Probabilistic Risk Assessment Studies Research Articles

Concentration of Heavy Metals in Traditional and Industrial Fruit Juices from Iran: Probabilistic Risk Assessment Study.

Exposure to heavy metals can endanger the health of exposed people in the long term. The consumption of fruit juice is increasing; it is important to estimate the health risk of consumers due to heavy metals. The current study was carried out for the analysis of toxic metals (lead (Pb), arsenic (As), and cadmium (Cd)) and essential elements (copper (Cu) and zinc (Zn)) in 60 samples of traditional and industrial fruit juices (10 samples of different brands of apple, orange, grape, peach, mango, and pineapple) in Hamadan, West Iran, using inductivity coupled plasma optical emission spectrometry (ICP-OES) method. The validation protocol included precision of the analytical method; recovery, the determination of the limit of detection (LOD), the limit of quantification (LOQ), and linearity were measured. Moreover, risk assessment was detected using target hazard quotient (THQ) and cancer risk (CR) by the Monte Carlo simulation (MCS) model. The ranking of metal concentration in traditional and industrial fruit juices was Zn > Cu > As > Pb > Cd. In all samples, concentrations of heavy metals in industrial fruit juices were higher than traditional fruit juices p < < 0.001. The level of metals in all samples was lower of the US Environmental Protection Agency (USEPA), the World Health Organization (WHO), and the Iran Standard (IS) permissible limit set for drinking water. In terms of non-carcinogenic, values of toxic elements for children and adult in traditional and industrial fruit juices were 1.6E-3 and 1.72E-3 and 2.6E-3 and 1.85E-3, respectively. The 95th percentile of CR in adults and children due to both industrial and traditional fruits juices was higher than 1E-6; hence, reducing the concentration of As in fruit juices should be conducted. Consumption of fruit juice can increase carcinogenic risk of consumers. Therefore, it is recommended to consume it with caution.

UNCERTAINTY QUANTIFICATION AND GLOBAL SENSITIVITY ANALYSIS OF SEISMIC FRAGILITY CURVES USING KRIGING

Seismic fragility curves have been introduced as key components of seismic probabilistic risk assessment studies. They express the probability of failure of mechanical structures conditional to a seismic intensity measure and must take into account various sources of uncertainties, the so-called epistemic uncertainties (i.e., coming from the uncertainty on the mechanical parameters of the structure) and the aleatory uncertainties (i.e., coming from the randomness of the seismic ground motions). For simulation-based approaches we propose a methodology to build and calibrate a Gaussian process surrogate model to estimate a family of nonparametric seismic fragility curves for a mechanical structure by propagating both the surrogate model uncertainty and the epistemic ones. Gaussian processes have indeed the main advantage to propose both a predictor and an assessment of the uncertainty of its predictions. In addition, we extend this methodology to sensitivity analysis. Global sensitivity indices such as aggregated Sobol' indices and kernel-based indices are proposed to know how the uncertainty on the seismic fragility curves is apportioned according to each uncertain mechanical parameter. This comprehensive uncertainty quantification framework is finally applied to an industrial test case consisting of a part of a piping system of a pressurized water reactor.

A Limited-Scope Probabilistic Risk Assessment Study to Risk-Inform the Design of a Fuel Storage System for Spent Pebble-Filled Dry Casks

This limited-scope study demonstrates the application of probabilistic risk assessment (PRA) methodologies to a spent fuel storage system for spent pebble-filled dry cask with a focus only on the necessary PRA technical elements sufficient to risk-inform the spent fuel storage system design. A dropping canister scenario in a silo of the spent fuel storage system is analyzed through an initiating event (IE) identification from the Master Logic Diagram (MLD); event sequence analysis (ES) by establishing the event tree; data analysis (DA) for event sequence quantification (ESQ) with uncertainty quantification; mechanistic source term (MST) analysis by using ORIGEN; radiological consequence analysis (RC) by deploying MicroShield, and risk integration (RI) by showing the Frequency-Consequence (F-C) target curve in the emergency area boundary (EAB). Additionally, a sensitivity study is conducted using the ordinary least square (OLS) regression method to assess the impact of variables such as failed pebble numbers, their location in the canister, and building wall thickness. Furthermore, the release categories grouped from the end states in the event tree are verified as safety cases through the F-C curve. This study highlights the implementation of PRA elements in a logical and structured manner, using appropriate methodologies and computational tools, thereby showing how to risk-inform the design of a dry cask system for storing spent pebble-filled fuel.

