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Appendix C Technologies for Materials Selection and Design Chapter 3 described how modeling and simulation (M&S) technology can enable the development and integration of a hierarchy of simulation tools into an interactive system design environment, or "virtual proving ground." Without this modeling envi- ronment, the trade-off analyses required to meet Army After Next (AAN) logistical goals and other performance requirements cannot be accomplished within the time and resource constraints the Army faces. Figures 3-l and 3-2 showed that the selection of materials is one of the many engineering considerations required for detailed designs of components and subsystems using this simulation environment. This appendix focuses on the technology and information requirements for extending the "virtual proving ground" approach down to the level of materials selection, and even to the lower level of the design of new (or newly structured) materials. The hierarchical relations in Figure 3-! will always hold: the performance requirements that determine the properties of a candidate material flow down from the higher levels of function and structure in the hierarchy. The duty cyclers) and structural demands of the components and subsystems in which a material is to be used determine which properties are critical for that application. When this structure-function hierarchy is traversed upward, it shows how the performance of a material for a specific use in a component (or subsystem) depends on the material's properties and their interactions with the properties of other materials. To select a material and model its performance for a particular application, the key properties must either be known from previous experience with the material or inferred from other knowledge about the material. Figure C-l, which shows the considerations that feed into the component design level of the hierarchy, shows that there are two opportunities (the two Tower-right ellipses) at which a design engineer can select candidate materials to feed into the modeling of the component and subsystem design and analysis. The first and most expedient opportunity is for the design engineer to have information resources about the physical properties of candidate materials, such as The National Materials Advisory Board of the National Research Council published two studies that cover important aspects of these two levels of materials engineering and design. The first report, Computer-Aided Materials Selection During Structural Design (NRC, l995b), is particularly relevant to the first level of materials selection technologies and the information bases needed to support more extensive application of them. The second report, Hierarchical Structures in Biology as a Guide for New Materials Technology (NRC, 1 994b) investigates the principles and potential approaches for biomimetic approaches to designing innovative materials. 183
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184 REDUCING THE LOGISTICS BURDEN FOR THE ARMY AFTER NEXT Component Design Perfonnance / /Design Performance \ \ Materials Options Requirements / / Options Requirements \ \ _ - - - Over Considerations ~ in retailed resign ~Matenals Selection Information (See Figure 3-2) ~\g Sources and Tools _ - Cnbcal Matenals Properties Desired ~ __ Modeling of Properties from Material Structure and Composition Innovative Structural and Formulation Concepts - FIGURE C- 1 Materials engineering technologies to support system design. materials databases or selection charts. By applying materials selection principles derived from the requirements of an application, the designer can choose the best candidate materials and the best material processing and fabrication techniques and incorporate it directly into the component design being simulated in the virtual testing environment. The second opportunity, depicted at the lowest level in Figure C-l, is used when well characterized existing materials cannot provide the combination of properties re- quired for the application (or more realistically, do not come close enough to the figures of merit for all application-critical requirements). This strategy incorporates knowledge from materials science into modeling environments for designing and controlling the production of innovative materials with specified properties. These new concepts for structuring or formulating materials could yield new alloys, intermetallics, composites with ordered microstructures, and materials with hierarchical structures. Although both of these levels are, to a limited extent, feasible with existing technology, much can be done to improve the enabling materials selection and materials design technologies for solving issues raised by AAN requirements. These technologies have broad applications not only for advanced systems for defense but also for advanced systems for innovative commercial products. Therefore, the Army could leverage its resources by participating in research or application-oriented networks, sometimes as a supporter of basic research, sometimes as an information-sharer, and sometimes as a co- investor in production capacity or a product purchaser. An example of one way that government agencies, including the defense services and agencies, can participate in these leveraging opportunities is the 1995 workshop on strategic materials sponsored by the National Materials Advisory Board (NRC, 1995b).
