• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.319-336
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• 2015

Life cycle performance of corrosion affected RC structures is an important and challenging issue for effective infrastructure management. The accurate condition assessment of corroded RC structures mainly depends on the effective evaluation of deterioration occurring in the structures. Structural performance deterioration caused by reinforcement corrosion is a complex phenomenon which is generally uncertain and non-decreasing. Therefore, a stochastic modelling such as the gamma process can be an effective tool to consider the temporal uncertainty associated with performance deterioration. This paper presents a time-dependent reliability analysis of corrosion affected RC structures associated bond strength degradation. Initially, an analytical model to evaluate cracking in the concrete cover and the associated loss of bond between the corroded steel and the surrounding cracked concrete is developed. The analytical results of cover surface cracking and bond strength deterioration are examined by experimental data available. Then the verified analytical results are used for the stochastic deterioration modelling, presented here as gamma process. The application of the proposed approach is illustrated with a numerical example. The results from the illustrative example show that the proposed approach is capable of assessing performance of the bond strength of concrete structures affected by reinforcement corrosion during their lifecycle.

• Journal of Powder Materials
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• v.24 no.6
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• pp.494-507
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• 2017

A three-dimensional physical part can be fabricated from a three-dimensional digital model in a layer-wise manner via additive manufacturing (AM) technology, which is different from the conventional subtractive manufacturing technology. Numerous studies have been conducted to take advantage of the AM opportunities to penetrate bespoke custom product markets, functional engineering part markets, volatile low-volume markets, and spare part markets. Nevertheless, materials issues, machines issues, product issues, and qualification/certification issues still prevent the AM technology from being extensively adopted in industries. The present study briefly reviews the standard classification, technological structures, industrial applications, technological advances, and qualification/certification activities of the AM technology. The economics, productivity, quality, and reliability of the AM technology should be further improved to pass through the technology adoption lifecycle of innovation technology. The AM technology is continuously evolving through the introduction of PM materials, hybridization of AM and conventional manufacturing technologies, adoption of process diagnostics and control systems, and enhanced standardization of the whole lifecycle qualification and certification methodology.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.200-210
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• 2013

It has become important to manage plant data effectively and to share these data among different organizations that are located in different places and participate in a variety of lifecycle phases. ISO 15926 is an international standard for integration of lifecycle data for process plants including oil and gas facilities. This standard consists of several parts providing a generic data model, reference data, and implementation methods. iRINGTools is a tool developed for the exchange of plant design data. This tool supports the implementation methods specified in ISO 15926. In this paper, the exchange of plant design data using iRINGTools is investigated. For this, sample P&ID data was modeled and data exchange experiment was performed. From the experiment, a data exchange procedure based on ISO 15926 is established and design data types that can be practically exchanged using ISO 15926 were identified.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.197-206
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• 2009

We introduce a novel high-level security metrics objective taxonomization model for software- intensive systems. The model systematizes and organizes security metrics development activities. It focuses on the security level and security performance of technical systems while taking into account the alignment of metrics objectives with different business and other management goals. The model emphasizes the roles of security-enforcing mechanisms, the overall security quality of the system under investigation, and secure system lifecycle, project and business management. Security correctness, effectiveness and efficiency are seen as the fundamental measurement objectives, determining the directions for more detailed security metrics development. Integration of the proposed model with riskdriven security metrics development approaches is also discussed.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2006.05a
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• pp.384-389
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• 2006

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.360-363
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• 2006

Regester & Larkin(2005) suggest the issue and risk lifecycle analysis method in risk management, made up of the potential, emerging, current, crisis, and dormant stages. Investment on New & Renewable Energy is meaningful in effect ive risk management for diminishing or reducing the shock of a energy current, at the potential stage. In this study, we survey the risk of traditional fossil fuel projects and develop the risk analysis model for new & renewable energy projects specially geothermal energy resources and gas-hydrate resources.

• Korean Journal of Computational Design and Engineering
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• v.22 no.1
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• pp.28-36
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• 2017

Sharing of CAD data plays a key role in the PLM and a lightweight model is widely used for visualizing and sharing a large data. The lightweight model is mainly composed of triangular elements to minimize file size. There is no problem at all to visually confirm the shape based on these triangular elements but there is a limit to numerically calculate the exact position on the curve or surface. In this paper, a boundary curve generation method using triangular elements is proposed to increase the utilization of lightweight models. After matching connectivity of triangular elements, boundary element edges are extracted. Boundary curves are generated by connecting of these boundary element edges. This proposed method has been tested on several models to demonstrate the feasibility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4174-4190
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• 2019

IEC 62304 is a standard for the medical device software lifecycle. Developers must develop software that complies with all specifications in the standard for licensing. However, because the standard contains not only a large number of specifications, but also domain-specific information and association relationships between specifications, it requires considerable effort and time for developers to understand and interpret the standard. To support developers, this paper presents a method for extracting the contents of the IEC 62304 standard as a goal model, which is the core methodologies of requirements engineering. The proposed method analyzes the grammar of the standard to robustly extract complex structures and various information from standard specifications and define rules that extract goals and links from syntactic element units. We validated the actual extraction process for the standard document experimentally. Based on the extracted goal model, developers can intuitively and efficiently comply with the standard and track specific information within the medical software and standard domains.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.49-57
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• 2018

The main objective of this paper is come up with methodology approach for FPGA-based system in verification and validation lifecycle regarding software reliability using system engineering approach. The steps of both reverse engineering and re-engineering are carried out to implement an FPGA-based of safety critical system in Nuclear Power Plant. The reverse engineering methodology is applied to elicit the requirements of the system as well as gain understanding of the current life cycle and V&V activities of FPGA based-system. The re-engineering method is carried out to get a new methodology approach of software reliability, particularly Software Reliability Growth Model. For measure the software reliability of a given FPGA-based system, the following steps are executed as; requirements definition and measurement, evaluation of candidate reliability model, and the validation of the selected system. As conclusion, a new methodology approach for software reliability measurement using software reliability growth model is developed.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.