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Research Papers

Numerical Optimization, Characterization, and Experimental Investigation of Additively Manufactured Communicating Microchannels

[+] Author and Article Information
Kathryn L. Kirsch

Department of Mechanical and
Nuclear Engineering,
The Pennsylvania State University,
University Park, PA 16802
e-mail: kathryn.kirsch@gmail.com

Karen A. Thole

Department of Mechanical and
Nuclear Engineering,
The Pennsylvania State University,
University Park, PA 16802

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 15, 2018; final manuscript received September 12, 2018; published online October 8, 2018. Editor: Kenneth Hall.

J. Turbomach 140(11), 111003 (Oct 08, 2018) (11 pages) Paper No: TURBO-18-1205; doi: 10.1115/1.4041494 History: Received August 15, 2018; Revised September 12, 2018

The degree of complexity in internal cooling designs is tied to the capabilities of the manufacturing process. Additive manufacturing (AM) grants designers increased freedom while offering adequate reproducibility of microsized, unconventional features that can be used to cool the skin of gas turbine components. One such desirable feature can be sourced from nature; a common characteristic of natural transport systems is a network of communicating channels. In an effort to create an engineered design that utilizes the benefits of those natural systems, the current study presents wavy microchannels that were connected using branches. Two different wavelength baseline configurations were designed; then each was numerically optimized using a commercial adjoint-based method. Three objective functions were posed to (1) minimize pressure loss, (2) maximize heat transfer, and (3) maximize the ratio of heat transfer to pressure loss. All baseline and optimized microchannels were manufactured using laser powder bed fusion (L-PBF) for experimental investigation; pressure loss and heat transfer data were collected over a range of Reynolds numbers. The AM process reproduced the desired optimized geometries faithfully. Surface roughness, however, strongly influenced the experimental results; successful replication of the intended flow and heat transfer performance was tied to the optimized design intent. Even still, certain test coupons yielded performances that correlated well with the simulation results.

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Figures

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Fig. 1

Depiction of communicating wavy channel design. The branches repeated every other period in the streamwise direction and every other channel in the spanwise direction. Flow goes left to right.

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Fig. 2

Two variations in baseline communicating wavy channel design. (a) λ = 0.1 L and (b) λ = 0.4 L. Flow goes left to right.

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Fig. 3

Top-down view at 50% channel height of wall-resolved, structured mesh for the λ = 0.1 L case

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Fig. 4

Channel wall outlines from a top-down view at 50% channel height for λ = 0.1 L baseline and optimized shapes. The gray color shows the location of the walls for the baseline case. (a) Zoomed-in view of middle branch, ((b) and (c)) zoomed-in view of branches subject to the periodic boundary condition.

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Fig. 5

Contours of normalized axial velocity at one slice location, immediately after the branch exit shown in Fig. 4(c)

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Fig. 6

Contours of nondimensional temperature with secondary velocity vectors overlaid

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Fig. 7

Channel wall outlines from a top-down view at 50% channel height for λ = 0.4 L baseline and optimized shapes. The gray color shows the location of the walls for the baseline case. (a) Zoomed-in view of middle branch, ((b) and (c)) zoomed-in view of branches subject to the periodic boundary condition.

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Fig. 8

Contours of normalized axial velocity at one slice location

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Fig. 9

Contours of nondimensional temperature with secondary velocity vectors overlaid

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Fig. 10

Coupon orientation on the build plate. On the left view, flow is into the page; on the right view, flow is left to right.

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Fig. 11

Channel wall outlines from a top-down view at 50% channel height for the as-built λ = 0.1 L baseline and optimized shapes. The gray color shows the location of the walls for the baseline case. The dotted lines show the intended baseline design for comparison. (a) Zoomed-in view of a middle branch, same location as in Fig. 4(a), ((b) and (c)) zoomed-in view of branches at same locations as in Figs. 4(b) and 4(c).

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Fig. 12

Channel wall outlines from a top-down view at 50% channel height for the as-built λ = 0.4 L baseline and optimized shapes. The gray color shows the location of the walls for the baseline case. The dotted lines show the intended baseline design for comparison. (a) Zoomed-in view of a middle branch, same location as in Fig. 7(a), ((b) and (c)) zoomed-in view of branches at same locations as in Figs. 7(b) and 7(c).

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Fig. 13

Experimental test rig for flow and heat transfer measurements

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Fig. 14

Friction factor augmentation versus Reynolds number for the λ = 0.1 L case

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Fig. 15

Friction factor augmentation versus Reynolds number for the λ = 0.4 L case

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Fig. 16

Top-down view at 25% channel height of the baseline and J1 configurations. Contours are normalized axial velocity, with velocity vectors overlaid to highlight flow direction.

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Fig. 17

Nusselt number augmentation versus Reynolds number for the λ = 0.1 L case

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Fig. 18

Nusselt number augmentation versus Reynolds number for the λ = 0.4 L case

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Fig. 19

Friction factor augmentation versus Nusselt number augmentation at a Reynolds number of 5000. Open markers indicate data from Kirsch and Thole [14], where microchannels were noncommunicating. Closed markers indicate data from the current study.

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