Novel Multi-scale/Multi-physics Integrated Tool for the Prediction of Manufacturing-Induced Defects in Autoclave Composite Airframe Parts
Navy STTR 2015.A - Topic N15A-T003
NAVAIR - Ms. Dusty Lang - [email protected]
Opens: January 15, 2015 - Closes: February 25, 2015 6:00am ET

N15A-T003 TITLE: Novel Multi-scale/Multi-physics Integrated Tool for the Prediction of Manufacturing-Induced Defects in Autoclave Composite Airframe Parts

TECHNOLOGY AREAS: Air Platform, Materials/Processes

OBJECTIVE: Develop a multi-scale/multi-physics integrated analytical tool, which predicts manufacturing-induced defects due to material, part, tools and processes, which could be utilized directly in the design, analysis, and fabrication optimization of structural composite components.

DESCRIPTION: The use of advanced composites is common in modern aircraft structural components. Benefits of composite structures include reducing the overall weight and life cycle cost of the aircraft. The use of advanced polymer composite materials allows for the possibility of significant reductions in maintenance and fuel expenditures while increasing service life, leading to an overall cost benefit.

Defects are inevitable in any manufacturing process for composite structures. Reduction in the safe operating lifetime of composite structures with defects, compared to pristine structures, has shown that the presence of manufacturing defects is critical for determining component reliability. Even though damage mechanics is a well-established field with pre-existing analysis and methodologies to provide a basis for evaluation of composite response with induced defects, current approaches do not include the influence of manufacturing induced defects at the design stage. The current practice in most industry is to set thresholds for defects as accept/reject criteria. For instance, the aerospace industry rejects parts found to have more than 2% void volume fraction. In some cases, knockdown factors are applied based on empirical data relating defect densities to performance parameters such as stiffness and strength. This situation needs improvement by using modeling and simulation of the manufacturing process, accounting for tooling, machining and assembly in order to quantify the resulting "material state" of the manufactured part.

An innovative way to improve aircraft composite parts reliability is to perform research to identify methods of predicting and characterizing manufacturing defects. In order to achieve a proper cost/performance trade-off, it is imperative that a quantitative assessment on manufacturing defects is made with respect to their impact on the desired structural performance.

Currently a number of existing processing models can be used to generate useful composite defect predictions for very simple structures. However, few models can analyze all the major processing phenomena in complex composite components. Another drawback of available models is their use of simplified boundary conditions and/or processing cycles. Regardless of the level of sophistication with which material behavior and processing phenomena are modeled, useful manufacturing defect prediction cannot be obtained without an accurate description of the boundary conditions actually seen by the modelled components.

An analytical tool which identifies important processing parameters in an autoclave process, such as component internal temperature, resin kinetics, and resin rheology, autoclave pressure and vacuum pressure, and takes these effects into account explicitly would need to be based on stochastic simulations of composite manufacturing. This would allow quantification of process variability as a function of material selection and processing parameters. Optimization decisions could then be made at an early stage. An integrated model would be able to completely characterize system boundary conditions for different setups, including component design details with specific ply drop-offs, small radii curvatures, tool-part interaction, part geometry molding, and bagging conditions. This model would have a multi-scale approach in which manufacturing defect predictions of local models could be used in "global discretization" level models to predict the processing behavior of the largest components. Finally, the analytical tool should be multi-physics so that the chemical, thermal, and mechanical program modules can interact with a central database that will contain a complete description of the system.

The aim of this program is to develop an analytical tool that predicts manufacturing defects, including voids, ply waviness, delaminations, fiber wrinkling, resin starvation/rich areas, and warpage caused from tool-part interaction. The tool will identify the interdependency between processing parameters and part geometries in an autoclave. This tool should include the effects of process tooling, which affects component stiffness, thermal expansion, and friction/contact resistance characteristics. Component defect prediction results will be utilized directly in subsequent structural analysis of airframe components.

PHASE I: Develop an innovative approach for predicting manufacturing defects in thermoset composite airframe structure. Demonstrate the feasibility of the approach by performing initial predictions.

PHASE II: Develop and demonstrate the new analytical tool's capabilities through analysis of an airframe component. Verify and validate the results with publically available test data and a selective coupon test program.

PHASE III: Demonstrate full operational functionality in Navy-supported test scenarios. Transition the multi-scale/multi-physics tool for use with commercially available computational tools to predict process-induced manufacturing defects on Navy aircraft platforms and provide a detailed supportability plan.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The presence of defects on manufactured composite parts is a concern that the aerospace, boat building and automotive industries face. The developed technology could be integrated with commercial software to address improvements on structural design and performance, and will benefit in-service maintenance issues faced by these industries.

REFERENCES:
1. Mesogitis, T. S., Skordos, A. A., & Long, A. C. (2014). Uncertainty in the manufacturing of fibrous thermosetting composites: A review. Composites Part A: Applied Science and Manufacturing, 57, 67-75. doi:10.1016/j.compositesa.2013.11.004

2. Wang, J., Potter, K. D., & Etches, J. (2013) Experimental investigation and characterization techniques of compressive fatigue failure of composites with fibre waviness at ply drops. Composite Structures, 100, 398 � 403. doi:10.1016/j.compstruct.2013.01.010

3. Zeng, X., & Raghavan, J. (2010). Role of tool-part interaction in process-induced warpage of autoclave-manufactured composite structures. Composites Part A: Applied Science and Manufacturing, 41(9), 1174 � 1183. doi:10.1016/j.compositesa.2010.04.017

4. Kaushik, V., & Raghavan, J. (2010). Experimental study of tool-part interaction during autoclave processing of thermoset polymer composite structures. Composites Part A: Applied Science and Manufacturing, 41(9), 1210 � 1218. doi:10.1016/j.compositesa.2010.05.003

5. Johnston, A., Hubert, P., Fernlund, G., Vaziri, R., & Poursartip, A. (1996). Process Modeling of Composite Structures Employing a Virtual Autoclave Concept. Science and Engineering of Composite Materials, 5(3-4), 235-252. doi:10.1515/SECM.1996.5.3-4.235

6. Riddle, T. W., Cairns, D. S., & Nelson, J. W. (2013). Effects of Defects Part A: Stochastic Finite Element Modeling of Wind Turbine Blades with Manufacturing Defects for Reliability Estimation. 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. doi:10.2514/6.2013-1627

KEYWORDS: Manufacturing; Composite; composite manufacturing process; composite manufacturing defects; composite manufacturing predictions; composite process induced warpage

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