Applying Materials State Awareness to Condition-Based Maintenance and System Life Cycle Management Summary of a Workshop (2016) / Chapter Skim
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3 Presentations and Discussions
3 Presentations and Discussions
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The special discussion sessions held at the end of the first day and at the end of the workshop are summarized together after all of the presentations, as they focused on crosscutting topics and issues.
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. • Another major roadblock to MSA implementation was inadequate under standing of the primary material degradation modes for a component in 1 James Malas, Universal Technology Corporation, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 2.
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Malas said, and there is still a lot of work to be done. The terminology can be difficult, he noted; for example, he distinguishes between MSA, which aims to characterize the mate rial state, and structural health monitoring (SHM)
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said that, based on Dr. Malas's presentation, the 2007 workshop, which predated the current interest in ICME and related computational approaches, seems to have emphasized NDE and sensing technology.
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One par ticipant suggested that many newer engines and other aircraft subsystems already have embedded sensors, but the issue is fusion of the real-time sensor data with sufficiently reliable historical failure data to make useful decisions about materials degradation and useful subsystem life. Other participants commented on addi tional types of data needed to provide benchmarks against which quantitative NDE (QNDE)
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He asked whether sensor-based monitoring for those kinds of nonstandard external events is done as part of MSA, as the types of material state monitoring that had been discussed so far seemed focused on "standard operating conditions." Dr. Malas responded that MSA includes monitoring for environmental effects such as corro sion and weathering, but the application focus has been on sensing for system life management in operational environments, rather than on detecting single-event conditions that lead to immediate system failure.
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Withers described how impact damage to a compos ite wing must be studied at various scales, using several tools, to understand how barely visible impact damage has affected the material structure and the temporal trajectory of the consequent degradation in material properties under service con ditions. CT and imaging quantification tools allow one to "digitally unpick" the laminated layers one by one and to make virtual cross sections across the layers, so that the damage to individual fibers, laminate structure, and interlaminar interfaces can be examined.
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Withers, University of Manchester, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 7. the much smaller opening at the surface of the wire.
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Withers presented in detail included progressive fatigue damage over a number of fatigue cycles in woven composites (Yu et al., 2014) and fatigue crack growth over time in a titanium–silicon carbide metal matrix composite (Withers et al., 2012)
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3 The website for this network is http://www.ccpi.ac.uk, accessed October 2014. 4 For information on the DREAM.3D architecture, see Groeber and Jackson (2014)
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Achenbach, Northwestern University, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 27.
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He acknowledged that more sophisticated approaches to modeling the evolu tion of structural damage such as fatigue cracking are emerging; for example, he foresees computational mechanics and multiscale modeling, supplemented with experimental information, being used in the future to provide a computational link from microstructure to material properties at the macrostructural level, such as strength, hardness, toughness, cracking, and perhaps even corrosion. These models, together with signals from diagnostic embedded sensors, will, he suggested, also provide a way to monitor the evolution of damage for "system-state awareness," which is sometimes called intelligent system health monitoring.
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This flow diagram reflects the following elements of what Dr. Achenbach called a "structural health monitoring grand plan." (His assessment of the difficulty and time frame for achieving each element is shown in square brackets.)
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SOURCE: Jan D Achenbach, Northwestern University, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 24.
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, and pre-crack fatigue damage; it should account for residual stresses. He acknowledged that, taken together, these challenges are technically demanding and will take time to meet.
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Chin said, because service life, or remaining life, is not a fundamental material property. A former consensus standard, ASTM E632, defined service life as the "period of time during which critical performance properties exceed minimum acceptable values,"6 and Figure 3.3 illustrates how service life would be measured with respect to a minimum acceptable value for one critical performance property.
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Chin, National Institute of Standards and Technology, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 7. rial and how they change but also a quantitative characterization of the end-use environment.
