9

Conclusions and Recommendations

This report describes a number of practices associated with identifying and mitigating corrosion of steel in contact with earth materials throughout the life cycle of infrastructure. The practices do not necessarily represent state of the art. Corrosion protection practices among industries differ, with some industries adopting a corrosion allowance approach (the geo-civil industries) and others adopting a corrosion avoidance approach (the oil and gas pipeline industries). The different practices are often driven by necessity, but inertia can prevent improvements in practices. It is always challenging to adopt new practices based on the best available science and technological developments, and advances in one industry are not translated easily to another. The spatially and temporally complex and heterogeneous subsurface environment makes it impossible to completely characterize the subsurface, and so it is difficult to accurately predict when, at what rates, and by which mechanisms corrosion will occur. Researchers and developers in industry and academe attempt to improve knowledge and practice related to corrosion, but they often are reliant on limited decades-old corrosion-related data (Romanoff, 1957) and random corrosion data referenced to subsurface environments. Additionally, practices are often driven by standards used for efficiency and reproducibility but that might be derived from standards developed for other purposes. Industries and different disciplines within an industry use inconsistent vocabularies and do not routinely share data related to system design and performance.

The oil and gas and the geo-civil industries have different corrosion-related challenges. The oil and gas industries cannot realistically perform comprehensive site assessments for the entire lengths of infrastructure. Corrosion is recognized as an important failure mechanism, infrastructure is designed to protect against corrosion, and corrosion protection systems (e.g., cathodic protection [CP] systems) are monitored. Geo-civil industry infrastructure designs, on the other hand, are driven by the need to withstand loads and hazards such as earthquakes and floods. Far less consideration is given to failure due to corrosion of buried steel. Design in the geo-civil industries is based largely on the expectation that corrosion will occur and either (1) extra material is incorporated into steel cross sections or (2) treatment or protection is added to the steel to inhibit corrosion for the design life of a structure. Failure due to corrosion is not expected in the typical infrastructure design life, and so corrosion generally is not monitored. A vulnerability of both industries is that changing conditions that affect corrosivity, corrosion mechanisms, and corrosion rates are not accounted for in design and are not monitored during service.

This chapter presents a set of recommendations intended to improve understanding of buried steel corrosion, corrosivity of the subsurface, and decision making related to subsurface characterization, infrastructure design, monitoring, and operation and maintenance. The recommendations are necessarily visionary in nature

and will require those with interest in and responsibility for corrosion of buried steel to think differently than is common in current practice. The committee contends, however, that visionary approaches are necessary to enable improvements in knowledge and practice related to site characterization, design, and monitoring. Without such improvements, practitioners will continue to rely on possibly overly conservative practices and high factors of safety based on sparse empirical evidence to compensate for high levels of uncertainty and few data to validate models. Such practices regularly result in safe infrastructure but perhaps at higher economic cost than necessary to achieve optimal performance.

There is a common need among industries and specific disciplines to reduce uncertainties at each phase of the steel infrastructure life cycle so that risks can be better understood, modeled, mitigated, and monitored, resulting in better and more efficient infrastructure design, construction, and management and increased welfare and safety for the nation. To address this need, conclusions and recommendations are presented in the following themes:

• consistent terminology and common lexicon,
• multidisciplinary research,
• comprehensive longitudinal experimentation,
• data analytical techniques,
• decision support systems (DSSs),
• opportunistic data collection, and
• development of a data clearinghouse.

Although a number of the recommendations build off each other, they are not provided in any order of importance, and many of the recommendations could be implemented in parallel.

IMPROVED COMMUNICATION THROUGH CONSISTENT TERMINOLOGY

The committee that produced this report did not expect the complex deliberations it experienced; after all, practice in multiple industries is driven by numerous standards and guidelines based (presumably) on knowledge gained from research and experience. However, the committee discovered that its members from different disciplines and industries sometimes spoke using the same words but with different meanings that have been generated within their respective silos of practice. They found that “common knowledge” might not be common to all industries, and it was often supported by too little data. Imprecise language could exacerbate misconceptions about corrosion and corrosivity.

To deliberate effectively, the committee found it essential to define a common vocabulary and to constantly check for consistency of its use throughout the preparation of this report. As examples, “corrosion potential”—an electrochemical term (see Box 2.1)—was used by some committee members to suggest a likelihood of corrosion; the scales at which “pitting” occurs (i.e., the size of what is considered a “pit”) was defined differently among committee members; and the definition of “soil” was a source of confusion early in the study process, as was the fact that soil is a multiphase electrolyte of interest consisting of solids, liquids, and gases. Until agreement was reached about terminology to be used in this report, discussions were confusing, and draft text was ambiguous and even contradictory. With common terminology, discussions were more productive, and conclusions drawn from them were made with greater (and more justifiable) confidence.

Just as the committee had to take a multidisciplinary approach in its deliberation, the broader technical communities that address corrosion need to apply a multidisciplinary approach to understand corrosion of steel in subsurface environments. This means that fields such as geotechnical engineering, structural engineering, earth science, materials science, hydrology, metallurgy, corrosion engineering and modeling, geophysics, geochemistry, and microbiology all need to inform a complete understanding of corrosion and subsurface corrosivity. However, there is limited communication among practitioners and researchers between these disciplines and between industries with interest in understanding, detecting, or protecting against the corrosion of buried steel infrastructure. Knowledge is not transferred, and, poor decisions may be made as a result of miscommunication. Benefits could

be realized by the larger community of corrosion scientists and engineers, researchers, and practitioners in all the relevant industries, and industry stakeholders—including the public—with improved communication.

Recommendation 1: Standards-making bodies from different industries, in collaboration with the public agencies with responsibilities related to buried steel infrastructure, and researchers interested in understanding and preventing buried steel corrosion should develop a common lexicon with precise definitions associated with corrosion of steel and the characterization and monitoring of subsurface environments in which steel is buried or placed.

