Tool to Predict Transient Spatial-Temporal Boundary Conditions for Processing Autoclave-cured Composite Parts

Navy SBIR 21.1 - Topic N211-008
NAVAIR - Naval Air Systems Command - Ms. Donna Attick - navairsbir@navy.mil
Opens: January 14, 2021 - Closes: February 18, 2021 (12:00pm EDT)

N211-008 TITLE: Tool to Predict Transient Spatial-Temporal Boundary Conditions for Processing Autoclave-cured Composite Parts

RT&L FOCUS AREA(S): General Warfighting Requirements

TECHNOLOGY AREA(S): Air Platforms; Materials / Processes

OBJECTIVE: Design, develop, and validate an analytical tool to accurately predict the local transient thermal and mechanical boundary conditions during the processing of composite parts within an autoclave.

DESCRIPTION: Autoclaves are widely used to process and cure high quality parts for composite structural components used on aircraft. This high quality is possible due to the autoclaveís high internal pressures and ability to apply high temperatures in excess of 350įF such that the intended resin systems can cure. When these assumed conditions are not met, defects such as porosity and poor fiber consolidation occur [Ref 5]. Autoclave systems are designed with these conditions in mind, but since part thickness, tool geometry, and part location can vary from run to run, the local conditions cannot be guaranteed. The conditions within are driven by the capabilities of the autoclave: air temperature, air flow and physical part geometry interaction with the tooling surface and vacuum bagging [Ref 6]. This environment is thus governed by a variety of physical interactions and requires a multiphysics modeling tool to accurately capture the boundary conditions experienced by the composite parts.

Modeling and simulation to predict composite part quality within an autoclave requires a coupling of the local boundary conditions with the mechanics and chemistry going on within the composite. The temperature of the part at the bag as well as the tooling surface is critical to couple with the cure kinetic models [Ref 4]. Boundary conditions are usually assumed in simple models where the air temperature throughout the autoclave is believed homogenous and the part is experiencing perfect hydrostatic pressure regardless of location or tool geometry. Without accurate boundary conditions, anticipating defects or reducing internal stresses and spring-back is very difficult to predict accurately [Ref 1]. Current modeling capabilities often utilize simplistic two-dimensional models or assumed boundary conditions [Ref 7]. The means to expand that to more complex three dimensions are commercially available but limited. Accurate modeling of the environment within the autoclave can be computationally expensive and require responsive software simulation integration to capture multi-physics interactions [Ref 2]. Hybrid models utilize a variety of physics including Computational Fluid Dynamics (CFD) and heat transfer which then feed into the boundary conditions for cure kinetic models. These models also require experimental validation from actual autoclave runs which can be difficult since each commercial autoclave system is unique [Ref 10]. This is where data fusion from in-situ monitoring can be used not only to validate but to tune a model for predicting boundary conditions. The goal of this SBIR topic is to provide a means to integrate both modeling capabilities as either a single tool or an add-on to existing software. This software tool will have validation from real-life autoclave runs and the means to be adapted to various autoclave systems per the userís need.

Many of the current methods for running parts in an autoclave come from simple models, best practices and extensive thermal surveys to confirm that the material has cured as intended. Autoclave runs completed in early acceptance testing feature parts that are outfitted with a multitude of sensors to measure temperatures throughout the part and tool. The temperature and pressure cycle is then adjusted until the desired cure profile is achieved throughout the part. Temperature ramp rates and early cycle dwell periods are critical to removing volatiles from the liquid resin and facilitating flow. Final cure temperatures and duration confirm that the resin has solidified and reached complete cure at every location in the composite part. Design engineers must intelligently place multiple tooling and parts within the autoclave such that the air flow is not blocked [Ref 3]. Any great change to this process must be preceded with another thermal survey and part inspection teardown. Having a multiphysics software tool capable of modeling the systemís boundaries would reduce the amount of expensive autoclave runs needed to start production. It can also provide production lead time flexibility since the operator can intelligently position multiple parts within the autoclave and still achieve the correct cure profile for each. When there are indications from Non Destructive Inspection (NDI), the software can then be run to assess problem areas within the cure as well as provide the operator feedback that the autoclave may be out of its designed thermal and pressure specification. The benefits of this software tool will allow engineers faster entry into production, gain flexibility in production stream through curing various part combinations and more rapidly assess problems that would later manifest themselves as part defects. Software simulations tools will reduce the number of test runs required for opening up a new composite part production run. They will also enable greater production scheduling freedom through process modeling of part layouts within autoclaves, which will make production more adaptive and save scheduling time and thus cost.

PHASE I: Propose a concept of a multiphysics tool that can address the local non-uniform transient thermal and mechanical boundary conditions accounting for conditions within an autoclave. Demonstrate the concept and quantify the effects of non-uniform environmental conditions via a numerical simulation of airflow temperature, pressure and heat transfer for a simple composite part during autoclave processing.

