Rauter, Natalie

Due to the capability of mold injecting manufacturing short fiber-reinforced composites are increasingly in use in the aeronautical and automotive industries. However, a crucial aspect is their spatially distributed material properties induced by the probabilistic characteristics of the microstructure. To predict the structural response of components made of short fiber-reinforced composites by numerical simulation correctly the probabilistic information must be included in the modeling approach. Furthermore, commonly used matrix material is characterized by a distinct plastic deformation even at low stress levels. Therefore, in this work, a modeling approach is proposed that utilizes second-order Gaussian random fields for the representation of the spatially distributed material properties on the component level in the elastic and plastic domain. The modeling approach comprises the cross-correlation analysis of the material parameters describing the elastic-ideal plastic material behavior and a subsequent representation of the parameters by second-order Gaussian random fields. The analysis reveals a complex cross-correlation structure of the parameters, which depends on the window size on the mesoscale and requires the use of suitable numerical methods like the multiple correlated Karhunen-Loève expansion to synthesize the representation of the material parameters. The numerical simulations of tensile test specimens in the elastic and plastic domain predict the structural response under uniaxial loading accurately. The localized plastic deformation of the specimen is observable and meets the experimental validation by tensile tests until failure. Furthermore, the experimental data is used to determine the correlation length. Besides this, the modeling approach is validated by nanoindentation tests on the mesoscale, which reveal the spatial distribution of the material properties. Furthermore, it is shown that the area characterized by nanoindentation tests is 25 times larger than the projected area of the used Berkovich tip. In conclusion, the proposed modeling approach utilizing random fields is capable of representing the localized deformation of short fiber-reinforced composites induced by the probabilistic characteristics of the microstructure. Furthermore, the correlation structure can be derived by numerical simulation on the mesoscale, which can be experimentally analyzed by nanoindentation tests. Finally, the correlation length is an independent material parameter, which can be derived from experimental data.

For the numerical simulation of short fiber-reinforced composites and the correct analysis of the deformation, information about the plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields, which requires information about the correlation structure of all material input parameters. In this study the correlation structure for finite strain elasto-plastic material behavior of short fiber-reinforced composites is analyzed. This approach combines the use of already established procedures for linear-elastic material behavior with a homogenization method for plasticity. The obtained results reveal a complex correlation structure, which is approximated with triangle and exponential correlation functions influenced by the window size. Due to the dependence of the hyperelastic and plastic material parameters on the fiber mass fraction, the strain-energy density function coefficients are cross-correlated with the yield strength of the composite. With this knowledge at hand, in a subsequent work numerical simulations of tensile tests are conducted that cover the elastic and plastic domain and include spatially distributed material properties.

For the numerical simulation of components made of short fiber-reinforced composites, the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches, the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study, numerical simulations of tensile test specimens were conducted utilizing a finite deformation elastic–ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach, tensile tests until failure were carried out experimentally, which confirmed the assumption of the spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations were performed for different values of the correlation length. The numerical simulations endorsed the influence of the correlation length on the overall behavior. For a correlation length of 5 (Formula presented.) (Formula presented.), a good conformity with the experimental results was obtained. Therefore, it was concluded that the presented modeling approach was suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

Indentation tests are widely used to characterize the material properties of heterogeneous materials. So far there is no explicit analysis of the spatially distributed material properties for short fiber-reinforced composites on the mesoscale as well as a determination of the effective cross-section that is characterized by the obtained measurement results. Hence, the primary objective of this study is the characterization of short fiber-reinforced composites on the mesoscale. Furthermore, it is of interest to determine the corresponding area for which the obtained material parameters are valid. For the experimental investigation of local material properties of short fiber-reinforced composites, the Young’s modulus is obtained by indentation tests. The measured values of the Young’s modulus are compared to results gained by numerical simulation. The numerical model represents an actual microstructure derived from a micrograph of the used material. The analysis of the short fiber-reinforced material by indentation tests reveals the layered structure of the specimen induced by the injection molding process and the oriented material properties of the reinforced material are observed. In addition, the experimentally obtained values for Young’s modulus meet the results of a corresponding numerical analysis. Finally, it is shown, that the area characterized by the indentation test is 25 times larger than the actual projected area of the indentation tip. This leads to the conclusion that indentation tests are an appropriate tool to characterize short fiber-reinforced material on the mesoscale.