More technically precise terminology will better convey issues related to corrosion of buried steel. Increasing communication and collaboration between disciplines and industries would facilitate attainment of common goals such as better understanding of the corrosivity of a subsurface environment, better prediction of corrosion and corrosion rates, and more effective design, construction, and management of buried steel infrastructure. However, the technical communities that need to collaborate often use different vocabularies to refer to the same concepts, or the importance of some concepts is not recognized. A common lexicon is a first step to sharing knowledge and advancing practice.

Agreeing on and using a common lexicon might seem a trivial recommendation, but achieving this goal will be difficult because of entrenched vocabulary usage. Nonetheless, until all use terminology with a common understanding, intellectual silos and silos of practice will persist and opportunities to advance innovations across disciplines or from research into practice will be limited. Professional societies (e.g., the Association for Materials Protection and Performance, the American Association of State Highway and Transportation Officials [AASHTO], and ASTM International) might collaborate to develop this lexicon. Because standards-making bodies already have influence in the public and private sectors, their collaborative development and dissemination of a common lexicon would help ensure that the individual technical communities they serve will incorporate the vocabulary into their work.

MULTIDISCIPLINARY RESEARCH

Engineers who design and conduct site characterization investigations are rarely knowledgeable about corrosion mechanisms, and corrosion engineers are often unfamiliar with complexities of the soil–groundwater–gas electrolyte. Even fewer engineers are familiar with subsurface microorganisms and how their presence influences corrosivity. No individual expert from any sector should be complacent about assumptions regarding the likelihood and occurrence of corrosion of buried steel. Corrosion protection will be more effective with improved understanding of corrosion and the factors that contribute to a corrosive environment rather than routine application of higher factors of safety. Improved understanding will yield better tools and standards, better practices, and, ultimately, more sustainable infrastructure. Given the complexities of the subsurface environment and the numerous factors that contribute to corrosivity, improved understanding of corrosion mechanisms and rates for buried steel will require research undertaken using a different approach than that which has been applied to research to date.

Increased interaction between, for example, corrosion scientists and practicing geotechnical engineers may help practitioners advance from the use of overly simplistic models to more sophisticated modeling techniques to improve corrosion prediction and management capabilities. Box 4.1 describes the successful application of multidisciplinary and multisectoral communication and collaboration during the forensic investigation of the failure of the Leo Frigo Memorial Bridge in Wisconsin. That investigation and identification of the necessary remediation required the combined specialty knowledge of structural and geotechnical engineers, hydrogeologists, geophysicists, CP specialists, corrosion engineers, microbial testing experts, and those with expertise in chemical analysis of fill and soil materials. No single individual could have identified the problem or solutions without the expertise of the others. Box 9.1 provides another example of a large-scale successful multidisciplinary effort.

There is a need for public agencies, industry groups, and academe with interest in or responsibilities related to corrosion of buried steel to formalize collaborative efforts to identify and facilitate multidisciplinary research for improved prediction of, protection against, and monitoring of the corrosion of buried steel. Primary goals of such collaborative multidisciplinary efforts include increasing understanding of how multiple ground conditions

contribute to corrosivity and corrosion mechanisms and translating fundamental research discoveries into practice. Multidisciplinary research in corrosion science would expose current researchers and practitioners to different ways of thinking and would provide educational opportunities to students at both the graduate and undergraduate levels. Decision making at every stage of the buried steel infrastructure life cycle can only be optimized if the knowledge from many disciplines can be effectively synthesized. This necessitates the formation of multidisciplinary teams of experts to conduct research. Such teams should include geotechnical and structural engineers, metallurgists, materials scientists, hydrologists, geochemists, geophysicists, microbiologists, and others. Topics to be explored include better ways to characterize the subsurface, combining geophysical, geochemical, hydrological, and microbiological techniques; the combined effects of different soil properties on corrosivity; and the ground response to a changing climate and its effects on corrosivity. Soong et al. (2020) predicted rapid and deep soil warming over the twenty-first century, estimating a global mean soil warming of 2.3 ± 0.7°C and 4.5 ± 1.1°C at 100-cm depths for two different greenhouse gas concentration trajectories. Increased temperatures will accelerate corrosion-dependent chemical reactions and will change the distribution of microorganisms and their rates of activity. Other examples of research are provided later in this chapter.

There are a variety of ways that multidisciplinary research might be facilitated. Two mechanisms are described here: formal partnerships between sectors, and multidisciplinary research centers.

Partnerships

Multidisciplinary research could be supported through the organization of formal partnerships between industry and academe, between private- and public-sector entities, and between government agencies and academic research facilities. Such partnerships between these sectors can result in the development of creative technical solutions,

the translation of research concepts into practice, the development of new standards, and the strengthening of the workforce. At present, research is supported by industry or government to improve understanding of the corrosion of buried steel, but these tend to be ad hoc, focused on a specific industry sector and problem, and focused on a specific discipline or approach. The support of individual research projects remains important, but formalized programmatic-level collaborative efforts that support more than a single small-scale research project could benefit all involved. One example is Manufacturing Institutes,¹ which are industry, academe, and government partnerships created to address manufacturing issues. The institutes are funded by federal programs and through company membership dues. The inclusion of practitioners as team members in such partnerships helps to ground research in practical realities. Practitioners in both the private and public sectors benefit from the accelerated translation of fundamental research discoveries to practical applications. University researchers benefit from increased resources (e.g., funding, access to field sites, infrastructure, and data) and the opportunity to pilot innovations in the field. Students are exposed to disciplines beyond their major fields of study, have opportunities to participate in research on practical problems, and can build professional relationships to improve future job prospects. Civil engineering students with greater exposure to geophysics, for example, will better understand electrical properties of soils and the theories behind site investigation methods—a topic taught often only briefly in junior-level soil mechanics classes. Exposure to a wider array of topics helps develop professionals with a better understanding of what is possible, the significance of different types of data, and when problem solving requires additional expertise.