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The NIST team began from the insight that defining the question as outdoor exposure versus laboratory exposure made the problem intractable; they asked how the problem of relating field and laboratory exposures had been addressed in other fields where UV expo sure is a key environmental factor, including biology, medicine, and agriculture. In those fields, she said, a model for total effective dosage was used, so NIST incorpo rated the Total Effective Dosage Model (shown in Box 3.2)
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Chin, National Institute of Standards and Technology, presentation to the Workshop on Materials State Awareness, August 6-7, 2014. was adopted as the basis of an initial consortium on coatings, which ended about 5 years ago, and for two new consortia, one on sealants and the other on polymers used in photovoltaic materials.
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. Based on the inhibition of chloride transport from the surface into the interior of concrete test cylinders, the group estimated that the FLAIR method for delivering the viscosity modifiers increases service life by a factor of 2.7, while adding the viscosity modifiers directly to the mixing water increases service life by only a fac tor of 1.3, Dr.
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; methodologies to determine the remaining service life of infrastructure materials and to guide development and use of sustainable infrastructure materials; and methodologies to ensure the disaster resilience of structures under extreme conditions (specifically hurricanes, tornadoes, and other windstorms)
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Hemker noted in his introduction that his perspective is that of an experi mentalist whose recent work has largely focused on supporting development of physics-based models that fit within the themes of ICME or the Materials Genome Initiative (MGI) , that is, "Materials by Design." In particular, Johns Hopkins has two major DOD-sponsored centers in these areas: a collaborative research alliance with the U.S.
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in models must be both represen tative and descriptive; there is, therefore, considerable merit in splitting RVEs into microstructural volume elements (MVEs) , property design volume elements (PVEs)
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distin guished a hierarchy of volume elements of interest: the volume necessary to define a microstructural feature of interest (the MVE) , the volume necessary to define a material property of interest (the PVE)
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SOURCE: d Kevin J Hemker, Johns Hopkins University, presentation to the Workshop on Materials State Aware R02905 ness, August 6-7, 2014.
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He listed the fol lowing types of experimental measurements that can be used for benchmarking model results: • Tensile characteristics -- Tensile strength -- ocal plasticity maps L -- Texture formation -- eometric and necessary dislocation maps inside grains G • Fatigue characteristics (N = number of cycles to fatigue effect) -- plasticity and the location and neighborhood of local plasticity Nlocal -- initiation and the location and neighborhood of crack initiation Ncrack -- Nfracture and the location and neighborhood of fast fracture • Fracture characteristics -- rack nucleation site and critical load C -- rack propagation path C -- ole of material microstructure in promoting/inhibiting fast fracture R He then turned to how mechanical benchmarking properties can be measured at the mesoscale -- the scale of what he called oligocrystals, or crystalline structures with hundreds of grains but not thousands or millions of grains, as found in macro scale measurements.
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using volume elements with length scales relevant to the application of interest, to try to understand the statistics of different processes that can occur at that scale.
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Physics-Based Mesoscale Modeling of Materials in Extreme Environments D.J. Luscher, Fluid Dynamics and Solid Mechanics Group, Theoretical Division, Los Alamos National Laboratory (LANL)
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SOURCE: D.J. Luscher, Los Alamos National Laboratory, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 2.
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Luscher, Los Alamos National Laboratory, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 3. to a shock wave, where the anisotropy due to differences in grain orientation and size leads to localized hot spots.
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It requires models that can instantiate various homogenization theories and can span length scales from the mesoscale to the macroscale. Critical aspects of the material state to be modeled include texture, porosity, and the influence of the material's processing and deformation history on texture and porosity.
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is an order of magnitude greater than thermal expansion in either the a or the b directions. In re sponse to thermal change, indi idual crystals are pushing and pulling in v interactions with each other, the highly irregular void structure interacts with the stress field, and the binder is not spread uniformly throughout the compounded material.
