Effects of Temperature, Chemical, and Mineral Admixtures on the Electrical Conductivity of Concrete
Bibliographic record
Abstract
Abstract ASTM C1202 has become a very common test method for prequalification purposes and for performance-based specifications in North America. Although the test neither directly determines the permeability or chloride resistance, it has often been shown to have good correlation to those properties since electrical conductivity is also related to the porosity and connectivity of the pore structure. The prevalence of the test is largely based on its ease of execution and its wide acceptance and use by many state and provincial DOTs. More recently, ASTM subcommittee C09.66 has discussed replacing the above test method with a more rapid method measuring conductivity. Several factors affect the conductivity of concrete, mixture design, inclusion of chemical and mineral admixtures, the temperature during testing and the age or maturity at test time. Research was carried out to investigate the magnitude of these variables on measured conductivity. Conductivity was measured using the same equipment as the ASTM C1202 method with changes in the magnitude and duration of the applied voltage as well as the solutions used in the test cell chamber. Conductivity was measured every three hours starting at one day after casting until seven days and weekly until 28 days. Conductivity was found to decrease with hydration as expected. It was determined that mixture design and temperature have significant effects on measured conductivity while chemical admixtures have less influence with the exception of corrosion inhibitors. The developed test method presents potential as a tool for prequalification and quality control that can be directly related to maturity and durability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".