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APPENDIX C INFORMATION RESOURCES TO SUPPORT MATERIALS SELECTION 185 Designing a component or subsystem involves translating an idea or a market need into detailed specifications for a product. Each stage requires making decisions about the materials to be used. Often the design dictates the choice of materials, but sometimes a new product, or the evolution of an existing product depends on the availability of a new material. A vast number of materials are available to design engineers sometimes 40,000 to 80,000 variations. Standardization reduces the number somewhat, but the continuing appearance of new materials with novel, exploitable properties increases the choices. Materials selection during the design process is very important. For demanding systems, such as a new Army combat vehicle or rotorcraft, the designer will probably begin with materials selection handbooks that contain guaranteed minimum properties for materials that have been used extensively. For example, the Military Handbook V covers materials for which there are extensive information bases about properties and performance. If materials from this handbook are selected, a designer can depend on meeting minimum requirements at various levels of statistical confidence. If a material is not in this handbook, the designer cannot use it for safety-critical systems, such as aircraft. Even if the material could be used, the designer may not have reliable data on the critical properties for the design application. Unfortunately, the designer may be unaware of promising new materials or may not have access to state-of-the-art research data for these materials. How, then, can a designer perform trade-off analyses that consider novel materials or materials for which there is information limited? Databases for Material Properties The Army, as well as the rest of the U.S. Department of Defense, could benefit by supporting and participating in partnerships with industry and academia in assembling databases on novel materials in various stages of development and in ensuring that existing data remains accessible (confidentiality is often an issue). Cooperative programs could be established to determine data on key properties of novel materials and to enter the data into appropriate databases. Databases might be developed for electronic materials, magnetic materials, structural materials, and so on. For the structural materials database, data could be linked with processing details, fabrication scales, product forms, and probable time frames for the availability of materials for full- scaTe production. An entry for a new structural material might include the following information: material designation composition ranges · fabrication history (e.g., powder metallurgy, ingot metallurgy, electron beam deposition, etc.) product form (e.g., extrusion, casting, rolled plate, etc.) scale of manufacturing (e.g., laboratory scale in ~ kg castings, pilot scale in I,000-kg Tots, full-scare production) · mechanical properties for various orientations and product forms (e.g., yield strength, Young's modulus, fracture toughness, fatigue data, etc.)
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186 REDUCING THE LOGISTICS BURDEN FOR THE ARMYAFTER NEXT physical properties (e.g., coefficients of thermal expansion, mass density, specific heat, Poisson's ratio, etc.) chemical properties (e.g., corrosion and flammability characteristics) cost (relative to purchase volume) and production timelines if a designer has access to this information early in the design process, he or she can make preliminary decisions concerning "design for reliability" or meeting the criti- cal performance requirements for the application, as well as "design for manufacturabil- ity." The designer may determine that a novel material could be the enabling technology for a particular component or subsystem if particular property data were available within the time frame for making design decisions. Materials databases provide an important contribution to the systems engineering approach to design, materials selection, and manufacturability (NRC, 1995b). Life-Cycle Cost Models Materials designers must invariably make trade-offs among performance, cost, and other requirements. These trade-offs often result in compromises in materials selec- tion and fabrication techniques. For instance, a designer working on materials for an AAN component or subsystem may need materials with high reliability as well as me- chanical robustness, corrosion resistance, and wear resistance. Damage tolerance might be specified by toughness and strength. However, the higher manufacturing and acquisition costs of materials with all of these properties may make them unacceptable in designs for long-term reliability. To make rational trade-offs, design decisions should be based on life-cycle cost rather than acquisition cost. For example, the higher acquisition cost of a more expensive material may be justified by its reduced life-cycle costs be- cause of its high reliability. In addition to databases with property information, various life-cycle cost codes could be developed using today's technology to assist the designer. As the overall system becomes more sophisticated, materials costs usually decrease as a percentage of total system cost. However, selection of a superior, but more expensive, material may be hard to justify unless the potential life-cycle cost savings and performance improvements can be convincingly modeled. A readily available life-cycle cost mode! that could be configured for various systems would give the designer and program manager the information to justify the selection of superior materials for enhanced reliability. Graphical Representations of Materials Properties to Support Materials Selection From the perspective of materials engineering, a material can be characterized by a set of properties, with the value of each property falling within a characteristic range for that material. The range of values possible for just one of these engineering properties can be immense. For example, values for properties such as toughness, strength, modulus, and thermal conductivity can span five orders of magnitude. The performance requirements for a material in a component usually must be specified by more than one of these engineering properties. A simple example that is crucial for AAN systems design is the performance requirement of reducing the weight of components.
