Pool Boiling on Wire in Microgravity - What Have We Learned

In the past years, steady pool boiling of degassed R113 on thin platinum wires has been studied systematically in our lab, including experiments in long-term microgravity aboard RS-22, in short-term microgravity in the Drop Tower Beijing / NMLC, and in normal gravity on the ground. Slight enhancement of nucleate boiling heat transfer is observed in microgravity, while dramatic changes of bubble behaviors are much evident. The value of CHF in microgravity is lower than that in normal gravity, but it can be predicted well by the Lienhard-Dhir correlation, although the dimensionless radius in the present case is far beyond its initial application range. The scaling of CHF with gravity is thus much different from the traditional viewpoint. Considering the influence of the Marangoni effects, the different characteristics of bubble behaviors in microgravity have been explained. A new bubble departure model has also been proposed, which can predict the whole observation both in microgravity and in normal gravity.

Forebody Compressibility Research of Hypersonic Vehicle

Three kinds of forebody model of hypersonic vehicles were studied with numerical simulation method. It shows that the two- order compressive ramp model is the best selection among the three for its good evaluative parameters value at the cowl of the inlet . This model can provide higher value of flux coefficient and total pressure recovery coefficient and lower average Mach number compared with those of the other two models . Simultaneously different compressive angles may have different effects . The configuration which the firstorder of compressive angle is 4°and the second 5°is the optimum combination. Furthermore factors such as attack angle were concerned. Better result may be obtained with a range of attack angles . Based on the work above the integrated design for forebodyPinlet of a hypersonic vehicle was performed. The numerical result shows that this integrated model provides good flow field quality for inlet and engine work.

Lateral motion and departure of vapor bubbles in nucleate pool boiling on thin wires in microgravity

A space experiment on bubble behavior and heat transfer in subcooled pool boiling phenomenon has been performed utilizing the temperature-controlled pool boiling (TCPB) device both in normal gravity in the laboratory and in microgravity aboard the 22(nd) Chinese recoverable satellite. The fluid is R113 at 0.1 MPa and subcooled by 26 degrees C nominally. A thin platinum wire of 60 mu m in diameter and 30mm in length is simultaneously used as heater and thermometer. Only the lateral motion and the departure of discrete vapor bubbles in nucleate pool boiling are reported and analyzed in the present paper. A scale analysis on the Marangoni convection surrounding a bubble in the process of subcooled nucleate pool boiling leads to formulas of the characteristic velocity of the lateral motion and its observability. The predictions consist with the experimental observations. Considering the Marangoni effect, a new qualitative model is proposed to reveal the mechanism underlying the bubble departure processes and a quantitative agreement can also be acquired.

Biomimetic (topological) pattern recognition - A new model of pattern recognition theory and its application

A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.