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[en] In order to understand and solve numerous problems related to sugar quality and its storage life, X-ray diffraction studies of sucrose and sucrose irradiated with γ-radiation have been made. It is observed that the interplanar spacing 'd' in irradiated sucrose is reduced indicating the partial damage of sucrose lattice. (author)
[en] This monograph on probabilistic safety assessment (PSA) is addressed to the wide community of professionals engaged in the nuclear industry and concerned with the safety issues of nuclear power plants (NPPs). While the monograph describes PSA of NPPs, the principles described in this monograph can be extended to other facilities like spent fuel storage, fuel reprocessing plants and non-nuclear facilities like chemical plants, refineries etc. as applicable. The methodology for risk assessment in chemical plants or refineries is generally known as quantitative risk analysis (QRA). The fundamental difference between NPP and chemical plant is that in NPPs the hazardous material (fuel and fission products) are contained at a single location (i.e. inside containment), whereas in a chemical plant and reprocessing plants, the hazardous material is present simultaneously at many places, like pipelines, reaction towers, storage tanks, etc. Also unlike PSA, QRA does not deal with levels; it uses an integrated approach combining all the levels. The monograph covers the areas of broad interest in the field of PSA such as historical perspective, fundamentals of PSA, strengths and weaknesses of PSA, applications of PSA, role of PSA in the regulatory decision making and issues for advancement of PSA
[en] Highlights: •Uncertainty in operator action time and allowed time is combined. •Probability distribution function for operator time is determined. •Probability distribution function for allowed time is determined. •HEP is predicted from these two distributions. -- Abstract: Operator error in diagnosis and execution of task have significant impact on Nuclear Power Plant (NPP) safety. These human errors are classified as mistakes (rule base and knowledge based errors), slip (skill based) and lapses (skill based). Depending on the time of occurrence, human errors have been categorized as i) Category ‘A’ (Pre-Initiators): actions during routine maintenance and testing wherein errors can cause equipment malfunction ii) Category ‘B’ (Initiators): actions contributing to initiating events or plant transients iii) Category ‘C’ (Post-Initiators): actions involved in operator response to an accident. There have been accidents in NPPs because of human error in an operator's diagnosis and execution of an event. These underline the need to appropriately estimate HEP in risk analysis. There are several methods that are being practiced in Probabilistic Safety Assessment (PSA) studies for quantification of human error probability. However, there is no consensus on a single method that should be used. In this paper a method for estimating HEP is proposed which is based on simulator data for a particular accident scenario. For accident scenarios, the data from real NPP control room is very sparsely available. In the absence of real data, simulator based data can be used. Simulator data is expected to provide a glimpse of probable human behavior in real accident situation even though simulator data is not a substitute for real data. The proposed methodology considers the variation in crew performance time in simulator exercise and in available time from deterministic analysis, and couples them through their respective probability distributions to obtain HEP. The emphasis is on suitability of the methodology rather than particulars of the cited example.
[en] The nuclear power industry worldwide has a number of nuclear power plants (NPP) that have surpassed more than 25 years of operation. The ageing of structures, systems and components progressively leads to the decrease in safety margins of an NPP. The probabilistic safety analysis (PSA) is an effective method to evaluate the plant risk and it supplements the traditional deterministic analysis. A number of ageing-related degradation mechanisms such as fatigue, stress corrosion cracking, irradiation embrittlement and flow accelerated corrosion and vibration can cause component failure affecting safety function, thereby increasing the plant risk (i.e. system unavailability, core damage frequency etc.). The engineered safety system unreliability, the core damage frequency (CDF) and Large Early Release Frequency (LERF) are expected to increase as the NPP ages. Use of ageing model in PSA system reliability evaluation would help in increasing the acceptability of PSA results and its application and to support safety related decision making. In this paper, linear ageing model has been considered for calculating the change in reliability of two NPP systems. (author)
[en] Uncertainty analysis and sensitivity (importance) analysis are essential parts of complex systems. Specifically uncertainty analysis refers to the determination of the uncertainty in analysis results that derives from uncertainty in analysis inputs, and sensitivity analysis refers to the determination of the contributions of individual uncertain analysis inputs to the uncertainty in analysis results. The uncertainty under consideration here is often referred to as epistemic uncertainty; alternative designations for this form of uncertainty include state of knowledge, subjective, reducible, and type B. Epistemic uncertainty derives from a lack of knowledge about the appropriate value to use for a quantity that is assumed to have a fixed value in the context of a particular analysis. A number of approaches to uncertainty and sensitivity analysis have been developed, including differential analysis, response surface methodology, Monte Carlo analysis and variance decomposition procedures. Sampling based (Monte Carlo) approach to uncertainty and sensitivity analysis is effective and widely used technique. The methodology adopted consists of the following steps: (i) Selection of input parameters (ii) Characterisation of uncertainty (iii) Propagation of uncertainties (iv) Assessment of uncertainties in key figures-of-merits relative to observations and Sensitivity/Importance analysis. The paper deals with the methodology of the sampling based uncertainty and sensitivity analysis. The paper also aimed at the applications of this methodology to the TMI-2 severe accident scenario and integration of probabilistic and deterministic safety assessment to estimate the safety margin assessment. (author)
[en] This paper describes probabilistic fracture mechanics for estimation of failure probability of the pressure tubes during normal operation. Canadian standard N285.8-10 was used for structural safety assessment of pressure tube. Numerical simulation was also carried out for different crack geometries for verification. Pressure tube failure probability was also estimated considering variations in crack depth, crack aspect ratio, material fracture toughness, material yield and tensile strength. Failure probability was estimated considering both fracture initiation and plastic collapse failure modes during normal plant operation
[en] Pipe wall thickness reduction due to Flow Accelerated Corrosion (FAC) depends on mass transfer coefficient (MTC), temperature, pH and roughness. The purpose of this research work is to predict the wall thickness reduction due to FAC in bends and orifice. The paper proposes a model for temporal wall thickness prediction in pipe bend and orifice taking into account the positive feedback from FAC induced roughness and spatial MTC. This is applied for two geometrical configurations (i) FAC experiment performed on 58° carbon steel pipe bend (ii) FAC experiment in an orifice with gypsum. In the 58° carbon steel pipe, the predictions were in good comparison with the experimental values at different locations with percentage error between the predicted and experimental wall thickness in the range (−5%, +12%) at all locations on pipe extrados. For the orifice, the error was in the range of (−0.3 mm, +0.6 mm) at all measured locations. The MTC was estimated using computational fluid dynamics (CFD) with k-w SST (shear stress transport) model for both configurations. The comparison of predicted values of wall thickness with experimental values shows that errors in prediction are moderate to low.
