3
A Team Strategy
Individuals from many disciplines confront the challenge to understand the full range of factors surrounding the evolution of micro- and macrostructure of a PMC during its lifetime in extreme environments. For many years, polymer scientists used microstructural modeling and such tools as microscopy, spectroscopy, calorimetry, and sonic analysis to understand the effects of environment and stress on polymer chemistries at the microscale. At the same time, mechanists and engineers applied continuum models at the macroscale to predict the properties of polymer composite structures under test conditions and in simulations of extreme environments. More than a few intrepid souls have attempted to link these two efforts at the mesoscale. Success in this area has been less than satisfactory, but it is hoped that improved partnering among individuals with depth in areas important to this endeavor may improve the results.
A number of collaborations are needed to facilitate understanding. For example, the end users of PMCs, including the designers of components, who come primarily from industry, should interact more with researchers and developers in government and academia. A number of government programs, including DARPA’s Accelerated Insertion of Materials for Composites (AIM-C) program and the Air Force MEANS program, have demonstrated the benefits of such interaction.
Other collaborations are needed at a more fundamental level. For example, the science of polymers must be brought to the mechanics community and the art of mechanics to polymer scientists. Another critical collaboration would link the validation and verification of models. Validation refers to getting the physics right, usually through comparison to test data, while verification refers to getting the math right, usually through comparison to other models. The formation of such teams could move PMC reliability forward and enable the continuing development and insertion of PMCs in critical extreme-environment applications.
Finding: Knowledge from multiple disciplines is needed to understand the evolution of a PMC’s structure during its lifetime.
While the benefits of teaming are clear, there are a number of reasons why it is not done more often. The primary reason is that potential collaborators can so easily conduct individual research—that is, obtain funding and publish papers. Moreover, many have not yet recognized the need to team. However, this lack of collaboration is becoming a huge impediment to the application of many materials.
Traditionally, the use of PMCs in aircraft engine applications was a last resort. Today, PMCs are looked at as a business opportunity that provides product differentiation. These newer applications are generally more demanding and require durability in extreme environments. It is now necessary to collaborate to improve PMC reliability, because the chemical, physical, and mechanistic effects must all be considered together to describe the behavior. Polymers are as interdisciplinary as any other class of materials, and polymer composites are even more so, because they function equally as structures and materials. To the detriment of the field, the disciplines of those working in it have long been segregated.
The present paradigm (Figure 3-1) in structural durability prediction methods for PMC material systems creates a disconnect between (1) the chemists and materials researchers who develop new systems and evaluate their molecular behavior, (2) the mechanicians who develop structural durability models and evaluate materials’ structural capabilities, and (3) the designers and fabricators who coordinate information, data, and models from the chemists and mechanicians as they design and fabricate components for applications in extreme environments.
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In most cases, PMC chemists and materials researchers focus their modeling efforts on material development, processing, chemical evolution, and mechanisms of damage in system constituents (fiber, matrix, interfaces, oxides, etc.) at the micro and nano levels. End-use requirements are usually only vaguely known.
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Mechanicians focus their modeling efforts on the behavior of material systems, initial material stress states from processing, damage processes/progression, and structural durability of both the constituents and the overall system on both the macro and micro levels. They have a slightly better understanding of end-use requirements.
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Using proven design methods (based on metallic components) and information from the other two groups of experts, designers and fabricators focus on component-level issues such as form, fit, and function.
Recommendation: To successfully address the complexities of predicting the performance of PMCs, organizations should assemble interdisciplinary teams with experience in chemistry, polymer physics, materials, processing, mechanics, testing, component and system design, and application of PMCs in extreme environments.
IMPLEMENTATION STRATEGIES
One way to overcome the reluctance to form teams with members from disparate fields may be to establish more complex performance goals that need expertise in all the fields to succeed. If such goals could be established, the very proposals for meeting them would need to be drawn up by interdisciplinary teams and evaluated on the basis of common goals. A dramatic advance in structural durability prediction methods for PMC material systems will require the cross-pollination of models across different fields (Figure 3-2). This paradigm will require close communication between the collaborators, probably through workshops, meetings, the Internet, telecommunication, and other new methods of communication. At least one level of shared understanding among the disciplines is required, but two or three levels would be better.
GOALS FOR IMPROVED TEAMING
One of the most important goals of teaming is to develop a modeling approach that can replace the empirical knockdown factors currently used in PMC design. The complexity of polymers and their composites, combined with the lack of effectively integrated teams tackling common problems, leads to design decisions based on brute force knockdown factors (Figure 3-3). Because the effect of the interaction between environmental and loading conditions on the performance of the polymer matrix over very long times cannot be explicitly tested, often the only test that is run is a short aging test with one environmental parameter. During this test, changes in key properties such as strength are noted. However, while designers understand that coupled mechanisms and longer exposures modify properties further, they lack a coherent physics-based modeling strategy to make decisions. Designers ultimately resort to material parameters that have been knocked down by a factor that may be either very conservative or otherwise inaccurate.
Empiricism must be replaced by accurate mechanistic modeling for many levels of damage. It is highly desired to correlate measured properties, in the form of markers, indicators, or symptoms, with meaningful conditions in the PMC. An equally important goal is to ensure that evolution is considered over the entire lifetime, from conception to death. Any such approach must include modeling the manufacturing process to understand the starting state of the material. This modeling might take into account residual stresses, initial surface and interface conditions, and other factors and would serve as the basis for understanding damage progression (i.e., evolution) and the resulting constraints on service life. Degradation mechanisms in PMCs must be understood in terms of fundamental chemical and physical mechanisms to understand material microstructure evolution.
It is critical to develop mechanistic models that range from chemical kinetics to structural dynamics. Integrating existing modeling approaches into a holistic modeling approach is a key goal. To do this, science-based multiphysics models must be implemented in structural design methods. The goal is a history-based, time-dependent reliability prediction. If experiments are designed hand-in-hand with modeling, they can be optimized to adequately inform the models.
Finally, it is vital to determine the rates of degradation in light of underlying mechanisms so as to gain a platform for accelerated testing. Accelerated testing is a central component of any durability program. Experimentalists are needed on the team to develop accelerated test methods that simulate the long-term behavior of PMCs. Eventually, additional modeling is essential for the proper interpretation and analysis of accelerated test data.
Phase I of such an implementation would use existing data to start the development of more effective models.1 The first steps are to find holes and to identify needed parameters and then to provide this information as feedback to database developers (Phase I in Chapter 5). An additional task is to identify and develop processes (blind testing, for example) for life prediction models that can evaluate material performance. In Phase II, modelers and designers would form interdisciplinary teams to fully
develop the needed models and strategies to replace knockdown factors with integrated, mechanistic, multiphysics models. This effort would be highly coupled with the development of the materials informatics database described in Chapter 5, which would not only contain all the critical data from chemistry through failure modes but also be accompanied by mining and analytical tools to assist extracting relationships from the data that would form a sound basis for modeling theory.