Multidisciplinary Research Centers

Another possible direction for facilitating multidisciplinary research is the development of multidisciplinary research centers. Several models for multidisciplinary research centers currently exist within the National Science Foundation (NSF). Once example is the NSF Science and Technology Centers: Integrative Partnerships program (NSF, 2021b), which advances interdisciplinary discovery and innovation among academic institutions, national laboratories, industrial organizations, and other public and private entities in any area of science and engineering. Another is the NSF Industry-University Cooperative Research Centers program (NSF, 2021a), which “generates breakthrough research by enabling close and sustained engagement between industry innovators, world-class academic teams and government agencies.” NSF Engineering Research Centers (ERCs) are another type of support offered for multidisciplinary research. ERCs invest specifically in research that can be scaled up to technological solutions and applied in industry. These are typically 5- to 10-year programs based on a particular research theme, and they support research, teaching, and community outreach. The program has resulted in the formation of hundreds of spinoff companies, the development of new technologies and granting of hundreds of patents, and the support of thousands of undergraduate and graduate students (NSF, 2020). The U.S. Department of Defense funds the Multidisciplinary University Research Initiative (MURI) program, which “supports research teams whose research efforts intersect more than one traditional science and engineering discipline.” MURI projects could be used as models for corrosion-focused centers. While the costs associated with multidisciplinary research centers can be large, benefits associated with advances in this field would also be large, given that metallic corrosion is estimated to cost the United States 3–4 percent of the U.S. gross domestic product (Koch, 2017).

COMPREHENSIVE LONGITUDINAL EXPERIMENTATION

A number of physical, chemical, and microbiological attributes of the soil environment can be related to corrosion: the type and grain size of the soil; the compaction and pore space; and the wetness, resistivity, ionic content, redox potential, oxygen concentration, pH, microbiology, and temperature. Data from statistically sound, long-term multivariate experiments that involve observations from steel buried in the subsurface make quantifying the fundamental relationships that control corrosion rates possible. Romanoff (1957) described one of the few such experimental studies on which the corrosion community relies, but conclusions drawn from those data are problematic because the soil environments in those tests were not thoroughly characterized, burial depths and

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¹ See https://www.themanufacturinginstitute.org (accessed July 7, 2022).

exposure times varied, climate conditions were reported as averages, many soil properties were measured off-site, and the statistical design of the experiment was weak (de Arriba-Rodriguez et al., 2018). The Romanoff (1957) data need to be supplemented with better-controlled longitudinal experiments in which the same properties are repeatedly measured.

Recommendation 2: Coordinated groups of multidisciplinary researchers, supported through commitments from private- and public-sector organizations and agencies with interest in or responsibilities related to buried steel infrastructure, should conduct comprehensive, long-term experiments to quantify corrosion rates and mechanisms associated with multiple variables on steel buried both in controlled and in carefully characterized natural subsurface conditions.

Comprehensive, long-term multivariate experiments (i.e., those that lead to conclusions regarding the synergistic effects of subsurface properties) need to be performed to observe the factors that contribute to corrosion and how those factors affect corrosion rates. Investigations need to allow multiple observations in the first 5 years to capture changes in corrosion rates when they are greatest, and observations 25 years or longer to capture how those rates attenuate over the service life of infrastructure. The investigations should include laboratory-based experiments with controlled initial and boundary conditions, as well as field-based experiments with extensive soil and hydrologic characterization and monitoring. Studies on buried plain carbon steel are needed, as are experiments on galvanized, aluminized, and polymer-coated steel, the long-term behaviors of which, when buried, are not well known. The latter samples (metallicized and polymer coated) would be tested using longer time frames such that degradation of the protection followed by corrosion of the underlying steel can be observed. Understanding the corrosion mechanisms likely under different conditions is also important because different mechanisms may have implications related to infrastructure decision making and management. To this end, the data collected through this effort should lead to a common validation dataset that can be used for benchmark purposes. They can then be used in a probabilistic manner to predict infrastructure reliability and to assess priorities for decision making and management.

The experiments should be designed to extract the influences of physical and chemical soil properties, soil water and gaseous phases, and soil spatial variations, and to capture the soil microbiology. Different approaches applied during the same experiments—for example, monitoring electrochemical testing and exhuming coupons for destructive testing—would benefit comparisons and integration. The experiments are intended to provide information on the performance of buried steel from an inventory of sites. Initial and emergent steel conditions will be related to climate, topography, drainage, anthropogenic activity, and details of the subsurface. An inventory of sites needs to be identified reflective of conditions that may be encountered in practice. Measurements and observations needed to characterize the subsurface include gradation, maximum particle size, Atterberg limits, pH, resistivity, salt content, organic content, redox potential, water content and degree of saturation, soil-water characterization curve, humidity, temperature, and alkalinity of the soil surrounding the metal element. Likewise, experiments should document the effects of climate change on corrosivity and corrosion of buried steel infrastructure. Descriptions of the spatial and temporal variations of these properties that may occur within the dimensions of the metal sample are also needed. Properties relating to the risk of microbially influenced corrosion (MIC) should also be quantified and monitored throughout the study. Some of the test procedures are under development and some are described within existing standards and recommended practices.

Experimental results could contribute to a reliable reference database useful to (1) identify the most relevant properties of the subsurface for corrosion rates, (2) quantify the synergistic effects of subsurface properties, (3) assess current corrosion-rate predictive models, and (4) develop corrosion models with less uncertainty in their predictive capabilities. The results will allow more strategic design of subsurface characterization and monitoring activities and inform decision making. Robust results from long-term experiments will enable designers, owners, operators, and managers to focus resources on assessing and monitoring the spatial and temporal variations of those properties with the largest impact on corrosivity and corrosion rates at a given site, thus being able to more efficiently design, construct, and manage safer and more resilient infrastructure.