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Dr. Luscher said that a macroscale constitutive model for engineering analysis has to take texture into account because of the high degree of anisotropy in single crystals and because the consolida tion process itself can induce texture in the bulk explosive that conveys that anisotropy (depending on the consolidation process)
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Luscher noted that the "real meat" of the group's work on the PBX-9502 problem will be to extend the theory instantiated in the model to cover the ratchet growth in thermal expansion. More broadly, he hoped the pre sentation had given the workshop participants a perspective on the breadth of what his group is interested in, the potential breadth of applications for this kind of modeling work, and how his group understands and uses some of the key terms and concepts employed in the mesoscale modeling of material state.
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CBM+: A Smart Predictive Approach Abdel E Bayoumi, Director, CBM Research Center, and Professor of Mechanical Engineering, University of South Carolina Dr.
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Bayoumi, University of South Carolina, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 7. Copyright 2014 CBM Research Center, University of South Carolina, all rights reserved.
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. Data fusion of inputs from a number of condition indicators, tracked by appropriate sensor modalities, provides a system-level health indication and a set of tools for predicting useful life or other system attributes.
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Dr. Bayoumi expanded on the initial effort that the CBM Research Center will undertake in data collection and data fusion for the aircraft usage/health management aspects of the Connected Aircraft initiative.
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. Traditionally, electronic-structure and atomic-scale computational methods have been viewed as useful in determining mechanisms and providing valuable descriptions for problems of materials state and behavior.
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Sinnott, University of Florida, presentation to the Workshop on Materials State Aware ness, August 6-7, 2014, slide 2. Determine mechanisms image reprinted with permission from I
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Dr. Sinnott said that if chemical changes are not an issue and material properties can be assumed as inputs to a model, then a micro-, meso-, or macro-level simulation may only need to be informed by experimental data or quantum-level electronic structure data.
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Hemker that atomic-scale com putations at best provide "a strong suggestion about what the atoms are doing," Dr. Sinnott said the computations are better than that description would suggest, but that the materials modeling and materials engineering communities are not yet sufficiently familiar and comfortable with the strengths and limitations of these computational approaches.
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is a term for van der Waals interactions SOURCE: Susan B Sinnott, University of Florida, presentation to the Workshop on Materials State Awareness, ugust 6-7, 2014.
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Sinnott's presentation described cyber infrastructures and databases and their role in addressing the technical challenges of broader community adoption and application of atomic-scale computational approaches 11 Dr. Sinnott emphasized that the barrier here is not access to the algorithms or the available parameterizations.
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Her objective for this cyber infrastructure is to advance the atomic-scale modeling of materials by increasing the "comfort level" in the user communities with how and when to use the various computational methods and the potentials calculated using them. She described CAMS as providing a "forum for disseminating new atomic-scale methods, educating nonexperts, and acting as a bridge between atomic-scale and complementary modeling communities." In addition to disseminating software codes and other tools for atomic-scale methods, CAMS has run summer schools 12 The homepage ofthe Materials Project is http://www.materialsproject.org/, accessed October 2014.
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He sees an important role for these computational approaches that address the thermodynamics of materials behavior and materials states changes directly. The property volume element as he had dis cussed it seems to him to be a reasonable way to think about when computational methods are appropriate.
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These computational approaches do work well, she said, for systems with just a few, deep minima in the potential energy surface. Because there are so many talented people working in this area, Dr.
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Dr. Plummer asked how the computational approaches discussed by Dr.
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At a corporate level, GE has been doing system health management for a long time, he continued, and at multiple levels. For example, at any given time, GE has about 20,000 aircraft engines in operation, as well as 10,000 flight data recording systems, 9,000 diesel-electric locomotives (GE Rail)
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A final problem or bottleneck for effective health management is that there is no single repository for the flight data downloaded from a given aircraft. Military aircraft have different data repositories at different levels of maintenance, including operational levels and depot levels.
