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1 Workshop Synopsis and Committee Findings and Recommendations INTRODUCTION The United States spends an enormous amount of money annually to replace or repair deteriorated equipment, machines, and other components of the infrastructure. In the next several decades, a significant percentage of the country's transportation, communications, environmental, and power system infrastructures, as well as public buildings and facilities, will have to be renewed or replaced. Next-generation infrastructure will have to meet very high expectations in terms of durability, constructability, performance, and life-cycle cost. Knowing when to replace facilities and systems or how to prolong their useful lifetimes will also become increasingly important. One way of meeting future expectations will be through improved, high- performance materials, but many barriers to the use of new materials in infrastructure will have to be overcome. Because infrastructure materials must perform in a complex physical environment defined by nonlinear relationships between multiple variables, a thorough and comprehensive understanding must be developed of their long-term performance in a variety of applications and physical environments before they can be confidently deployed in the field. Engineers will be reluctant to apply empirically based design methods to materials used outside the range of their observed performance (assuming empirical data exists at alll , ,1 . A ~ ~ A ~ until their rates of cteteriorat~on can be accurately predicted, measured, and ultimately controlled and their life-cycles determined. Developing design methodologies and/or inspection, monitoring, and replacement strategies that could significantly extend the life of a complete system would then be feasible and would yield corresponding savings to society. BACKGROUND The Civil and Mechanical Systems Division of the National Science Foundation (NSF), recognizing that a major barrier to the development and deployment of advanced infrastructure systems and materials has been the difficulty of simulating long-term service conditions or collecting and analyzing data over Tong periods of time, launched an initiative in December 1997 on the Long Term Durability of Materials and Structures: Modeling and Accelerated 3
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4 RESEARCHAGENDA FOR TEST METHODS AND MODELS Techniques (the Durability initiative). The aim of this initiative was to promote the development of innovative short-term laboratory or in-situ tests for making accurate, reliable predictions of the Tong-term performance of materials, machines, and structures and provide engineers with reliable data for using and specifying new infrastructure materials. Because this knowledge base involves many disciplines at varying levels of maturity, NSF requested that the National Research Council (NRC) conduct a reconnaissance-level assessment of the simulation-modeling and accelerated-testing methods that are being used, or potentially could be used, to determine the Tong-term performance of infrastructure materials and components. Under the joint auspices of the Board on Infrastructure and the Constructed Environment and the National Materials Advisory Board, the NRC established a committee of 10 renowned scientists and engineers to plan and organize a two-day workshop on the subject. The committee decided the focus of the workshop should be on computational modeling and accelerated physical testing, the two primary ways of simulating long-term service conditions. Extensive research in these areas that has been done in other fields (e.g., aerospace, biomedical devices, nuclear weapons) could also be applicable to the determination of the life-cycle performance of infrastructure materials. The objectives of the workshop are listed below: define the objectives for infrastructure-based research that would use accelerated testing and computational simulations to determine life-cycle performance assess the state of the knowledge base to identliFy gaps and overlaps in research activities establish outcome-oriented metrics for setting research priorities identify promising lines of research and collaborations ORGANIZATION OF THE WORKSHOP The Workshop to Develop a Research Agenda for Test Methods and Models to Simulate Accelerated Aging of infrastructure Materials was held on August 24 and 25, 199S, at the NRC in Washington, D.C. In addition to the committee, the workshop was attended by 25 experts from academia, government, and industry who were chosen for their familiarity with life-prediction and accelerated-testing methods and represented a broad range of disciplines and perspectives. The first morning of the workshop was devoted to five prefatory presentations. The first afternoon and second morning of the workshop were devoted to discussions of life-prediction methodologies and accelerated-testing techniques, respectively. To maximize the interaction among the diverse perspectives represented at the workshop, participants were divided into five subgroups of experts from a variety of material disciplines and application areas. Two members of the committee were assigned to each subgroup. Each subgroup
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WORKSHOP SYNOPSIS AND COMMITTEE FINDINGS AND RECOMMENDATIONS was requested to define objectives for life prediction and accelerated testing, identify useful methods for applying these techniques to infrastructure systems, and identify potential barriers and limitations. The subgroups presented their findings regarding the state of knowledge and what needs to be done, and in the final, plenary session of the workshop, the committee chair summarized the results of the roundtable discussions. This report summarizes the information presented during the workshop, the summary results of the roundtable discussions, and includes the briefings presented during the workshop. Subsequent to the workshop, the committee developed the findings and conclusions, identified research areas that should be pursued, and recommended the framework for a research agenda that could be implemented by NSF. The initial plan for the workshop included an exploration