Optimization and Thermal Control of a multi-layered structure for space electronic device

Paper number

IAC-10.C2.1.14

Author

Dr. Riccardo Monti, University of Rome “La Sapienza”, Italy

Coauthor

Prof. Renato Barboni, University of Rome “La Sapienza”, Italy

Coauthor

Prof. Paolo Gasbarri, Università di Roma "La Sapienza", Italy

Coauthor

Dr. Leonardo Chiwiacowsky, University of Vale do Rio dos Sinos, Brazil

Year

2010

Abstract

All electronic devices present heat dissipation, by Joule Effect, when they are electrically fed. The heat overstocking
produces efficiency and performances reduction. On account of this the thermal control is mandatory. On small
electronic equipments, the difficult or impossibility of using a cooling fluid for the free or forced convection heat
dissipation, imposes the presence of cooling systems based on another kind of functioning principle such as the conduction.
In this paper the thermal control, via pyroelectric materials is presented. Furthermore, an optimization of
geometric, thermal and mechanical parameters, influence the thermal dissipation, is studied and presented. Pyroelectric
materials are able to convert heat into electrical charge spontaneously and due to this capability, such materials
could represent a suitable choice to increase the heat dissipation. The obtained electric charge or voltage could be
used to charge a battery or to feed other equipments. In particular, a sequence of different materials such as Kovar,
Molybdenum or Copper-Tungsten, used in a multi-layer pyroelectric wafer, together with their thicknesses, are design
features to be optimized in order to have the optimal thermal dissipation. The optimization process is performed by
a hybrid approach where a genetic algorithm (GA) is used coupled with a local search procedure, in order to provide
an appropriate balance between exploration and exploitation of the search space, which helps to find the optimal or
quasi-optimal solution. Since the design variables used in the optimization procedure are defined in different domains,
discrete (e.g. the number of layers in the the pyroelectric wafer) and continuous (e.g. the layers thickness) domain,
the genetic representation for the solution should take it into account. The chromosome used in the genetic algorithm
will mix both integer and real values, what will also be reflected in the genetic operators used in the optimization
process. Moreover, a parallel version of the genetic algorithm is used to speed up the optimization process. The GA
parallelization is based on the island model and is developed by using the MPI library. Finally, numerical analyses and
results complete the work.

Abstract document

IAC-10.C2.1.14.brief.pdf

Manuscript document

IAC-10.C2.1.14.pdf (🔒 authorized access only).

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