In this study a modeling approach for short fiber-reinforced composites is presented which allows one to consider information from the microstructure of the compound while modeling on the component level. The proposed technique is based on the determination of correlation functions by the moving window method. Using these correlation functions random fields are generated by the Karhunen–Loève expansion. Linear elastic numerical simulations are conducted on the mesoscale and component level based on the probabilistic characteristics of the microstructure derived from a two-dimensional micrograph. The experimental validation by nanoindentation on the mesoscale shows good conformity with the numerical simulations. For the numerical modeling on the component level the comparison of experimentally obtained Young’s modulus by tensile tests with numerical simulations indicate that the presented approach requires three-dimensional information of the probabilistic characteristics of the microstructure. Using this information not only the overall material properties are approximated sufficiently, but also the local distribution of the material properties shows the same trend as the results of conducted tensile tests.

The present work provides a profound analytical and numerical analysis of the material properties of SFRC on the mesoscale as well as the resulting correlation structure taking into account the probabilistic characteristics of the fiber geometry. This is done by calculating the engineering constants using the analytical framework given by Tandon and Weng as well as Halpin and Tsai. The input parameters like fiber length, diameter and orientation are chosen with respect to their probability density function. It is shown, that they are significantly influenced by the fiber length, the fiber orientation and the fiber volume fraction. The verification of the analytically obtained values is done on a numerical basis. Therefore, a two-dimensional microstructure is generated and transferred to a numerical model. The advantage of this procedure is, that there are several fibers with different geometrical properties placed in a preset area. The results of the numerical analysis meet the analytically obtained conclusions. Furthermore, the results of the numerical simulations are independent of the assumption of a plane strain and plane stress state, respectively. Finally, the correlation structure of the elasticity tensor is investigated. Not only the symmetry properties of the elasticity tensor characterize the correlation structure, but also the overall transversely-isotropic material behavior is confirmed. In contrast to the influencing parameters, the correlation functions vary for a plane strain and a plane stress state.

In recent research on Structural Health Monitoring (SHM) guided waves, especially nonlinear Lamb waves, turned out to be a suitable means for monitoring material deterioration in thin-walled structures. In the corresponding numerical simulations on wave propagation the nonlinear elastic theory by Murnaghan is often implemented, which requires 14 material parameters for transversely isotropic materials. Enhancing an existing linear strain energy potential, a new nonlinear hyperelastic transversely isotropic material model is introduced which reduces the number of independent material parameters to six. In order to verify the applicability of the presented material model with respect to the simulation of nonlinear wave propagation in composite structures, and the generation of higher harmonic wave modes, the existence of a power flux from the fundamental to the higher harmonic mode is investigated analytically and numerically. Analytical considerations show that this power flux exists like in Murnaghan's theory. For the numerical validation the S0–S0 mode pair in the low frequency range is used. Therefore, the amplitude of the second harmonic wave mode is oscillating with increasing propagation distance. This behavior is in excellent agreement with the theoretical prediction. It is shown further, that even for an oscillating behavior the amplitude of the second harmonic mode can be approximated by a linear curve fit over a considerably propagation distance and hence shows a quasi cumulative behavior. Therefore, the introduced material model is an advantageous alternative to Murnaghan's theory to simulate the second harmonic Lamb wave generation due to in composite structures. © 2017 Elsevier Ltd

Im Rahmen dieser Arbeit wird die Möglichkeit der Verwendung der nichtlinearen Wellenausbreitung auf Basis der Generierung höher harmonischer Moden auf Grund von mikrostrukturellen Schäden in Faserverbundstrukturen analysiert. Es wird mit Hilfe experimenteller Untersuchungen gezeigt, dass die infolge zyklischer Zugbeanspruchung entstehende Werkstoffdegradation mit dem relativen akustischen Nichtlinearitätsparameter korreliert. Um die auf mikrostrukturellen Schäden beruhende Werkstoffdegradation und die daraus resultierende nichtlineare Wellenausbreitung numerisch abzubilden, wird ein hyperelastisches Materialmodell für faserverstärkte Kunststoffe entwickelt. Im Gegensatz zu den bekannten Formulierungen aus der Biomechanik werden dabei kompressible Effekte berücksichtigt und die Verwendung der modifizierten Invarianten vermieden. Ferner kann im Vergleich zu der nichtlinearen Potentialformulierung nach Murnaghan die Anzahl der benötigten Materialkonstanten auf sechs reduziert werden. Die durchgeführten numerischen Simulationen bestätigen die Anwendbarkeit dieses nichtlinearen Materialmodells zur Abbildung der Entstehung und Ausbreitung höher harmonischer Moden in unidirektionalen Faserverbundstrukturen bei der Wellenausbreitung entlang einer Symmetrieachse.