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Session Overview
6.07: New methodologies for plant safety analysis
Monday, 16/Mar/2020:
3:15pm - 5:00pm

Session Chair: Tomofumi Yamamoto, Mitsubishi Heavy Industries, Ltd, Japan
Location: R-3014

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Passive gamma emission tomography with ordered subset expectation maximization method

Shigeki Shiba, Hiroshi Sagara

Tokyo Institute of Technology

In nuclear power facilities, the digital Cherenkov viewing device (DCVD) and the improved Cherenkov viewing device (ICVD) possessing high mobility and economic performance in nuclear safeguards are available for the non-destructive assay (NDA) to detect missing fuels in spent fuel pools (SFP). ICVD and DCVD, however, have limitations with regards to fully verifying nuclear material data. Thus, as a potential verification tool, gamma emission tomography (GET) was developed to visualize passive gamma-ray emitter source of fuel rods. The reality that convergence iteration in MLEM algorithm used in GET is proportional to the pixel size leading to slow convergence and elevated calculation cost for practical application. For the reason, GET using ordered subset expectation maximization method (OSEM) was developed to reduce calculation cost. As a feasibility study, rod-wise relative gamma intensity distribution of a PWR 17 × 17 mock-up fuel assembly was reconstructed by GET using OSEM. As a result, OSEM reconstructed the distribution with effective decrease in iteration calculations. GET using OSEM was concluded to be an effective visualization technique of gamma ray emitters for verification.

The effect of interpolation on the fast Fourier transform based calculation of three-dimensional dose rate field

Junkai Liu, Hong Li, Sheng Fang, Xinpeng Li

Tsinghua University

The calculation of the three-dimensional dose rate field plays a key role in radiation dose estimation and nuclear emergency .

The recent fast calculation method based on Fast Fourier transform (FFT) can greatly speed up the calculation without losing accuracy, which is promising for operational usage in nuclear emergency response system. But it can only be used for uniform grid. Unfortunately, most atmospheric dispersion models use a non-uniform grid, which prevent the direct application of FFT-based calculation. Therefore, interpolation must be performed beforehand to use the Fourier transform, which may cause errors and affect computing efficiency. So optimization is necessary. In this paper, an atmospheric dispersion modeling case of a typical nuclear power plant is used to study the efficiency of different interpolation methods, which is based on non-uniform grid. The investigated factors include linear interpolation, cubic spline interpolation, and nearest neighbor interpolation. The study also covers the effect of grid resolution. The calculated dose rates at typical positions are compared to the point-kernel integration method. The accuracy of different methods are analyzed and the appropriate interpolation method is recommended to make a good balance between accuracy and speed.

Application of Artificial Intelligence in Analysis of Ultimate Response Guidelines of Lungmen Nuclear Power Plant

Yumin Chen, Yusheng Wang, Feijan Tsai, Min Lee

National Tsing Hua University

Ultimate Response Guidelines (URGs) was proposed by Taiwan Power Company to mitigate the so-called “Fukushima type accident” of nuclear power plants. As specified in URGs, if it is necessary, operators will depressurize the reactor coolant system to bring in the low-pressure water. Decay heat is then removed via containment venting. These collective actions are called DIVing (depressurizing, injecting, and venting) in URGs. The actions are designed to avoid large-scale evacuation of public around the damaged plant during the accident. In the present study, the effectiveness of URGs to prevent the large release of radionuclide to the environment is assessed using RELAP5 and MAAP5 codes. The plant analyzed is Lungmen Nuclear Power Station. The purpose of the study is to identify the acceptable initial state for operators to carry out depressurization actions. The success criterion is the peaking cladding temperature is kept below 1500 °F during the transient. It can be noticed that the peak cladding reached depends on the timing of emergency depressurization, the flow rate of low-pressure injection, water level and pressure upon the initiation of emergency depressurization. The results provide guidance for operators when the depressurization actions of URGs are executed. Based on the results of RELAP5 simulation, artificial intelligence (A.I.) technique is applied into the identification of success criterion. Identification of success criterion is a classification type problem in A.I. technique. To identify a given plant state, the posteriori probability density function of an event represented by the feature vector is considered. Gaussian kernel is chosen for the likelihood function. The accuracy of the identification is about 95%.

