Advanced lightweight structural materials like composites are being increasingly utilized in various engineering applications due to high specific strength and stiffness with tailorable properties. Even though composites have the advantage of modulating a large number of design parameters to achieve various application-specific requirements, this concurrently brings the challenge of dealing with inevitable uncertainties during manufacturing and service-life conditions. This dissertation focuses on practically relevant modelling of random spatial variability coupled with the influence of damage to quantify the effect of source-uncertainties following an efficient surrogate based framework. Layer-wise random variable based approach and the random field based approaches of uncertainty modelling are investigated to quantify the stochastic dynamics and stability characteristics of in a probabilistic multi-scale framework. A novel concept of stochastic representative volume element is proposed to consider the spatially varying structural attributes effectively. A physically relevant random field based modelling approach with correlated material properties is adopted based on the Karhunen-Loève expansion. To understand the relative influences, sensitivity of the stochastic input parameters are analyzed for the global structural responses of composite laminates considering micro and macro mechanical properties separately. Besides the conventional sources of uncertainty in material and structural properties, another source of uncertainty is considered in the form of noise. Besides probabilistic analysis, this dissertation proposes a fuzzy representative volume element based approach for modelling spatial variability in non-probabilistic analysis for the cases where statistical distributions of the stochastic input parameters are not available. The results reveal that stochasticity affects the system performance significantly. A notable difference in the global stochastic behaviour is identified depending upon the adopted uncertainty modeling approach. Thus, it is imperative to appropriately model the sourceuncertainties during the analysis and design process. The dissertation provides comprehensive insights on the effect of source-uncertainties on composites following an efficient, yet practically relevant modelling approach.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:759999 |
| Date | January 2018 |
| Creators | Naskar, Susmita |
| Contributors | Sriramula, Srinivas |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=239036 |
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