Prediction of delamination in glass fibre reinforced composite materials using elasto-plastic modelling

Glass Fibre reinforced composite (GFRC) has been used for numerous structural applications in Aerospace, Chemical, Automotive and Civil infrastructure fields over a hundred of years. Due to this reason, understanding the intricate fracture behaviour of GFRC materials is crucial and essential for designing critical structural components. Voids and micro-cracks are considered as imperfections in Glass Fibre Reinforced composites. Much research has been undertaken on approaches to calculate and evaluate the effects of the imperfections on mechanical properties. However, it is an established fact that the micro-mechanical approach alone is not sufficient to understand a complete damage accumulation process during delamination. The damage mechanism which largely affects the performance of GFRC structures is commonly known as 'delamination'. Since the delamination is invisible, and hard to detect with ordinary non-destructive evaluation methods, therefore it is considered as a hidden killer which can cause catastrophic failure without any prior warnings. Due to this reason, research work on delamination modelling, damage detection and self-healing materials have been the highly placed research topics for more than five decades. Unfortunately there are a number of unresolved problems in delamination damage modelling and prediction, and few grey areas regarding application of Structural Health Monitoring systems to monitor delamination damages. This thesis has proposed to study the insight into the cause of delamination damage and its propagation mechanisms, by analytical modelling and experimental verifications. Within this research project, extension of the work by Tsukrov and Kachanov (2000) – “An innovative Elasto-plastic model” has been undertaken to evaluate, investigate and model the onset and propagation of delamination damages. Mode I, Mode II as well as Mixed Mode I/II delamination damage analysis has been utilised to study the proposed model predictions for GFRC structures for both in-plane and out-of-plane load applications. The proposed model has been validated using the Double Cantilever Beam (DCB), End Notch Flexure configurations (ENF) and Cracked Lap Shear (CLS) experiments on 0/90-glass woven cloth specimens. For the validation process, the procedures stipulated by ASTM standards were employed. It was observed that there were significant discrepancies between calculated fracture energies using standard procedures and the proposed model. Interestingly these observations have revealed some inconsistencies associated with the standard method for strain measurements that majorly controls the fracture energy calculations. This research project has demonstrated and evidently proven the accuracy of the proposed model predictions using the strain measured with embedded Fibre Bragg Grating (FBG) sensors, located inside the sample in proximity of the crack tip. The extended use of FBG strain measurement has created a breakthrough in Structural Health Monitoring (SHM) of composite structures. Non-availability of a suitable damage prediction model is an issue for accurate damage monitoring process. The proposed model has also demonstrated the potential for its integration with Structural Health Monitoring (SHM) systems. Additionally, Thermoplastic Stress Analysis (TSA) has been employed to monitor delamination. The potential for integration of FBG sensors and TSA techniques has been experimentally demonstrated during this project and, it is another breakthrough in SHM field as a result of this research. In addition to analytical model, a detailed Finite Element model was also created on ABAQUS commercial software. The cohesive elements with state variables (SDV) and UMAT codes were used for FEA simulations. Interestingly, the FEA results have shown an excellent correlation with the experimental results. Finally, this thesis has evidently proved the validity of the proposed model and integration of model with SHM system based on FBG sensors and TSA techniques. The outcomes of the thesis have provided a novel and innovative damage prediction model and a breakthrough technology for SHM systems

New innovations in pavement materials and engineering: A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging. Deterioration of pavement infrastructure is a typical multi-physics problem. Because of actual coupled behaviors of traffic and environmental conditions, predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis. In order to summarize the current and determine the future research of pavement engineering, Journal of Traffic and Transportation Engineering (English Edition) has launched a review paper on the topic of “New innovations in pavement materials and engineering: A review on pavement engineering research 2021”. Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering, this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the world. The content includes asphalt binder performance and modeling, mixture performance and modeling of pavement materials, multi-scale mechanics, green and sustainable pavement, and intelligent pavement. Overall, this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering

Computational Studies on Functionalized ZnO Surfaces and Nanostructures

In this work, we have used computer simulations to investigate the effect of organic functionalization on ZnO surfaces and nanostructures. Density Functional Theory has been employed to study the interactions of ZnO surfaces with different organic groups, identifying stabilization mechanisms involved in each case and the most promising anchoring groups for ZnO functionalization. Additionally, a semi-empirical model for ZnO large scale simulations has been developed and validated by comparison against DFT calculations. The was successful in simulating Zn-containing bulk solids and molecular complexes, ZnO surfaces and nanostructures, and the adsorption of organic acids on (1010)-ZnO surfaces. We have also employed this model to characterize native defects in ZnO nanowires. Finally, we have demonstrated that the interaction of surface oxygen vacancies with organic acids may explain the suppression of photoluminescence anomalies observed for polymer coated ZnO nanowires

Determination of the strain distribution in the adhesive joints using fiber bragg grating (FBG)

Tese de mestrado integrado. Engenharia Mecânica. Faculdade de Engenharia. Universidade do Porto. 201

Tailored-design of molecularly imprinted polymers with induced cavities of high conformational stability as new platforms for chemical sensing applications

Molecularly imprinted polymers (MIP) are highly promising materials that have many applications in different fields such as chromatography, catalysis, chemical and biochemical sensing, or even drug delivery. These materials can be tailored to contain intrinsic nano scaled cavities within their structure. These cavities are highly interesting, because they can be made selective for an intended template. Thus, MIP are deeply researched to replace proteins in sensing applications. Proteins are highly delicate and labile to slight changes in the surrounding media, however MIP are polymer based. Therefore, they are easy to handle and mechanically more stable. In addition, they are much cheaper. Still MIP are not fully ready to replace proteins, because their selectivities are usually lower than that of proteins. The current study aims at controlling the physical and chemical properties of the cavities within MIP. Cavities in MIP are the template binding sites, which are the main determinants of the performance of MIP. Two parameters were selected to be studied and to reflect MIP performance; conformational stability and the binding capacity of the cavities. Conformational stability to the best of our Knowledge has never been studied in MIP. This feature was intended to be studied, in order to get information about the ability of different MIP systems to keep the conformational shape and specifity of their nanoscaled cavities. The study began first by a theoretical investigation of a library of monomers using computational modeling, and then was followed by a practical investigation. The theoretical investigation screened a library of monomers, and the best scoring two monomers with regards to conformational stability and binding energy were selected for practical investigation. The practical investigations aimed at validating the correlation between the theoretical performance of the selected candidates, and the practical performance of their MIP in a media containing the selected template, through measuring the MIP\u27s binding capacities. The study could show the significant importance of assessing the conformational stabilities of the MIP building blocks (monomers), and that they directly affected the binding capacities of the studied MIP. Thus it can be suggested that research should not only focus on assessing the binding capacities of MIP, but also special focus should be given to studying the conformational stability of the binding sites

Physics-Based Modeling of Material Behavior and Damage Initiation in Nanoengineered Composites

abstract: Materials with unprecedented properties are necessary to make dramatic changes in current and future aerospace platforms. Hybrid materials and composites are increasingly being used in aircraft and spacecraft frames; however, future platforms will require an optimal design of novel materials that enable operation in a variety of environments and produce known/predicted damage mechanisms. Nanocomposites and nanoengineered composites with CNTs have the potential to make significant improvements in strength, stiffness, fracture toughness, flame retardancy and resistance to corrosion. Therefore, these materials have generated tremendous scientific and technical interest over the past decade and various architectures are being explored for applications to light-weight airframe structures. However, the success of such materials with significantly improved performance metrics requires careful control of the parameters during synthesis and processing. Their implementation is also limited due to the lack of complete understanding of the effects the nanoparticles impart to the bulk properties of composites. It is common for computational methods to be applied to explain phenomena measured or observed experimentally. Frequently, a given phenomenon or material property is only considered to be fully understood when the associated physics has been identified through accompanying calculations or simulations. The computationally and experimentally integrated research presented in this dissertation provides improved understanding of the mechanical behavior and response including damage and failure in CNT nanocomposites, enhancing confidence in their applications. The computations at the atomistic level helps to understand the underlying mechanochemistry and allow a systematic investigation of the complex CNT architectures and the material performance across a wide range of parameters. Simulation of the bond breakage phenomena and development of the interface to continuum scale damage captures the effects of applied loading and damage precursor and provides insight into the safety of nanoengineered composites under service loads. The validated modeling methodology is expected to be a step in the direction of computationally-assisted design and certification of novel materials, thus liberating the pace of their implementation in future applications.Dissertation/ThesisDoctoral Dissertation Aerospace Engineering 201

