The local heat transfer characteristics of air jet impingement at nozzle-plate spacings of less than one nozzle diameter have been examined experimentally using an infrared thermal imaging technique. Fully-developed nozzles were used in the study. The flow structure was investigated using laser-Doppler velocimetry and wall pressure measurements. The stagnation Nusselt number was correlated for nozzle-plate spacings of less than one diameter. The customary Nusselt number dependence on Re12 for impinging jet transport was observed. A power-law relationship between Nusselt number and nozzle-plate spacing of the form Nu0 ∼ (zd)−0.288 observed experimentally is explored from theoretical considerations. The effects of accelerating fluid between the nozzle-plate gap as well as a significant increase in local turbulence leads to substantially increased local heat transfer with decreased nozzle-plate spacing. A stagnation point minimum surrounded by an inner and outer peak in the local heat transfer was observed for nozzle-plate spacings less than zd = 0.25. These primary and secondary maxima are explained by accelerated radial flow at the exit of the jet tube and an observed local maximum in the turbulence, respectively. These conclusions are drawn from observations made relative to the turbulent flow structure and wall pressure measurements. The outer peak in local Nusselt number was found to move radially outward for larger nozzle-plate spacings and higher jet Reynolds numbers.

The application of minimum cross-entropy (MCE) spectral analysis to successive blocks of biological time series is considered. Examples demonstrate the effectiveness of the MCE procedure for the analysis of cardiovascular ultrasound return and low-frequency electroencephalograph (EEG) signals.< >

Trellis coding of analog memoryless sources with respect to the squared-error distortion criterion is investigated via simulation. Sources treated are the Gaussian, uniform, Laplacian, and Gaussian mixture models, and the encoding algorithms studied are the Viterbi andMalgorithms. Performance versus complexity trade-offs are presented for these source models, and practical aspects of finite encoder memory and unknown source statistics are examined.

Maximum-likelihood estimates for the levels of the mean value function and the covariance function of a Gaussian random process are investigated. The stability of these estimates is examined as the actual covariance function of the process deviates from the form assumed in the estimators. It is found that the time-bandwidth product for stationary processes represents an upper bound on the number of estimator terms that can be safely used when estimating with uncertainty about the process covariance function. This result is consistent with other interpretations of the time-bandwidth product and tempers the conclusion that, in principle, an infinite number of estimator terms can be used to obtain a perfect estimate of the covariance level. In practice, the estimate of the level can never be perfect, and the accuracy of the estimate depends on the observation interval. Finally, conditions are established to ensure asymptotic stability of the estimates and physical interpretations are presented.