Federal public agencies responsible for infrastructure management and hazard prevention and mitigation (e.g., U.S. Bureau of Reclamation and U.S. Army Corps of Engineers) could partner with public agencies with long-term funding to support longitudinal studies. Alternatively, a collection of industry groups could commit long-term funding. A good example of a long-term collaboration includes the Geosynthetic Institute (GSI,² originally the Geosynthetics Research Institute), which was founded in 1986 and still exists at the time of this publication (2023). The GSI is a consortium of organizations engaged in the manufacturing, design, supply, and installation of various types of geosynthetics.³ The institute includes more than 70 members including federal and state governmental agencies, facility owners, designers, consultants, quality assurance/quality control organizations, testing laboratories, resin and additive suppliers, manufacturers, manufacturer representatives, and installation contractors who pay annual dues that sustain the institute. The GSI has developed and transferred knowledge, resources, and standards needed for the geosynthetics industry to evolve and has facilitated applications of geosynthetics in the construction industry. Longitudinal studies related to corrosion of buried steel might similarly be supported by a consortium of industry groups and state and governmental agencies.

It may be possible to leverage resources and take advantage of already established experimental sites such as those managed by various state transportation agencies to monitor corrosion.⁴ Site conditions at those installations are measured and observed over time as are conditions of buried metal samples, but the installations were established for specific applications and existing data are insufficient for the types of long-term experiments recommended here. Measurement types and techniques, the properties and characteristics of the metal samples, and the subsurface conditions differ at the sites. However, existing data from these sites might inform the design of longer-term experiments, as could data found in the existing literature from laboratory experiments, and measurement of corrosion under controlled conditions. Preliminary analyses of these data would help identify data gaps. A review of the different practices would enlighten the subsurface characteristics that are most important and need to be included in plans for comprehensive and coordinated longitudinal experiments.

DATA ANALYTICS

Numerous methodologies to characterize subsurface corrosivity have been developed for specific applications (e.g., mechanically stabilized earth [MSE], soil nails, piles, culverts, pipelines; see Table 6.5), but many of those methodologies are based on a single measured property such as resistivity (NRC, 2009). Only some methods may consider the influence of multiple properties (multivariate approaches; see, e.g., Table 6.4). These multivariate approaches attempt to weight the effects of various properties on corrosivity, but the weighting factors are based primarily on judgment rather than on robust testing and modeling. None of the existing approaches incorporate all potentially relevant properties, and some include properties that may be irrelevant. Additionally, the present approaches do not describe comprehensively the synergies between subsurface properties, the value of which was recognized following presentations at the committee’s workshop (e.g., presentation by Jennifer McIntosh of the University of Arizona; see Appendix B). There is a need for better understanding of the individual and combined physical phenomena that result in corrosion of buried steel, and until data from longitudinal and multivariate experiments are available, systematic examination of existing data may be useful to identify statistically important relationships among various properties and with corrosion and corrosion rates.

Recommendation 3: Researchers should use advanced data science techniques on available and new data to determine systematically the statistically important contributions of individual and combined subsurface properties to corrosivity in different subsurface environments.

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² See https://geosynthetic-institute.org (accessed July 7, 2022).

³ Geosynthetics are used in environmental, geotechnical, transportation, and hydraulic engineering. They include porous geotextiles, impermeable geomembranes, reinforcement geogrids, drainage geonets, and clay layers in/on other geosynthetics, among other materials.

⁴ These include Caltrans, the North Carolina Department of Transportation, the Florida Department of Transportation, the New York State Department of Transportation, the Nebraska Department of Transportation, the South Carolina Department of Transportation, and the Wisconsin Department of Transportation. The British Columbia Ministry of Transportation and Infrastructure and the Canadian National Railway have also established sites.

There is a need to pursue modeling approaches (for both characterization and performance modeling) that are rooted in improved physical understanding of the phenomena. Longitudinal and multivariate research as described above will provide the basis for that improved understanding. However, researchers and infrastructure designers and managers could better target their resources now from systematic consideration of data from previous investigations and as new data are regularly collected. This would inform better targeted site characterization, infrastructure design, and monitoring, as well as the research needed to better understand the science behind the relationships between the physical properties and corrosion. Data analytical techniques (e.g., cluster analysis or Bayesian theory; see Chapter 8) can be applied to currently available datasets and to new data from longitudinal experiments as they become available (see Recommendation 2). These techniques should be used to investigate relationships among properties, and between properties and corrosion rates. Given enough data, machine learning techniques can be applied to identify previously unrecognized relevant subsurface properties or synergies between different subsurface properties.

In addition to understanding the relationship of properties already related to corrosion of steel, data analytical techniques may help to identify relevant subsurface properties that are not traditionally or regularly used to characterize corrosivity. For example, MIC has been attributed as a cause of failure of buried steel infrastructure (Abedi et al., 2007; California Public Utilities Commission, 2019; Kiani Khouzani et al., 2019; Sempra, 2019), but only 5 of 12 examined classification and rating schemes in Table 6.5 include measures of sulfate-reducing bacteria (SRB) or sulfides (which may indicate the activity of SRB). This lack of testing for susceptibility to MIC is likely because it is not possible to correlate numbers of particular microorganisms with the prediction or diagnosis of MIC (see Chapter 6). Furthermore, Chapter 3 describes temperature as a subsurface property that controls reaction rates, the abundance of microorganisms, and microorganism activity rates. The relationship between corrosion and temperature will be particularly relevant for retaining walls or in shallowly placed steel but less an issue for steel at greater depths. However, temperature is not considered in any of the 12 different classification and rating schemes examined in Table 6.5.

