John Venables, Strategic Analysis, Inc., and Leo Christodoulou, DARPA/Defense Science Office
Notwithstanding all the improvements made through research on structural materials, damage accumulation through fatigue, creep, or overloads, for example, can lead to highly undesirable engine and/or structure failures in military platforms. For this reason, the Air Force and other branches of the military spend millions each year doing routine inspections and engine tear-downs. In a desire to improve this situation, the Defense Advanced Research Projects Agency (DARPA) has for the last several years sponsored a “Prognosis” program that attempts a new asset management approach based on predicting the remaining useful life (RUL) of aircraft engines, airframes, and helicopter drive trains. To accomplish this, the program focuses on uncertainty management by first exploiting existing sensor technology to define current materials state awareness and then incorporating physics-of-failure models to predict the future evolution of damage accumulation. Such information, along with prior history, measured stresses, etc., are then fed into appropriate reasoners whose RUL estimates are fed to the pilot or mission commander, who in turn can then assess the viability of the platform for the intended mission.
Along with many laboratory tests designed to establish a database of fatigue and creep properties of relevant materials, for example, the program is including numerous spin tests on engine components and low cycle fatigue tests on actual wing panels. By so doing, the physics-of-failure models, state awareness sensors, and state-of-the-art reasoners are combined to test whether the predicted RUL values are consistent with observed lifetimes.
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Session I: Key Issues for Materials State Awareness PROGNOSIS John Venables, Strategic Analysis, Inc., and Leo Christodoulou, DARPA/Defense Science Office Notwithstanding all the improvements made through research on structural materials, damage accumulation through fatigue, creep, or overloads, for example, can lead to highly undesirable engine and/or structure failures in military platforms. For this reason, the Air Force and other branches of the military spend millions each year doing routine inspections and engine tear-downs. In a desire to improve this situation, the Defense Advanced Research Projects Agency (DARPA) has for the last several years sponsored a “Prognosis” program that attempts a new asset management approach based on predicting the remaining useful life (RUL) of aircraft engines, airframes, and helicopter drive trains. To accomplish this, the program focuses on uncertainty management by first exploiting existing sensor technology to define current materials state awareness and then incorporating physics-of-failure models to predict the future evolution of damage accumulation. Such information, along with prior history, measured stresses, etc., are then fed into appropriate reasoners whose RUL estimates are fed to the pilot or mission commander, who in turn can then assess the viability of the platform for the intended mission. Along with many laboratory tests designed to establish a database of fatigue and creep properties of relevant materials, for example, the program is including numerous spin tests on engine components and low cycle fatigue tests on actual wing panels. By so doing, the physics- of-failure models, state awareness sensors, and state-of-the-art reasoners are combined to test whether the predicted RUL values are consistent with observed lifetimes. 3
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4 Proceedings of a Workshop on Materials State Awareness APPLICATION OF MATERIALS STATE AWARENESS TO AIRFRAME STRUCTURES—KEY ISSUES Donald D. Palmer, Jr., Boeing Phantom Works In order to gain an understanding of the issues related to materials state awareness as applied to airframe structures, one must understand the range of materials applied, failure modes and mechanisms associated with these materials, and the benefits and drawbacks of the nondestructive evaluation (NDE) sensing modalities used to assess the state. In addition, understanding of the operational environment, combined with the limitations of modeling approaches, is essential in predicting the future state. From the 1930s through the early 1980s, airframe structures consisted mainly of mechanically fastened aluminum. The key concern was fatigue cracks and the ability to detect them. Although models were developed to predict fatigue crack growth given specific loading spectrums, little attention was paid to the material system other than the presence of the crack. As aging aircraft issues came to the forefront in the 1990s, damage conditions such as corrosion, heat damage, and residual stress received greater attention. With this attention came a greater awareness of the properties of the materials and the impact of the operating environment on material properties. Composite materials, continuous or discontinuous fibers embedded in a resin matrix, began making their way onto airframe structures in the 1970s as a means to reduce weight while compromising little relative to structural integrity. Today, they make up a significant percentage of military aircraft structures and up to 50 percent of the newest commercial airplanes. Initial concerns centered on delaminations introduced during the manufacturing process or from impact damage. Since then, resin porosity, thermal damage, and ultraviolet degradation prompted studies associated with macro- and micromechanical breakdown of the resin, fiber/resin interfacial properties, and fiber breakage. Specialty materials, such as ceramic-based thermal protection systems and polymeric- based observable materials, may not be critical to the structural integrity of the airframe; however, they are critical to the mission performance of the vehicles for which their use is intended. Given this, understanding the material state of these nonstructural specialty materials is important. It is well understood that no one NDE method will tell the entire story about a structure. This is especially true given the wide variety of materials found on airframes today, and is made even more apparent given the range of conditions associated with each material. In some cases, there are no reliable sensing approaches to detect the conditions of interest. In order to fully implement a materials state awareness program, NDE must move from a defect-focused technology area to a properties-based technology area. This creates needs from the sensor development standpoint, especially for cases in which conditions of interest cannot be adequately evaluated. The desire to continuously monitor the state of a material opens up opportunities for utilizing NDE sensors in a structural health monitoring (SHM) capacity. SHM approaches are desirable from several standpoints, including that of reducing maintenance costs and promoting a greater awareness of the materials state. However, there are some roadblocks in the path to implementation. These include sensor technologies incapable of detecting key properties, weight issues associated with the number of sensors required to provide adequate fidelity, limited efforts
