Computational Investigation of Strain and Damage Sensing in Carbon Nanotube Reinforced Nanocomposites with Descriptive Statistical Analysis
| dc.contributor.author | Talamadupula, Krishna Kiran | en |
| dc.contributor.committeechair | Seidel, Gary D. | en |
| dc.contributor.committeemember | Tarazaga, Pablo Alberto | en |
| dc.contributor.committeemember | Case, Scott W. | en |
| dc.contributor.committeemember | Nain, Amrinder | en |
| dc.contributor.committeemember | Kapania, Rakesh K. | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2022-03-06T07:00:16Z | en |
| dc.date.available | 2022-03-06T07:00:16Z | en |
| dc.date.issued | 2020-09-11 | en |
| 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. | en |
| dc.description.abstractgeneral | Carbon nanotubes or CNTs belong to a class of novel materials known as nanomaterials which are materials with length scales on the order of nanometers. CNTs have been widely studied due to their unique mechanical, electrical and thermal properties in comparison to traditional materials such as metals or plastics. Often times, research and applications concerning the use of CNTs involves embedding the CNTs as a filler within a larger composite material system. In the present work, CNTs are considered to be embedded within a polymer. It is known that the electrical properties of such a CNT/polymer composite change in response to the application of a mechanical force. This change in electrical properties is caused due to the presence of CNTs and is used as a means of sensing the mechanical state of the composite, i.e. real time structural monitoring. The extent of the change in electrical properties, also known as sensing, depends upon a number of different factors such as the amount of CNTs used per unit volume of the polymer, how well dispersed or clumped together the CNTs are within the polymer and the type of polymer material used, among other factors. A statistical analysis is performed with several case studies where these factors are varied and the resulting change in the sensing response is monitored. Several important conclusions were made from the statistical analysis with some of the results providing new insights into the sensing behavior of CNT/polymer composites. For example, it was found that a key parameter known as barrier potential, which directly influences the extent of sensing achieved through a mechanism known as electrical tunneling, needs to be several orders of magnitude lower than previously reported values to accurately capture the sensing effects. Key metrics quantifying the extent of sensing from the analysis were found to be in agreement with previously reported experimental results. The significance of such a statistical study lies in the fact that CNT embedded composites are increasingly being proposed and used for sensing applications. The use of CNT embedded polymers to encase explosive crystalline grains such as HMX or RDX is one such example. These explosive grains are used in a number of different civil and military applications such as fuel rocket propellants, industry explosives, military munitions etc. The grains possess extremely high energy densities and are susceptible to undergo violent chemical reaction if a trigger is provided through thermal or mechanical means. As such, the monitoring of the structural state of these explosives is crucial for their safe handling and processing. In this work, the sensing response of a composite material comprising of explosive grains surrounded by polymer material containing CNTs is studied in response to different types of mechanical loads, ranging from mild stimuli to impact. It was found that the sensing mechanism was capable of tracking mechanical damage as well as the resulting temperature increases interior to the composite. In addition to its application to safety and preventative measures, the use of CNTs in this context also provided insight into the mechanisms related to the sudden release of energy in these explosive grains which is of significant interest since this is an active area of research as well. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:26961 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/109180 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | peridynamics | en |
| dc.subject | polymer nanocomposites | en |
| dc.subject | microstructure | en |
| dc.subject | piezoresistivity | en |
| dc.subject | carbon nanotube | en |
| dc.subject | energetic materials | en |
| dc.subject | damage | en |
| dc.subject | friction | en |
| dc.subject | hotspots | en |
| dc.subject | electron tunneling | en |
| dc.subject | gage factor | en |
| dc.subject | percolation | en |
| dc.subject | orientation | en |
| dc.subject | alignment | en |
| dc.subject | wavy | en |
| dc.title | Computational Investigation of Strain and Damage Sensing in Carbon Nanotube Reinforced Nanocomposites with Descriptive Statistical Analysis | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
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