Measurement Of Pressure Distribution Over A Clark Y 14 Airfo

Measurement Of Pressure Distribution Over A Clark Y 14 Airfoil At Vari

The objectives of the experiment are to measure the surface pressure distribution on a Clark Y-14 airfoil at various angles of attack, to calculate the pressure coefficient, lift coefficient, and lift force acting on the airfoil. The experiment involves setting up the airfoil in a steady, uniform flow within a wind tunnel, measuring pressures at multiple points around the airfoil surface using pressure taps connected to manometers, and recording the free-stream velocity and temperature. Data reduction involves computing pressure coefficients, integrating pressure distributions to find the lift force, and calculating the lift coefficient. Uncertainty analysis will be performed on the measurements, focusing primarily on bias uncertainties in pressure measurements. The experimental results will be compared with benchmark data from Marchman and Werme (1984) to evaluate accuracy and consistency. The experiment is designed to analyze how lift varies with angle of attack and Reynolds number, and to assess the applicability of low Reynolds number data to full-scale aircraft. The key variables include velocity, pressure, and temperature, with related non-dimensional parameters such as pressure coefficient (Cp) and lift coefficient (Cl). The data obtained will help in understanding the aerodynamic characteristics of the Clark Y-14 airfoil and in validating experimental and theoretical models used in aeronautics.

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The measurement of pressure distribution over an airfoil, such as the Clark Y-14, at various angles of attack serves as a foundational experiment in fluid mechanics and aerodynamics. This experiment's primary aim is to understand how pressure variation around the airfoil's surface influences lift generation, which is essential for aircraft performance and design. By capturing pressure data at multiple points on the airfoil’s surface, calculating pressure coefficients, and integrating these to determine overall lift, researchers can elucidate the relationship between flow conditions, airfoil geometry, and aerodynamic forces.

In the experimental setup, the airfoil is mounted within a low-turbulence wind tunnel, with pressures sampled at 18 predefined locations using pressure taps connected to a multiport manometer. The wind tunnel, equipped with a contraction section, honeycomb flow straightener, and a variable-frequency drive for the fan, provides a steady, uniform airflow at the desired velocities, notably around 7.04 m/s to achieve a Reynolds number of approximately 143,000. This Reynolds number is within the low to moderate regime where the Clark Y-14 exhibits good correlation with benchmark data, allowing for relevant aerodynamic analysis.

The experiment involves measuring static and dynamic pressure via a Pitot-static tube for flow velocity and temperature measurement for fluid property calculations. The pressure taps are positioned along the airfoil according to specific coordinates, matching the geometry of the Clark Y-14, which is characterized by a maximum thickness ratio of 0.014 m and a chord length of 0.089 m. The pressure data collected are used to compute the pressure coefficient (Cp), which normalizes the surface pressures relative to the free-stream conditions according to the equation:

\( C_p = \frac{p_i - p_\infty}{\frac{1}{2}\rho U_\infty^2} \)

where \( p_i \) is the pressure at tap \( i \), \( p_\infty \) is the free-stream static pressure, \( \rho \) is air density, and \( U_\infty \) is the free-stream velocity. The free-stream velocity is calculated from measurements of stagnation and static pressures with the Pitot-static tube, and the air density is derived from temperature and pressure measurements, referencing standard fluid property tables.

Once pressure coefficients are obtained, the local pressure differences are used to compute the lift force by summing the pressure force components over the surface. Using the pressure distribution data, the lift coefficient \( C_L \) for each angle of attack is calculated by integrating pressures along the chord and multiplying by the airfoil span, following the equation:

\( C_L = \frac{L}{\frac{1}{2}\rho U_\infty^2 c b} \)

where \( L \) is the lift force, \( c \) is the chord length, and \( b \) is the span. The lift force itself is determined by integrating the pressure distribution considering the surface normal angles \( \theta_i \) related to the flow direction and the local surface orientation. The variation of \( C_L \) with angle of attack, \( \alpha \), provides insight into the aerodynamic efficiency and stall characteristics of the airfoil.

Uncertainty analysis is vital in assessing the accuracy of pressure measurements and subsequent derived quantities. The dominant uncertainty source is bias in the pressure measurements, estimated via uncertainty propagation equations that consider the sensitivity coefficients of the pressure coefficients and lift coefficients to their respective measured variables. The total uncertainty in the pressure coefficient \( C_p \) incorporates both bias and precision uncertainties, although bias dominates given the negligible uncertainties in flow velocity and air properties based on prior experiments.

Data obtained experimentally are then compared to benchmark data from Marchman and Werme (1984), which provide pressure distributions and lift coefficients at equivalent Reynolds numbers and angles of attack. The comparison highlights the accuracy of the measurement system, the fidelity of the experimental setup, and the relevance of low Reynolds number data to practical aeronautical applications.

Understanding how the measured pressure distributions translate into full-scale aircraft performance involves considering the similarity parameters—non-dimensional groups such as the Reynolds number and Mach number. The experiment's findings, particularly the pressure coefficient distributions and lift curves, can be scaled using similarity principles, enabling predictions of aerodynamic performance at different sizes, speeds, and flow conditions. This scaling relies on the assumption that the flow physics are primarily governed by the dimensionless parameters, thus allowing laboratory results to inform real-world aircraft design and analysis.

References

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