Although Chapter 2 describes numerous experimental studies that have measured corrosion on buried steel across a number of climates, these studies, to the committee’s knowledge, have not been systematically “mined” for data to assess the relationship between temperature and corrosion and corrosion rates, or for their relationships to MIC. Given changing climates and the higher likelihood of many geographical locations to experience temperature extremes, such information could be valuable. Similarly, Little et al. (2020) reported that more than 2,000 papers on MIC had been published in the previous 25 years that describe anecdotal failures associated with MIC as well as laboratory and field testing conducted under varying conditions (e.g., natural microbial populations versus pure cultures of a single microorganism; natural electrolytes such as seawater, estuarine water versus enriched laboratory media that did not approximate any natural electrolyte; and varying temperatures, exposure durations, and metallurgies). The result is a collection of independent observations that have not produced a predictive capability for any material–microorganism–metal substratum. The collective data for MIC are extensive and could be systematically examined for relationships directly related to MIC (e.g., assimilable nutrients, relationships between electron donors or electron acceptors and aggressive or inhibiting anions). The results will provide an integrated approach to predict MIC that is based on the total environment and not the identification of specific putative microorganisms.

Improved estimates of corrosion rates will result from analytical approaches that (1) consider all relevant subsurface properties, (2) apply data-driven weighting factors to relevant subsurface properties, and (3) calculate the synergies between the relevant subsurface properties. However, data analytical approaches alone cannot improve basic fundamental understanding of the underlying physical processing influences, and advanced predictive modeling will only be improved with improvements in physics-based modeling. The results of successful experiments will direct the future development of new characterization methodologies and ultimately inform enhanced ability to anticipate failures, estimate remaining service life for existing facilities, and incorporate efficient corrosion management practices into designs.

DECISION SUPPORT SYSTEMS

The fundamental mechanics of corrosion are the same for the pipeline and geo-civil industries, as is the need to make decisions that prioritize actions and investments where they are most impactful. However, decisions related to site characterization are often made in an ad hoc manner or following specific industry standards. For example, the geo-civil industries conduct site investigations to determine the mechanical and hydraulic properties needed for design and analysis of foundation systems, global stability, drainage, and problems that involve transport, but few site characterization protocols guide proper data collection for characterizing corrosivity and corrosion modeling. The same can be said for management decisions concerning previously buried steel assets. Decisions based solely on individual past practices or industry-specific standards do not benefit from the experience of other industries or new innovations.

A DSS is a tool that guides decision makers through alternatives. Global positioning system–based navigation systems are examples of DSSs in common use. The systems suggest routes to a requested location based on input from the user (e.g., the desire to avoid certain types of roads, minimize travel times, or maximize fuel efficiency) and incorporate information about historical travel times, road closures, traffic, and construction into suggested alternatives with information about expected travel times (i.e., outcomes). The systems are sophisticated enough to refine the route based on real-time changing conditions (e.g., newly reported accidents). A DSS can be as simple as a two-dimensional flowchart guiding choices between binary options (see Figures 6.6 and 6.7), or it can be a complex digital system connected to multiple input databases that leads a decision maker through numerous options. GeoTechTools⁵ is a DSS developed by the Strategic Highway Research Program of the National Academies of Sciences, Engineering, and Medicine, deployed by the Federal Highway Administration. It is now hosted by the Geo-Institute of the American Society of Civil Engineers (ASCE) and is used in the engineering community to support ground improvement decisions.

Whether a simple flowchart or sophisticated computer algorithm, DSSs for engineers are designed to categorize and rank alternatives based on data, models, design standards, and engineering judgment, and can be used to define the uncertainties associated with specific techniques and methods. For example, to compute corrosion rates from linear polarization resistance (LPR) data, one must assume a certain rate-controlling process (that the corrosion reaction is activation controlled), fit a line to the plot of overpotential versus corrosion current measurements, and determine values for Tafel constants, the surface area, density, equivalent molecular weight, and valance of the metal. These quantities are rated to metal type and, for a galvanized element, whether zinc or base steel exposure at the surface may be uncertain. The element under test must be electrically isolated such that the surface area involved in the metal loss is known. These uncertainties can be revealed or reduced by scrutinizing various aspects of the data (e.g., the measured corrosion potential can indicate whether zinc or steel is exposed at the surface, and soil resistance is indicative of the surface area of the element included with the measurement). Performing an LPR test is a simple matter, but discerning if the data are good requires knowledge and experience. A robust DSS will help to reduce uncertainty by formalizing standard practices and present logical and reproducible sequences of decisions based on existing data. They could be particularly helpful in decision areas that rely on large volumes of data combined with predictive modeling.

Simplified and empirical methods for modeling metal loss, corrosion rates, and performance of protection systems have limitations and are only reliable for particular sets of conditions. Without a common database of reported case histories of failures, it is difficult to assess past performance of given protection systems in given environments and validate models. Deciding which model is best applied for choosing a protection system or amount of steel to add to the infrastructure to account for steel loss for a particular site, depth of burial, specific design details, and other factors could be assisted with the use of a DSS. In theory, a single DSS could support decisions through all stages of infrastructure design life, but development and implementation of separate DSSs for site characterization and monitoring might be more practical. A site characterization DSS is needed to guide the formulation of site characterization plans that capture the individual and combined subsurface characteristics that affect corrosivity as well as the important aspects of lateral, vertical, and temporal variabilities and the uncertainties

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⁵ See geotechtools.org (accessed July 7, 2022).

associated with those variabilities. Such a DSS would be an improvement over current standard characterization practices in all industries managing corrosion.

The simple DSS presented in Figures 6.6 and 6.7 guides the choice of tests for pH, salt content, and resistivity depending on the gradation of the sample and correlation of those properties given observed conditions. That DSS only includes standard tests for a few properties, and only those developed by AASHTO and the Texas Department of Transportation. Test standards have been developed by other state transportation agencies and promulgated by various agencies or industry groups such as the U.S. Environmental Protection Agency, ASTM International, the American Water Works Association, and the Soil Science Society of America. Many regionally or industry-developed test standards could be useful but are likely unknown outside the region or industry for which they were developed. The DSS in Figures 6.6 and 6.7 does not provide information regarding how uncertainties in the results might influence decisions under various conditions. A common, more comprehensive characterization framework and DSS is needed that informs decisions related to subsurface characterization appropriate for multiple combinations of subsurface properties. A DSS for practitioners should outline the minimum information needed to design a site characterization program, and it should provide guidance regarding preliminary field and laboratory tests and spatial sampling frequencies needed based on the natural setting of the site, land use, infrastructure life cycle, surface and groundwater hydrology, and atmospheric conditions. The framework and DSS should then help guide decisions regarding additional characterization necessary to reduce uncertainties to acceptable levels for modeling.

