• Journal of the Korean Institute of Gas
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• v.23 no.4
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• pp.65-73
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• 2019

A spiral steel pipe has been more used widely as a structural member as well as transport pipeline because the pipe can be manufactured continuously, consequently more economical than the conventional UOE pipe. As improved pipe manufacture technology makes spiral pipes to have high strength and to have larger diameters, the spiral pipes have been recently used as long distance transport pipeline with a large diameter and strain-based design is thus required to keep structural integrity and cost effectiveness of the spiral pipe. However, design codes of spiral pipe have not been completely established yet, and structural behaviors of a spiral pipe are not clearly understood for strain-based design. In this paper, the effects of residual stresses due to the spiral pipe manufacture process are investigated on the flexural behavior of the spiral pipe. Finite element analyses were conducted to estimate residual stresses due to the manufacturing process for the pipes which have different forming angle, thickness, and strength, respectively. After that, the results were used as initial conditions for flexural analysis of the pipe to numerically investigate its flexural behaviors.

• Smart Structures and Systems
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• v.23 no.6
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• pp.695-702
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• 2019

The number of cable-stayed bridges has been increasing worldwide, causing issues in maintaining the structural safety and integrity of bridges. The stay cable, one of the most critical members in cable-stayed bridges, is vulnerable to wind-induced vibrations owing to its inherent low damping capacity. Thus, vibration mitigation of stay cables has been an important issue both in academia and practice. While a semi-active control scheme shows effective vibration reduction compared to a passive control scheme, real-world applications are quite limited because it requires complicated equipment, including for data acquisition, and power supply. This study aims to develop an Arduino-based integrated cable vibration control system implementing a semi-active control algorithm. The integrated control system is built on the low-cost, low-power Arduino platform, embedding a semi-active control algorithm. A MEMS accelerometer is installed in the platform to conduct a state feedback for the semi-active control. The Linear Quadratic Gaussian control is applied to estimate a cable state and obtain a control gain, and the clipped optimal algorithm is implemented to control the damping device. This study selects the magnetorheological damper as a semi-active damping device, controlled by the proposed control system. The developed integrated system is applied to a laboratory size cable with a series of experimental studies for identifying the effect of the system on cable vibration reduction. The semi-active control embedded in the integrated system is compared with free and passive mode cases and is shown to reduce the vibration of stay-cables effectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.290-296
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• 2019

Head-up displays for vehicles play an important role in displaying various information about the safety and convenience of driving on the windshield of the vehicle. In this study, ultra-precision machining was performed and evaluated as a method for machining a large-area aspheric free-form mirror that is applicable to augmented reality technology. Precision diamond cutting is highly accurate and suitable for the production of advanced parts with excellent surface integrity, low surface roughness, and low residual stress. By using an aspheric free-form mold, it is possible to improve the optical transfer function, reduce the distortion path, and realize a special image field curvature. To make such a mold, the diamond cutting method was used, and the result was evaluated using an aspherical shape-measuring machine. As a result, it was possible to the mold with shape accuracy (PV) below $1{\mu}m$ and surface roughness (Ra) below $0.02{\mu}m$.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.73-82
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• 2018

In this work, a hardware based cryptographic module for the cyber security of nuclear power plant is developed using a system engineering approach. Nuclear power plants are isolated from the Internet, but as shown in the case of Iran, Man-in-the-middle attacks (MITM) could be a threat to the safety of the nuclear facilities. This FPGA-based module does not have an operating system and it provides protection as a firewall and mitigates the cyber threats. The encryption equipment consists of an encryption module, a decryption module, and interfaces for communication between modules and systems. The Advanced Encryption Standard (AES)-128, which is formally approved as top level by U.S. National Security Agency for cryptographic algorithms, is adopted. The development of the cyber security module is implemented in two main phases: reverse engineering and re-engineering. In the reverse engineering phase, the cyber security plan and system requirements are analyzed, and the AES algorithm is decomposed into functional units. In the re-engineering phase, we model the logical architecture using Vitech CORE9 software and simulate it with the Enhanced Functional Flow Block Diagram (EFFBD), which confirms the performance improvements of the hardware-based cryptographic module as compared to software based cryptography. Following this, the Hardware description language (HDL) code is developed and tested to verify the integrity of the code. Then, the developed code is implemented on the FPGA and connected to the personal computer through Recommended Standard (RS)-232 communication to perform validation of the developed component. For the future work, the developed FPGA based encryption equipment will be verified and validated in its expected operating environment by connecting it to the Advanced power reactor (APR)-1400 simulator.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.118-124
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• 2021

The article examines the formation of a competitive paradigm of economic security of industrial enterprises in the formation of a circular economy. The basic laws of industrial enterprises are formed, which determined the characteristics of competitive positions and threats. The basic competitive concepts and their application at maintenance of economic safety of the industrial enterprises in the conditions of formation of circular economy are described. Thus, the technological approach to the formation of a competitive paradigm is based on production technologies, opportunities for technological modernization and development of infrastructure and intellectual competencies. The institutional concept reveals the regulatory mechanisms for ensuring competitiveness through the protectionism of national industrial enterprises, standardization and regulation of market imbalances. The innovation-investment approach within the competitive paradigm is also manifested in the creation of competitive advantages due to the presence of active innovative developments and their commercialization, knowledge and competencies of staff, capitalization of intelligence and communications, constant updating of infrastructure and technologies. Collectively, innovation and investment effects on the level of economic security allow industrial enterprises to ensure resilience to increasing competition, the emergence of new market challenges in the formation of a circular economy. A strategic approach to the application of a competitive paradigm to ensure the economic security of industrial enterprises allows you to justify the prospects for development and design behavioral models to predict and assess potential threats. The concept of system management is based on the complexity of threat analysis, the integrity of the economic security system, system-forming functions and patterns of implementation of industrial development tasks in the formation of a circular economy. The application of the described concepts is formalized by the authors through the definition of the basic patterns, directions and characteristics of their impact on the elements of the security system of industrial enterprises in the formation of a circular economy.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.773-779
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• 2021

