Corrosion of Buried Steel at New and In-Service Infrastructure (2023) / Chapter Skim
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9 Conclusions and Recommendations
9 Conclusions and Recommendations
Pages 105-120
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From page 105... ...
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.
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From page 106... ...
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)
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From page 107... ...
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.
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From page 108... ...
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.
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From page 109... ...
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)
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From page 110... ...
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 commit ments 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.
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From page 111... ...
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. 2 See https://geosynthetic-institute.org (accessed July 7, 2022)
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From page 112... ...
Improved estimates of corrosion rates will result from analytical approaches that (1) consider all relevant subsurface properties, (2)
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From page 113... ...
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.
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From page 114... ...
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.
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From page 115... ...
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.
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From page 116... ...
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.
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From page 117... ...
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.
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From page 118... ...
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.
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From page 119... ...
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.
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