To make its development a more practical exercise, the DSS could be developed in stages, with earlier versions of the DSS guiding decisions about tests needed to characterize the subsurface properties most utilized to model corrosivity (e.g., moisture content, resistivity, pH, chlorides, and sulfates; see Table 6.5). Later versions can be expanded to include guidance regarding promising but less commonly measured properties (sulfides, microbial-related properties, and redox potential). The system should include guidance regarding both laboratory- and field-based methods and should distinguish which laboratory tests are intended to replicate field conditions versus those that do not. Uncertainties associated with each method need to be identified, examples of method application should be provided, and the properties under which the test is accurate should be indicated. This includes guidance regarding how to understand errors in modeling given the disparities between the scales of measurements and the scales at which corrosion is initiated on the steel surface. Guidance regarding how to account for spatial and temporal variation in the surface and subsurface is an important aspect of the DSS that also needs to be incorporated into the system. As the community gains understanding regarding the multivariate controls on corrosivity (see Recommendation 2), the DSS should then be expanded to include guidance informed by those controls. Likewise, new test methods based on a multidisciplinary understanding of the subsurface should be incorporated into the DSS as their results are understood.

As the characterization DSS is developed, a second DSS based on risk-informed decision making (i.e., informed by the likelihood and severity of negative impacts) should be developed to inform management actions and investments. This second DSS should be developed and maintained in parallel or in concert with the characterization DSS so that it uses outputs from the characterization DSS (including present and future uncertainties about the environment in which the steel is buried) as part of its input. The DSS could be applied to risk-based decision making associated with both new infrastructure design and the modeling and monitoring of existing infrastructure. The DSS could provide screening and selection criteria for constructed earth that mitigate steel corrosion (i.e., that control pH, resistivity, salt content, and organics content).

To advance appropriate and useful interindustry utilization of monitoring techniques, standards-setting bodies should work with state and federal agencies and industries to develop a common corrosion management practices DSS. This will require coordinated input, planning, and action of all agencies and organizations with interest in or responsibilities associated with corrosion of buried steel. These groups will need to develop a framework that is able to tie available multivariate information and guide prioritization of actions using risk-informed approaches. The DSS would be based on comprehensive information regarding protection methods (physical barriers and CP systems), the type of environments for which they are well suited, the environments in which they fail, and the combinations of factors within those environments that resulted in the failures. Terminology and descriptions used in the DSS would be drawn from a common lexicon (see Recommendation 1). The system would indicate what coatings are susceptible to microbial degradation (see Chapter 4) and would allow practitioners to input conditions under which the protective system failed. It should be interactive and guide selection of protective design systems by practitioners, given selected inputs (e.g., electrical continuity, depth to infrastructure). The DSS should guide decisions regarding monitoring techniques depending on a number of inputs, including the variable to be monitored (coating defects, corrosion rate, CP effectiveness), the depth and dimensions of the infrastructure, and the risk associated with failure. This DSS would serve the broader community, including smaller organizations (e.g., small water utilities) that may not have expertise in all areas, and would assist the geo-civil industries in improving asset management (see Chapter 7).

INDIRECT OBSERVATION AND OPPORTUNISTIC DATA COLLECTION

Corrosion of buried steel can be monitored directly and indirectly through destructive and electrochemical tests on the infrastructure itself, such as those described in Chapter 7. Alternatively, if the subsurface environment is thoroughly understood and defined, it is theoretically possible to predict which corrosion mechanisms are likely to occur at what rates. While the risks associated with the failure of some infrastructure may support implementation of robust subsurface and infrastructure monitoring programs, such programs may not always be economically feasible. For example, it is not feasible to monitor subsurface properties across hundreds of kilometers in oil and gas projects. It also is not economically feasible to repeatedly expose geo-civil steel infrastructure for direct monitoring. Finally, it is not feasible (or, at present, possible) to quantify all the properties relevant to corrosivity for entire infrastructure systems, and certainly not continuously for the duration of the infrastructure life cycle. However, surface monitoring (indirect observations) and opportunistic data collection could inform where localized site-specific monitoring is warranted. Those data could be used to build a database to inform future research and infrastructure-related decision making.

Recommendation 5: Private- and public-sector infrastructure owners should monitor the land surface for changes that could alter subsurface corrosivity and determine whether localized monitoring of subsurface properties is warranted to maintain infrastructure performance and safety. Surface changes to be monitored include but are not limited to changes in land, land use, and atmospheric conditions that affect surface and groundwater flow, and any asset management decisions by colocated infrastructure managers that might affect subsurface hydrology, geochemistry, microbiology, or the production of stray currents.

Ideally, research and development could lead to future capacity to directly measure corrosivity, corrosion, and corrosion rates. At present, infrastructure managers must rely on indirect measurements to estimate corrosivity and corrosion rates. Because changes on the land surface can affect surface and groundwater flow, permeability, soil saturation, soil and water chemistries, subsurface temperatures, and other characteristics that affect corrosivity, monitoring changes on the surface provides a cost-effective early indicator of possible detrimental changes in the subsurface. Noting changes on the land surface or in management practices would be instructive of when and where more direct measurements are appropriate.

