NUMERICAL HEAT TRANSFER PART A-APPLICATIONS

THERMAL ANALYSIS OF INTRAOCULAR ELECTRONIC DISPLAY PROJECTOR VISUAL PROSTHESIS
Gongal D, Thakur S, Panse A, Pawar R, Yu CQ and Foster CD
Corneal opacity is a leading cause of blindness, accounting for about 4% of global blindness. With corneal opacity, light is unable to pass through the cornea to form a clear image on the retina, resulting in blindness. To address this condition, an intraocular projection device has been designed. This device, while in use, would produce heat. According to international standard regulations, the temperature on the surface of the tissues should not increase more than 2°C due to medical devices. In order to establish the power budget of this intraocular electronic device, a steady state thermal finite element analysis was conducted on two different eye models. The device was placed at 9.98 mm from the retina, and was seen to run up to a maximum power of 82 mW for the first model and 91 mW for the second model. To reduce heating of tissues, the device was extended by 0.5 mm to create an air gap which acted as an insulator. The temperature in the nearest living tissue then dropped below the prescribed limit of 2°C at 100 mW.
Point Mean Beam Length, a New Concept to Enhance the Computational Efficiency of Multi-Dimensional, Non-Gray Radiative Heat Transfer
Yuen WW and Tam WC
A new concept of point mean beam length (PMBL) is introduced. For enclosures with simple geometry, this concept provides a fundamental self-consistent interpretation on the various different definition of the conventional mean beam length. The concept is further demonstrated to be effective in enhancing the computational efficiency for multi-dimensional radiative heat transfer in non-gray media. In the evaluation of radiative exchange between two perpendicular areas with a common edge, the use of PMBL leads to a factor of 100 to 400 reduction in computational effort compared to the direct integration approach. For practical applications, PMBL is combined with RADNNET (a neural network correlation for a one-dimensional CO/HO/soot combustion mixture) to generate two highly efficient and accurate solvers for the evaluation of exchange factors between two parallel or perpendicular rectangular areas of arbitrary dimensions with an intervening combustion mixture.