Back close

Particulate Polymer Composites for Space Applications: Modeling and Simulation of Physical, Mechanical and Rheological Properties

Start Date: Wednesday, May 22,2013

End Date: Thursday, Apr 21,2016

School: School of Engineering, Coimbatore

Project Incharge:Dr. P. K. Krishnan Namboori
Co-Project Incharge:Dr. Bhagawan S. S.
Co-Project Incharge:Dr S. S. Bhagawan
Funded by:VSSC, Indian Space Research Organization (ISRO), Trivandrum
Particulate Polymer Composites for Space Applications: Modeling and Simulation of Physical, Mechanical and Rheological Properties

Different types of polymer composites are used in launch vehicles and satellite systems. The polymer matrices include polyurethanes, silicones, epoxies, PEEK, phenolics, acrylonitrile – butadiene copolymer [NBR], polyisoprene [NR] etc. Fillers which provide reinforcement, or specific properties may be particulate [eg silica, carbon black, silicon carbide] or fibrous / fabric, continuous or discrete [eg fibre/fabric of carbon, silica fabric, Kevlar, glass etc]. Such composites are extensively used for structural parts, coatings, thermal protection systems (TPS), speciality coatings, adhesives, sealants, etc in various stages of launch vehicle and satellites. In many cases, the properties are evaluated after blending the systems by trial and error that demands enormous experimentation, time and energy and work. This proposal envisages modeling structure – property relationships in a few such polymer composites systems using computational chemistry techniques like molecular mechanics (MM), molecular dynamics (MD) simulations, Monte Carlo simulations etc. for prediction of physical properties, mechanical behavior and rheological properties.

The surface characteristics of polymer chains [different molecular weights, surface group] and particulate reinforcements [different sizes, loadings] would be modeled to generate the possible interactions, filler adsorption and temperature effects.

The environment of individual groups can be examined using molecular mechanics and the energetic of assume relaxation mechanisms such as ring rotation or functional group deformation can be calculated. Simulations can be used to study the amorphous systems below or above the glass transition or melting temperature.

OBJECTIVES

Broadly speaking, the proposal envisages modeling the interactions in filled polymer composite systems with special focus on particulate composites used in launch vehicles and spacecraft. Typical examples are silicon carbide-siloxane, silica-siloxane, micro cell-phenolic/ epoxy which are in use at different stages in space applications

The objectives include:

  • Study of physical interactions: Surface energy, effect of molecular weight of polymer, shape and size of particulate reinforcement; diffusion, surface phenomena and energy transfer and study of conformational changes-macroscopic.
  • Mechanical properties of polymer-particulate composites generated from molecular dynamics simulations.
  • Study the physical and thermal properties of polymers (theoretical and experimental)
  • Computation of rheology related properties. Predict the time and temperature dependent properties like .viscosity, cohesive forces (and thus indirectly the bulk properties)
  • Study of thermodynamic properties of the composites

Related Projects

Mitigation of dam induced flood disaster due to hydrological extremes (CoPI)
Mitigation of dam induced flood disaster due to hydrological extremes (CoPI)
Durability of High Performance Nano Adhesive Bonding of Aluminium under Aerospace Environments
Durability of High Performance Nano Adhesive Bonding of Aluminium under Aerospace Environments
Synthesis and Characterization of Functionally Graded Copper Metal Matrix Composites
Synthesis and Characterization of Functionally Graded Copper Metal Matrix Composites
Influence of Boron Carbide Addition on Neutron Shielding Ability of Cement Mortar Mix
Influence of Boron Carbide Addition on Neutron Shielding Ability of Cement Mortar Mix
Decoding of Turbo Product Codes using Deep Learning Technique
Decoding of Turbo Product Codes using Deep Learning Technique
Admissions Apply Now