Adverse impacts of Asian dust events on human health and the environment—A probabilistic risk assessment study on particulate matter-bound metals and bacteria in Seoul, South Korea

This study aimed to assess the impact of Asian dust (AD) on the human health and the environment. Particulate matter (PM) and PM-bound trace elements and bacteria were examined to determine the chemical and biological hazards associated with AD days and compared with non-AD days in Seoul. On AD days, the mean PM10 concentration was ∼3.5 times higher than that on non-AD days. Elements generated from the Earth's crust (Al, Fe, and Ca) and anthropogenic sources (Pb, Ni, and Cd) were identified as major contributors to coarse and fine particles, respectively. During AD days, the study area was recognized as “severe” for pollution index and pollution load index levels, and “moderately to heavily polluted” for geoaccumulation index levels. The potential cancer risk (CR) and non-CR were estimated for the dust generated during AD events. On AD days, total CR levels were significant (in 1.08 × 10−5–2.22 × 10−5), which were associated with PM-bound As, Cd, and Ni. In addition, inhalation CR was found to be similar to the incremental lifetime CR levels estimated using the human respiratory tract mass deposition model. In a short exposure duration (14 days), high PM and bacterial mass deposition, significant non-CR levels, and a high presence of potential respiratory infection-causing pathogens (Rothia mucilaginosa) were observed during AD days. Significant non-CR levels were observed for bacterial exposure, despite insignificant levels of PM10-bound elements. Therefore, the substantial ecological risk, CR, and non-CR levels for inhalation exposure to PM-bound bacteria, and the presence of potential respiratory pathogens, indicate that AD events pose a significant risk to both human lung health and the environment. This study provides the first comprehensive examination of significant non-CR levels for bacteria and carcinogenicity of PM-bound metals during AD events.

Effects of an Ozone-Based Domestic Clothes Washer/Dryer on Indoor Air Quality: A Probabilistic Risk Assessment Study

New technologies are facing the market to overcome high energy costs and efficiency regulations. Among these, the use of ozone in domestic appliances has been recently proposed for a cold-water sanitizing system for clothes or even a no-water cycle to refresh clothes. Ozone is a contaminant in indoor environments and its toxicity is mainly due to the strong oxidizing action on cellular components that can reduce lung function and increase respiratory symptoms. This study illustrates a risk assessment for ozone emissions released from new domestic clothes washer/dryer during normal operation and in the case of a failure. Indoor ozone concentrations were measured, and a mass-balance model was applied, considering ozone released from the appliance during the no-water cycle and the outdoor ozone contribution. Monte Carlo analysis was used to derive the probability of exceeding the air quality standards established by the main international organizations for the protection of human health. This study indicated the most suitable ozone generator and the best refresh cycle to minimize health risks. This method can be generally used to assess the potential health risk for the indoor environment, due to the release of harmful emissions from household appliances.

Determination of heavy metal content in whey protein samples from markets in Giza, Egypt, using inductively coupled plasma optical emission spectrometry and graphite furnace atomic absorption spectrometry: A probabilistic risk assessment study

Whey protein is a by-product obtained from cheese manufacturing, contains high amounts of essential metals and amino acids. We assessed levels and health risk of Co, Ni, Sn, Cr, Cu, Mn, Zn, Fe, Al, Na, Ca, Mg, Pb, Cd, and Hg in different whey protein samples collected in Egypt using inductively coupled plasma optical emission spectrometry (ICP OES) and graphite furnace atomic absorption spectrometry (GF AAS). Large differences were found between the measured and defined values for some metals (such as Na, Mn, Cr, Cu, and Mg), whereas others showed only minor variation (Fe and Zn). The maximum concentration of Ca, Na, Mg, Zn, Fe, Cu, Al, Mn, Ni, Cr, and Sn was 12860, 5336, 3248, 66.11, 40.14, 16.78, 16.26, 14.37, 0.927, 0.685, and 0.502 mg/kg, respectively. The Co levels in all samples were found to be varied between N.D (not detectable) and lower than the limit of quantification (<LOQ). The concentration of Cd was found to range between 0.022 and 0.335 mg/kg, while Pb concentration was found to vary between 0.036 and 0.096 mg/kg. Also, all samples were found to be free of any detectable amount of Hg. The health risk assessment was evaluated for estimated daily intake (EDI), average body weight (70 kg), hazard quotient (HQ), and hazard index (HI) using the FAO/WHO and US EPA recommendations. Based on our results, the EDI and HQ values for most of elements in whey protein were lower than 1, which indicates no adverse effects may occur. The HI values for most of whey protein samples were lower than 1. Among the samples, only two brands had HI > 1, indicates that there is some possibility that non-cancer effects may occur through consumption in the future.

An integrated modeling approach for event sequence development in multi-unit probabilistic risk assessment

To obtain a complete site risk profile for multi-unit nuclear power plants (NPPs), the existing single-unit probabilistic risk assessment (PRA) model needs to be upgraded to address both intra-unit and inter-unit dependencies. The high temperature gas cooled reactor-pebble bed module (HTR-PM), with two reactor-steam generator modules and one shared steam turbine-generator set, is a ready-in-hand pilot for multi-unit PRA (MUPRA) studies. In this paper, a general framework for MUPRA is firstly developed based on HTR-PM PRA methodology. An Integrated Modeling (IM) approach is then proposed for multi-unit event sequence modeling. The approach is discussed in detail and illustrated with a loss of offsite power (LOOP) case study. Also, the limitations of the current analysis are put forward for open discussion.

Simplified Framework for Blast-Risk-Based Cost-Benefit Analysis for Reinforced Concrete-Block Buildings

Probabilistic risk assessment (PRA) is essential for evaluating different options for blast risk management. However, depending on the risk management approach being considered, a rigorous blast PRA study can be quite demanding. To expedite this process, a simplified PRA framework is proposed for reinforced concrete-block shear wall buildings, in order to determine design basis threat (DBT) fragility curves based on revised damage limit states most suitable for risk assessment. The current definitions of damage states by North American standards for blast resistant design involve global response limits--such as the support rotations of a structural element--that are relatively simple to calculate. However, such damage state descriptors can be insufficient for the cost-benefit analysis required to evaluate different risk mitigation options. As such, building on recent advances in the area of performance-based seismic design of concrete-block shear wall buildings, this study proposes revised damage states that can be associated with more useful metrics, including repair technique and building downtime. To illustrate the proposed methodology, a hypothetical shear wall building is analyzed under different DBT levels. The DBT fragility curves are obtained through Monte Carlo sampling of the random variables describing the shear wall system and are used to identify the locations that are most suitable for the erection of barriers for blast protection. The proposed PRA framework can be used to identify target performance requirements, formulated in terms of stakeholders' tolerable probability of failure and consequent risk management, for different classes of buildings under a range of DBTs. Language: en

Reduced Order Models for Prediction of Groundwater Quality Impacts from CO2 and Brine Leakage

Abstract A careful assessment of the risk associated with geologic CO2 storage is critical to the deployment of large-scale storage projects. A potential risk is the deterioration of groundwater quality caused by the leakage of CO2 and brine leakage from deep subsurface reservoirs. In probabilistic risk assessment studies, numerical modeling is the primary tool employed to assess risk. However, the application of traditional numerical models to fully evaluate the impact of CO2 leakage on groundwater can be computationally complex, demanding large processing times and resources, and involving large uncertainties. As an alternative, reduced order models (ROMs) can be used as highly efficient surrogates for the complex process-based numerical models. In this study, we represent the complex hydrogeological and geochemical conditions in a heterogeneous aquifer and subsequent risk by developing and using two separate ROMs. The first ROM is derived from a model that accounts for the heterogeneous flow and transport conditions in the presence of complex leakage functions for CO2 and brine. The second ROM is obtained from models that feature similar, but simplified flow and transport conditions, and allow for a more complex representation of all relevant geochemical reactions. To quantify possible impacts to groundwater aquifers, the basic risk metric is taken as the aquifer volume in which the water quality of the aquifer may be affected by an underlying CO2 storage project. The integration of the two ROMs provides an estimate of the impacted aquifer volume taking into account uncertainties in flow, transport and chemical conditions. These two ROMs can be linked in a comprehensive system level model for quantitative risk assessment of the deep storage reservoir, wellbore leakage, and shallow aquifer impacts to assess the collective risk of CO2 storage projects.