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There is much less health monitoring instrumentation on the C-5, he said, than on an F-18 or F-35. When single-point solutions for improving the engine diagnostics are used -- such as adding a sensor or other monitoring system component; im proving the onboard computer that captures and preprocesses the sensor data; or making a single-point improvement in the ground system for receiving the engine data, doing the analytics, and preparing a report -- these solutions typically run into a roadblock.
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Kolbe's discussion of engine diagnostics for the C-5 aircraft, Dr. Achenbach asked if the data transfer and data management problems could be mitigated by collecting data intermittently rather than with continuous system health monitoring.
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Dr. Achenbach referred to the 15-year strategic plan that Airbus has for intro ducing advanced system health monitoring in its commercial aircraft, which he had described at the end of his presentation, and suggested that it showed how an OEM, being a single company, could move forward in this direction on its own.
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Consortium, particularly the contributions of the MAI BA-11 Team on large aluminum forgings and advanced techniques for measuring residual stresses in structural forgings. The MAI Con sortium of 14 companies was formed in 1999,14 and projects funded under it are required to have focused technical efforts, focused and defined implementation plans, and significant and realistic business cases (Bayha et al., 2002)
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• Reduce number and cost of design iterations • Reduce cost of scale-up SOURCE: Dale L Ball, Lockheed Martin Aeronautics Company, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 8.
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The detailed FEA modeling of the machining step currently simply simulates the removal of material from the worked shape; it does not simulate the action of the machining process on the material properties, including residual stresses.
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.15 The contour data, he 15 Dale Ball, Lockheed Martin Aeronautics Company, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slides 23-26.
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to predict residual stresses and deformations in finished parts; and 16 Dale Ball, Lockheed Martin Aeronautics Company, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 28.
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These kinds of data, he noted, are valuable for optimizing the aircraft structure with respect to residual stresses, strength, and service life requirements. In his closing summary, Dr.
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If a designer asked, for example, about using an aluminum alloy with smaller grain size, higher strength, but lower creep resistance, would that lower creep resistance show up in lower residual stresses in the simulations? Or if designers thought a thinner structure could have better heat-shedding behavior, would that flow down into the design simulations?
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Numerous researchers have studied the impact of life-extension tech nologies on life analysis, including work done at Lockheed Martin on the beneficial impact on service life of compressive residual stresses. However, those benefits are generally not counted toward service life when doing component design; instead, they are taken as balanced against unplanned-for realities of operational life, such as more severe than anticipated usage or increased stresses or loads.
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Because composite materials are, in effect, designed to survive the develop ment of defects or to sustain damage at multiple locations distributed through the material, he said, finding a single defect or point of damage is not the goal when predicting remaining life, as it may be for a homogeneous metallic material. The material state evolution of a composite is not a problem of damage propagation for the majority of the composite's service life.
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better than all of the others in all metrics; the aim is to use them collectively to serve the major objective of reliably predicting remaining service life prior to catastrophic system failure. Efforts that have produced sig nificant recent progress include postmortem NDE, detection methods (which are relatively mature at the macroscale but an ongoing R&D activity at smaller length scales)
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Majumdar asked, when the physics of electrical current flows and of electrical/electronic device performance, for ex ample, are factors in system life, in addition to the physics of mechanical stresses and loads that have been the focus of life prediction frameworks? Life prediction of multifunctional material systems, he emphasized, cannot be done unless the material state evolution of those synergistic and interacting property domains can be successfully modeled.
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Questions and Discussion Dr. Gerhardt asked about the experimental procedure used to determine the re maining service life of the material samples at the specific percentages of service life indicated in the impedance versus frequency graphs presented by Dr.
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He replied that related work is in fact being done by his collaborating colleagues at the University of South Carolina, u sing modifications of atomic force microscopy to measure the electrical proper ties across heterogeneous microstructures -- for example, damaged and undamaged areas. He emphasized that remaining service life and strength characteristics are global (macroscale)
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Warren's presentation focused on the NIST role in pursuing the third National Strategy Goal of four presented in the MGI Strategic Plan: "Facilitate Access to Materials Data." After a brief overview of NIST's mis sion and high-level organization, he said that NIST's traditional role in provid ing standard reference data has defined a niche role for NIST with respect to this third MGI goal. After recounting the history of how this role for NIST has evolved, Dr.
