LOCA frequency evaluation using expert elicitation

The double-ended-guillotine break (DEGB) criterion of the largest primary piping system in the plant, which generally provides the limiting condition for the emergency core cooling system requirements, is widely recognized as an extremely unlikely event. As a result, US Nuclear Regulatory Commission (NRC) staff are currently considering a risk-informed revision of the design-basis break size requirements for commercial nuclear power plants. In support of this effort, loss-of-coolant accident (LOCA) frequency estimates have been developed using an expert elicitation process by consolidating service history data and insights from probabilistic fracture mechanics (PFM) studies with knowledge of plant design, operation, and material performance. Baseline LOCA frequency estimates for the 5th percentile, median, mean and 95th percentile were determined from each panelist's elicitation responses. Group estimates were determined by aggregating the individual estimates using the geometric mean of the individual estimates for each frequency parameter. Group variability was estimated by calculating 95% confidence bounds for each of the group frequency parameters (i.e., median, mean, and 5th and 95th percentiles). A number of sensitivity analyses were conducted to examine the effects on the quantitative results from varying the assumptions, structure and techniques of the baseline analysis procedure.     

Integrating Safety Critical Software System in Probabilistic Safety Assessment

In the recent times, computer-based systems are frequently used for protection and control of Nuclear Power Plants (NPPs). In the conventional Probabilistic Safety Assessment (PSA), the contribution from software in these computer-based systems was not given necessary attention. However, from operating experience, it has been found failures in such systems can also result in initiating events that have the potential for leading into Core Damage in the event of unavailability of the respective Engineered Safety Features. The impact of a typical computer-based system on PSA of Indian Nuclear Power Plant is demonstrated.     

Development of Fe‐, Sb‐, Bi‐ and Al‐impregnated silica catalysts using rice husk silica as a support for Friedel–Crafts benzylation of arenes

The milling by‐product of rice, rice husk, constitutes a major waste of the agricultural industry. It is mainly used as a fuel additive for various purposes, leaving behind residual ash which is rich in silica (Biogenic silica). In the present project, rice husk silica was impregnated with Fe³⁺, Sb³⁺, Bi³⁺ and Al³⁺ from both their aqueous and organic solutions. The resultant catalysts were activated at 120 °C and 550 °C and used for the Friedel–Crafts benzylation of benzene using benzyl chloride. Copyright © 2003 Society of Chemical Industry     

Artificial neural network-driven federated learning for heart stroke prediction in healthcare 4.0 underlying 5G

In recent years, smart healthcare, artificial intelligence (AI)-aided diagnostics, and automated surgical robots are just a few of the innovations that have emerged and gained popularity with the advent of Healthcare 4.0. Such technologies are powered by machine learning (ML) and deep learning (DL), which are preferable for disease diagnosis, identifying patterns, prescribing treatments, and forecasting diseases like stroke prediction, cancer prediction and so forth. Nevertheless, much data is needed for AI, ML, and DL-based systems to train effectively and provide the desired outcomes. Further, it raises concerns about data privacy, security, communication overhead, regulatory compliance and so forth. Federated learning (FL) is a technology that protects data security and privacy by limiting data sharing and utilizing model information of distributed systems to enhance performance. However, existing approaches are traditionally verified on pre-established datasets that fail to capture real-life applicability. Therefore, this study proposes an AI-enabled stroke prediction architecture consisting of FL based on the artificial neural network (ANN) model using data from actual stroke cases. This architecture can be implemented on healthcare-based wearable devices (WD) for real-time use as it is effective, precise, and computationally affordable. In order to continuously enhance the performance of the global model, the proposed FL-based architecture aggregates the optimizer weights of many clients using a fifth-generation (5G) communication channel. Then, the performance of the proposed FL-based architecture is studied based on multiple parameters such as accuracy, precision, recall, bit error rate, and spectral noise. It outperforms the traditional approaches regarding accuracy, which is 5% to 10% higher.     

Adaptive relay co-ordination using a busbar splitting approach for a system integrity protection scheme

Power system faults can often result in excessively high currents. If sustained for a long time, such high currents can damage system equipment. Thus, it is desirable to operate the relays in the minimum possible time. In this paper, a busbar splitting approach is used for adaptive relay setting and co-ordination purposes for a system integrity protection scheme (SIPS). Whenever a fault occurs, the busbar splitting scheme splits a bus to convert a loop into a radial structure. The splitting schemes are chosen such that the net fault current is also reduced. Busbar splitting eliminates the dependency upon minimum breakpoints set (MBPS) and reduces the relay operating time, thus making it adaptive. The proposed methodology is incorporated into the IEEE 14-bus and IEEE 30-bus systems with single and multiple fault conditions. The modeling and simulation carried out in ETAP, and the results of the proposed busbar splitting-based relay co-ordination are compared with the MBPS splitting-based relay co-ordination.     

Effect of ferulic acid on inhibition of polyphenoloxidase and quality changes of Pacific white shrimp (Litopenaeus vannamei) during iced storage

Effects of ferulic acid (FA) on polyphenoloxidase (PPO) and the quality changes of Pacific white shrimp (Litopenaeus vannamei) during iced storage for 10 days were investigated. Both FA and oxygenated FA (OFA) with different concentrations (0.1%, 0.5%, 1% and 2% (w/v)) showed PPO inhibitory activity in a dose dependent manner. FA was generally more effective in PPO inhibition than was OFA. Based on activity staining, white shrimp PPO with an apparent molecular weight of 210 kDa was inhibited by FA. When whole shrimps were treated with FA solution with concentrations of 1% or 2% and stored in ice for up to 10 days, the increase in psychrophilic and mesophilic bacterial count were retarded, in comparison with the control and those treated with 1.25% sodium metabisulphite (SMS). The coincidental lower rates of increase in pH and total volatile base content were obtained. Additionally, shrimps treated with 2% FA possessed the lowest peroxide value and thiobarbituric acid reactive substances (TBARS) value during the storage. After 10 days of storage, shrimps treated with 2% FA had the lower melanosis score and higher score for colour, flavour and overall likeness, compared with the control and SMS treated shrimps (P < 0.05).     

Photoelectrochemical analysis of band gap modulated TiO2 for photocatalytic water splitting

In this study the photocatalysis efficiency of titania (TiO₂) is increased by conjugating it with folic acid (FA) molecules through a silane linker (APTMS) layer. Electrochemical testing demonstrated higher negative open circuit potential (OCP) in surface engineered TiO₂ as compared to TiO₂ indicating higher Schottky barrier leading to suppressed electron–hole pair recombination. The photocurrent density under no bias conditions demonstrated 55% increase in modified titania due to lower band gap and suppressed electron hole pair recombination. The mechanism behind higher photocatalytic properties of surface engineered TiO₂ was derived using density functional theory (DFT).