• Nuclear Engineering and Technology
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• v.49 no.4
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• pp.817-824
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• 2017

Residual stress is a critical element in determining the integrity of parts and the lifetime of welded structures. It is necessary to estimate the residual stress of a welding zone because residual stress is a major reason for the generation of primary water stress corrosion cracking in nuclear power plants. That is, it is necessary to estimate the distribution of the residual stress in welding of dissimilar metals under manifold welding conditions. In this study, a cascaded support vector regression (CSVR) model was presented to estimate the residual stress of a welding zone. The CSVR model was serially and consecutively structured in terms of SVR modules. Using numerical data obtained from finite element analysis by a subtractive clustering method, learning data that explained the characteristic behavior of the residual stress of a welding zone were selected to optimize the proposed model. The results suggest that the CSVR model yielded a better estimation performance when compared with a classic SVR model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1477-1485
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• 2003

The displacement vector field can be represented in terms of a scalar potential ${\phi}$ and a vector potential ${\phi}$. The scalar potential ${\phi}$ is related to dilatational waves and the vector potential ${\phi}$ is related to rotational waves. Using these two complex displacement potentials, the stress and displacement fields for steadily growing interface cracks in dissimilar materials are obtained. The energy release rate for steadily growing interface cracks in dissimilar materials are also obtained. And with photoelastic isochromatic patterns simulated by computer graphics, the stress intensity factors are discussed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.5 no.3
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• pp.233-244
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• 2001

Stress-strain behaviour of soil varies based on stress path and stress history. There has been few study on the characteristics of yielding curve which has anisotropic compression stress history in decomposed granite soil. During this study, various stress path tests in previous anisotropic compression stress history are performed on compacted decomposed granite soil sampled at Iksan, Chonbuk. Yielding points are determined from various stress-strain curves (${\eta}-{\varepsilon}$, ${\eta}$-v, and ${\eta}$-k, ${\eta}$-W curves). Stress-strain curve is certified which shows yielding point very clearly. The shape and characteristics of anisotropic compression yielding curves are examined. The main results are summarized as follows : 1) p' constant and compressive direction in stress paths, which has experienced previous anisotropic compression stress history, shows relatively dear yielding points. 2) Yielding curves defined from ${\eta}$-k and ${\eta}$-W curve show almost perfect ellipse. 3) Directions of plastic strain incremental vector($dv^p/d{\varepsilon}^p$) are not perpendicular to yielding curve.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.207-214
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• 2020

In this paper, we implement linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) instead of conventional extended Kalman filter based vector tracking loop (EKF-VTL). The LQG-VTL can improve the performance compared to the EKF-VTL by generating optimal control input at a specific performance index. Performance analysis is conducted through two factors, frequency thermal noise and frequency dynamic stress error, which determine total frequency tracking error. We derive the thermal noise and the dynamic stress error formula in the LQG-VTL. From frequency tracking error analysis, we can determine control gain matrix in the LQG controller and show that the frequency tracking error of the LQG-VTL is lower than that of the EKF-VTL in all C/N0 ranges. The simulation results show that the LQG-VTL improves performance by 30% in Doppler tracking, so the LQG-VTL can extend pre-integration time longer and track weaker signals than the EKF-VTL. Therefore, the LQG-VTL algorithm is more robust than the EKF-VTL in weak signal environments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.45-51
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• 2012

In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.177-187
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• 2022

Theoretical literature agrees on the interaction between financial instability and economic activity but explains it's dynamic in two points of view: one is that the transmission mechanism occurs in one unique regime and the other reckons a shift of regime leads to the alteration of the transmission mechanism. This study aims to find evidence of the multi-regime transmission for ASEAN developing countries. The author employs the technique of Threshold vector auto regression using the financial stress index standing for financial instability. Monthly data is collected, covering a period long enough with many episodes of high stress in recent decades. There are two conclusions: (1) A financial shock has a negative and stronger impact on economic activity during a high-stress period than it does during a low-stress period; (2) the response of economic activity to a negative financial shock during high-stress periods is stronger than it is during normal times. The findings point to the importance of the financial stress index as an additional early warning indicator for the real economy sector, as well as the positive effect that a reduction in financial stress may have on economic activity, implying the importance of "unconventional" monetary policy in times of high financial stress.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2258-2271
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• 2016

In this paper, some crucial performance characteristics related to the operational reliability of the post-fault Pulse Width Modulated (PWM) rectifiers, such as line current harmonic distortion, Common Mode Voltage (CMV), and current stress on the capacitors, are fully investigated. The aforementioned performance characteristics of post-fault rectifiers are highly dependent on the utilized space vector modulation (SVM) schemes, which are also examined. Detailed analyses of the three most commonly used SVM schemes for post-fault PWM rectifiers are provided, revealing the major differences in terms of the zero vector synthesis approaches. To compare the performances of the three SVM schemes, the operating principles of a post-fault rectifier are presented with various SVM schemes. Using analytical and numerical methods in the time domain, the performances of the line current distortion, common mode voltage and capacitor current are evaluated and compared for each SVM scheme. The proposed analysis demonstrates that the zero vector synthesis approaches of the considered methods have significant impacts on the performance characteristics of rectifiers. In addition, the advantages and disadvantages of the proposed SVM schemes are discussed. The experimental results verify the effectiveness and validity of the proposed analysis.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.433-440
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• 2016

Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure can significantly affect railway operations with potentially disastrous consequences, early stress detection of point machine is critical for monitoring and managing the condition of rail infrastructure. In this paper, we propose a stress detection method for point machine in railway condition monitoring systems using sound data. The system enables extracting sound feature vector subset from audio data with reduced feature dimensions using feature subset selection, and employs support vector machines (SVMs) for early detection of stress anomalies. Experimental results show that the system enables cost-effective detection of stress using a low-cost microphone, with accuracy exceeding 98%.

• Geophysics and Geophysical Exploration
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• v.5 no.2
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• pp.99-107
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• 2002

An analytical forward modeling algorithm was developed for the efficient application to the geotechnical engineering in SASW (Spectral Analysis of Surface Waves) method. for the theoretical dispersion curve, the finite difference method using motion stress vector, which was proposed by Aki and Richards, was employed and verified with two earth models. For the stable and fast calculation, it was found that the model size depending on the frequency range is suitable $1.5\~2$ times bigger than the wavelength.

• Structural Engineering and Mechanics
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• v.72 no.1
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• pp.31-41
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• 2019

Structural integrity assessment of piping components is of paramount important for remaining life prediction, residual strength evaluation and for in-service inspection planning. For accurate prediction of these, a reliable fracture parameter is essential. One of the fracture parameters is stress intensity factor (SIF), which is generally preferred for high strength materials, can be evaluated by using linear elastic fracture mechanics principles. To employ available analytical and numerical procedures for fracture analysis of piping components, it takes considerable amount of time and effort. In view of this, an alternative approach to analytical and finite element analysis, a model based on relevance vector machine (RVM) is developed to predict SIF of part through crack of a piping component under fatigue loading. RVM is based on probabilistic approach and regression and it is established based on Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Model for SIF prediction is developed by using MATLAB software wherein 70% of the data has been used for the development of RVM model and rest of the data is used for validation. The predicted SIF is found to be in good agreement with the corresponding analytical solution, and can be used for damage tolerant analysis of structural components.