<p dir="ltr">The demand and utilization of fiber-reinforced composites are increasing in various sectors, including aerospace, civil engineering, and automotive industries. Non-destructive methods are necessary for monitoring fiber-reinforced composites due to their complex and often visually undetectable failure modes. An emerging method for monitoring composite structures is through the integration of self-sensing capabilities. Self-sensing in nanocomposites can be achieved through nanofiller modifications, which involve introducing an adequate amount of nanofillers into the matrix, such as carbon nanotubes (CNTs) and carbon nanofillers (CNFs). These fillers form an electrically well-connected network that allows the electrical current to travel through conductive pathways. The disruption of connectivity of these pathways, caused by mechanical deformations or damages, results in a change in the overall conductivity of the material, thereby enabling intrinsic self-sensing.</p><p dir="ltr">Currently, the majority of predictive modeling attempts in the field of self-sensing nanocomposites have been dedicated to microscale piezoresistivity. There has been a lack of research conducted on the modeling of strain-induced resistivity changes in macroscale fiber-matrix material systems. As a matter of fact, no analytical macroscale model that addresses the impact of continuous fiber reinforcement in nanocomposites has been presented in the literature. This gap is significant because it is impossible to make meaningful structural condition predictions without models relating observed resistivity changes to the mechanical condition of the composite. Accordingly, this dissertation presents a set of three research contributions. The overall objective of these contributions is to address this knowledge gap by developing and validating an analytical model. In addition to advancing our theoretical understanding, this model provides a practical methodology for predicting the piezoresistive properties of continuous fiber-reinforced composites with integrated nanofillers.</p><p dir="ltr">To bridge the above-mentioned research gap, three scholarly contributions are presented in this dissertation. The first contribution proposes an analytical model that aims to predict the variations in resistivity within a material system comprising a nanofiller-modified polymer and continuous fiber reinforcement, specifically in response to axial strain. The fundamental principle underlying our methodology involves the novel use of the concentric cylindrical assembly (CCA) homogenization technique to model piezoresistivity. The initial step involves the establishment of a domain consisting of concentric cylinders that represent a continuous reinforcing fiber phase wrapped around by a nanofiller-modified matrix phase. Subsequently, the system undergoes homogenization to facilitate the prediction of changes in the axial and transverse resistivity of the concentric cylinder as a consequence of longitudinal deformations. The second contribution investigates the effect of radial deformations on piezoresistivity. Here, we demonstrate yet another novel application of the CCA homogenization technique to determine piezoresistivity. This contribution concludes by presenting closed-form analytical relations that describe changes in axial and transverse resistivity as functions of externally applied radial strain. The third contribution involves computationally analyzing piezoresistivity in fiber-reinforced laminae by using three-dimensional representative volume elements (RVE) with a CNF/epoxy matrix. By comparing the single-fiber-based analytical model with the computational model, we can investigate the impact of interactions between multiple adjacent fibers on the piezoresistive properties of the material. The study revealed that the differences between the single-fiber CCA analytical model and the computational model are quite small, particularly for composites with low- to moderate-fiber volume fractions that undergo relatively minor deformations. This means that the analytical methods herein derived can be used to make accurate predictions without resorting to much more laborious computational methods.</p><p dir="ltr">In summary, the impact of this dissertation work lies in the development of novel analytical closed-form nonlinear piezoresistive relations. These relations relate the electrical conductivity/resistivity changes induced by axial or lateral mechanical deformations in directions parallel and perpendicular to the reinforcing continuous fibers within fiber-reinforced nanocomposites and are validated against in-depth computational analyses. Therefore, these models provide an important and first-ever bridge between simply observing electrical changes in a self-sensing fiber-reinforced composite and relating such observations to the mechanical state of the material.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/25607475 |
| Date | 16 April 2024 |
| Creators | Sultan Mohammedali Ghazzawi (18369387) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Macroscale_Modeling_of_the_Piezoresistive_Effect_in_Nanofiller-Modified_Fiber-Reinforced_Composites/25607475 |
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