Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization

Conformal cooling is an additive manufacturing-based solution and it is a rapidly developing method for reducing the cooling time of the plastic injection process. The present study investigates the thermal and mechanical performances of the 3D-printed conformal cooling channels using computational...

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Main Authors: Shen, Suping, Kanbur, Baris Burak, Zhou, Yi, Duan, Fei
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/148630
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1486302021-05-08T20:11:51Z Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization Shen, Suping Kanbur, Baris Burak Zhou, Yi Duan, Fei School of Mechanical and Aerospace Engineering Singapore Centre for 3D Printing Engineering 3D Printing Conformal Cooling Conformal cooling is an additive manufacturing-based solution and it is a rapidly developing method for reducing the cooling time of the plastic injection process. The present study investigates the thermal and mechanical performances of the 3D-printed conformal cooling channels using computational analyses and multi-objective optimization. For a real injection mold product, two different conformal cooling channel profiles, which are circular and elongated, are analyzed individually. Their cooling time, temperature non-uniformity, and pressure drop are assessed. Compared to the traditional channels, the cooling time of designed CCCs is reduced in the range of 30-60%. The cooling and fatigue life performances of the elongated channel are analyzed for different channel pathways and cross section areas. As for the circular channel, the coolant temperature, volume flow rate, and channel diameter are selected as the parameters within the ranges of 288.0-298.0 K, 1.0-10.0 L/min, and 2.1-2.5 mm, respectively. According to these parameters, the multi-objective optimization study is performed and the best trade-off point is found at the channel diameter of 2.5 mm, coolant temperature of 297 K, and the flow rate of 1 L/min when all the objectives have equal weights in the optimization problem. Accepted version 2021-05-05T07:18:41Z 2021-05-05T07:18:41Z 2020 Journal Article Shen, S., Kanbur, B. B., Zhou, Y. & Duan, F. (2020). Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization. Journal of Materials Engineering and Performance, 29(12), 8261-8270. https://dx.doi.org/10.1007/s11665-020-05251-5 1059-9495 https://hdl.handle.net/10356/148630 10.1007/s11665-020-05251-5 2-s2.0-85094143809 12 29 8261 8270 en Journal of Materials Engineering and Performance Copyright 2020 ASM International. All rights reserved. This paper was published in Journal of Materials Engineering and Performance, Vol. 29, Issue 12, pp. 8261–8270 and is made available as an electronic reprint with the permission of ASM International. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
3D Printing
Conformal Cooling
spellingShingle Engineering
3D Printing
Conformal Cooling
Shen, Suping
Kanbur, Baris Burak
Zhou, Yi
Duan, Fei
Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
description Conformal cooling is an additive manufacturing-based solution and it is a rapidly developing method for reducing the cooling time of the plastic injection process. The present study investigates the thermal and mechanical performances of the 3D-printed conformal cooling channels using computational analyses and multi-objective optimization. For a real injection mold product, two different conformal cooling channel profiles, which are circular and elongated, are analyzed individually. Their cooling time, temperature non-uniformity, and pressure drop are assessed. Compared to the traditional channels, the cooling time of designed CCCs is reduced in the range of 30-60%. The cooling and fatigue life performances of the elongated channel are analyzed for different channel pathways and cross section areas. As for the circular channel, the coolant temperature, volume flow rate, and channel diameter are selected as the parameters within the ranges of 288.0-298.0 K, 1.0-10.0 L/min, and 2.1-2.5 mm, respectively. According to these parameters, the multi-objective optimization study is performed and the best trade-off point is found at the channel diameter of 2.5 mm, coolant temperature of 297 K, and the flow rate of 1 L/min when all the objectives have equal weights in the optimization problem.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Shen, Suping
Kanbur, Baris Burak
Zhou, Yi
Duan, Fei
format Article
author Shen, Suping
Kanbur, Baris Burak
Zhou, Yi
Duan, Fei
author_sort Shen, Suping
title Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
title_short Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
title_full Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
title_fullStr Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
title_full_unstemmed Thermal and mechanical assessments of the 3D-printed conformal cooling channels : computational analysis and multi-objective optimization
title_sort thermal and mechanical assessments of the 3d-printed conformal cooling channels : computational analysis and multi-objective optimization
publishDate 2021
url https://hdl.handle.net/10356/148630
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