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Session I: Key Issues for Materials State Awareness 5 relative to data collection methods and signal processing, and a production/maintenance infrastructure that is resistant to change. A key element of materials state awareness is predicting the future state of the material system. This requires robust models that factor in all key characteristics of the operating environment. Models for fatigue crack growth are well established; however, models to support properties-based assessments are very immature as they relate to impact on a material or structural system. Successful implementation of a materials state awareness program also requires close collaboration between the physicist developing sensor technology, the materials specialist who understands material properties and their impact on the structure, the structural analyst who can identify failure modes and define acceptable limits, and the NDE specialist who understands the measurement principles and applications and would serve as the technology integrator. Often, each of these disciplines operates in a silo, not fully communicating key information required for seamless transition. KEY ISSUES IN MATERIALS STATE AWARENESS FOR AVIATION PROPULSION SYSTEMS Robert Schafrik and Jeffrey Williams, GE Aviation Nondestructive evaluation encompasses sensing techniques that provide quantitative information regarding materials properties. These techniques would not adversely affect the condition of the material being examined. The scope of NDE encompasses material evaluation, component evaluation, and in situ (on-platform) monitoring. In order to accomplish materials state awareness, appropriate NDE methods must be selected on the basis of required functionality and the ability to perform satisfactorily in the application environment. Current fleet management capability is constrained by uncertainty in the current state of the individual aircraft engines. The ability to sense or measure the damage state of an individual part is limited at best. Further, specific part operational capability is not captured with the current lifing process; hence many components are not operating to their life entitlement because the life is based on fleet weighted average missions. Materials in propulsion applications are subjected to severe environments, often at high temperature. Key material degradation modes of interest are fatigue and creep, plus environmental attack from oxidation and hot corrosion. Prime driving forces for incorporating materials state awareness (MSA) into critical propulsion system components include the following: • More precisely estimating the remaining useful life of an individual component based on actual usage in the application environment. The current practice uses a fixed maintenance schedule based on fleetwide statistics and then retires parts based on a hard time limit calculated on the basis of a typical mission profile. • Lower risk application of new materials in structural applications without necessitating extensive field experience.
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6 Proceedings of a Workshop on Materials State Awareness MSA offers considerable advantages to engine fleet owners and operators: • Increasing the sustainability of engine fleets, since maintenance, repair, and replacement decisions are based on the condition of the hardware. Prognosis requires an on-engine assessment of material condition (that is, MSA) to allow an estimation of the useful remaining life of a component by modeling degradation progression. • Facilitating advanced planning of required maintenance actions. Health management uses the prognostic information on an engine-by-engine basis to make decisions about maintenance and logistics actions to minimize cost and maximize readiness. • Minimizing field failures. The key to success in MSA involves a basic understanding of the primary material degradation modes for a component in the application environment; using this knowledge, the appropriate material parameters can be evaluated. This level of understanding exists for certain propulsion material applications, but further study is warranted in several areas, particularly for the advanced classes of materials. The second key to success involves matching sensor and NDE techniques to the MSA requirement in the application of interest. Importantly, a systems approach is needed so that MSA is included as a basic requirement during the product design cycle. During design, a number of considerations for each candidate sensing technique would be taken into account; they include the following: • Inherent limitations and constraints of the sensing method; • Speed, accuracy, and repeatability, along with the capability to quantify anomalies; • Scalability regarding large and small components; • Development and qualification costs of sensors and associated reasoner software; and • Cost to incorporate sensors and their network into the propulsion system hardware, plus operations and maintenance costs throughout the lifetime of the engine. Within the turbine engine, structural components offer a significant opportunity for MSA. These components range from mainshaft engine bearings, to polymer and ceramic matrix composite components, to superalloy turbine airfoils and disks. Initial NDE to characterize the baseline as-manufactured condition of the component is important, followed by methods to monitor in-service condition. In general, during the operation of the engine, the sensor data are analyzed by diagnostic reasoner software to continually evaluate the ability of a component to perform its intended function. This diagnostic system must have a high degree of fault detection and isolation to properly detect material degradation without producing false alarms. As an example, superalloy turbine airfoils that continually operate in a high-stress, high-temperature environment offer a significant opportunity for benefit from MSA; in this case, the degradation modes are dominated by the thermal history of the blade, and hence accurate surface-temperature measurement across the airfoil is particularly critical to MSA success. Research and development opportunities to advance MSA include the following: • Furthering the fundamental understanding of material degradation modes, especially those of advanced materials targeted for production applications; historically this work has not been well funded;
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Session I: Key Issues for Materials State Awareness 7 • Development of in situ NDE techniques that provide technology options to detect changes in the material state by functionality, for example, temperature measurement; • Database storage and retrieval capability for large, persistent databases, including images, and analysis algorithms; and • Secure, reliable network technology, including wireless technology that meets demanding military requirements. In summary, MSA requires a fundamental knowledge of materials degradation mechanisms in the service environment, although empirical-based models can be useful if extrapolation outside the experience base is not crucial. NDE methods must measure physical changes in a material that in turn can be physically linked to the progress of degradation modes. A systems approach is necessary to selecting sensors, developing reasoner software, and designing hardware that can be suitably interrogated by MSA methods. Sensing and inspection technologies are enabling technologies; importantly, sensors must be highly reliable over a long time period in severe environments. Constraints imposed by computing power, data storage and access, and data transmission are also critically important.
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