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Introduction
Published in Dale A. Anderson, John C. Tannehill, Richard H. Pletcher, Munipalli Ramakanth, Vijaya Shankar, Computational Fluid Mechanics and Heat Transfer, 2020
Dale A. Anderson, John C. Tannehill, Richard H. Pletcher, Munipalli Ramakanth, Vijaya Shankar
In the experimental approach, a circular cylinder model would first need to be designed and constructed. This model must have provisions for measuring the wall pressures, and it should be compatible with an existing wind tunnel facility. The wind tunnel facility must be capable of producing the required free stream conditions in the test section. The problem of matching flow conditions in a wind tunnel can often prove to be quite troublesome, particularly for tests involving scale models of large aircraft and space vehicles. Once the model has been completed and a wind tunnel selected, the actual testing can proceed. Since high-speed wind tunnels require large amounts of energy for their operation, the wind tunnel test time must be kept to a minimum. The efficient use of wind tunnel time has become increasingly important in recent years with the escalation of energy costs. After the measurements have been completed, wind tunnel correction factors can be applied to the raw data to produce the final results. The experimental approach has the capability of producing the most realistic answers for many flow problems; however, the costs are becoming greater every day.
Steady-State Heat Transfer Measurement Techniques
Published in Je-Chin Han, Lesley M. Wright, Experimental Methods in Heat Transfer and Fluid Mechanics, 2020
With wind tunnel studies of this nature, the freestream velocity is often monitored using a Pitot tube. As Pitot tubes measure both the static and dynamic pressures, the velocity inside the wind tunnel can easily be calculated from Bernoulli’s equation. Therefore, it is necessary to determine the flow velocity (and differential pressure) that is needed to provide the desired Reynolds number. In the current example, the desired Reynolds number is Re = 300,000. For the given experimental setup, the Reynolds number can be calculated in Equation (5.39). () Re=ρVCμ
Theoretical fundamentals of experimental aerodynamics
Published in Stefano Discetti, Andrea Ianiro, Experimental Aerodynamics, 2017
Andrea Ianiro, Stefano Discetti
The generation of lift has as a counterpart the production of induced drag in finite 3D wings. In fact, the pressure difference between upper and lower sides of the wing results at the wing edges in the production of an induced motion from the bottom to the upper side (as sketched in Figure 1.6): the fluid on the high-pressure side is accelerated outward and the fluid on the suction side is accelerated inward resulting in what is referred to as the tip vortex. This motion, practically, results in a higher angle of attack seen by the wing. As a consequence, especially near the wing tips the aerodynamic force has a higher inclination angle with respect to freestream velocity, resulting in force component contributing to the drag.
Computational Study of Hypersonic Rarefied Gas Flow over Re-Entry Vehicles Using the Second-Order Boltzmann-Curtiss Constitutive Model
Published in International Journal of Computational Fluid Dynamics, 2021
Tushar Chourushi, Satyvir Singh, Vishnu Asokakumar Sreekala, Rho Shin Myong
A further comparison of drag and heat flux coefficients for varying degrees of rarefaction is presented in Figure 9. As the gas becomes more rarefied, fewer gas molecules interact with the surface, resulting in a reduction in drag. However, since the freestream dynamic pressure decreases more rapidly than the drag, the resultant drag coefficient (defined as drag divided by freestream dynamic pressure) increases. Similarly, an enhanced heat flux coefficient is observed because of the reduced freestream kinetic energy. It is seen that the drag coefficient for the OREX vehicle is lower than that of the Apollo vehicle due to the reduced resistance from the smoother shape. Nonetheless, the heat flux coefficient for the OREX vehicle is relatively higher when compared with the Apollo vehicle. Besides, the second-order model predicts lower values for the drag and heat flux coefficients than the first-order model because of the shear-thinning characteristics for velocity and temperature, respectively.
Shape descriptors - settling characteristics of irregular shaped particles
Published in Chemical Engineering Communications, 2021
Bhuvaneswari Govindan, Parthiban Mohanmani, Sarat Chandra Babu Jakka, A. K. Tiwari, A. K. Kalburgi, T. M. Sudhakar, A. Sanyal, S. Sarkar
The effective drag is due to form drag and friction drag. While form drag dominates in a stagnant fluid, skin drag is more pronounced in free turbulence. Brucato et al. (1998) have indicated that the drag coefficient is strongly influenced by the characteristics of free stream turbulence. Concha and Almendra (1979) has pointed out that the asymmetry of pressure distribution contributes to the form drag which essentially depends upon the point of separation. Pressure asymmetry leads to an asymmetrical shear ensuing rotation in irregularly shaped particles. Thus the resulting flow field around the particle dominates the variations around the particle leaving the form drag almost constant. Terminal velocity is more dependent on the aspect ratio in the Stokes regime than in the Newtonian regime (Gabitto and Tsouris 2008). There have been extensive reviews reported on existing correlations for predicting drag coefficient (Ganguly 1990; Chhabra et al. 1999). It is evident from the reviews that in order to improve the predictability of particle behavior, the equivalence of shape factors needs to be selected appropriately to suit the hydrodynamics and the drag coefficient. The present work, as Part–I, addresses the key geometrical parameters to correlate to the settling velocity of irregularly shaped particles in a stagnant fluid, i.e., air.
Effect of blade attachments on the performance of an asymmetric blade H-Darrieus turbine at low wind speed
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2020
Hussain Mahamed Sahed Mostafa Mazarbhuiya, Agnimitra Biswas, Kaushal Kumar Sharma
After rigorous measuring of free-stream velocities these two different positions were found out at wind tunnel exit where average wind speeds 5.0 m/s and 6.0 m/s were obtained. The free-stream velocity was measured using digital anemometer having range 0–30 m/s and ±2% accuracy. The non-contact tachometer having range 10–99,999 rpm and ±0.05% accuracy was used to measure the angular velocity of the H-Darrieus VAWT. The torque was calculated using a rope brake dynamometer arrangement, which was also adopted by different researchers (Bhuyan and Biswas 2014; Singh, Biswas, and Misra 2015). A rope brake dynamometer is an absorption type dynamometer used for measuring the torque of an engine. It consists of rope wound around the shaft of an engine. One end of the rope is attached to a spring balance while the other end of the rope is attached to a load pan carrying dead weight. Thus, a string of nylon was rolled up around turbine shaft whose one end was fastened to the spring balance and other was fastened with brake load pan (Figure 5) where dead weight was applied during torque calculation of turbines. It is necessary to supervise the steady wind flow before executing the core investigations. Wind tunnel motor takes a little time to throw a steady-state flow and it depends upon the hp of the motor. Instantaneous wind speeds were measured at an interval of 10 s to obtain flow staidness for free stream velocities 5.0 and 6.0 m/s. Datasets were repeated to ensure the accuracy of wind speed measurement. This was done by measuring free stream wind speed at each data point (total seven data points were considered as shown in Figure 6) at the mid height of the turbine across the width of it, and for each data point five number of free stream wind speed was taken. By this way total wind speed data were collected. The average of this five wind speed data was then taken for a single data point. The flow constancy was obtained about 40 s after switching on the wind tunnel motor as shown in Figure 7. Therefore, all readings were taken after 40 s of the start of motor to get the steady-state flow. The repeatability of all filed datasets was convinced throughout the present investigation.