a piping support structure. Subsequently, we perform a simulation analysis for the loading test of a piping support structure using this model. As the analysis results and test results were in good agreement, we confirmed the effectiveness of the formulation of the model. The main contents, such as the formulation of the elasto-plastic spring model, the simulation analysis of the loading test, and the comparison between the analysis results and the test results, and the results of this study are reported in this paper.

Quantifying the risk of medical evacuation in spaceflight

IntroductionTraditionally, NASA mission planners have used a heuristic and qualitative approach to design medical systems based on prior experience; however, this approach may result in implicit bias in design. The risk of needing to return to definitive care (RTDC) or medevac, has been particularly difficult to quantify due to the complexity of exploration spaceflight. The Informing Mission Planning through Analysis of Complex Tradespaces (IMPACT) tool is a probabilistic risk assessment approach designed by NASA to model medical risk in long duration spaceflight. This paper discusses how this tool can inform RTDC risk and improve the health and safety of astronaut crews. MethodsIMPACT was developed by subject matter experts using an evidence-based approach and can be used to quantify the risk of exceeding the onboard medical capabilities. Within the model, RTDC occurs when a condition meets a specific threshold that exceeds the on-board capabilities and requires a higher level of care. A notional lunar surface design reference mission (DRM) was modeled using IMPACT, and the RTDC rate was analyzed. ResultsOf the 119 medical conditions evaluated, thirty-four were preassigned to have zero probability of RTDC based on lack of acuity. Thirty-one conditions used the need for inpatient hospitalization or admission to intensive care as the RTDC surrogate. Twenty-six conditions used the probability of needing surgery, and ten conditions used treatment failure rates as the RTDC surrogate. The remaining 18 conditions had unique surrogates that did not fall into the above categories or were assigned a 100 % probability of RTDC due to their definition. In the sample DRM, the overall risk for RTDC was 0.32 events per mission. DiscussionQuantifying medical risk for human spaceflight is challenging but important in designing medical systems that support the health and performance of our astronaut crews. IMPACT can use the best available evidence to quantify the risk of an RTDC event based on mission parameters and help mission planners make informed design decisions. More work is underway to further refine the model and evidence that drives the RTDC calculation to improve model fidelity and utility for missions to the Moon, Mars, and beyond.