Title:
Computational modeling, stochastic and experimental analysis with thermoelastic stress analysis for fiber reinforced polymeric composite material systems

dc.contributor.advisor Haj-Ali, Rami M.
dc.contributor.author Johnson, Shane Miguel en_US
dc.contributor.committeeMember Makeev, Andrew
dc.contributor.committeeMember White, Donald
dc.contributor.committeeMember Will, Kenneth
dc.contributor.committeeMember Zureick, Abdul-Hamid
dc.contributor.department Civil and Environmental Engineering en_US
dc.date.accessioned 2010-09-15T18:27:55Z
dc.date.available 2010-09-15T18:27:55Z
dc.date.issued 2010-05-05 en_US
dc.description.abstract Many studies with Thermoelastic Stress Analysis (TSA) and Infrared Thermography, in Fiber Reinforced Polymeric materials (FRPs), are concerned with surface detection of "hot spots" in order to locate and infer damage. Such experimental analyses usually yield qualitative relations where correlations between stress state and damage severity cannot be obtained. This study introduces quantitative experimental methodologies for TSA and Digital Image Correlation to expand the use of remote sensing technologies for static behavior, static damage initiation detection, and fatigue damage in FRPs. Three major experimental studies are conducted and coupled with nonlinear anisotropic material modeling: static and TSA of hybrid bio-composite material systems, a new stochastic model for fatigue damage of FRPs, and fracture analysis for FRP single-lap joints. Experimental calibration techniques are developed to validate the proposed macromechanical and micromechanical nonlinear anisotropic modeling frameworks under multi-axial states of stress. The High Fidelity Generalized Method of Cells (HFGMC) is a sophisticated micromechanical model developed for analysis of multi-phase composites with nonlinear elastic and elastoplastic constituents is employed in this study to analyze hybrid bio-composites. Macro-mechanical nonlinear anisotropic models and a linear orthotropic model for fracture behavior using the Extended Finite Element method (XFEM) are also considered and compared with the HFGMC method. While micromechanical and FE results provide helpful results for correlating with quasi-static behavior, analyzing damage progression after damage initiation is not straightforward and involves severe energy dissipation, especially with increasing damage progression. This is especially true for fatigue damage evolution, such as that of composite joints as it is associated with uncertainty and randomness. Towards that goal, stochastic Markov Chain fatigue damage models are used to predict cumulative damage with the new damage indices proposed using full-field TSA image analysis algorithms developed for continuously acquired measurements during fatigue loading of S2-Glass/E733FR unidirectional single-lap joints. Static damage initiation is also investigated experimentally with TSA in single-lap joints with thick adherends providing for new design limitations. The computational modeling, stochastic and experimental methods developed in this study have a wide range of applications for static, fracture and fatigue damage of different FRP material and structural systems. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/34668
dc.publisher Georgia Institute of Technology en_US
dc.subject TSA en_US
dc.subject FRP en_US
dc.subject HFGMC nonlinear orthotropic en_US
dc.subject Markov chain en_US
dc.subject Fatigue en_US
dc.subject Fracture en_US
dc.subject Lap joint en_US
dc.subject Calibration en_US
dc.subject.lcsh Thermoelastic stress analysis
dc.subject.lcsh Remote sensing
dc.subject.lcsh Markov processes
dc.subject.lcsh Stochastic processes
dc.title Computational modeling, stochastic and experimental analysis with thermoelastic stress analysis for fiber reinforced polymeric composite material systems en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename College of Engineering
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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