• Title/Summary/Keyword: power-divergence

Search Result 92, Processing Time 0.018 seconds

Static Fluid-Structure Coupled Analysis of Low-Pressure Final-Stage Turbine Blade (발전용 저압터빈 최종단 블레이드의 정적 유체-구조 연계해석)

  • Kwon, Sun-Guk;Lee, Young-Shin;Bae, Yong-Chae
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.34 no.8
    • /
    • pp.1067-1074
    • /
    • 2010
  • In this study, a loosely coupled fluid-structure interaction (FSI) analysis was conducted for a low-pressure (LP) final-stage rotor blade. Preliminary FSI analyses of a $15^{\circ}$ sweptback wing and a NASA Rotor 37 compressor blade were performed for verifying the boundary conditions. The results were compared with the established literatures for each model. The FSI analysis of the $15^{\circ}$ sweptback wing was carried out under both stable and unstable conditions. The excessive deformation of the wing was observed within 0.05 s under the unstable condition which is higher than the divergence speed of a wing compared with the stable condition. On the basis of the results of a steady-state study, an unsteady state FSI analysis was conducted for a NASA Rotor 37. Different deformations were observed at trailing edge of the blade in the static FSI and dynamic FSI analysis. A 3D FE model of a LP rotor was generated from the span-wise section data. In order to develop a reasonable model, an impact test was performed and compared to the FE model. Using this FE model, the steady-state FSI analysis was performed successfully.

The Effect of Control-Ownership Wedge on Stock Price Crash Risk (소유지배 괴리도가 주가급락위험에 미치는 영향)

  • Chae, Soo-Joon;Ryu, Hae-Young
    • The Journal of Industrial Distribution & Business
    • /
    • v.9 no.7
    • /
    • pp.53-59
    • /
    • 2018
  • Purpose - This study examines the effect of control-ownership wedge on stock crash risk. In Korea, controlling shareholders have exclusive control rights compared to their cash flow rights. With increasing disparity, controlling shareholders abuse their power and extract private benefits at the expense of the minority shareholders. Managers who are controlling shareholders of the companies tend not to disclose critical information that would prevent them from pursuing private interests. They accumulate negative information in the firm. When the accumulated bad news crosses a tipping point, it will be suddenly released to the market at once, resulting in an abrupt decline in stock prices. We predict that stock price crash likelihood due to information opaqueness increases as the wedge increases. Research design, data, and methodology - 831 KOSPI-listed firm-year observations are from KisValue database from 2005 to 2011. Control-ownership wedge is measured as the ratio (UCO -UCF)/UCO where UCF(UCO) is the ultimate cash-flow(control) rights of the largest controlling shareholder. Dependent variable CRASH is a dummy variable that equals one if the firm has at least 1 crash week during a year, and zero otherwise. Logistic regression is used to examine the relationship between control-ownership wedge and stock price crash risk. Results - Using a sample of KOSPI-listed firms in KisValue database for the period 2005-2011, we find that stock price crash risk increases as the disparity increases. Specifically, we find that the coefficient of WEDGE is significantly positive, supporting our prediction. The result implies that as controlling shareholders' ownership increases, controlling shareholders tend to withhold bad news. Conclusions - Our results show that agency problems arising from the divergence between control rights and cash flow rights increase the opaqueness of accounting information. Eventually, the accumulated bad news is released all at once, leading to stock price crashes. It could be seen that companies with high control-ownership wedge are likely to experience future stock price crashes. Our study is related to a broader literature that examined the effect of the control-ownership wedge on stock markets. Our findings suggest that the disparity is a meaningful predictor for future stock price crash risk. The results are expected to provide useful implications for firms, regulators, and investors.