Defect Prediction in Composites Based on Numerical Simulation and - PDF document

18 TH INTERNATIONAL CONFERENCE ON COMPOSITE MATERIALS Defect Prediction in Composites Based on Numerical Simulation and Expertise Knowledge Li YanXia*, LI Min, GU Yi-Zhuo, Sun Jing and ZHANG Zuo-Guang Key Laboratory of Aerospace Materials and Performance (Ministry of Education), Beihang University, Beijing, 100191, P R China * Corresponding author ( liyanxia@buaa.edu.cn ) Keywords : Carbon fiber composite , manufacture , defects , void methods of defects in composites has attracted Abstract Advanced composites components for aircraft increasing consideration over the past few decades. application continues to rise and primary structures The types of composite components applied to are increasingly made from advanced composites. aircraft are different and complex; therefore, the The quality and its stability of the composites resin flow of composite components is much more structure are very important. As we known, the complicated because of the complexity of composites structure is formed together with the temperature distribution and pressure transfer in composite material. The material, processes and components. In more detail, the ratio of defect design practices that are used to generate the appearance would increase and the controllability of composite structure will affect the quality. It is such defects would also become difficult when some necessary to develop a method being able to structure parameters exceed a certain range. previously predict the defect in the composites and In this paper, Numerical models were to improve the quality of the composites material. In developed and simulations were conducted for this paper, based on the numerical simulation composites to study the temperature and pressure in module (temperature and pressure field prediction the laminates during the cure process. Combined including the auxiliary material and composites) and with the model of pore growth and the expertise expertise knowledge i.e. combined with statistical knowledge (experimental data), the probability of results and defect micrographs, the strong generation of pore in the laminate can be predicted. correlation between geometric characteristics (for These results can provide a good reference for the instance, thickness, curvature radius) in composite processor and designer, and are very helpful for the components and controllability of manufacturing improvement and quality control of composite parts. defects was obtained, the void defect can be 2 Process Model predicted for the L-shaped laminates. These results can provide a good reference for the processor and 2.1 Temperature Field designer, and are very helpful for the improvement For the heat transfer in composites during the and quality control of composite parts. autoclave process, the governing equations combined the heat transfer and resin reaction 1 Introduction kinetics is established, which is responsible for Advanced composites are commonly used as calculation of the distribution of component structural components in aircraft, aerospace, and temperature and the cure degree of resin. For the automotive industries. Autoclave molding two-dimensional case, and with the coordinate axes technology is one of the most popular techniques for aligned with the material principal axes, heat these materials. However, during the manufacturing transfer equation can be written as: process of composites components, various defects ∂ ∂ ⎛ ∂ ⎞ ∂ ⎛ ∂ ⎞ T T T such as void, delamination and debonding, etc., ρ = + + ρ & C k k R H ⎜ ⎟ ⎜ ⎟ (1) p ∂ ∂ xx ∂ ∂ zz ∂ t x ⎝ x ⎠ z ⎝ z ⎠ inevitably appear as results of curing schedule, Where T is the temperature, t is the time; ρ and environment, raw materials, and unreasonable structure design of composite components. These C p are the composite density and specific heat manufacturing defects sometimes cause serious capacity, respectively. k xx and k zz are the thermal & is the rate of threat to mechanical properties and service life of conductivities, ρ R is the resin density, H composites, paralleled with making a great heat generation of the resin exothermic reaction. economic loss. Exploring the causes and controlled Coordinate z refers to the thickness direction of the laminate while x refers to the length direction. At

each step, a variety of equations are used to calculate [2]. Resin viscosity, fiber bed permeability and fiber the composite thermo-physical properties in Eq.1 volume fraction are updated at each time step in the from the local fiber volume fraction, and solution. instantaneous resin and fiber properties. 3 Manufacturing Defects in Autoclave Molding The rate of heat generation in Eq.1 can be In reference [3], the manufacturing defects determined from: were summarized systematically according to the da & = = α H H H f T u ( , ) (2) results of non-destructive identification such as u dt ultrasonic and X-ray, in which some defects of fiber Where H u is the total amount of heat generated waviness, fiber volume fraction non uniformity, and during a ‘complete’ resin reaction, a is the degree of thickness non-uniformity were not included in the cure, da/dt is cure rate and is a function of statistical range. temperature T and degree of cure a. The main defects often formed in autoclave For the tool and auxiliary materials, the Fourier molding and the defect ratio between the number of heat transfer model is used, the material property every type of defects and the number of total defects parameters including thermal conductivity, heat are presented in Figure 1. specific, density obtained by experiments. The statistical data sample for various types of manufacturing defects distributed in every compo- 2.2 Pressure Field site component is listed in table 1. The squeezed sponge model was employed to In Fig.1 and Table 1, D1, D2, D3, D4, D5, D6, describe the resin flow and fiber compaction D7, and D8 refers to delamination, void, pore, behavior in composite. The composite material is debonding, rich resin, lack resin, loose, and deform- assumed to be an elastic, deformable, porous ation, respectively.A1 and A2 in Table 1 represent medium in which the resin flows relative to the fiber the total number of components with defects and bed obeying Darcy’s law. For the representative total number of components. element, the differential equilibrium equation can be written as: 50 ∂ σ ∂ P ij + = Defect ratio(% ) 0 (3) 40 ∂ ∂ x x j i 30 Where σ ij and P are the fiber effective stress and resin pressure, respectively. Subscript i and j 20 stand for Cartesian coordinates x or z . According to the mass conservation, the flow 10 continuity equation is expressed as: 0 D6 D8 D7 D5 D4 D3 D2 D1 ∂ ε ∂ ⎛ ∂ ⎞ ∂ ⎛ ∂ ⎞ S S P P Defect type = + v xx zz (4) ⎜ ⎟ ⎜ ⎟ Fig.1 Contrast graph for manufacturing defects ∂ ∂ µ ∂ ∂ µ ∂ t x x z z ⎝ ⎠ ⎝ ⎠ Table1. Statistical data sample of manufacturing defects Where S xx , S zz are the fiber bed permeability in composite components which varies with varying fiber volume fraction, µ is resin viscosity, ε v is the bulk strain. The simplified constitutive equation [3, 11-12] is σ = ε E xx xx xx ( ) ( ) 4 (5) σ = ⋅ − − A s 1 V / V V V 1 From Fig.1, obviously, delamination occupies a zz f 0 a f τ = γ dominant position among the manufacturing defects; G xz xz xz pore and void are also two important defects of where E xx , E zz and G xz are the fiber bundle which ratios are much lower than delamination ratio elastic constants, ε xx , ε zz and γ xz are the strains, V f is but higher than the other defect ratios. the fiber volume fraction, V a is the maximum Curvature radius is a typical geometric charac- available fiber volume fraction, V 0 is the initial fiber teristic of composite components, which are widely volume fraction, As is a spring constant. applied in beams, webs, and stiffened plates. The The finite element formulations and validations effect of different curvature radius on manufacturing of the flow-compaction model can be found in Ref.