Surface monitoring should include monitoring changes in

• land use, including upgradient land use, installation of pavements, large foundations, or other underground structures, and installation of surface, subsurface, or aerial transmission or pipelines that may produce stray currents (e.g., including from CP);
• land cover, such as transition from rural to urban, and changes in vegetation, such as those that may indicate moisture accumulation;
• installation of upgradient power plants, mining operations, or waste disposal operations that could affect groundwater and soil geochemistries;
• surface water- or groundwater flow or retention, changes at the surface that would alter surface-water flow or retention, or the appearance or disappearance of springs;
• infrastructure conditions such as those that result in the intentional or unintentional release of fluids or change in subsurface temperatures;
• infrastructure or land management decisions such as use of or change in deicing salts on pavements or the application of fertilizers that could leach into the subsurface and increase electrochemical potential or encourage the growth of microbes that influence corrosion;
• changes in construction practices; and
• climate and atmospheric conditions (seasonal and global) that result in changes in temperature and precipitation that in turn affect subsurface temperature, groundwater and the groundwater table, degree of saturation, and saltwater intrusion and that may alter the magnitude or frequency of extreme events.

Based on surface conditions, it would then be feasible to monitor key sites (e.g., a mining operation upgradient from a retaining wall) or to establish site-specific and localized monitoring based on identified corrosion mechanisms, environments, or infrastructural components. For example, if it was learned that MIC is possible at a site, a localized monitoring program such as was established for the new (2021) Frederick Douglass Memorial Bridge on the Anacostia River (R. Poston, Pivot Engineers, personal communication, May 26, 2022) could determine whether corrosive conditions persist.

Monitoring some surface changes can be relatively inexpensive and could even be accomplished from one’s desktop with few computational resources—for example, tracking information about precipitation, surface temperatures, land use changes, traffic pattern changes, and changes in topography that might be publicly available from the Internet. Other monitoring could be accomplished by installing or retrofitting infrastructure with sensors—for example, fitting sections of pavement to monitor the effects of seasonal rainfall in the first few feet of the subsurface. Moisture sensors, resistivity meters, in situ pH sensing with specific ranges, and lysimeters (e.g., those installed at the base of landfills to collect in situ pore water) are available or are in various stages of development and could be incorporated into “smart structures” to monitor for corrosivity (Drumm et al., 2006; Genc et al., 2019; Hinshaw and Northrup, 1991; Lee et al., 2009; Liang et al., 2006; Loi et al., 1992; McCartney and Khosravi, 2013; Taamneh and Liang, 2010). However, understanding the relevance of all this information requires longitudinal research and data not only of the type described in Recommendation 3 but also on topics such as long-term fate and transport and unsaturated soil mechanics (i.e., percent saturation and hydraulic conductivity). Tracking, recording, and recognizing the significance of these and other types of data across infrastructure types will require a systems management approach. A manager of subsurface steel infrastructure might, for example, benefit from knowing that another infrastructure manager changed deicing salts applied to nearby pavement and understanding how the change in salts might change soil and water chemistries and therefore corrosivity.

Recommendation 6: Private- and public-sector infrastructure owners should capitalize on opportunities to record properties of the subsurface and steel in a standardized way when infrastructure needs to be maintained, decommissioned, or replaced.

There are numerous opportunities for opportunistic observation, inspection, and data collection in the geo-civil industries. These opportunities exist when infrastructure reaches the end of a service life or is undergoing

improvements and is partially or completely decommissioned or replaced. At these times, standardized protocols to collect data regarding subsurface properties and infrastructure corrosion should be implemented. Developing and implementing data-gathering protocols at such times could greatly increase data availability. Additionally, if it is noticed that a type of steel component is prone to failure in a particular structure or in certain environmental conditions, monitoring that component type or those conditions might be warranted. For example, during expansion projects when MSE walls are partially deconstructed, samples of galvanized steel reinforcements may be observed as they are exhumed and measurements made to describe the conditions and metal losses. There may be no expectation of performance-threatening corrosion, but if found, retrofit or rehabilitation of the MSE walls may be necessary (Nicks et al., 2015, 2017). Because excavation is costly, infrastructure owners should take advantage of unexpected opportunities to monitor steel, collect subsurface information, and track infrastructure and subsurface changes. Data from fortuitous monitoring opportunities should be systematically saved to inform longitudinal research, DSS, and future decisions for that infrastructure and for buried steel infrastructure more generally.

A DATA CLEARINGHOUSE

There is a general lack of access to data with which to build and strengthen corrosion-related models. As discussed in Chapter 2, engineers addressing corrosion of buried steel rely on limited data published in the middle of the past century (Romanoff, 1957) to predict corrosivity and inform corrosion models. Those data are useful, but their utility is limited. In some cases, other data may exist, but either there is no platform from which those data may be accessed, or the data may be proprietary and not publicly accessible. Researchers; infrastructure designers, owners, and managers; and steel and steel protection manufacturers could benefit from a public-domain data clearinghouse from which standardized data from multiple industries can be queried and combined to better inform empirically based corrosion rate modeling and corrosion prediction capabilities. The ability to mine data and information would inform corrosion-related experimental designs (see the above recommendations) and inform modeling and analysis used for infrastructure-related design and decision making.

Recommendation 7: Industry groups, public-sector agencies with responsibilities related to buried steel infrastructure, and research organizations should coordinate to establish a public-domain data clearinghouse organized around consistent data-recording standards and a common lexicon for secure sharing of data related to the corrosion of buried steel including data on soil environment, corrosion potential and rates, and corrosion monitoring data.

Public-domain cyber infrastructure platforms for engineering data exist in which standardized data are deposited by researchers, infrastructure owners, and industry. These were created to allow access to and use of the data. Some examples are the Natural Hazards Engineering Research Infrastructure DesignSafe-CI, funded by NSF (NHERI, 2022); and the Collaborative Reporting for Safer Structures US,⁶ which is a database of safety information for structural engineers, supported by the Structural Engineering Institute of ASCE. The International Stormwater Best Management Practices Database (BMPDB⁷; see Box 9.2), established in 1996, is an example repository designed to archive field data gathered from the design and performance of stormwater best management practices. Like buried steel, the performance of stormwater systems is influenced by numerous variables, so the BMPDB is a good example framework for collecting data that might inform a corrosion-related database.

