My Account | Careers | Downloads | Blog

ABSTRACT:

This paper deals with the thermal design of an electronics package and a demonstration of reduced thermal resistance for high-power amplifiers (HPAs). The focus is package internal thermal management. A carbon fiber-reinforced carbon composite- (C/C composite) based heat sink is proposed as a means of enhancement over the more conventional CuMo material. The C/C composite has anisotropic thermal properties. Thermal performance of the material with anisotropic thermal properties depends strongly on taking advantage of superior properties in the desired directions. Finite-element analysis is performed to determine the correct orientation of the C/C composite material with anisotropic thermal conductivities to minimize thermal resistance. A 32% reduction in thermal resistance of the HPA has been predicted in the initial simulation. A package incorporating the C/C composite material is built with the optimal orientation of thermal anisotropy obtained by numerical simulations. A 20% reduction in thermal resistance has been successfully obtained by surface temperature measurements for the HPA with the C/C composite material. The difference between numerical (32%) and experimental results (20%) is well explained by the difference in boundary conditions at the package base. Also, nonlinearity in thermal resistance is explained by taking account of temperature dependence of semiconductor materials, such as SiC and GaN.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Redundancy Minimization and Cost Reduction for Workflows with Reliability Requirements in Cloud-Based Services ABSTRACT: When it comes to the execution of workflows using cloud-based services, reliability requirement
PROJECT TITLE : CDPM A Combinational Data Prediction Model for Data Transmission Reduction in WSN ABSTRACT: In wireless sensor networks (WSN), data prediction methods have recently emerged as a significant way to reduce the
PROJECT TITLE : Adaptive Local Embedding Learning for Semi-supervised Dimensionality Reduction ABSTRACT: In recent years, a lot of attention has been focused on semi-supervised learning, which is recognized as one of the most
PROJECT TITLE : A Novel Method for Creating an Optimized Ensemble Classifier by Introducing Cluster Size Reduction and Diversity ABSTRACT: Within the scope of this research project, a novel approach to generating an improved
PROJECT TITLE : A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks ABSTRACT: In deregulated energy markets, accurate electricity price forecasting (EPF)

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry