Bubble Behavior in a Taylor Vortex

We present an experimental study on the behavior of bubbles captured in a Taylor vortex. The gap between a rotating inner cylinder and a stationary outer cylinder is filled with a Newtonian mineral oil. Beyond a critical rotation speed (ω[subscript c]), Taylor vortices appear in this system. Small air bubbles are introduced into the gap through a needle connected to a syringe pump. These are then captured in the cores of the vortices (core bubble) and in the outflow regions along the inner cylinder (wall bubble). The flow field is measured with a two-dimensional particle imaging velocimetry (PIV) system. The motion of the bubbles is monitored by using a high speed video camera. It has been found that, if the core bubbles are all of the same size, a bubble ring forms at the center of the vortex such that bubbles are azimuthally uniformly distributed. There is a saturation number (N[subscript s]) of bubbles in the ring, such that the addition of one more bubble leads eventually to a coalescence and a subsequent complicated evolution. Ns increases with increasing rotation speed and decreasing bubble size. For bubbles of non-uniform size, small bubbles and large bubbles in nearly the same orbit can be observed to cross due to their different circulating speeds. The wall bubbles, however, do not become uniformly distributed, but instead form short bubble-chains which might eventually evolve into large bubbles. The motion of droplets and particles in a Taylor vortex was also investigated. As with bubbles, droplets and particles align into a ring structure at low rotation speeds, but the saturation number is much smaller. Moreover, at high rotation speeds, droplets and particles exhibit a characteristic periodic oscillation in the axial, radial and tangential directions due to their inertia. In addition, experiments with non-spherical particles show that they behave rather similarly. This study provides a better understanding of particulate behavior in vortex flow structures.

Parameter Estimation in Chaotic Systems

This report examines how to estimate the parameters of a chaotic system given noisy observations of the state behavior of the system. Investigating parameter estimation for chaotic systems is interesting because of possible applications for high-precision measurement and for use in other signal processing, communication, and control applications involving chaotic systems. In this report, we examine theoretical issues regarding parameter estimation in chaotic systems and develop an efficient algorithm to perform parameter estimation. We discover two properties that are helpful for performing parameter estimation on non-structurally stable systems. First, it turns out that most data in a time series of state observations contribute very little information about the underlying parameters of a system, while a few sections of data may be extraordinarily sensitive to parameter changes. Second, for one-parameter families of systems, we demonstrate that there is often a preferred direction in parameter space governing how easily trajectories of one system can "shadow'" trajectories of nearby systems. This asymmetry of shadowing behavior in parameter space is proved for certain families of maps of the interval. Numerical evidence indicates that similar results may be true for a wide variety of other systems. Using the two properties cited above, we devise an algorithm for performing parameter estimation. Standard parameter estimation techniques such as the extended Kalman filter perform poorly on chaotic systems because of divergence problems. The proposed algorithm achieves accuracies several orders of magnitude better than the Kalman filter and has good convergence properties for large data sets.

Thermal Noise Behavior of the Bridge Circuit

This paper considers a connection between the deterministic and noisy behavior of nonlinear networks. Specifically, a particular bridge circuit is examined which has two possibly nonlinear energy storage elements. By proper choice of the constitutive relations for the network elements, the deterministic terminal behavior reduces to that of a single linear resistor. This reduction of the deterministic terminal behavior, in which a natural frequency of a linear circuit does not appear in the driving-point impedance, has been shown in classical circuit theory books (e.g. [1, 2]). The paper shows that, in addition to the reduction of the deterministic behavior, the thermal noise at the terminals of the network, arising from the usual Nyquist-Johnson noise model associated with each resistor in the network, is also exactly that of a single linear resistor. While this result for the linear time-invariant (LTI) case is a direct consequence of a well-known result for RLC circuits, the nonlinear result is novel. We show that the terminal noise current is precisely that predicted by the Nyquist-Johnson model for R if the driving voltage is zero or constant, but not if the driving voltage is time-dependent or the inductor and capacitor are time-varying