• Nuclear Engineering and Technology
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• v.49 no.3
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• pp.517-524
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• 2017

Cyber security is an important issue in the field of nuclear engineering because nuclear facilities use digital equipment and digital systems that can lead to serious hazards in the event of an accident. Regulatory agencies worldwide have announced guidelines for cyber security related to nuclear issues, including U.S. NRC Regulatory Guide 5.71. It is important to evaluate cyber security risk in accordance with these regulatory guides. In this study, we propose a cyber security risk evaluation model for nuclear instrumentation and control systems using a Bayesian network and event trees. As it is difficult to perform penetration tests on the systems, the evaluation model can inform research on cyber threats to cyber security systems for nuclear facilities through the use of prior and posterior information and backpropagation calculations. Furthermore, we suggest a methodology for the application of analytical results from the Bayesian network model to an event tree model, which is a probabilistic safety assessment method. The proposed method will provide insight into safety and cyber security risks.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1791-1801
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• 2023

The multi-physics coupled methodologies that have been widely used to analyze the complex process occurring in nuclear reactors have also been used to the R&D of numerical reactors. The advancement in the field of computer technology has helped in the development of these methodologies. Herein, we report the integration of ADPRES code and RELAP5 code into the SALOME-ICoCo framework to form a multi-physics coupling platform. The platform exploits the supervisor architecture, serial mode, mesh one-to-one correspondence and explicit coupling methods during analysis, and the uncertainty analysis tool URANIE was used. The correctness of the platform was verified through the NEACRP-L-335 benchmark. The results obtained were in accordance with the reference values. The platform could be used to accurately determine the power peak. In addition, design margins could be gained post uncertainty analysis. The initial power, inlet coolant temperature and the mass flow of assembly property significantly influence reactor safety during the rod ejections accident (REA).

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.225-233
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• 2012

A comprehensive research effort in order to develop and disseminate modernized Korean housing (Hanok) has recently been initiated by Korean government. This large scale research project encompasses a wide spectrum of housing development including public policy, architectural plans, modules, construction materials and methods, prefabricated assemblies, automated production, construction management, and advanced information systems. For the purpose of integrating and automating the whole processes from an industry perspective, it is of great importance to develop a standard classification system and project numbering system (PNS) for the modernized Korean housing. This paper focuses on the standard classification systems and PNS for cost and schedule control. The distinct characteristics and managerial requirements were explored and embedded into the proposed classifications for modernized Hanok.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.484-492
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• 2023

Time-to-digital converters (TDCs) based on the tapped delay line (TDL) architecture have been widely used in various applications requiring a precise time measurement. However, the poor uniformity of the propagation delays in the TDL implemented on FPGA leads to bubble error and large nonlinearity of the TDC. The purpose of this study was to develop an advanced TDC architecture capable of minimizing the bubble errors and improving the linearity. To remove the bubble errors, the decimated delay line (DDL) architecture was implemented on the UltraScale + FPGA; meanwhile, to improve the linearity of the TDC, a histogram uniformization (HU) and multi-chain TDL (MCT) methods were developed and implemented on the FPGA. The integral nonlinearities (INLs) and differential nonlinearities (DNLs) of the plain TDCs with the 'HU method' (HU TDC) and with 'both HU and MCT methods' (HU-MCT TDC) were measured and compared to those of the TDC with 'DDL alone' (plain TDC). The linearity of HU-MCT TDC were superior to those of the plain TDC and HU TDC. The experiment results indicated that HU-MCT TDC developed in this study was useful for improving the linearity of the TDC, which allowed for high timing resolution to be achieved.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.283-292
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• 2022

Advanced radiation applications have been widely used and extended to many fields. As a result of this fact, choosing an appropriate shielding material based on the radiation application has become vital. In this regard, the integration of elements into polymer composites has been investigated and contributed to the quantity and quality of radiation shielding materials. This study reports photon attenuation parameters and electromagnetic shielding effectiveness of a novel polymer composite prepared with a matrix reinforced with three different proportions (5, 10, and 15 wt%) of niobium content. Addition of Nb dopant improves both photon attenuation and electromagnetic shielding effectiveness for the investigated composites. Therefore, Nb(15%) polymer composite with highest concentration has been found to be the best absorber for ionizing and non-ionizing radiations. Consequently, the performed analyzes provide evidences that the prepared Nb-reinforced polymer composite could be effectively used as photon radiation attenuator and electromagnetic shielding material.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.3975-3984
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• 2022

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2376-2385
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• 2022

Two groups of oxide dispersion-strengthened reduced-activation ferritic/martensitic steels (A and B) were prepared by adding Y, Ti, and Zr into steels through vacuum induction melting to investigate the inclusions, microstructures, mechanical properties of the alloys. Results showed that particles with Y, Ti, and Zr easily formed. Massive, Zr-rich inclusions were found in B steel. Density of micron inclusions in A steel was 1.42 × 10¹⁴ m^-3, and density of nanoparticles was 3.61 × 10¹⁶ m^-3. More and finer MX carbides were found in steel tempered at 650 ℃, and yield strengths (YS) of A and B steel were 714±2 and 664±3.5 MPa. Thermomechanical processing (TMP) retained many dislocations, which improved the mechanical properties. YSs of A and B treated by TMP were 725±3 and 683±4 MPa. The existence of massive Zr-rich inclusions in B steels interrupted the continuity of the matrix and produced microcracks (fracture), which caused a reduction in mechanical properties. The presence of fine prior austenite grain size and inclusions was attributed to the low DBTTs of the A steels; DBTTs of A650 and A700 alloy were -79 and -65 ℃. Tempering temperature reduction and TMP are simple, readily useable methods that can lead to a superior balance of strength and impact toughness in industry applications.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.570-581
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• 2018

Recently, a software program has been used in nuclear power plants (NPPs) to digitalize many instrumentation and control systems. To guarantee NPP safety, the reliability of the software used in safetycritical instrumentation and control systems must be quantified and verified with proper test cases and test environment. In this study, a software testing method using a simulation-based software test bed is proposed. The test bed is developed by emulating the microprocessor architecture of the programmable logic controller used in NPP safety-critical applications and capturing its behavior at each machine instruction. The effectiveness of the proposed method is demonstrated via a case study. To represent the possible states of software input and the internal variables that contribute to generating a dedicated safety signal, the software test cases are developed in consideration of the digital characteristics of the target system and the plant dynamics. The method provides a practical way to conduct exhaustive software testing, which can prove the software to be error free and minimize the uncertainty in software reliability quantification. Compared with existing testing methods, it can effectively reduce the software testing effort by emulating the programmable logic controller behavior at the machine level.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4072-4079
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• 2021

This article presents a study on the state-of-the-art methods for automated radioactive material detection and identification, using gamma-ray spectra and modern machine learning methods. The recent developments inspired this in deep learning algorithms, and the proposed method provided better performance than the current state-of-the-art models. Machine learning models such as: fully connected, recurrent, convolutional, and gradient boosted decision trees, are applied under a wide variety of testing conditions, and their advantage and disadvantage are discussed. Furthermore, a hybrid model is developed by combining the fully-connected and convolutional neural network, which shows the best performance among the different machine learning models. These improvements are represented by the model's test performance metric (i.e., F1 score) of 93.33% with an improvement of 2%-12% than the state-of-the-art model at various conditions. The experimental results show that fusion of classical neural networks and modern deep learning architecture is a suitable choice for interpreting gamma spectra data where real-time and remote detection is necessary.