CNG, which has recently been attracting attention as an alternative fuel in the transportation field to reduce emissions caused by global warming, is natural gas with abundant reserves and mainly composed of methane. Being in a gaseous state, natural gas requires the compression and liquefaction processes for transportation. Until now, general shut-off valves for liquid and gas piping have been developed in Korea, but there are few studies on shut-off valves for high pressures of about 200 bar. Currently, research on the flow analysis of valves is being actively conducted around the world. However, there are relatively many studies on large valves such as low-pressure valves or shipbuilding and marine, and the safety factor through structural analysis to check the structural integrity of the valve is checked at the design stage. Since it is necessary to have a fast response speed while minimizing pressure and speed loss due to flow change, basic research was conducted on the flow analysis of the valve to secure design data, and the numerical analysis was performed on high-pressure automatic shut-off valves applied to CNG refueling stations. After securing the basic valve shape through reverse engineering for advanced products, we compared the valve flow coefficient Cv coefficient with advanced products. As a result, it was found that the reverse engineering model was at the level of about 60%. However, we compared the Cv coefficient by modifying the reverse engineering model, and the result showed that it was improved to about 96%.

• Smart Structures and Systems
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• v.29 no.1
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• pp.77-91
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• 2022

Various monitoring systems have been implemented in civil infrastructure to ensure structural safety and integrity. In long-term monitoring, these systems generate a large amount of data, where anomalies are not unusual and can pose unique challenges for structural health monitoring applications, such as system identification and damage detection. Therefore, developing efficient techniques is quite essential to recognize the anomalies in monitoring data. In this study, several machine learning techniques are explored and implemented to detect and classify various types of data anomalies. A field dataset, which consists of one month long acceleration data obtained from a long-span cable-stayed bridge in China, is employed to examine the machine learning techniques for automated data anomaly detection. These techniques include the statistic-based pattern recognition network, spectrogram-based convolutional neural network, image-based time history convolutional neural network, image-based time-frequency hybrid convolution neural network (GoogLeNet), and proposed ensemble neural network model. The ensemble model deliberately combines different machine learning models to enhance anomaly classification performance. The results show that all these techniques can successfully detect and classify six types of data anomalies (i.e., missing, minor, outlier, square, trend, drift). Moreover, both image-based time history convolutional neural network and GoogLeNet are further investigated for the capability of autonomous online anomaly classification and found to effectively classify anomalies with decent performance. As seen in comparison with accuracy, the proposed ensemble neural network model outperforms the other three machine learning techniques. This study also evaluates the proposed ensemble neural network model to a blind test dataset. As found in the results, this ensemble model is effective for data anomaly detection and applicable for the signal characteristics changing over time.

• Steel and Composite Structures
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• v.43 no.2
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• pp.165-183
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• 2022

Most transportation departments have recognized and developed procedures to address the ever-increasing weights of trucks traveling on bridges in a service today. Transportation agencies also recognize the issues with overheight vehicles' collisions with bridges, but few stakeholders have definitive countermeasures. Bridges are becoming more vulnerable to collisions from overheight vehicles. The exact response under lateral impact force is difficult to predict. In this paper, nonlinear impact analysis shows that the degree of deformation recorded through the modeling of the unprotected vehicle-girder model provides realistic results compared to the observation from the US-61 bridge overheight vehicle impact. The predicted displacements are 0.229 m, 0.161 m, and 0.271 m in the girder bottom flange (lateral), bottom flange (vertical), and web (lateral) deformations, respectively, due to a truck traveling at 112.65 km/h. With such large deformations, the integrity of an impacted bridge becomes jeopardized, which in most cases requires closing the bridge for safety reasons and a need for rehabilitation. We proposed different sacrificial cushion systems to dissipate the energy of an overheight vehicle impact. The goal was to design and tune a suitable energy absorbing system that can protect the bridge and possibly reduce stresses in the overheight vehicle, minimizing the consequences of an impact. A material representing a Sorbothane high impact rubber was chosen and modeled in ANSYS. Out of three sacrificial schemes, a sandwich system is the best in protecting both the bridge and the overheight vehicle. The mitigation system reduced the lateral deflection in the bottom flange by 89%. The system decreased the stresses in the bridge girder and the top portion of the vehicle by 82% and 25%, respectively. The results reveal the capability of the proposed sacrificial system as an effective mitigation system.

• Journal of Industrial Convergence
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• v.20 no.10
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• pp.17-24
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• 2022

Lora, a non-band network technology of the long-distance wireless standard LPWAN standard, uses ABP and OTTA methods and AES-128-based encryption algorithm (shared key) for internal terminal authentication and integrity verification. Lora's recent firmware tampering vulnerability and shared-key encryption algorithm structure make it difficult to defend against MITM attacks. In this study, the consensus algorithm(PBFT) is applied to the Lora network to enhance safety. It performs authentication and PBFT block chain creation by searching for node groups using the GPS module. As a result of the performance analysis, we established a new Lora trust network and proved that the latency of the consensus algorithm was improved. This study is a 4th industry convergence study and is intended to help improve the security technology of Lora devices in the future.