با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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Joint optimization of safety barriers for enhancing business continuity of nuclear power plants against steam generator tube ruptures accidents
بهینه سازی مشترک موانع ایمنی برای افزایش تداوم تجارت نیروگاه های هسته ای در برابر حوادث پارگی لوله مولد بخار-2020 In nuclear power plants (NPPs), different types of safety barriers are designed to ensure the safe and continuous operation of the NPP against disruptive events. These safety barriers, although designed to operate in different phases of the accidents evolution, are often optimized separately, without considering their collective effects on preventing disruptions and quickly recovering from the disruptions. This paper develops a joint optimization model for synthetically optimizing safety barriers of different natures, including prevention, mitigation, emergency and recovery barriers to enhance the business continuity of the NPP, considering the threat of steam generator tube rupture (SGTR) accidents. The joint optimization is guided by a business continuity metric called expected business continuity value (EBCV). A physics-of-failure model is developed to describe the crack growth process of the steam generator tube and to model the effect of the prevention barriers, i.e., periodical inspection of the crack length. An event tree model is developed to describe the evolution of the SGTR-initiated accident and to model the effect of the mitigation and emergency barriers. Recovery measures are also considered via a widely-used logarithmic function model. A mixed-integer genetic algorithm (MIGA) is used to obtain optimal solutions of the joint optimization model. The results show that the developed joint optimization model can achieve better performance in terms of business continuity, compared to the conventional methods that optimize the safety barriers separately. Keywords: Business continuity management (BCM) | Safety barrier | Joint optimization | Event tree (ET) | Mixed-integer genetic algorithm (MIGA) | Nuclear power plant (NPP) | Steam generator tube rupture (SGTR) |
مقاله انگلیسی |
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ViDAQ: A computer vision based remote data acquisition system for reading multi-dial gauges
ViDAQ: سیستم کسب اطلاعات از راه دور مبتنی بر بینایی ماشین برای خواندن سنجهای چند زبانه-2019 This paper presents and evaluates design improvements to the Visual Data Acquisition (ViDAQ) system for
reading multi-dial gauges. ViDAQ in general, is targeted to occupy a niche application for a cost effective and
readily deployable solution for non-intrusive and remote acquisition of data from legacy human machine interface
(HMI) indicators. Legacy HMI indicators that pose numerous technological hurdles in being digitally
monitored, include analogue rotary multi-dial gauges, alarm lamps, switches etc, much like those common to
industrial process monitoring systems can benefit from ViDAQ. Furthermore, ViDAQ is poised to assist in realizing
an overarching design goal of a generic EYE-on-HMI (Expert supervisorY systEm) framework. As a framework,
EYE-on-HMI stands to integrate the burgeoning field of machine learning and computer vision for realtime
detection of human-in-the-loop operator errors and gather human performance data in any commercial
and/or industrial process control domain for improving operational safety. Operator interaction with HMI is
vital to the operational safety of any process control such as in nuclear power plant operation, aviation, public
transit vehicles, driverless vehicles, etc. and thus should be monitored actively. Keywords: Computer vision | Human machine interface (HMI) | Human factors engineering (HFE) | Expert supervisory system | Nuclear power plant (NPP) | Cyber physical systems (CPS) | Remote monitoring |
مقاله انگلیسی |