• Proceedings of the KSME Conference
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• 2003.04a
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• pp.617-621
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• 2003

The purpose of this paper is to analyze piping failure trend of safety pipings In domestic nuclear power plants. First, database for the piping failure was constructed with 105 data fields. The database includes plant population data, event data, and service history data. 7 kinds of piping failures in domestic NPPs were investigated. Among the 7 cases, detailed root causes were investigated for 3 cases. The first one is pipe wall thinning in main feedwater pipings of Westinghouse 3 loop type plants. The root cause of the wall thinning was flow accelerated corrosion near welding area. The next one is leak event in chemical and volume control system(CVCS) due to vibration. Some cracks occurred in socket welding area. The events showed that the integrity or socket weld is very vulnerable to vibration. The last one is also a leak event in primary sampling line in Korean standard reactor due to thermal fatigue. Although the structural integrity was not maintained by the events, there was no effect on nuclear safety in the above 3 piping failure eases.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.3
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• pp.243-251
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• 2018

In the shipyard, a lot of data is generated, stored, and managed during design, construction, and operation phases to build ships and offshore structures. However, it is difficult to handle such big data efficiently using existing data-handling technologies. As the big data technology is developed, the ship and offshore industries start to focus on the existing big data to find valuable information from it. In this paper, the material requirement estimation method of offshore structure piping materials using big data analysis is proposed. A big data platform for the data analysis in the shipyard is introduced and it is applied to the analysis of material requirement estimation to solve the problems in piping design by a designer. The regression model is developed from the big data of piping materials and verified using the existing data. This analysis can help a piping designer to estimate the exact amount of material requirement and schedule the purchase time.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.349-359
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• 2017

During the past 25 years, in the context of probabilistic safety assessment, efforts have been directed towards establishment of comprehensive pipe failure event databases as a foundation for exploratory research to better understand how to effectively organize a piping reliability analysis task. The focused pipe failure database development efforts have progressed well with the development of piping reliability analysis frameworks that utilize the full body of service experience data, fracture mechanics analysis insights, expert elicitation results that are rolled into an integrated and risk-informed approach to the estimation of piping reliability parameters with full recognition of the embedded uncertainties. The discussion in this paper builds on a major collection of operating experience data (more than 11,000 pipe failure records) and the associated lessons learned from data analysis and data applications spanning three decades. The piping reliability analysis lessons learned have been obtained from the derivation of pipe leak and rupture frequencies for corrosion resistant piping in a raw water environment, loss-of-coolant-accident frequencies given degradation mitigation, high-energy pipe break analysis, moderate-energy pipe break analysis, and numerous plant-specific applications of a statistical piping reliability model framework. Conclusions are presented regarding the feasibility of determining and incorporating aging effects into probabilistic safety assessment models.

• Corrosion Science and Technology
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• v.12 no.3
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• pp.142-148
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• 2013

Safety is a major concern in Nuclear Power Plants (NPPs). Piping systems in NPPs are very complex and composed of many components such as tees, elbows, expanders and straight pipes. The high pressure and high temperature water flows inside piping components. As high speed water flows inside piping, the pipe wall thinning occurs in various reasons such as FAC (Flow Accelerated Corrosion), LDIE (Liquid Droplet Impingement Erosion) and Flashing. To inspect the wall thinning phenomenon and protect the piping from damages, piping components are checked by UT measurement in every overhaul. During every overhaul, approximately 200~300 components (40,000~60,000 UT data) are examined in NPPs. There are some methods from EPRI for evaluating wear rate of components. However, only few studies have been conducted to find out the raw data reliability for the wear rate evaluation. Securing the reliable raw data is the key factor for a reasonable evaluation. This paper suggests the reliability analysis method for the repeatedly measured data for wear rate evaluation.

