An experimental study was conducted to observe/visualize, the formation of circulation patterns inside a square cavity due to the movement of a lid at constant velocity. Lid driven cavity flow is one of the benchmark studies used in the verification/improvement of CFD codes for internal flow applications/predictions. Previous work on this topic is primarily focused on improving the steady state predictions of the CFD codes using different numerical schemes and algorithms. Furthermore, almost all of the studies reported in computational fluid mechanics literature relates to steady state predictions of lid or shear driven flows. Experimental work that is reported in these studies is limited in scope and number. This paper reports on the measurements we made using Particle Image Velocimeter (PIV) technique to determine the flow field as it develops from stagnation to steady state inside a square cavity driven by a lid. For this purpose, we employed a 2-D PIV system, which uses a double-cavity, Nd:Yag laser to illuminate the test cavity. Experiments were conducted using water as the working fluid inside a square cavity that is one inch (25.4 mm) high and one inch wide. The depth of the cavity is five inches (127 mm) to ensure two-dimensional circulations patterns. Hollow glass sphere particles with 10 microns in diameter were used as seeding of the working fluid, water. Experiments were repeated for different lid velocities corresponding to lid Reynolds numbers (laminar to beginning of transition of turbulence.) Velocity fields were captured during the development of the circulations patters each being unique for the time of the measurement and value of the lid velocity. The center of the circulation pattern and its path inside the cavity is constructed from the captured images as steady state is attained. Also, the strength of the circulation (as manifested by the increase in the diameter of the circulation) is determined at different times for different Reynolds numbers.
Erratum to: Analytical approximations of sensitivities of steady-state predictions to errors in parameter estimation: II. Michaelis-Menten kinetics