• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1162-1165
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• 2001

Operational Modal Analysis also known as Output Only Modal Analysis has in the recent years been used for extracting modal parameters of civil engineering structures and is now becoming popular for mechanical structures. The advantage of the method is that no artificial excitation need to be applied to the structure or force signals to be measured. All the parameter estimation is based upon the response signals, thereby minimising the work of preparation for the test. This test case is a controlled lab set-up enabling different parameter estimation methods techniques to be used and compared to the Operational Modal Analysis. For Operational Modal Analysis two different estimation techniques are used： a non-parametric technique based on Frequency Domain Decomposition (FDD), and a parametric technique working on the raw data in time domain, a data driven Stochastic Subspace Identification (SS!) algorithm. These are compared to other methods such as traditional Modal Analysis.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.87-92
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• 2015

Numerous IT organizations and companies around the world aspire to improve the efficiency and general standard of their software development. The IT organizations want to seize the opportunities and take advantages of new development processes and methodologies. These advantages include higher customers' satisfaction and better software quality among many. In order to achieve them, different agile software methodologies such as scrum, Feature driven development, eXtremeProgramming (XP), Dynamic system development method, Kanban and others have been frequently adopted by IT organizations across the world. Several studies have shown that agile software development methods are effective in a lot of settings. This study, in which 40 agile practitioners from Malaysia participated, additionally confirms the effectiveness of agile development methods. Furthermore, this paper presents some of the critical barriers not well-known by IT-organizations. The results of this analysis can be used to guide IT organization from the obstacles they may face while adopting agile in their environments.

• Smart Structures and Systems
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• v.23 no.5
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• pp.405-420
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• 2019

In this study, vibration characteristics of offshore wind turbine tower (WTT) with gravity-based foundation (GBF) are identified from dynamic responses under wave-induced excitations. The following approaches are implemented to achieve the objective. Firstly, the operational modal analysis methods such as frequency domain decomposition (FDD) and stochastic subspace identification (SSI) are selected to estimate modal parameters from output-only dynamic responses. Secondly, a GBF WTT model composed of superstructure, substructure and foundation is simulated as a case study by using a structural analysis program, MIDAS FEA. Thirdly, wave pressures acting on the WTT structure are established by nonlinear regular waves which are simulated from a computational fluid software, Flow 3D. Wave-induced acceleration responses of the target structure are analyzed by applying the simulated wave pressures to the GBF WTT model. Finally, modal parameters such as natural frequencies and mode shapes are estimated from the output-only acceleration responses and compared with the results from free vibration analysis. The effect of wave height and period on modal parameter extraction is also investigated for the mode identification of the GBF WTT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4555-4571
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• 2019

Due to increasing interest in distributed agile software development, there is a need to systematically review the literature on challenges encountered in the agile software development environment. Using the Systematic Literature Review (SLR) approach, 32 relevant publications, dated between 2013 and 2018 were selected from four electronic databases. Data from these publications were extracted to identify the key challenges across the system development life cycle (SDLC) phases, which essentially are short phases in each agile-based iteration. 5 types of key challenges were identified as impacting the SDLC phases; these challenges are Communication, Coordination, Cooperation, Collaboration and Control. In the context of the SLDC phases, the Communication challenge was discussed the most often (79 times, 33%). The least discussed challenges were Cooperation and Collaboration (26 times, 11% each). The 5 challenges occur because of distances which occur in distributed environment. This SLR identified 4 types of distances which contribute to the occurrence of these key challenges - physical, temporal, social-cultural and knowledge/experience. Of the 32 publications, only 4 included research which proposed new solutions to address challenges in agile distributed software development. The authors of this article believe that the findings in this SLR are a resource for future research work to deepen the understanding of and to develop additional solutions to address the challenges in distributed agile software development.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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• pp.579-590
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• 2018

Anomaly detection on building energy consumption has been regarded as an effective tool to reduce energy saving on building operation and maintenance. However, it requires energy model and FDD expert for quantitative model approach or large amount of training data for qualitative/history data approach. Both method needs additional time and labors. This study propose a machine learning and data science approach to define faulty conditions on hourly building energy consumption with reducing data amount and input requirement. It suggests an application of Support Vector Data Description (SVDD) method on training normal condition of hourly building energy consumption incorporated with hourly outdoor air temperature and time integer in a week, 168 data points and identifying hourly abnormal condition in the next day. The result shows the developed model has a better performance when the ${\nu}$ (probability of error in the training set) is 0.05 and ${\gamma}$ (radius of hyper plane) 0.2. The model accuracy to identify anomaly operation ranges from 70% (10% increase anomaly) to 95% (20% decrease anomaly) for daily total (24 hours) and from 80% (10% decrease anomaly) to 10%(15% increase anomaly) for occupied hours, respectively.