Schema for consistent data terminology intended to facilitate data transfer have also been developed, for example, by the Data Interchange for Geotechnical and Geoenvironmental Specialists (DIGGS),⁸ which is a data transfer protocol supported by the ASCE Geo-Institute. DIGGS follows a protocol developed by the Association of Geotechnical and Geoenvironmental Specialists (AGS) and localized for a given region (e.g., New Zealand Geotechnical Society Inc., 2017). The geotechnical data interchange protects and may enhance data integrity and

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⁶ See https://www.cross-safety.org/us (accessed April 5, 2022).

⁷ See https://bmpdatabase.org (access July 8, 2022).

⁸ See https://www.geoinstitute.org/special-projects/diggs (accessed July 8, 2022).

allows transfer of data between stakeholders (e.g., project owners, engineers, and technicians) in a data structure that can be fused and fed seamlessly into processing applications, such as data visualization. Although difficult to implement in the United States because of the diversity of data collection methodologies used by 50 different states, DIGGS is being adopted elsewhere, such as in New Zealand and the United Kingdom. Some platforms were originally developed for research purposes but are growing to serve industry and to move state-of-the-art technologies and knowledge to practice.

Developing a data clearinghouse is a long-term investment for the field of underground corrosion. Other technical communities, such as the biomedical research community, who are more mature in their efforts to create data platforms and are committed to the concept of making data findable, accessible, interoperable, and reusable (known as FAIR data) should be considered (Wilkinson et al., 2016). Experts from appropriate engineering and scientific disciplines, as well as the relevant data scientists, software engineers, information technology specialists, and data curators, should be convened to identify the mission and goals of a clearinghouse. Decisions regarding the type of data resources to be made available, characteristics of typical data contributors and users, the potential value of the data now and in the future, the infrastructure and personnel necessary to manage the clearinghouse over the short and long terms, the major cost drivers, and even associated lifetime costs of curating and managing data over the short and long terms need to be considered (e.g., NASEM, 2020).

The results of this effort would be a searchable repository of observations and measurements that can describe the effects of subsurface properties and characteristics on steel and variations of these quantities on the durability, performance, and corrosion rates of buried steel in a variety of applications. The platform will provide researchers the necessary data to accelerate fundamental research, which will in turn advance the state of the art and of practice in industry. Given proprietary or security and vulnerability concerns, data could be identified uniquely and without relation to specific location or infrastructure, which may encourage industry to include its data for the benefit of the entire technical community. Ultimately, as more data are deposited and made available, advanced data analytical techniques including artificial intelligence and machine learning may be used to mine and analyze the data and enable a more holistic understanding of the environmental contributors to corrosivity and corrosion rates. With increased availability of standardized, multidisciplinary, and high-quality data collected from well-documented sites, engineering practitioners could investigate and better understand the contributions of combined subsurface properties to corrosivity and corrosion rates in a given type of environment. Future site characterization investigations can be designed more effectively, infrastructure design and management can be more efficient, and monitoring programs can target environments and conditions shown to be problematic for certain types of infrastructure.

Whereas designing, determining the governance for, and establishing a clearinghouse may take years, steps can be taken in the shorter term to identify existing data that should be included in the clearinghouse. These might be the data types such as those included in Table 6.5 of this report, and consideration should be given as to how they should be reported and what other data might be included. As such decisions are made, it will be necessary to develop common data-recording standards (including for metadata) for future data collections.

CONCLUDING THOUGHTS AND MOVING FORWARD

Corrosion is a trillion-dollar problem (Koch, 2017) that requires knowledge from a variety of disciplines—from microbiology to metallurgy and various fields of engineering—and it affects a wide array of industries. After steel is buried in the ground, it cannot be easily observed without expensive excavations or complex monitoring programs. The implementation of the recommendations in this report will require extensive support and resources from and coordination and cooperation among industry sectors and experts from the public and private sectors and academe. The study committee was not charged with considering what agencies and organizations should be responsible for leading or funding implementation of the recommendations, nor was the committee constituted to deliberate the economic and policy considerations that should inform such recommendations. However, coordinated effort among a variety and range of organizations will be necessary. Implementation of the recommendations may require, for example, cross-disciplinary and cross-sector workshops to identify interested and affected parties, needs and priorities, commonalities and differences in the understanding of key concepts, and existing resources, and to organize and coordinate processes and responses. Broadening and deepening engagement with a broad base of interested agencies and organizations at the earliest stages of implementation will result in better identification of issues, resources, and solutions. However difficult implementation will be, it will result in improved understanding and communication and will allow for model validation, more realistic prediction of corrosion, and more efficient and cost-effective engineering and infrastructure management.

The significantly different approaches of the geo-civil and oil and gas pipeline industries have resulted in intellectual and practical silos. This situation is made worse because researchers and practitioners rarely move between the pipeline and geo-civil industries. These silos lead to parallel—or even competing—research initiatives and foci. The recommendations in this report are intended to help break down the silos and encourage the multidisciplinary and multiscale considerations from atomistic to global climate change. Significantly improving understanding of corrosion mechanisms and rates for buried steel will require a multidisciplinary approach with an inclusive vocabulary that is easily translated between disciplines. As comprehensive long-term multivariate experiments are conducted and observational data are collected, reliable and accessible databases can be established. Data support systems for site characterization program design and risk-informed decision making can be developed. Advanced data analytics should be applied using the current dataset, but more complicated methods such as machine learning will benefit from this robust, collective database.

The committee envisions that industry groups will work through their memberships to develop research needs statements and calls for research proposals based on the needs identified in this report. Ultimately, the recommendations will lead to an understanding of corrosion that will improve the ability to predict corrosion mechanisms and rates, protect against that corrosion, and monitor and model to predict performance more accurately. It is the committee’s expectation that the recommendations will also lead to movement in industry-specific practices, where geo-civil works will adopt protection and monitoring approaches where they make sense, and pipeline industries might adopt characterization approaches used in geo-civil practices. Changes that result from the implementation of the recommendations could reduce the costs of maintaining safety and the environment, and for operation and preservation of buried steel infrastructure.

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