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How well the data resulting from computational methods apply to reality depends on 20 According to Wikipedia (http://en.wikipedia.org/wiki/George_E._P._Box) , the exact quotation is "Essentially, all models are wrong, but some are useful." It appears in print in Box and Draper (1987, p.
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Dr. Warren said that, although he previously believed that understanding materials meant turning materials science into physics, his work over the past several years on the MGI has con vinced him that materials science and facilitating access to materials data have much to learn from both sides: physics and biology.
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He described a variety of NIST activities for working with specific industry, aca demia, and government partners to develop standards, tools, and techniques for the acquisition, representation, and discovery of materials data; for interoperability of computer simulations of materials phenomena across multiple length and time scales; and for quality assessment of materials data, models, and simulations.22 NIST has set up an open-access data repository, which is beginning to accumulate 21 A YouTubeversion of the video cartoon is available from the website of the Institute for Health Technology Transformation at http://ihealthtran.com/wordpress/2013/01/youtube-data-sharing with-bears-great-video-by-nyu-health-sciences-libraries/, accessed December 2014. 22 For more on NIST activities with specific partners, see "The Materials Genome Initiative at NIST," available at http://www.nist.gov/mgi/overview.cfm, accessed December 2014.
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Warren discussed the extent to which compatibility issues would be a problem for users interested in working with both defense-related materials data repositories and the open access repositories that are the objective of the NIST programs. A New Statistical Method for Assuring Mechanical Reliability Stephen Freiman, Freiman Consulting, Inc.
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had to be w 24 Duringthe questions and discussion session following his presentation, Dr. Freiman clarified that the aircraft fuselage windows in question were "double windows" with an outer window designed to sustain high impacts and particulate/precipitation erosion over the aircraft's operational life.
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Freiman said, the NIST team began deviating from the traditional method for estimating probability of failure. That traditional ap proach uses the two-parameter Weibull model, shown in Box 3.6, for deriving the probability of failure by fitting experimental fracture data to the model.
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Other models -- for example, a three-parameter BOX 3.6 Two-Parameter Weibull Model for Probability of Failure ⎡ ⎛ ⎞m ⎤ σ P = 1− exp ⎢− ∫ ⎜ ⎟ dV ⎥ ⎢ ⎝ σ 0 ⎠ ⎣ ⎥ ⎦ P is the probability of failure σ is the fracture stress σ0 is a scaling parameter m is the Weibull modulus, or slope of the probability-strength curve V is the volume (or area under stress) SOURCE: Stephen Freiman, Freiman Consulting, Inc.,presentation to the Workshop on Ma terials State Awareness, ugust 6-7, 2014, slide 10.
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Freiman advised, "and from that select [the model] to use to make your predictions." -- ased on their analysis of the goodness of fit, the NIST team chose to B fit the strength data from the test set of airplane window specimens to a three-parameter Weibull distribution.
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A lthough this may be a new concept in the ceramics-testing world, it is of value as a better alternative than is comparing the total area of the tested specimen set to an estimate of the total area of the population in the universe of components. • Although a two-parameter Weibull distribution often works well for mod eling strength data from the test set, it may not be the best fit to the experi mental data.
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is based on the physics of crack growth, which engineers think they understand. The expression used to fit the data (e.g., the two-parameter Weibull distribution in Box 3.6 or an alternative distribution equation)
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Lindgren began by acknowledging the contributions, to his presentation and to AFRL's MSA efforts, from his colleagues in the Materials State Awareness and Supportability Branch of AFRL and from other AFRL personnel engaged in relevant projects and programs, including the Digital Twin and Digital Thread pro grams, which had been mentioned by others during the workshop. As requested by the workshop committee, his presentation focused on how MSA could affect the Air Force's capabilities for CBM, in the context of fleet sustainability rather than new materials development.