Monitoring System for Data integrity of Reactor Protection System using Blockchain Technologies

Moon Kyoung Choi1, Chan Yeob Yeun2, Poon Hyun Seong1

1Korea Advanced Institute of Science and Technology; 2Khalifa University

Nuclear Power Plants (NPPs) are physically isolated from external networks and have a different operational environment from the conventional IT systems. As a result, NPPs were regarded safe from external cyber-attacks. However, it was determined that the isolated networks are not safe from cyber-attacks. Unlike the IT field which prioritizes confidentiality, the nuclear power plant, which is critical infrastructure, prioritizes integrity and availability. Malicious data injection attacks on Programmable Logic Controllers (PLCs) deployed in the safety system of NPPs would be critical such as Stuxnet attack to nuclear facilities. It is necessary to monitor the integrity of PLC logic and to protect them from cyber threats such as modification of deployed logics or set-points in PLCs. RG5.71 by U.S NRC recommends security controls must be implemented to ensure the integrity of the critical systems and to monitor cyber-attacks against them. Cybersecurity controls such as Host-based Intrusion Detection System (HIDS) satisfying the security requirements should be developed and applied to NPPs. In order to address the problem, a monitoring system for data integrity of PLC using blockchain technologies was developed in this research. The private blockchain network to monitor for the integrity of PLC data in NPPs is developed. Instead of bitcoin transaction data, memory data in PLC was converted to hash value and stored in the blockchain. Integrity monitoring system for Reactor Protection System (RPS) which is a safety system in NPPs is developed by using the proposed blockchain system. It can detect cyber attacks such as false code injection attacks to PLC logic, and monitor which PLC's code integrity has been compromised. The security level of NPPs is expected to be improved because the attacker's stealth is not guaranteed and the integrity of systems is continuously monitored.

Development of a wireless radiation monitoring and mapping robot based on Geiger-Muller counter and Global Positioning System

Sadman Sakib1, Md. Tanvir Hasan1, Md. Akib-Ul Islam Safa1, M.A. Rashid Sarkar2

1Military Institute of Science & Technology; 2Bangladesh University of Engineering & Technology

This paper reports a simple model which will provide an opportunity to monitor and create a mapping system, providing us with sufficient amount of data to relocate the hidden radioactive sources. It briefly reports the fabrication of a wireless robot which will be able to measure the radiation with the help of Geiger-Muller counter. It will also be able to send the data to a remote computer. The remote computer, then will analyze the CPM corresponding to global coordinates i.e. latitude and longitude and will create a grid style mapping pattern. The robot can work both in manual or remote-controlled mode and in automatic mode. This remote-controlled robot can survive hazardous environment if given proper shielding which is also considered here. The main achievement of this project is this system is suitable for detecting radiation from point sources and which can single-handedly maintain the monitoring and mapping part. We scanned a certain area with our robot and it sent us 323 cpm at Latitude: 23.829339; Longitude: 90.387779, 125 cpm at Latitude: 23.829323; Longitude: 90.387771, 78 cpm at Latitude: 23.829321; Longitude: 90.387764, 52 cpm at Latitude: 23.829318; Longitude: 90.387759, 25 cpm at Latitude: 23.829311; Longitude: 90.387751. By the result, we can conclude that, cpm is inversely proportional to distance between counter and source. We can also prepare a grid style mapping pattern based on the observed data. Because of principally dangerous nature of gamma-radiation, the idea was developed to broadly use robotic systems and automation in radiation environment to minimize human exposure to radiation. Mobile robot has eliminated the problems of measuring radiation in hazardous cases.

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