of metrics that could be developed to guide research funding, (i.e., funding priority would be given to activities with the highest probability of improving predictive capability). These metrics were envisioned as measures of the combined potential for improving the knowledge base and the likelihood of success, essentially an "expected value." However, during the course of the workshop it became apparent to the committee that there was not enough time to deal with the issues of metrics in a meaningful way. Rather than do so superficially, the committee chose not to address metrics in this report. However, the committee does believe that this is a potentially fruitful area that should be considered by NSF. The observations, findings, and recommendations for further research that follow are based on discussions facilitated by the workshop and the knowledge and experience of committee members. This report does not purport to be a comprehensive state-of-the-art assessment; rather, it represents the consensus of the committee regarding what was learned at the workshop and is intended to guide NSF in setting research priorities and evaluating proposals received in response to its Durability Initiative. Although the knowledge and participation of the workshop attendees were invaluable for the preparation of this report, the findings and recommendations represent the opinion of the NRC committee that was appointed for this purpose. The responsibility for the final content of the report rests entirely with the committee. COMMITTEE FINDINGS AND RECOMMENDATIONS Rather than highlighting differences, the presentations and discussions at the workshop strongly reinforced the common elements of different applications. Although materials deterioration mechanisms (i.e., the "deterministic" aspect of the problem) may change with different materials, applications, environments, and systems, the computational and analytical tools that provide a basis for predicting performance, lifetimes, and reliability can be adapted to study numerous systems. The presentations and discussions also showed that an understanding of the performance of materials has usually progressed fastest when the material is very well characterized and the relevant property is controlled by a small set of
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6 RESEARCH A GENDA FOR TEST METHODS AND MODELS mechanisms (e.g., semiconductors for electronic devices). Most participants, however, agreed that infrastructure materials tend to be very difficult to characterize because of the large number of degradation mechanisms, the broad range of regional variations (e.g., environments, constituent materials, and construction techniques and quality), and the strong nonlinear interactions that occur between them. in spite of the great improvements that have been made in the fundamental understanding of complex material systems (e.g., concrete), the prognosis for dealing, on a fundamental level, with complexities such as life prediction in real environments are very limited if they are based solely on the capabilities of traditional materials science. Many participants were optimistic about the future of infrastructure materials research because of significant advances in instrumentation and analytical capability on the experimental side and a dramatic improvement in the simulation of material properties on the theoretical side. For example, although still in its early days, an exciting advance on the experimental side that was discussed at the workshop is the potential application of synchrotron x-rays for the nondestructive evaluation (NDE) of engineering materials. Examples on the theoretical side are advances in computational methods and computer capabilities, which provide new opportunities in computational simulation. The workshop participants agreed that the study of complexity has become one of the foremost challenges in materials science, but fundamental research focused on infrastructure appears to be lagging behind other application areas, such as aerospace or biomaterials. This discrepancy was considered more a reflection of resource availability in other fields than of the level of interest within the research community. As a result of the discussions at the workshop and the - 1 · committee's subsequent deliberations, the committee agreed that NSF should develop mechanisms (~) to promote the materials-based issues associated with the life prediction and reliability of infrastructure in order to attract the interest of scientists at the forefront of the study of complexity in materials research and (2) to foster collaborations among scientists and engineers engaged in life prediction and accelerated testing to encourage the transfer of knowledge, methods, and techniques among various fields and applications. One potential mechanism would be for NSF to continue to sponsor multidisciplinary workshops on modeling and acceleratecI-aging testing. These workshops could either be independent events or part of larger conferences on materials science. A corollary problem for the development and deployment of new infrastructure materials that was identified during the workshop is that infrastructure involves many different types of systems and, consequently, very different technical and regulatory communities. If an infrastructure sector is well organized institutionally, technological developments find their way more easily into practice. In some sectors, however, the community is so fragmented that poor communication between research and practice has seriously hindered the deployment of new technology. In some cases, fundamental research is completely disassociated from practice. The committee believes that NSF should evaluate each infrastructure sector and attempt to organize its research across -