PHASE II: Enhance and develop the proposed concept prototype tool to address the manufacturing of composite parts containing inserts, complex curvatures, and thick laminates exceeding 1.5 inches in thickness. Validate the prototype tool by comparing simulation results to a live autoclave run containing a variety of composite parts and tooling with select geometries. Capture transient thermal and pressure distributions through in-situ monitoring to be then compared to simulation results. Demonstrate the ability to use this prototype tool coupled with a cure kinetics model for a chosen material system. Verify that this prototype tool can be used on a variety of autoclave systems and part/tool load-outs. Provide the developed prototype software tool for the Navy to use.

PHASE III DUAL USE APPLICATIONS: Transition this software tool to the program and production. Optimize this tool for difficult-to-process parts and layouts that have historically hindered production due to defects and warpage from incorrect autoclave heating.

The product outcome of this SBIR topic has extensive applications for companies producing autoclaved composite parts as well as other industrial processes that require the controlled enclosed heating and pressurization of a product. Software simulations tools will reduce the number of test runs required for opening up a new composite part production run. They will also enable greater production scheduling freedom through process modeling of part layouts within autoclaves. This will make production more adaptive and save scheduling time and thus cost. Secondary applications extend to any enclosed processing of a product using convective heating and external pressure. This includes, but is not limited to, heat treatment of metal, ceramic, and glass products as well as baked goods.

REFERENCES:

  1. Baran, I.; Cinar, K.; Ersoy, N.; Akkerman, R. and Hattel, J. "A review on the mechanical modeling of composite manufacturing processes." Archives of Computational Methods in Engineering, 24(2), January 20, 2016, pp. 365-395. https://doi.org/10.1007/s11831-016-9167-2
  2. Dumont, F.; Fröhlingsdorf, W. and & Weimer, C. "Virtual autoclave implementation for improved composite part quality and productivity." CEAS Aeronautical Journal, 4(3), September 2013, pp. 277-289. https://doi.org/10.1007/s13272-013-0072-1
  3. Maffezzoli, A. and Grieco, A. "Optimization of parts placement in autoclave processing of composites." Applied Composite Materials, 20(3), June 2013, pp. 233-248. https://doi.org/10.1007/s10443-012-9265-8
  4. Mesogitis, T.; Skordos, A. and Long, A. "Stochastic simulation of the influence of cure kinetics uncertainty on composites cure." Composites Science and Technology, 110, April 6, 2015, pp. 145-151. https://doi.org/10.1016/j.compscitech.2015.02.009
  5. Potter, K. "Understanding the origins of defects and variability in composites manufacture [Paper presentation]." Proceedings of the 17th International Conference on Composite Materials. Edinburg, United Kingdom, July 27-31, 2009. http://www.iccm-central.org/Proceedings/ICCM17proceedings/papers/P1.5%20Potter.pdf
  6. Potter, K.; Campbell, M.; Langer, C. and Wisnon, M. "The generation of geometrical deformations due to tool/part interaction in the manufacture of composite components." Composites Part A: Applied Science and Manufacturing, 36(2), February 2005, pp. 301-308. https://doi.org/10.1016/S1359-835X(04)00150-2
  7. Sreekantamurthy, T.; Hudson, T.B.; Hou, T.-H. and Grimsley, B.W. "Composite Cure Process Modeling and Simulations using COMPRO (Registered Trademark) and Validation of Residual Strains using Fiber Optic Sensors [Paper presentation]." 31st Technical Conference of the American Society for Composites (ASC), Williamsburg, VA, United States, September 19-22, 2016. https://ntrs.nasa.gov/search.jsp?R=20160012030
  8. Svanberg, J. and Holmberg, J. "Prediction of shape distortions, Part I: FE-implementation of a path dependent constitutive model." Composites Part A: Applied Science and Manufacturing, 35(6), June 2004, pp. 711-721. https://doi.org/10.1016/j.compositesa.2004.02.005
  9. Svanberg, J. and Holmberg, J. "Prediction of shape distortions. Part II. Experimental validation and analysis of boundary conditions." Composites Part A: Applied Science and Manufacturing 35(6), June 2004, pp. 723-734. https://doi.org/10.1016/j.compositesa.2004.02.006
  10. Weber, T.; Arent, J.-C.; Munch, L.; Duhovic, M. and Balvers, J. "A fast method for the generation of boundary conditions for thermal autoclave simulation." Composites Part A: Applied Science and Manufacturing, 88, September 2016, pp. 216-225. https://doi.org/10.1016/j.compositesa.2016.05.036

KEYWORDS: Composites; autoclave; simulation; computational fluid dynamics; heat transfer; processing

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