Evaluation of a recently proposed record selection and scaling procedure for low‐rise to mid‐rise reinforced concrete buildings and its use for probabilistic risk assessment studies

SUMMARYThis paper evaluates a recent record selection and scaling procedure of the authors that can determine the probabilistic structural response of buildings behaving either in the elastic or post‐elastic range. This feature marks a significant strength on the procedure as the probabilistic structural response distribution conveys important information on probability‐based damage assessment. The paper presents case studies that show the utilization of the proposed record selection and scaling procedure as a tool for the estimation of damage states and derivation of site‐specific and region‐specific fragility functions. The method can be used to describe exceedance probabilities of damage limits under a certain target hazard level with known annual exceedance rate (via probabilistic seismic hazard assessment). Thus, the resulting fragility models can relate the seismicity of the region (or a site) with the resulting building performance in a more accurate manner. Under this context, this simple and computationally efficient record selection and scaling procedure can be benefitted significantly by probability‐based risk assessment methods that have started to be considered as indispensable for developing robust earthquake loss models. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Risk assessment of the lead intake by consumption of red deer and wild boar meat in Southern Spain

The presence of heavy metals in big game meat may pose a risk to human health. The main objective of this paper is to carry out a risk assessment study (using a probabilistic and point-estimate approach) of lead intake by consumption of red deer and wild boar meat in Southern Spain based on Spanish data collected in the period 2003–2006. In general, the concentration levels found for wild boar meat (mean = 1291 µg kg−1) were much higher than those observed in red deer meat (mean = 326 µg kg−1). The results from a point-estimate risk assessment showed that the estimated average intake of lead among different exposure scenarios varied from 0.1 to 6.5 and from 0.3 to 38 µg kg−1 week−1 for red deer and wild boar meat, respectively; and from 0.3 to 35 µg kg−1 week−1 for individuals consuming both red deer and wild boar meat, and that the estimated intake of lead by consumption of big game meat differed significantly between hunters and non-hunters, it being higher for hunters. Besides this, results from the probabilistic risk assessment study corroborated the fact that risk is greater in hunter populations, reaching a maximum in individuals consuming only wild boar and both types of meat, with 0.4% and 0.2% of the population above the provisional tolerable weekly intake (PTWI), respectively. Likewise, the hunter populations consuming wild boar and both types of big game meat (red deer and wild boar meat) were exposed to the maximum lead level (56 µg kg−1 week−1), which corresponded approximately to 224% of the PTWI. Further data and studies will be needed to give a complete risk estimation in which it will be crucial to consider the contribution to the lead intake level of other foods in the diet of both population groups.

Fuzzy fault tree analysis: revisited

Fault tree analysis is one of the most effective techniques for estimating the frequency of occurrence of hazardous events in probabilistic risk assessment study. The analyst needs to study a multi component system and identifies vulnerable sections of hazardous plant based on formalized procedure. In this sequel, we have made an attempt to demonstrate the effective ness of using fuzzy fault tree formalism over the conventional approach and the concept is termed as Fuzzy Top Event Probability (FTEP). The case study 1 relates to flash vessel in an ammonia tank, while in case study 2, using fuzzy set theory, the FTEP has been estimated for the existing ammonia storage tank in a large fertilizer complex located in Mumbai India. In addition, a new formalism for estimating the possibility of a fuzzy event is presented with application.

CFD simulation study to investigate the risk from hydrogen vehicles in tunnels

Abstract When introducing hydrogen-fuelled vehicles, an evaluation of the potential change in risk level should be performed. It is widely accepted that outdoor accidental releases of hydrogen from single vehicles will disperse quickly, and not lead to any significant explosion hazard. The situation may be different for more confined situations such as parking garages, workshops, or tunnels. Experiments and computer modelling are both important for understanding the situation better. This article reports a simulation study to examine what, if any, is the explosion risk associated with hydrogen vehicles in tunnels. Its aim was to further our understanding of the phenomena surrounding hydrogen releases and combustion inside road tunnels, and furthermore to demonstrate how a risk assessment methodology developed for the offshore industry could be applied to the current task. This work is contributing to the EU Sixth Framework (Network of Excellence) project HySafe, aiding the overall understanding that is also being collected from previous studies, new experiments and other modelling activities. Releases from hydrogen cars (containing 700 bar gas tanks releasing either upwards or downwards or liquid hydrogen tanks releasing only upwards) and buses (containing 350 bar gas tanks releasing upwards) for two different tunnel layouts and a range of longitudinal ventilation conditions have been studied. The largest release modelled was 20 kg H 2 from four cylinders in a bus (via one vent) in 50 s, with an initial release rate around 1000 g/s. Comparisons with natural gas (CNG) fuelled vehicles have also been performed. The study suggests that for hydrogen vehicles a typical worst-case risk assessment approach assuming the full gas inventory being mixed homogeneously at stoichiometry could lead to severe explosion loads. However, a more extensive study with more realistic release scenarios reduced the predicted hazard significantly. The flammable gas cloud sizes were still large for some of the scenarios, but if the actual reactivity of the predicted clouds is taken into account, moderate worst-case explosion pressures are predicted. As a final step of the risk assessment approach, a probabilistic QRA study is performed in which probabilities are assigned to different scenarios, time dependent ignition modelling is applied, and equivalent stoichiometric gas clouds are used to translate reactivity of dispersed non-homogeneous clouds. The probabilistic risk assessment study is based on over 200 dispersion and explosion CFD calculations using the commercially available tool FLACS. The risk assessment suggested a maximum likely pressure level of 0.1–0.3 barg at the pressure sensors that were used in the study. Somewhat higher pressures are seen elsewhere due to reflections (e.g. under the vehicles). Several other interesting observations were found in the study. For example, the study suggests that for hydrogen releases the level of longitudinal tunnel ventilation has only a marginal impact on the predicted risk, since the momentum of the releases and buoyancy of hydrogen dominates the mixing and dilution processes.

