Numerical investigation on optimal arrangement of IC chips mounted on a SMPS board cooled under mixed convection. (September 2018)
- Record Type:
- Journal Article
- Title:
- Numerical investigation on optimal arrangement of IC chips mounted on a SMPS board cooled under mixed convection. (September 2018)
- Main Title:
- Numerical investigation on optimal arrangement of IC chips mounted on a SMPS board cooled under mixed convection
- Authors:
- Mathew, V.K.
Hotta, Tapano Kumar - Abstract:
- Highlights: Heat transfer from seven non-identical IC chips mounted on a SMPS board under mixedconvection. Optimal arrangement of these heat sources using hybrid optimization strategy. Use of numerical data driven ANN-GA technique to predict the optimal distribution. Temperature of heat sources is a strong function of their size, position on the substrate board. Comparison of the optimal arrangement obtained from ANN-GA technique with conventional methods. Abstract: The paper aims to investigate numerically the mixed convection heat transfer characteristics from seven non-identical IC chips (Aluminium) mounted on a Switch Mode Power Supply (SMPS) board (substrate) made by FR-4 (glass-reinforced epoxy laminate material). The objective is to determine the optimum configuration of these IC chips positioned at different locations on the substrate board. The optimum configuration is proposed by defining a non-dimensional geometric distance parameter ( λ ) and by employing a hybrid strategy (collaborating Artificial neural network (ANN) and Genetic algorithm (GA)). 3D, steady state numerical simulations are carried out using ANSYS Icepak to determine the temperature distribution of the IC chips. It has been confirmed that, the temperature of the IC chips strongly rely on their shape, size, and location on the substrate board. The hybrid optimization is the most robust technique to predict the arrangement of the IC chips on the substrate board more accurately, as compared toHighlights: Heat transfer from seven non-identical IC chips mounted on a SMPS board under mixedconvection. Optimal arrangement of these heat sources using hybrid optimization strategy. Use of numerical data driven ANN-GA technique to predict the optimal distribution. Temperature of heat sources is a strong function of their size, position on the substrate board. Comparison of the optimal arrangement obtained from ANN-GA technique with conventional methods. Abstract: The paper aims to investigate numerically the mixed convection heat transfer characteristics from seven non-identical IC chips (Aluminium) mounted on a Switch Mode Power Supply (SMPS) board (substrate) made by FR-4 (glass-reinforced epoxy laminate material). The objective is to determine the optimum configuration of these IC chips positioned at different locations on the substrate board. The optimum configuration is proposed by defining a non-dimensional geometric distance parameter ( λ ) and by employing a hybrid strategy (collaborating Artificial neural network (ANN) and Genetic algorithm (GA)). 3D, steady state numerical simulations are carried out using ANSYS Icepak to determine the temperature distribution of the IC chips. It has been confirmed that, the temperature of the IC chips strongly rely on their shape, size, and location on the substrate board. The hybrid optimization is the most robust technique to predict the arrangement of the IC chips on the substrate board more accurately, as compared to conventional methods. … (more)
- Is Part Of:
- Thermal science and engineering progress. Volume 7(2018)
- Journal:
- Thermal science and engineering progress
- Issue:
- Volume 7(2018)
- Issue Display:
- Volume 7, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 7
- Issue:
- 2018
- Issue Sort Value:
- 2018-0007-2018-0000
- Page Start:
- 221
- Page End:
- 229
- Publication Date:
- 2018-09
- Subjects:
- ANSYS Icepack -- Artificial neural network -- Genetic algorithm -- IC chips -- Mixed convection -- Optimal configuration
Heat engineering -- Periodicals
Heat engineering
Thermodynamics
Periodicals
621.402 - Journal URLs:
- http://www.sciencedirect.com/science/journal/24519049 ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.tsep.2018.06.010 ↗
- Languages:
- English
- ISSNs:
- 2451-9049
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12873.xml