An Overview of Additive Manufacturing Technologies—A Review to Technical Synthesis in Numerical Study of Selective Laser Melting

Additive Manufacturing (AM) processes enable their deployment in broad applications from aerospace to art, design, and architecture. Part quality and performance are the main concerns during AM processes execution that the achievement of adequate characteristics can be guaranteed, considering a wide range of influencing factors, such as process parameters, material, environment, measurement, and operators training. Investigating the effects of not only the influential AM processes variables but also their interactions and coupled impacts are essential to process optimization which requires huge efforts to be made. Therefore, numerical simulation can be an effective tool that facilities the evaluation of the AM processes principles. Selective Laser Melting (SLM) is a widespread Powder Bed Fusion (PBF) AM process that due to its superior advantages, such as capability to print complex and highly customized components, which leads to an increasing attention paid by industries and academia. Temperature distribution and melt pool dynamics have paramount importance to be well simulated and correlated by part quality in terms of surface finish, induced residual stress and microstructure evolution during SLM. Summarizing numerical simulations of SLM in this survey is pointed out as one important research perspective as well as exploring the contribution of adopted approaches and practices. This review survey has been organized to give an overview of AM processes such as extrusion, photopolymerization, material jetting, laminated object manufacturing, and powder bed fusion. And in particular is targeted to discuss the conducted numerical simulation of SLM to illustrate a uniform picture of existing nonproprietary approaches to predict the heat transfer, melt pool behavior, microstructure and residual stresses analysis

A New Atomistic Simulation Framework for Mechanochemical Reaction Analysis of Mechanophore Embedded Nanocomposites

abstract: A hybrid molecular dynamics (MD) simulation framework is developed to emulate mechanochemical reaction of mechanophores in epoxy-based nanocomposites. Two different force fields, a classical force field and a bond order based force field are hybridized to mimic the experimental processes from specimen preparation to mechanical loading test. Ultra-violet photodimerization for mechanophore synthesis and epoxy curing for thermoset polymer generation are successfully simulated by developing a numerical covalent bond generation method using the classical force field within the framework. Mechanical loading tests to activate mechanophores are also virtually conducted by deforming the volume of a simulation unit cell. The unit cell deformation leads to covalent bond elongation and subsequent bond breakage, which is captured using the bond order based force field. The outcome of the virtual loading test is used for local work analysis, which enables a quantitative study of mechanophore activation. Through the local work analysis, the onset and evolution of mechanophore activation indicating damage initiation and propagation are estimated; ultimately, the mechanophore sensitivity to external stress is evaluated. The virtual loading tests also provide accurate estimations of mechanical properties such as elastic, shear, bulk modulus, yield strain/strength, and Poisson’s ratio of the system. Experimental studies are performed in conjunction with the simulation work to validate the hybrid MD simulation framework. Less than 2% error in estimations of glass transition temperature (Tg) is observed with experimentally measured Tgs by use of differential scanning calorimetry. Virtual loading tests successfully reproduce the stress-strain curve capturing the effect of mechanophore inclusion on mechanical properties of epoxy polymer; comparable changes in Young’s modulus and yield strength are observed in experiments and simulations. Early damage signal detection, which is identified in experiments by observing increased intensity before the yield strain, is captured in simulations by showing that the critical strain representing the onset of the mechanophore activation occurs before the estimated yield strain. It is anticipated that the experimentally validated hybrid MD framework presented in this dissertation will provide a low-cost alternative to additional experiments that are required for optimizing material design parameters to improve damage sensing capability and mechanical properties. In addition to the study of mechanochemical reaction analysis, an atomistic model of interphase in carbon fiber reinforced composites is developed. Physical entanglement between semi-crystalline carbon fiber surface and polymer matrix is captured by introducing voids in multiple graphene layers, which allow polymer matrix to intertwine with graphene layers. The hybrid MD framework is used with some modifications to estimate interphase properties that include the effect of the physical entanglement. The results are compared with existing carbon fiber surface models that assume that carbon fiber has a crystalline structure and hence are unable to capture the physical entanglement. Results indicate that the current model shows larger stress gradients across the material interphase. These large stress gradients increase the viscoplasticity and damage effects at the interphase. The results are important for improved prediction of the nonlinear response and damage evolution in composite materials.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201