Enhanced fin-effectiveness of micro-scale concentric-shape roughened target surface subjected to array jet impingement

Abstract

Array jet impingement when combined with strategically placed short height (<1.25 mm) roughness elements on the target wall results in enhanced heat dissipation at high fin-efficiency (>95%) without much penalty on pumping power. Advances in metal-powder-based additive manufacturing enables the printing of roughness scales (< 0.5 mm) with acceptable accuracy. This paper presents an experimental and numerical study on the characterization of heat transfer performance of concentric-shaped micro pin-fins subjected to array jet impingement. The experimental study served the dual purpose of establishing manufacturability of such configurations and validating the computational model. Three concentric micro-pin fin configurations were additively manufactured with AlSi10Mg alloy through Direct Metal Laser Sintering (DMLS) with dimensions between 0.25 - 2.25 mm on the target wall subjected to a 5 × 5 array of jets with normalized jet-to-jet spacing of X/Djet =Y/Djet = 3 and normalized jet-to-target spacing Z/Djet of 1. The resultant Nusselt number (Nu) and fin effectiveness (ε) values have been reported for Reynolds number ranging between 3,000 and 12,000. The three target plate configurations produced effectiveness between 1.8 - 2.4 and the configuration with maximum wetted surface area (wall thickness of 250 µm) and void fraction produced highest effectiveness. Further, a validated numerical model was used to perform a parametric study on geometrical parameters of roughness element viz. pin-fin spacing (S), inner diameter (D1), outer diameter (D2) and height (H) at a ReDjet = 6,000. Significant enhancement in ε was observed with H being the dominant parameter affecting the heat transfer. The effect of void fraction (α), which denotes the free flow area between pin-fin elements (Ab –Apin) was also explored. There exists an αopt at which maximum heat transfer was achieved. A correlation for fin effectiveness is proposed as a function of different non-dimensional variables derived from the parametric study and its predictive capabilities were found to be within ±10%.