• Ocean Systems Engineering
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• v.9 no.1
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• pp.79-95
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• 2019

The material analysis of an offshore structure is generally conducted in the contract design phase for the price quotation of a new offshore project. This analysis is conducted manually by an engineer, which is time-consuming and can lead to inaccurate results, because the data size from previous projects is too large, and there are so many materials to consider. In this study, the piping materials in an offshore structure are analyzed for contract design using a big data framework. The big data technologies used include HDFS (Hadoop Distributed File System) for data saving, Hive and HBase for the database to handle the saved data, Spark and Kylin for data processing, and Zeppelin for user interface and visualization. The analyzed results show that the proposed big data framework can reduce the efforts put toward contract design in the estimation of the piping material cost.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.13-26
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• 2014

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.19-24
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• 2021

This paper presents a method to generate three-dimensional AR/VR models using the information in Isogen data files (IDFs). An IDF is an output file produced by ISOGEN that contains piping isometric drawings. A piping isometric drawing is used for pipeline installation in the shipyard; therefore, the drawing describes assembly information with symbolic features, not with detailed geometric features. An IDF specifies relationships between piping routes and components with three-dimensional points and tag information as well as the bill of the materials of a pipeline. The key idea of this paper is that AR/VR models can be generated with the piping route points data and piping components tag information in real time, without any conversion of standard data exchange file formats, such as STP, IGES, and SAT. This paper describes IDF data structure and suggests the geometry generation process with IDF data and parametric functions.

• Corrosion Science and Technology
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• v.13 no.2
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• pp.62-69
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• 2014

A huge number of carbon steel piping components installed in the secondary system of nuclear power plants are exposed to aging mechanisms such as FAC (Flow-Accelerated Corrosion), Cavitation, Flashing, and LDIE (Liquid Droplet Impingement Erosion). Those aging mechanisms can lead to thinning of the piping components. To manage the wall thinning degradation, most of utilities in the world predict the wall thinning rate based on the computational program such as CHECWORKS, COMSY, and BRT-CICERO, evaluate the UT (Ultrasonic Test) data, and determine next inspection timing, repair or replacement, if needed. There are several evaluation methods, such as band, blanket, and strip methods, commonly used for determining the wear of piping components from single UT inspection data. It has been identified that those single UT evaluation methods not only do not consider the manufacturing features of pipes, but also may exclude the data of the most thinned point when determining the representative wear rate of piping components. This paper describes a newly developed single UT evaluation method, E-Cross method, for solving above problems and introduces application examples for several pipes and elbows. It was identified that the E-Cross method using the length and width of UT data excluded the most thinned points appropriate as the single UT evaluation method for thinned piping components.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.784-791
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• 2013

Recent advanced IT made layout design fast and accurate by using algorithms. Layout design should be determined by considering the position of equipment with satisfying various space constraints and its component works with optimum performance. Especially, engine room layout design is performed with mother ship data, theoretical optimal solution, design requirements and several design constraints in initial design stage. Piping design is affected by position of equipment seriously. Piping design depends on experience of designer. And also piping designer should consider correlation of equipment and efficiency of space. In this study, space evaluation method has been used to evaluate efficiency of space. And also this study suggested object function for optimal piping route, Average Reservation Index(ARI), Estimated Piping Productivity(EPP) and with modified space evaluation method. In this study, optimum pipe routing system has been developed to reflect automated piping route with space efficiency and experience of piping designer. Engine room is applied to the design of the piping in order to confirm validity of the developed system.

• Journal of Power System Engineering
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• v.13 no.6
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• pp.35-42
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• 2009

The piping systems in the steam-driven power engines lie under the cyclic condition of thermal expansion and contraction by superheated steam. These phenomena might cause some severe damages on the pipes and the accessory devices. To avoid these damages, the calculation of the proper strength and the consideration of the reduced resultant forces on the materials are needed. In the present study, numerical investigations on the effects of the thermal deformation of the industrial piping system were performed with comparison of the design data. Commercial software, ABAQUS with the thermal-fluidic loadings based on the design conditions was used for the thermal stress analysis of the piping system. From the analysis of the initially-designed pipe supporters, the rearrangement was suggested to improve the piping design.