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WORKSHOP SYNOPSIS AND COMMITTEE FINDINGS AND RECOMMENDATIONS 7 communities and disciplines so that (~) practical needs can be formulated as research goals and objectives and (2) the results can be transferred smoothly into practice. NSF should investigate organizational strategies to maximize its funding, including the establishment of highly interactive, focused programs that span many physically and scientifically distinct laboratories. NSF should also investigate ways to improve coordination both within its own organization (e.g., between the Engineering Directorate and the Division of Materials Research) and among other federal agencies with similar concerns (e.g., Federal Highway Administration). Life-Prediction Modeling Based on the information collected during the workshop, the committee concluded that a reasonable objective for infrastructure-based research is to develop methodologies for predicting the total and remaining life of a structure. These predictions would enable engineers to construct, manage, and maintain infrastructure at the lowest life-cycle cost. Thus, a useful life-prediction model must be able to (~) narrow the field of acceptable candidate materials for an application; (2) provide a quantitative rationale for the adoption of new materials, processes, or procedures; and (3) provide a basis for formulating maintenance and rehabilitation schedules to increase the longevity of infrastructure systems. improved life-prediction models will require (~) a fundamental understanding of the physical behavior of the materials incorporated into infrastructure applications, (2) models of the processes associated with that behavior, (3) observables (e.g., field experience and accelerated-testing methods) that can be used to validate and refine the models, and (4) methodologies for combining and validating models to estimate the time remaining until a system or structure can no longer meet its performance objectives. The workshop discussions revealed a general agreement that the "root cause" of the deterioration and failure of any system is related to materials and that fault trees, risk analyses, and other related methods should be used to identify the most important degradation mechanisms. Evidence was also presented showing that specific, detailed materials investigations have been (and are being) conducted to quantify the behavior of materials as a function of time, environment, and other factors. However, incorporation of the results of these studies into models that can quantitatively predict the future performance and reliability of complex systems has not been uniform. For example, in the field of light guide fibers, reliability studies have been used to predict fiber lifetimes. There was little evidence presented at the workshop, however, that this is being done in other areas. Many materials studies provide exquisite detail of how chemical and physical changes occur in specific laboratory environments, but these data cannot always be related directly to system behavior in a real-world environment.
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8 RESEARCH AGENDA FOR TEST METHODS AND MODELS Accelerated-testing methods can be used to rank the performance of materials in a real-world system but are not, at present, sufficiently reliable to be used for making system-life predictions. The committee identified this as an area for filcher research. The Electric Power Research Institute (EPRI) has reported considerable success in using life-prediction modeling systems to formulate ~ ~ 11 _ _ 1_ _ 1_ 1 . _ . _ ~ ~ 1 Ran; Ma renau~a~on scneau~es and increase the longevity of infrastructure systems. EPRI's work, however, snout ne ~o~owect up by more traditional materials research on the Tong-term mechanisms for failure. Very often the failure mode is associated with fatigue, but this is not well understood (and thus difficult to predict) for many of the materials used in infrastructure systems. A better understanding of the relationships between the onset of fatigue and remaining system life would be extremely beneficial. The current trend of pushing the real-life limits of many aging systems clearly calls for research on all aspects of fatigue and its relationship to component or systems failure. _ ~/ · fin ,1 1 ~. ~ 1 1 1 1 ~1' ~ The initiation and propagation of other degradation mechanisms (e.g., corrosion, diffusion, erosion, and wear) can also be important. Synergetic interactions that are not well understood can (and do) occur between these mechanisms. NSF understanding these ... .. .. .. ~ , . . should support materials research directed toward combined effects and applying that understanding to quantitative precllct~ons of system life. The three main life-prediction modeling systems discussed at the workshop were mechanistic-based models (both empirical and analytical); constituent-based models; and predictive damage models that include interactions between materials and structures (e.g., the corrosion of coated and uncoated rebars). The workshop presentations and discussions showed that life-prediction capabilities could be improved by state-of-the-art tools in characterization and simulation. Analytical characterization tools are now available that allow the key changes in materials microstructure and composition to be determined at increasingly high levels of sensitivity and resolution. These tools have the capability to determine mechanisms and measure changes at lower levels of degradation (i.e., shorter times at ambient or accelerated conditions). In addition, as computing tools are improved, they should be able to simulate materials performance more accurately with respect to microstructural features, such as anisotropy (e.g., crystallography or grain orientation), nonhomogeneity (e.g., inclusions, phase structure, or grain size), and defect structure (e.g., solutes, dislocations, or grain boundaries). Thus, it may be possible to include more microstructural effects in the performance simulations of systems and capture the effects of changes in microstructure due to deterioration (e.g., wear, corrosion, or loading). Properly constructed computational simulation models can account for the effects of uncertainty not only in materials behavior but also in environmental and other conditions. The workshop discussion revealed that selected "high-end" tools and associated support are available at university. government. --1-1-~ --in =~ ~ and private laboratories and that using or adapting existing capabilities may be less costly and more efficient than acquiring or building new, dedicated facilities.
