Uncertainty in the manufacturing of fibrous thermosetting composites: A review

Composites manufacturing involves many sources of uncertainty associated with material properties variation and boundary conditions variability. In this study, experimental and numerical results concerning the statistical characterization and the influence of inputs variability on the main steps of composites manufacturing including process-induced defects are presented and analysed. Each of the steps of composite manufacturing introduces variability to the subsequent processes, creating strong interdependencies between the process parameters and properties of the final part. The development and implementation of stochastic simulation tools is imperative to quantify process output variabilities and develop optimal process designs in composites manufacturing

Stochastic simulation of the influence of fibre path variability on the formation of residual stress and shape distortion

A stochastic cure simulation approach is developed and implemented to investigate the influence of fibre misalignment on cure. Image analysis is used to characterize fiber misalignment in a carbon non-crimp fabric. It is found that variability in tow orientation is significant with a standard deviation of 1.2°. The autocorrelation structure is modeled using the Ornstein-Uhlenbeck sheet and the stochastic problem is addressed by coupling a finite element model of cure with a Monte Carlo scheme. Simulation of the cure of an angle shaped carbon fiber-epoxy component shows that fiber misalignment can cause considerable variability in the process outcome with a coefficient of variation in maximum residual stress up to approximately 2% (standard deviation of 1 MPa) and qualitative and quantitative variations in final distortion of the cured part with the standard deviation in twist and corner angle reaching values of 0.4° and 0.05° respectively. POLYM. COMPOS., 2015. © 2015 The Authors Polymer Composites published by Wiley Periodicals, Inc. on behalf of Society of Plastics Engineer

Mechanical Properties of Glass Fiber Composites Reinforced by Textile Fabric

Interest to structural application of textile reinforced polymer matrix composite materials (CM) is growing during last years. In different branches of machine building, aerospace, automotive and others industries we can find structural elements preferably be produced using such reinforcement. At the same time, such materials are exhibiting elastic and strength properties scatter. In the framework of the present investigation, we observe yarn penetrated by a resin in a composite as a reinforcing “macro” fiber. Such “macro” fiber mechanical properties were measured experimentally, for this purpose was produced and was tested by tension until fracture fiber samples, having different length. Then was elaborated and was realized structural strength probabilistic model. In the textile geometry, was picked out repeating structural element – polymer matrix volume with two curved “macro” fiber’s chunks inside it. Complete composite material volume is possible to represent as a set of repeating structural elements. External loads application leads to disperse structural elements failure. Neighboring to ruptured elements are overloaded leading to higher probability to fail for them. Using FEM was modeled stress state in “macro” fibers inside CM. Then, was numerically obtained stress distribution in composite material, having different number of broken loops. Probabilities of different numbers of failed elements were calculated.  Strength probability function, based on Weibull approach was obtained. CM samples were tested under tension and obtained results were compared with numerical modeling as well as were analyzed

Development of carbon fiber acrylonitrile styrene acrylate composite for large format additive manufacturing

The increasing interest of Large Format Additive Manufacturing (LFAM) technologies in various industrial sectors mainly lies on the attainable production of pieces reaching several cubic meters. These new technologies require the development of optimized materials with two-folded capabilities, able to satisfy functional in-service requirements but also showing a proper printability. Acrylonitrile Styrene Acrylate (ASA) is among the most interesting thermoplastic materials to be implemented in a LFAM device due to its excellent wettability and mechanical properties. This research focuses on the development and characterization of ASA and carbon fiber (CF) ASA composites suitable for LFAM. The rheological, thermal and mechanical properties of neat ASA and ASA containing 20 wt% CF are addressed. The results evidence the higher performance of the CF loaded composite compared to the raw ASA polymer (i.e., the 20 wt% CF composite shows a 350% increase in flexural Young's Modulus and a 500% increment in thermal conductivity compared with neat ASA). Additionally, both materials were successfully printed along perpendicular directions (X and Z), showing the maximum tensile strain for the composite printed along the X orientation as was expected. The results of the flexural tests are comparable or slightly higher than those of injected parts. Finally, the fracture surface was analysed, identifying different types of porosity

Multiscale Damage Modelling of Notched and Un-Notched 3D Woven Composites With Randomly Distributed Manufacturing Defects

This work proposes a stochastic multiscale computational framework for damage modelling in 3D woven composite laminates, by considering the random distribution of manufacturing-induced imperfections. The proposed method is demonstrated to be accurate, while being simple to implement and requiring modest computational resources. In this approach, a limited number of cross-sectional views obtained from micro-computed tomography (µCT) are used to obtain the stochastic distribution of two key manufacturing-induced defects, namely waviness and voids. This distribution is fed into a multiscale progressive damage model to predict the damage response of three-dimensional (3D) orthogonal woven composites. The accuracy of the proposed model was demonstrated by performing a series of finite element simulations of the un-notched and notched tensile tests (having two different hole sizes) for resin-infused thermoplastic (Elium®) 3D woven composites. Excellent correlation was achieved between experiments and the stochastic finite element simulations. This demonstrates the effectiveness of the proposed stochastic multiscale model. The model successfully captured the stochastic nature of tensile responses (ultimate tensile strength and stiffness), damage modes (matrix damage and fibre failure), and initiation and propagation of transverse cracks in thermoplastic 3D woven composites, consistent with experimental observation. The stochastic computational framework presented in this paper can be used to guide the design and optimization of 3D textile composite structures

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

섬유강화 폴리머 적층 복합재료의 확률론적 점진 손상해석 모델

학위논문 (석사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2019. 2. 윤군진.Fiber reinforced polymer matrix composites (FRPMC) laminate composites are widely used for its high strength and high stiffness-to-weight ratio. Although FRPMC holds many advantages, it has low matrix strength. This thesis proposes a stochastic progressive damage simulation model for FRPMC laminates. Damage mechanisms considered in this thesis are internal damages of fiber and matrix. Deterministic predictions by the existing damage progressive analysis model of laminate composites could be very different from the experimental global strength and failure modes due to effects of material uncertainties. In polymer matrix composites, such material uncertainties arise from different cure kinetics and chemically induced shrinkage. Therefore, uncertainties of constituents physical properties were taken into account in this study. An anisotropic damage model was used for damage initiation and evolution of each layer. Strength and fracture energy of layers were modelled as spatially varying random fields through the Karhunen-Loeve expansion method. For demonstrations of the proposed stochastic progressive damage analysis, a three-dimensional meso-scale finite element model of a multiple-layer was developed.Abstract i Table of contents iii List of figures v List of tables vii 1. Introduction 1 1.1. Background and Motivation 1 1.2. Objectives and Thesis Overview 4 2. Spatial randomness of material properties 5 2.1. Modeling of three-dimensional random field of materials. 6 2.2. Numerical implementation of KL expansion 7 2.3. Application for fiber reinforced polymer 13 3. Progressive damage analysis model of fiber-reinforced polymer matrix composites 16 3.1. Damage initiation criteria 16 3.2. Damage evolution process 18 3.3. Damage material constitutive law 21 3.4. Viscous regularization technique 23 3.5. Numerical implementation 25 3.6. Verification of UMAT 31 3.7. Stochastic damage material model 36 4. Numerical examples 38 4.1. A progressive damage analysis 38 4.2. Effects of spatial strength 41 4.3. Effects of spatial fracture energy 51 4.4. Effects of spatial fracture energy with cohesive elements 54 5. Conclusion and future works 57 5.1. Conclusion 57 5.2. Future works 58 6. Reference 60 국문초록 63Maste