Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses can result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, a process modeling methodology was developed and implemented into Sandia National Laboratories' SIERRA/SolidMechanics code. This method can be used to predict the process-induced stresses in any composite structure, regardless of material composition or geometric complexity. However, to develop confidence in these predictions, they must be rigorously validated. Specifically, sensitivity studies should be completed to define which model parameters are critical to the residual stress predictions. Then, the uncertainty associated with those critical parameters should be quantified and processed through the model to develop stress-state predictions encompassing the most important sources of physical variability. Numerous sensitivity analysis and uncertainty quantification methods exist, each offering specific strengths and weaknesses. Therefore, the objective of this study is to compare the performance of several accepted sensitivity analysis and uncertainty quantification methods during the manufacturing process simulation of a composite structure. The examined methods include simple sampling techniques as well as more sophisticated surrogate approaches. The computational costs are assessed for each of the examined methods, and the results of the study indicate that the surrogate approaches are the most computationally efficient validation methods and are ideal for future residual stress investigations.
Process-induced residual stresses occur in composite structures composed of dissimilar materials. As these residual stresses could result in fracture, their consideration when designing composite parts is necessary. However, the experimental determination of residual stresses in prototype parts can be time and cost prohibitive. Alternatively, it is possible for computational tools to predict potential residual stresses. Therefore, the objectives of the presented work are to demonstrate an efficient method for simulating residual stresses in composite parts, as well as the potential value of statistical methods during analyses for which material properties are unknown. Specifically, a simplified residual stress modeling approach is implemented within Sandia National Laboratories’ SIERRA/SolidMechanics code. Concurrent with the model development, bi-material composite structures are designed and manufactured to exhibit significant residual stresses. Then, the presented modeling approach is rigorously verified and validated through simulations of the bi-material composite structures’ manufacturing processes, including a mesh convergence study, sensitivity analysis, and uncertainty quantification. The simulations’ final results show adequate agreement with the experimental measurements, indicating the validity of a simple modeling approach, as well as a necessity for the inclusion of material parameter uncertainty in the final residual stress predictions.
Fiber reinforced polymer composites are frequently used in hybrid structures where they are co-cured or co-bonded to dissimilar materials. For autoclave cured composites, this interface typically forms at an elevated temperature that can be quite different from the part’s service temperature. As a result, matrix shrinkage and CTE mismatch can produce significant residual stresses at this bi-material interface. This study shows that the measured critical strain energy release rate, Gc, can be quite sensitive to the residual stress state of this interface. If designers do not properly account for the effect of these process induced stresses, there is danger of a nonconservative design. Tests including double cantilever beam (DCB) and end notched flexure (ENF) were conducted on a co-cured GFRP-CFRP composite panel across a wide range of temperatures. These results are compared to tests performed on monolithic GFRP and CFRP panels.
Residual stresses induced during forging and welding can cause detrimental failure in reservoirs due to enhanced possibility of crack propagation. Therefore, reservoirs must be designed with yield strengths in a tight range. This report summarizes an effort to verify and validate a computa- tional tool that was developed to aid in prediction of the evolution of residual stresses throughout the manufacturing process. The application requirements are identified and summarized in the context of the Predictive Capability Maturity Model (PCMM). The phenomena of interest that the model attempts to capture are discussed and prioritized using the Phenomena Identification and Ranking Table (PIRT) to identify any gaps in our approach. The fidelity of the modeling approach is outlined and details on the implementation and boundary conditions are provided. The code verification requirements are discussed and solution verification is performed, including a mesh convergence study on the series of modeling steps (forging, machining and welding). Validation activities are summarized, including validation of the displacements, residual stresses, recrystal- lization, yield strength and thermal history. A sensitivity analysis and uncertainty quantification are also performed to understand how variations in the manufacturing process affect the residual stresses.
Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be defined through estimation. The objectives of this study deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. The presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.
Process induced residual stresses commonly occur in composite structures composed of dissimilar materials. These residual stresses form due to differences in the composite materials' coefficients of thermal expansion as well as the cure shrinkage exhibited by polymer matrix materials. These residual stresses can have a profound effect on the measured performance of a loaded composite structure. A material property of particular interest when modeling the formation of damage in composite materials is the mode I fracture toughness. Currently, the standard method of measuring the mode I fracture toughness involves a double cantilever beam (DCB) experiment, where a pre-crack is introduced into a laminate and subsequently opened under tension. The resulting apparent fracture toughness from the DCB experiment may depend upon a coupled interaction between a material property, the mode I energy release rate, and the effect of residual stresses. Therefore, in this study, a series of DCB experiments are completed in conjunction with the solution of representative finite element models to quantify and understand the effect of process-induced residual stresses and temperature variations on the apparent fracture toughness. Specifically, double cantilever beam experiments are completed at three temperatures to characterize three types of specimens composed of carbon fiber/epoxy and glass fiber/epoxy materials: carbon bonded to carbon, glass bonded to glass, and carbon bonded to glass. The carbon-to-carbon and glass-to-glass specimens provide estimates of the composite's fracture toughness in the absence of significant residual stresses and the carbon-to-glass specimens indicate the effect of measurable process induced stresses. Upon completion of testing, the measured results and observations are used to develop high-fidelity finite element models simulating the residual stresses formed throughout the manufacturing process and the subsequent DCB testing of a laminate composed of the carbon/epoxy and glass/epoxy materials. The stress fields and delamination behavior predicted through simulation assist in understanding the trends observed during the DCB experiments and demonstrate the important relationship between experimental and computational efforts.