Radiological risk assessment for field radiography based on two dimensional Monte Carlo analysis

Probabilistic risk assessment studies use probability distributions for one or more variables of the risk equation in order to quantitatively characterize the variability and uncertainty. In this study, an advanced technique called the two-dimensional Monte Carlo analysis (2D MCA) is applied to estimation of radiological risk for worker and member of the public in the vicinity of the work place for field radiological system in Korea. The variables of the risk model along with the parameters of these variables are described in terms of probability density functions (PDFs). Because the frequencies of normal tasks were far higher than those of accidents, the total risk associated with normal tasks was higher than the accidental risk. The result derived from this work can be used as guidance for the decision-making in controlling the radiological risk in the field of radiography area.

2D Monte Carlo Analysis of Radiological Risk Assessment for the Food Intake In Korea

Most public health risk assessments assume and combine a series of average, conservative and worst-case values to derive an acceptable point estimate of risk. To improve quality of risk information, insight of uncertainty in the assessments is needed and more emphasis is put on the probabilistic risk assessment. Probabilistic risk assessment studies use probability distributions for one or more variables of the risk equation in order to quantitatively characterize variability and uncertainty. In this study, an advanced technique called the two-dimensional Monte Carlo analysis (2D MCA) is applied to estimation of internal doses from intake of radionuclides in foodstuffs and drinking water in Korea. The variables of the risk model along with the parameters of these variables are described in terms of probability density functions (PDFs). In addition, sensitivity analyses were performed to identify important factors to the radiation doses.

Sensitivity and uncertainty issues in the integrated PRA studies

The performance of risk analyses in the Probabilistic Risk Assessment (PRA) format is being done based on various internationally accepted standards. As part of the compliance with those standards the issue of credibility of results of the levels 2 and 3 and their correlation with the results from deterministic analyses is a very important one. If these margins are properly identified, then the level 2 results for support and/or main source to the Severe Accident Procedures and the level 3 as technical input in deriving the emergency zoning criteria, would be solved to a significant level. The paper presents some specific approaches to be adopted for the sensitivity analyses of an integrated PRA model and attempts to clarify the place and interface of the uncertainty analyses versus sensitivity analyses for PRA levels 2 and 3.

2D Monte Carlo versus 2D Fuzzy Monte Carlo health risk assessment

Risk estimates can be calculated using crisp estimates of the exposure variables (i.e., contaminant concentration, contact rate, exposure frequency and duration, body weight, and averaging time). However, aggregate and cumulative exposure studies require a better understanding of exposure variables and uncertainty and variability associated with them. Probabilistic risk assessment (PRA) studies use probability distributions for one or more variables of the risk equation in order to quantitatively characterize variability and uncertainty. Two-dimensional Monte Carlo Analysis (2D MCA) is one of the advanced modeling approaches that may be used to conduct PRA studies. In this analysis the variables of the risk equation along with the parameters of these variables (for example mean and standard deviation for a normal distribution) are described in terms of probability density functions (PDFs). A variable described in this way is called a “second order random variable.” Significant data or considerable insight to uncertainty associated with these variables is necessary to develop the appropriate PDFs for these random parameters. Typically, available data and accuracy and reliability of such data are not sufficient for conducting a reliable 2D MCA. Thus, other theories and computational methods that propagate uncertainty and variability in exposure and health risk assessment are needed. One such theory is possibility analysis based on fuzzy set theory, which allows the utilization of incomplete information (incomplete information includes vague and imprecise information that is not sufficient to generate probability distributions for the parameters of the random variables of the risk equation) together with expert judgment. In this paper, as an alternative to 2D MCA, we are proposing a 2D Fuzzy Monte Carlo Analysis (2D FMCA) to overcome this difficulty. In this approach, instead of describing the parameters of PDFs used in defining the variables of the risk equation as random variables, we describe them as fuzzy numbers. This approach introduces new concepts and risk characterization methods. In this paper we provide a comparison of these two approaches relative to their computational requirements, data requirements and availability. For a hypothetical case, we also provide a comperative interpretation of the results generated.

Accident sequence precursor analyses for steam generator tube rupture events that actually occurred

Steam generator tube ruptures (SGTRs) at pressurized water reactors are identified as one of the risk significant events in the probabilistic risk assessment studies. In addition, operating experience indicates that SGTRs might result in complex transients, some of which involved additional anomalies such as the delayed recognition of event, resulting in the retarded isolation of the ruptured SG and/or failure to timely equalize the primary and secondary pressures. In order to identify the risk significant anomalies and to obtain generic insights useful for examining alternative mitigation measures for STGR, the present study systematically analyzed ten actual and one potential SGTR events using an accident sequence precursor model consistently. The analysis results show that the SGTR event involving the delayed identification of tube rupture or failure to timely depressurize the reactor could have a relatively high possibility of leading to core damage and would be a significant precursor, though the models and failure probabilities applied might be further examined. This implies the importance of improving the capability to detect SGTR and the operating procedures. It is also shown that some of the other anomalies observed would largely contribute to the possibility of core damage, which points out the need of examining alternative measures for recovering from such conditions.

Aging Effects on Time-Dependent Nuclear Plant Component Unavailability: An Investigation of Variations from Static Calculations

In the nuclear industry, aging effects have been traditionally incorporated into probabilistic risk assessment studies by using a constant (static) unavailability (q s ) averaged over time. However, recent work shows that because of aging, substantial deviations may occur in time-dependent nuclear plant component unavailability from that predicted by static models well within the plant lifetime. A methodology based on the standard extension of the classic renewal equation when repair is explicitly considered is used to investigate (a) the trends in the effects of aging on time-dependent component unavailability as a function of changing first failure density (FFD) and test parameters and (b) the circumstances for which static approximations may be inadequate to describe these effects. The investigation uses several point- and time-averaged unavailability measures based on time-dependent unavailability, such as before-test unavailability (BTU), average-interval unavailability (AIU) and year-average unavailability (YA U), and is restricted to periodically tested components whose FFDs satisfy the Weibull distribution with aging threshold. The results show that while point measures (e.g., BTU) can substantially differ from static unavailability and while all measures are sensitive to changes in the Weibull shape parameter b, aging threshold time τ, and time between tests T, the differences between the time-averaged measures used (e.g., AIU, YA U) and the static unavailability were only found to be relatively significant for one case among more than 100 combinations of b, τ, and T that were investigated. The differences area factor of 18 months) and may describe the late effects ofaging on component unavailability irrespective of b and T (i. e., beyond 25 yr of component age for the data under consideration).

ATWS scoping calculations for a BWR plant performed using RELAP5/MOD2 and contain codes

In the context of the licensing process for Alto Lazio nuclear power plant (a BWR/6, MARK III design) some calculatio have been performed for evaluating the plant response during an ATWS transient. Specifically, the ATWS related safety systems were simulated in order to evaluate their influence on the plant behaviour. Furthermore, the containment behavior and the effectiveness of hypothetical containment venting have been evaluated. Two best-estimate codes have been used for this study: • - RELAP5/MOD2 for the Reactor Cooling System (RCS) behaviour calculation; • - CONTAIN 1.1 for the containment response calculation. The initiating event chosen was a Main Steam Isolation Valve (MSIV) closure because the associated ATWS was found, by an Alto Lazio specific Probabilistic Risk Assessment study, to have the highest core melt frequency. In order to assess the corresponding effect, three different Stand-by Liquid Control System (SLCS) actuation modes have been considered: 1. (a) NOSLCS case: the SLCS is assumed to be unavailable; 2. (b) SLCS2 case: the SLCS starts two minutes after the initiating event; 3. (c) SLCS10 case: the SLCS is assumed to start 10 min after the initiating event. The paper contains the calculation results and the related analysis of the above-mentioned cases.