Biodeterioration of concrete sewer pipes: a practical analytical model
Bibliographic record
Abstract
Durability of buried infrastructure is often "out-of-sight and out-of-mind". In Canada alone, according to a Federation of Canadian Municipality study from 2007, upgrading and building new water infrastructure to an acceptable level of service requires an expenditure of more than $40 billion. Unlike different types of degradation due to local soil contaminants, construction materials, or weather conditions, biodeterioration in sewage transportation and treatment systems is generally faced by all municipalities worldwide. Biodeterioration of concrete sewers occurs when microorganisms living in biofilm formation on unsubmerged sections of concrete excrete sulfuric acid, which is deleterious to the concrete because it contains acidity (H+ ions) and sulfates. This research program combines different areas of civil and environmental engineering by integrating important biological and chemical concepts. More specifically, the research program proposes two analytical models applicable to predicting reactions occurring during biodeterioration of concrete sewers. First, a new modeling approach for pH changes is proposed. In this new proposed pH approach, pH changes are calculated in each process definition by the stoichiometric coefficient (–∆H+/β), where ∆H+ is the production or consumption of protons and β is the buffering capacity. The method also includes the effects of the ionic strength. The method can predict pH changes due to the input or biological production of acids and bases, or equilibrium with gases and minerals. It is found to be simpler than the existing methods, while maintaining the same level of accuracy. The approach was then applied to reactions where pH changes kinetically. Two reactions occurring during the biodeterioration of concrete sewers were studied: the continuous production of sulfuric acid by sulfur-oxidizing biomass (decrease in pH), and dissolution of hydrated cement paste (increase in pH). In batch-reactors, the dissolution of hydrated cement paste was modeled by a surface reaction where calcium hydroxide dissolves preferentially. The decrease in pH due to the production of sulfuric acid from thiosulfate could be accurately modeled by a disproportionation reaction where the biomass stores part of the thiosulfate as sulfur granules and oxidizes the rest as sulfates and protons. The same reactions occurring in biofilm formation were also studied to represent the sewer conditions more closely. While the deleterious effects of sulfuric acid to hydrated cement paste and concrete are well known, the impact of the w/c ratio on the extent of degradation is not as clear. To help alleviate this situation, the dissolution kinetics of calcium from hydrated cement paste in acidic solution was parameterized. Sample characteristics (w/c ratio and carbonation) were tested but were not found to have a statistically significant impact on the dissolution parameters. However, acid type and concentration were found to significantly affect the same parameters. The parameterization was applied to predict the mass loss of concrete discs subjected to sulfuric acid and different brushing regimes. Brushing of the concrete surface creates shearing forces representing the effect of sewerage flow at the water line in sewers. These forces were found to cause a significant increase in deterioration. The part of mass loss due to diffusion was determined from the previous calcium solubilisation experiment on hydrated cement paste prism. Overall, this thesis offers a multi-disciplinary review of the biodeterioration of concrete sewers, proposes a new modeling approach to pH changes in process models, and develops some insights on the impact of acidic solutions on hydrated cement paste and concrete durability. Further research on this topic should focus on validating the buffering capacity approach to existing wastewater and biosolides treatment models, and modeling the interactions between concrete and biofilms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".