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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:
committee findings