[en] Highlights: → Deterministic and probabilistic safety analysis is combined. → Deterministic analysis is carried using BEPU. → This is for few accident sequences from event tree in probabilistic model. → Safety margin with 95% confidence and 95% probability is predicted. - Abstract: Deterministic Safety Analysis and Probabilistic Safety Assessment (PSA) analyses are used to assess the Nuclear Power Plant (NPP) safety. The conventional deterministic analysis is conservative. The best estimate plus uncertainty analysis (BEPU) is increasingly being used for deterministic calculation in NPPs. The PSA methodology integrates information about the postulated accident, plant design, operating practices, component reliability and human behavior. The deterministic and probabilistic methodologies are combined by analyzing the accident sequences within design basis in the event trees of a postulated initiating event (PIE) by BEPU. The peak clad temperature (PCT) distribution provides an insight into the confidence in safety margin for an initiating event. The paper deals with calculating the safety margin with 95% confidence and 95% probability in large break loss of coolant accident (LBLOCA). In the present study, five uncertain input parameters were selected. Uniform probability density function was assigned to the uncertain parameters in the selected range and these uncertainties are propagated using Latin Hypercube Sampling (LHS) technique. The sampled data for five parameters was randomly mixed by LHS to obtain 25 input sets. An event tree for the initiating event, LBLOCA inside containment, has been used from a VVER study on Level-1 PSA and four non-core damage (NCD) accident sequences were identified for this study. In the accident analysis the success and failure of safety systems reflected in event tree was appropriately modeled in the system thermal hydraulics code runs. The PCT was obtained for each of 25 code runs for each accident sequence. A Kolmogorov - Smirnov goodness-of-fit test carried out for PCTs indicated that they followed normal distribution for each of the accident sequences. The probability distribution of safety margin (difference between acceptable value and PCT) in each accident sequence was also obtained. The values of safety margin for the 95% confidence and 95% probability are estimated. The robustness of the system can be judged based on this. This paper describes the methodology. LBLOCA in a VVER type reactor is considered as an example.
[en] Highlights: • Core Damage Frequency and Large Early Release Frequency. • Multi –Unit Risk Metrics. • Aggregation of CDF of NPP through Mean Values. • Aggregation of CDF of NPP as Random Variable. - Abstract: The nuclear generating sites around the world are mostly twin unit and multi-unit sites. The PSA risk metrics Core Damage Frequency (CDF) and Large Early Release Frequency (LERF) currently are based on per reactor reference. The models for level 1 and level 2 PSA have been developed based on single unit. The Fukushima accident has spawned the need to address the issue of site base risk metrics, Site Core Damage Frequency (SCDF) and Site Large Early Release Frequency (SLERF), on the site years rather than reactor years. It is required to develop a holistic framework for risk assessment of a site. In the context of current study, the holistic framework refers to integration of risk from all units, dependencies due to external events and operation time of individual units. There is currently no general consensus on how to arrive at site-specific risk metrics. Some documents provide suggestions for site CDF and site LERF. This paper proposes a new method of aggregation of risk metric from the consideration of operating time of individual units under certain assumptions with a purpose to provide a new conceptual aspect for multi-unit PSA. The result of a case study on hypothetical data shows that site level CDF is not sum of CDF of all units but around 18% higher than unit level CDF. When the CDF is considered to be a random variable then, the new methodology produces site CDF as 50% higher than single unit CDF. These two approaches have been detailed in the paper. For a general data set of CDF for individual units, site CDF would more than individual unit CDF however, it would not be multiples of a single unit value.
[en] Highlights: • Hougaard process statistical model for Flow Accelerated Corrosion (FAC) • Mean and standard error of parameters of the Hougaard process. • Prediction: FAC data from experimental and literature. • Comparison with gamma process and linear least square fit. - Abstract: Nuclear Power Plants (NPPs) operate at very high temperature and high fluid mass flow rate which are favourable for Flow Accelerated Corrosion (FAC) resulting in wall thickness reduction in pipes, bends and other geometries. The prediction of progressive reduction in pipe wall thickness is required for safety of operating NPP. In this paper, Hougaard process stochastic model is proposed for prediction of wall thickness reduction in pipes between two consecutive in-service-inspections. The probability distribution function (PDF) for the Hougaard process is computationally unstable near the origin. Hence, its saddle point approximation was used along with method of maximum likelihood (MLE) to derive the mathematical expressions for the three parameters with generally given time interval between in-service-inspection and corresponding changes in wall thickness. The gamma process model fit and linear fit to data have also been carried out. The predictions of change in pipe wall thickness from probabilistic model are validated by using (a) Experimental data for FAC for 58° bend pipe and (b) NPP feeder pipe data on FAC. The results compare well with the experimental and field data used in analysis.