Archive for tag: boiling

Fun with Boiling

Inferring information from video is desirable since video data is becoming more accessible due to improvements in recording and storage. Machine learning techniques are also rapidly maturing with new methods being applied to datasets in different fields. I have been keenly interested in gathering knowledge from past experience or test results and applying this knowledge to new conditions. An approach that I outline in my thesis utilizes a new methodology for reducing the dimension of large variable number data streams and developing a probability density function from known conditions to make estimates on new data.

An example related to fluid mechanics utilizes high speed video of a flow boiling system was recorded at different heat flux levels.[i] Nine videos were used in the analysis corresponding to five values of heat flux which are shown below at selected points in time. The larger values of heat flux are shown to have a larger number of bubbles due to the higher amount of energy being transferred to the working fluid. It is apparent that the change in the number of bubbles is not linear.

movies_images_boiling

To demonstrate the result of the method, two videos at heat fluxes of 80 kW/m2, 120 kW/m2, 140 kW/m2, and 160 kW/m2, were used as the known inputs and the heat flux was predicted for the 100 kW/m2video. Each image in the 340 frames of the video corresponds to 141 x 400 pixels resulting in 19,176,000 elements or variables to evaluate per movie. The 19 million variables are reduced to 64 variables which are embedded into a two dimensional diffusion space (Shown in the Figure below). These two element vectors are used to predict the heat flux. Thus, the two diffusion coordinates of the eight videos corresponding to four known heat fluxes are used to construct a probability distribution for the remaining video which is shown in the Figure below.

diss_boiling_pdf

The resulting mean of the probability density function closely predicts the actual heat flux applied. Thus, one can potentially use video of known operating conditions to predict new states.



[i] C. ESTRADA-PEREZ, E. DOMINGUEZ-ONTIVEROS, H. AHN, N. AMINI, and Y. HASSAN, "PTV Experiments of Subcooled Boiling Flow through a Rectangular Channel," in16thInternational Conference on Nuclear Engineering, Orlando, Florida, 2008.