• Current Applied Physics
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• v.18 no.11
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• pp.1327-1337
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• 2018

This paper investigates the vibration behavior of pristine and defected triangular graphene sheets; which has recently attracted the attention of researchers and compare these two types in natural frequencies and sensitivity. Here, the molecular dynamics method has been employed to establish a virtual laboratory for this purpose. After measuring the different parameters obtained by the molecular dynamics approach, these data have been analyzed by using the frequency domain decomposition (FDD) method, and the dominant frequencies and mode shapes of the system have been extracted. By analyzing the vibration behaviors of pristine triangular graphene sheets in four cases (right angle of 45-90-45 configuration, right angle of 60-90-30 configuration, equilateral triangle and isosceles triangle), it has been demonstrated that the natural frequencies of these sheets are higher than the natural frequency of a square sheet, with the same number of atoms, by a minimum of 7.6% and maximum of 26.6%. Therefore, for increasing the resonance range of sensors based on 2D materials, nonrectangular structures, and especially the triangular structure, can be considered as viable candidates. Although the pristine and defective equilateral triangular sheets have the highest values of resonance, the sensitivity of defective (45,90,45) triangular sheet is more than other configurations and then, defective (45,90,45) sheet is the worst choice for sensor applications.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.532-548
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• 2021

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1331-1344
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• 2021

This study is to evaluate the seismic capacity of the fire-damaged cabinet facility in a nuclear power plant (NPP). A prototype of an electrical cabinet is modeled using OpenSees for the numerical simulation. To capture the nonlinear behavior of the cabinet, the constitutive law of the material model under the fire environment is considered. The experimental record from the impact hammer test is extracted trough the frequency-domain decomposition (FDD) method, which is used to verify the effectiveness of the numerical model through modal assurance criteria (MAC). Assuming different temperatures, the nonlinear time history analysis is conducted using a set of fifty earthquakes and the seismic outputs are investigated by the fragility analysis. To get a threshold of intensity measure, the Monte Carlo Simulation (MCS) is adopted for uncertainty reduction purposes. Finally, a capacity estimation model has been proposed through the investigation, which will be helpful for the engineer or NPP operator to evaluate the fire-damaged cabinet strength under seismic excitation. This capacity model is presented in terms of the High Confidence of Low Probability of Failure (HCLPF) point. The results are validated by the proper judgment and can be used to analyze the influences of fire on the electrical cabinet.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3472-3484
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• 2023

The objective of this research is to assess the seismic performance of different types of electrical cabinets in nuclear power plants. The cabinets under investigation are: (a) Case 1: a short single cabinet; (b) Case 2: a tall single cabinet; (c) Case 3: separated cabinets; and (d) Case 4: a combined cabinet with coupling effects. To accurately capture the real behavior of the cabinet, three-dimensional finite element models are developed using ANSYS with connection non-linearity. Frequency domain decomposition (FDD) is used to determine the dynamic properties of the cabinets from shaking table testing data, and these results are utilized to validate the numerical model. The close match between the experimental and numerical results obtained from the modal analysis demonstrates the accuracy of the numerical model. Subsequently, transient structural analysis is performed on the validated models to explore seismic performance. The results show that the acceleration response of the combined cabinet is lower than the single cabinet and the separated cabinet. This observation suggests that top anchors used to combine two different types of cabinets play a crucial role in assessing the efficiency and seismic resistance of electrical cabinets in a nuclear power plant.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.865-870
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• 2003

A motion controller has been used variously in industry such as semiconductor manufacture equipment, industrial robot, assembly/conveyor line applications and CNC equipment. There are several types of controller in motion control. One of these is a PC-based motion controller such as PCI or ISA, and another is stand-alone motion controller. The PC bus-based motion controller is popular because of improving bus architectures and GUI (Graphic User Interface) that offer convenience of use to user. There are some problems in this. The PC bus-based solution allows for only one of the form factors, so it has a poor flexibility. The overall system package size is bigger than other motion control system. And also, additional axes of control require additional slot, however the number of slots is limited. Furthermore, unwieldy and many wirings come to connect plants or I/O. The stand-alone motion controller has also this limit of axes of control and wiring problems. To resolve these problems, controller must have capability of operating as stand-alone devices that resides outside the computer and it needs network capability to communicate to each motion device. In this paper, a network-based stand-alone motion system is proposed. This system integrates PC and motion controller into one stand-alone motion system, and uses CAN (Controller Area Network) as network protocol. Single board computer that is type of 3.5" FDD form factor is used to reduce the system size and cost. It works with Windows XP Embedded as operating system. This motion system operates by itself or serves as master motion controller that communicates to slave motion controller. The Slave motion controllers can easily connect to master motion system through CAN-network.