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Service life extension decisions use a risk management methodology, and periodic inspection is still the preferred approach. Air Force propulsion systems have their own safe life approach, codified in Military Standard 3024.
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, sufficiently reliable structural damage characterization with statistical metrics for a typical aerospace system is not now available for any approach; the current Technology Readiness Level is only around 3. Instead, the current state of the art
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. Their service lives have been and continue to be extended, and operational stresses, combined with variable modes of operation and new operational parameters, have further exacerbated that original variability in structural details that are relevant to flaw modes such as fatigue crack initiation and growth.
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A model-driven quantitative representation of material/damage state, including statistical metrics (middle of Figure 3.9) , is produced by applying signal analysis and uncertainty quantification techniques as well as a method for discerning for 3D representation and validat ing microstructure to the data from the NDE sensing technologies (top row of Figure 3.9)
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SOURCE: Eric A Lindgren, Air Force Research Laboratory, presentation to the Workshop on Materials State Awareness, August 6-7, 2014, slide 27.
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• They are examining ways to characterize variance in tailored micro structures and new resonance methods to explore localized character ization of aterial/damage state, particularly localized perturbations in m the resonance signal that indicate nucleation sites associated with crack initiation and/or crack growth.
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• The research strategy of AFRL's Materials State Awareness and Support ability Branch to realize NDE-based characterization is model centric. Demonstration projects have shown the feasibility of this strategy.
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Not only were the costs substantial, he said, but there were also risks that the qualification might not succeed due to the changes that invariably happen when a process is scaled up -- some process changes greatly affect required material properties. When the development and qualification
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Ball said that the team was unable to demonstrate a cost savings for manufacturing cost alone, but if life cycle costs were included, the estimated cost savings with the ICME ap proach were "huge." The large disconnect between manufacturing cost savings and sustainment / life cycle cost savings, he added, was "incredible." Dr. Luscher commented on qualification issues as they affect life extension programs for nuclear weapon systems.
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Schafrik, GE Aircraft Engines (retired) , presentation to the Workshop on Materials State Awareness, August 6-7, 2014.
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As an example, he described how production-scale auto claving to cure composites might be adjusted in situ through the use of material state monitoring during the process. In short, he said, could we do corrective processing by adjusting processing conditions in real time?
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If ICSE and ICME techniques can truncate that time lag, Mr. Lindgren said, and MSA plays a role in understanding the material variability and evolu tion in qualification testing, then there is a very powerful place for MSA in new material qualification processes.
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Day 2 Closing Discussion: Implications of MSA for CBM and Life Extension Decisions Dr. Wadley of the University of Virginia and Jesus M
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Wadley, University of Virginia, and Jesus M de la Garza, Virginia Polytechnic Institute and State University, presentation to the Workshop on Materials State Awareness, August 6-7, 2014.
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Their exchange led to other comments on whether to include the different techniques for finding out about the health of a system (system/structural health monitoring)
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Wadley, University of Virginia, and Jesus M de la Garza, Virginia Polytechnic Institute and State University, presentation to the Workshop on Materials State Awareness, August 6-7, 2014.
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Dr. Wadley asked, "Can that ‘induction period' before false positives decline to an acceptable rate be shortened?
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McGrath spoke about the summary report of the workshop and said that the lists of implications and potential consequences, for both the long-term goal of a "perfected" MSA and the interim improvements in MSA capabilities, would be of value for communicat ing the advances in the field, the trajectory toward future capabilities, and what can be reasonably anticipated if that trajectory continues to receive support. Jeffrey Zabinski of the Army Research Laboratory spoke of the workshop's value for in forming the process by which DOD prioritizes technology investments to give U.S.
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