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Virginia Tech

Computational Investigation of Strain and Damage Sensing in Carbon Nanotube Reinforced Nanocomposites with Descriptive Statistical Analysis

Abstract

dc:description.abstract

Polymer bonded explosives (PBXs) are composites comprised of energetic crystals with a very high energy density surrounded by a polymer binder. The formation of hotspots within polymer bonded explosives can lead to the thermal decomposition and initiation of the energetic material. A frictional heating model is applied at the mesoscale to assess the potential for the formation of hotspots under low velocity impact loadings. Monitoring of the formation and growth of damage at the mesoscale is considered through the inclusion of a piezoresistive carbon nanotube network within the energetic binder providing embedded strain and damage sensing. A coupled multiphysics thermo-electro-mechanical peridynamics framework is developed to perform computational simulations on an energetic material microstructure subject to these low velocity impact loads. With increase in impact energy, the model predicts larger amounts of sensing and damage thereby supporting the use of carbon nanotubes to assess damage growth and subsequent formation of hotspots. The framework is also applied to assess the combined effects of thermal loading due to prescribed hotspots with inertial effects due to low velocity impact loading. It has been found that the present model is able to detect the presence of hotspot dominated regions within the energetic material through the piezoresistive sensing mechanism. The influence of prescribed hotspots on the thermo-electro-mechanical response of the energetic material under a combination of thermal and inertial loading was observed to dominate the lower velocity impact response via thermal shock damage. In contrast, the higher velocity impact energies demonstrated an inertially dominated damage response. Quantifying the piezoresistive effect derived from embedding carbon nanotubes in polymers remains a challenge since these nanocomposites exhibit significant variation in their electro-mechanical properties depending upon factors such as CNT volume fraction, CNT dispersion, CNT alignment and properties of the polymer. Of interest is electrical percolation where the electrical conductivity of the CNT/polymer nanocomposite increases through orders of magnitude with increase in CNT volume fraction. Estimates and distributions for the electrical conductivity and piezoresistive coefficients of the CNT/polymer nanocomposite are obtained and analyzed with increasing CNT volume fraction and varying barrier potential, which is a parameter that controls the extent of electron tunneling. The effect of CNT alignment is analyzed by comparing the electro-mechanical properties in the alignment direction versus the transverse direction for different orientation conditions. Estimates of piezoresistive coefficients are converted into gage factors and compared with experimental sources in literature. The methodology for this work uses automated scripts which are used in conjunction with high performance computing to generate several 5 μm ×5 μm realizations for different CNT volume fractions. These realizations are then analyzed using finite elements to obtain volume averaged effective values, which are then subsequently used to generate measures of central tendency (estimated mean) and variability (standard deviation, coefficient of variation, skewness and kurtosis) in a descriptive statistical analysis.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Mechanical Engineering
Department dc:contributor.department
Mechanical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Talamadupula, Krishna Kiran
Chair dc:contributor.committeechair
  • Seidel, Gary D.
Committee members dc:contributor.committeemember
  • Tarazaga, Pablo Alberto
  • Case, Scott W.
  • Nain, Amrinder
  • Kapania, Rakesh K.

Subjects

dc:subject × 15

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:26961
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/109180

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Talamadupula, Krishna Kiran. Computational Investigation of Strain and Damage Sensing in Carbon Nanotube Reinforced Nanocomposites with Descriptive Statistical Analysis. doctoral thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/109180