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WORKSHOP SYNOPSIS AND COMMITTEE FINDINGS AND RECOMMENDS TIONS 9 The development of useful and valid life-prediction models will thus require the following advances: a better fundamental understanding of infrastructure materials and systems, including interfaces and degradation modes · the development of behavioral models of materials and systems that span the continuum from microstructural to total-system performance the development of a standardized database of the characteristics and properties of materials and infrastructure systems a better understanding and definition of the characteristics and effects of the operational environments of materials and systems the development of sensors and test methods for monitoring and testing infrastructure systems during construction and use the design of valid, standardized, accelerated-testing methods and test-bed demonstrations of materials and systems to provide data for the validation and refinement of life-prediction models (see next section) the incorporation of economic models as a basis for accurate trade-off assessments and the determination of total life-cycle costs of implementing a new material or process The committee firmly believes that the successful development of life- prediction models will require an interdisciplinary approach that draws on expertise from a number of fields, including materials science and engineering, structural engineering, and end-user engineering applications. Materials studies should be closely coordinated with system applications, and continuous comparisons of field data with laboratory data should be used to validate results. One way of facilitating this comparison is by using analytical characterization tools to quantify relevant micro structural and compositional aspects of accelerated-testing results and field-returned material. Simulation is another toot for making comparisons; simulated responses (based on materials models) can be compared to measured system responses. Accelerated-Testing Methods Based on the information collected during the workshop, the objective of 1 ~ ~ ~ ~ _ al l ~ 1 ~ 1 ~ the long-term performance accelerated-testlug methods is to accumulate data on and degradation of materials in a time period of, at most, 10 to 20 percent of the expected lifetime of the infrastructure system. For example, accelerated-testing methods must be able to produce reliable data for a one hundred-year period in five to ten years, but preferably in less than two years. The results of accelerated- testing methods could then be used to validate and refine life-prediction models and thus help (~) reveal the performance of new and traditional materials in various service conditions, (2) narrow the field of candidate materials for a
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10 RESEARCHAGENDA FOR TESTMETHODSAND MODELS particular application, (3) screen and characterize new materials and systems, (4) determine the residual service life of existing structures, (5) suggest directions for product improvements, and (6) reduce the legal risk to the design and construction communities of utilizing new materials that have not been fully characterized in practice. Accelerated-testing methods, combined with real-time data and life- prediction models, can also help determine the long-term residual properties of current infrastructure systems. Accelerated-testing methodologies must have the following characteristics: . · faithful replication of the processes that occur in practice, based on a thorough understanding of all of the possible degradation mechanisms, their kinetics, and the effects of their interactions the flexibility to evaluate multiple factors and identify those that should be the focus of future research · the ability to account for scaling effects to ensure that laboratory results reflect true environments the ability to account for the possible effects of the infrastructure application, design, and quality of construction, all of which can significantly affect lifetimes · monitoring of all environmental variables (e.g., temperature, humidity, ultraviolet exposure) and other variables (e.g., age, history, composition, porosity, and crack size) so the sensitivity of different mechanisms to variations in parameters can be determined and competing theories and models can be tested · the ability to identify and track the physical phenomena resulting from degradation (and their interactions), preferably using NDE methods The development of useful, valid life-prediction models will require the following advances: · the development of NDE methods for characterizing the microstructure of materials (e.g., fresh, in-place concrete), the development of microstructure over time, and the growth of any degradation phenomena · the development and standardization of nationally available databases that span all levels of the product chain (e.g., from laboratory to construction) · the development of sufficient fundamental understanding of the damage mechanism to enable the prediction of component life outside of the accelerated-test database Real-time tests in real environments (e.g., outdoors, in viva) cannot be eliminated, however, especially in the last stages of product development. Field tests will also be necessary for validating models and providing definitive data on failure modes that cannot be accelerated.
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WORKSHOP SYNOPSIS AND COMMITTEE FINDINGS AND RECOMMENDATIONS 11 LIMITATIONS AND BARRIERS Life-prediction models and accelerated-testing procedures have the potential to increase the deployment of new materials in infrastructure applications and to improve traditional materials. However, the workshop identified several barriers to using model output or accelerated-test data as surrogates for empirical field observations and experience. Traditionally, the construction industry has been cautious about adopting new materials and practices and has not been a significant force in materials-based research. The discussions identified two related reasons for this: poor integration of the engineering community into materials-based infrastructure research, and concerns about risk and liability. Engineers who design and construct infrastructure are not generally involved with materials research, either in their university training or in practice. Thus, end-users have had little input into materials-based research programs, and the transfer of results to the user groups has been minimal. Practicing engineers have little opportunity or incentive to develop the same level of trust in simulation models and accelerated laboratory tests as they have in their many years of empirical field observations. Because of the consequences of construction failures (legal, financial, and professional) and the engineers' exposure to risk, the validity of models and test methods w~11 have to be proven over a wide range of applications, materials, and environmental conditions before their results will be widely accepted in the engineering community. The government and professional organizations will play major roles in encouraging the acceptance of new materials through the use of life-prediction models and accelerated testing.
Representative terms from entire chapter: