Abas Abdoli
Florida International University
21 Papers
68 Citations
Abas Abdoli is an academic researcher from Florida International University. The author has contributed to research in topics: Heat flux & Heat transfer. The author has an hindex of 9, co-authored 20 publications. Previous affiliations of Abas Abdoli include Urmia University & University of Miami.
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Papers
Thermo-fluid analysis of micro pin-fin array cooling configurations for high heat fluxes with a hot spot
TL;DR: In this paper, the effect of micro pin-fin shapes on cooling of high heat flux electronic chips with a single hot spot was investigated numerically, and the performance of different micro pinfin shapes were evaluated.
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Multi-Objective Optimization of Micro Pin-Fin Arrays for Cooling of High Heat Flux Electronics with a Hot Spot
Sohail R. Reddy,Abas Abdoli,George S. Dulikravich,César C. Pacheco,Genesis Vasquez,Rajesh Jha,Marcelo J. Colaço,Helcio R. B. Orlande +7 more
TL;DR: In this article, the authors presented a multobjective constrained optimization to find the sizes of pin-fins, inlet water pressure, and average speed for arrays of micro pinfins used in the forced convection cooling of an integrated circuit.
40
Multi-Element Winglets: Multi-Objective Optimization of Aerodynamic Shapes
TL;DR: In this paper, the wing tip device was designed to mimic the wing tips of a soaring bird, featuring three smoothly blended elements, and each such element was integrated into a complete wing-tail-body aircraft configuration.
31
Multi-Objective Optimization of Micro Pin-Fin Arrays for Cooling of High Heat Flux Electronics With a Hot Spot
Sohail R. Reddy,Abas Abdoli,George S. Dulikravich,César C. Pacheco,Genesis Vasquez,Rajesh Jha,Marcelo J. Colaço,Helcio R. B. Orlande +7 more
- 06 Jul 2015
TL;DR: In this article, the ability of various arrays of micro pin-fins to reduce maximum temperature of an integrated circuit with a 4 × 3 mm footprint and a 0.5 mm hot spot was investigated numerically.
19
Denoising of MR spectroscopic imaging data using statistical selection of principal components
TL;DR: The proposed SSPC denoising improved the SNR and metabolite quantification uncertainty in MRSI, with minimal compromise of the spectral information, and can result in increased accuracy.