• 제목/요약/키워드: Rounded Square Cylinder

검색결과 3건 처리시간 0.021초

3D Numerical investigation of a rounded corner square cylinder for supercritical flows

  • Vishwanath, Nivedan;Saravanakumar, Aditya K.;Dwivedi, Kush;Murthy, Kalluri R.C.;Gurugubelli, Pardha S.;Rajasekharan, Sabareesh G.
    • Wind and Structures
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    • 제35권1호
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    • pp.55-66
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    • 2022
  • Tall buildings are often subjected to steady and unsteady forces due to external wind flows. Measurement and mitigation of these forces becomes critical to structural design in engineering applications. Over the last few decades, many approaches such as modification of the external geometry of structures have been investigated to mitigate wind-induced load. One such proven geometric modification involved the rounding of sharp corners. In this work, we systematically analyze the impact of rounded corner radii on the reducing the flow-induced loading on a square cylinder. We perform 3-Dimensional (3D) simulations for high Reynolds number flows (Re=1 × 105) which are more likely to be encountered in practical applications. An Improved Delayed Detached Eddy Simulation (IDDES) method capable of capturing flow accurately at large Reynolds numbers is employed in this study. The IDDES formulation uses a k-ω Shear Stress Transport (SST) model for near-wall modelling that prevents mesh-induced separation of the boundary layer. The effects of these corner modifications are analyzed in terms of the resulting variations in the mean and fluctuating components of the aerodynamic forces compared to a square cylinder with no geometric changes. Plots of the angular distribution of the mean and fluctuating coefficient of pressure along the square cylinder's surface illustrate the effects of corner modifications on the different parts of the cylinder. The windward corner's separation angle was observed to decrease with an increase in radius, resulting in a narrower and longer recirculation region. Furthermore, with an increase in radius, a reduction in the fluctuating lift, mean drag, and fluctuating drag coefficients has been observed.

NUMERICAL ANALYSIS OF FLOW CHARACTERISTIC WITH DIFFERENT CORNER RADIUS OF SQUARE CYLINDER

  • Gao, Zhefeng;Sohn, Chang-Hyun
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2010년 춘계학술대회논문집
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    • pp.315-319
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    • 2010
  • The near wake of square section cylinders with different corner radii is studied by numerical method to investigate the influence of corner radius. Eight models, R/D=0, 0.05, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5 (R is the corner radius and D is the characteristic dimension of the body) at Re=500 were studied. The numerical results of St, CD and CL at R/D=0 and R/D=0.5 were compared with experiments to prove the feasibility and also investigate the trend of flow phenomena by the various radius corners. Results indicate that, as R/D ratio is increased, the Strouha lnumber is increased, the minimum pressure point on the cylinder surface moved own stream. The calculated results shows that between R/D=0.15 to R/D=0.3 have CD and CL.

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Application of Multivariate Adaptive Regression Spline-Assisted Objective Function on Optimization of Heat Transfer Rate Around a Cylinder

  • Dey, Prasenjit;Das, Ajoy K.
    • Nuclear Engineering and Technology
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    • 제48권6호
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    • pp.1315-1320
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    • 2016
  • The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.