Variation of the mechanical properties of the natural rubberused in bridges’ bearings and seismic isolators in Canada
Bibliographic record
Abstract
Seismic base isolation is a widely used earthquake-resistant system to protect structures from earthquake-induced damage, focusing on mitigating the seismic demand. Elastomer-based isolators are one of the common systems used in seismic bridge isolation. Elastomers used in the isolators are mostly classified into two main categories: Polyisoprene (natural rubber) and polychloroprene (synthetic rubber known as neoprene). The mechanical properties of these elastomers play a crucial role in the performance and behaviour of the isolation system. However, these properties are variable, being influenced by several factors, notably low temperatures, aging, as well as fabrication and material source. Exposure to low temperatures increases the stiffness and hysteresis of elastomers, causing variations in their key mechanical properties, which alter the seismic response of the seismic isolators and affect the seismic performance of the structure. In this study, the variation of mechanical properties of natural rubber, commonly used in seismic isolation applications and laminated bearings for bridges in Canada, is experimentally studied. Four different sources of natural rubber, including aged rubber extracted from recuperated laminated bearings of the original Champlain Bridge and new rubber, are considered to establish the variation of mechanical properties due to source, age, conditioning duration, and test temperature as well as the frequency of cycling. Specimens from each source of natural rubber are conditioned at different temperatures, namely 23ºC, -8ºC, and -30ºC, for different durations, going from 1 hour to 28 days. Experimental tests are conducted, at the conditioning temperatures, on quadruple shear samples. They consist of imposing a sequence of three cyclic shear loading at an increasing strain amplitude ranging from 25 to 150%. Tests were conducted at different frequencies (0.1, 0.25, and 0.5 Hz). Test results are used to extract the key characteristic properties of hysteresis, notably the effective shear modulus and the equivalent viscous damping, as a function of the studied parameters and shear deformation level. Instantaneous stiffening and crystallization curves are constructed. The effects of the studied parameters are investigated and statistical distributions of the mechanical properties of natural rubber are identified. The experimental results show that increasing conditioning time intensifies the stiffening of natural rubber. However, this effect is minimal at -8ºC but more pronounced at very low temperatures (-30ºC). The frequency of cycling has a negligible effect, within the studied range, while aging induces a notable stiffening of the rubber. Additionally, statistical analysis shows that the variations of mechanical properties due to sources and low temperatures (-30ºC), specifically for prolonged conditioning time, are statistically significant. Finally, it is found that the generalized extreme value and lognormal distributions provide the best fit to the mechanical properties (shear modulus) of natural rubber at room (23ºC) and low (-8ºC and -30ºC) temperatures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".