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APPENDIX C 187 Simply looking for materials that weigh less is not the answer. What one really means by a "lightweight" material for an application is a material that satisfies the requirements for other properties, such as strength and modulus, but at a Tower mass per volume flower density) than conventional options. Thus, a "lightweight" material must really have a higher "specific strength" or "specific modulus" (the desired property relative to density) (Ashby, 1992~. Even if detailed engineering data on the properties of nonconventional materials were available to designers through materials databases, designers would still need tools for comparing them in terms of the combination of properties required for a particular design (such as the "specific" properties described above for lightweight materials). ~ ~ ~ ~ ~ ~ ~ Or · ~ .~ 1 , · ~ · ~ ~ ~ · ~ ~ . . ~ . ~ . Although materials engineers have long used specific selection charts, designers need graphical tools that can tailor a chart for a set of materials or material classes that can be created from the database, similar to the way charts can be created by using a computer spreadsheet program. This is just one example of how information technology could be used to support design engineers by making materials data more comprehensible, as well as more accessible. Failure Detection as a Performance Option It may be more cost effective to design a self-diagnostic system that can detect impending material failure and trigger preventive maintenance than to invest in a superior material. The systems engineering approach envisioned in this report would clarify the trade-offs among these design options. Materials selection technologies should be used in conjunction with a virtual testing environment in which physical properties at a lower level of a structure or function are explicitly linked to potential failure modes at the next higher level. This is the basic principle of "physics of failure" modeling. MODELING AND SIMULATION TECHNOLOGY FOR DESIGNING NEW OR SPECIALIZED MATERIALS In a Tong-tenm forecast of science and technology for Army applications, the STAR 21 study highlighted two major trends. The first was materials design through computational physics and chemistry. The second was increased use of hybrid materials, that is, materials with controlled microstructures consisting of components with different compositions (NRC, 1993a). Directions in material science since the STAR 21 study are bringing these two trends together, which has greatly expanded the range of opportunities. The STAR 21 study discussed computational approaches to materials design primarily in terms of atomic-scale properties (e.g., crystal lattice effects, interatomic interactions, and molecular bonds in energetic materials and polymers). The properties of a bulk material that are determined by physicochemical interactions at this scale (measured in Angstroms, or 10-~° m) are sometimes called "intrinsic" properties. In addition to progress in analyzing and modeling how intrinsic properties arise from the atomic-scale structure of a homogeneous material, much more has been learned about bulk properties that depend on how components of the same or different materials are structured at larger scales. (The bulk properties of a material that depend on how
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188 REDUCING THE LOGISTICS BURDEN FOR THE ARMY AFTER NEXT homogeneous components of a material are put together, rather than on the intrinsic properties of these components, are sometimes called "extrinsic properties.") Two-phase composites, in which a discontinuous phase consisting of one material is embedded in a matrix (organic, metallic, or ceramic) of another material, are relatively simple but still present a challenge to modelers. Research on materials with different structural patterns at varying spatial scales features whose unit sizes range from microns (Io-6 m) to nanometers (10-9 m) has shown that these hierarchically structured materials offer an astonishing range of nonconventional combinations of bulk properties. Much of the insight into hierarchical structures originated in work on natural materials, hence the importance of biomimetic ("imitating biology") research to this area of materials engineering. Data on heterogeneous structured materials and hierarchically structured materials are particularly important to AAN needs; these materials often offer much higher values than conventional materials for "specific properties" of interest to a component or subsystem designer (e.g., combining high values for strength and toughness with low density). The Army has been active in sponsoring and promoting research in these areas of materials science, including the current strategic research focus on biomimetic materials. Cooperative partnerships in research and application-development networks fostered by the Army Research Office, the Army Research Laboratory, and the various Army research, development, and engineering centers will continue to be productive ways for the Army to leverage science and technology resources while keeping abreast of new research and applications. The Army should consider making two more steps to ensure a Tong-term contribution to meeting AAN requirements. First, as particular materials requirements for AAN system concepts are identified, they should be communicated to the materials research and application networks in which the Army participates. Better answers will be forthcoming from the materials community if the Army requirements are stated in unambiguous performance metrics. In short, AAN system designers should interact even more closely with materials researchers and developers to ensure that the Army takes advantage of new applications and materials. Second, the Army should consider "materials by design" in terms of the emerging knowledge of how structure at all scales affects material properties.2 The goal of modeling intrinsic properties of a bulk material based solely on the physics and chemistry of atomic-scare interactions is too simplistic for most materials that are likely to be of interest. Models must be able to simulate features at larger scales, whether random (e.g., grain size and orientation, effects of structural discontinuities during processing) or controlled structures (ranging from matrix composites to hierarchical architectures). Just as the single "mother of all models" approach failed to produce an adequate environment for designing systems through mission and system simulations (see Chapter 3), it would also be inadequate for designing materials. Both will require distributed systems that can be used iteratively to address structure-property relations at multiple levels. 2A significant stride in this direction will be taken if the Army approves a proposed strategic research objective on "armor materials by design" as discussed with the committee by the Army Research Office.
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APPENDIX C 189 REFERENCES Ashby, M.F. 1992. Materials Selection in Mechanical Design. New York: Pergamon Press. NRC National Research Council). 1993a. STAR 21: Strategic Technologies for the Army of the Twenty-First Century. Technology Forecast Assessments. Board on Army Science and Technology. National Research Council. Washington, D.C.: National Academy Press. NRC. 1994b. Hierarchical Structures in Biology as a Guide for New Materials Technology. National Materials Advisory Board. National Research Council. Washington, D.C.: National Academy Press. NRC. 1994c. Workshop Report on Critical Issues for the Aerospace Specialty Materials Industrial Base. National Materials Advisory Board. National Research Council. Washington, D.C.: National Academy Press. NRC. 1995b. Computer-Aided Materials Selection During Structural Design. National Materials Advisory Board. National Research Council. Washington, D.C.: National Academy Press.
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