Development and assessment of non-destructive evaluation techniques for the measurment of stress and strain in biological materials
Bibliographic record
Abstract
The heterogeneous and anisotropic nature of wood material creates additional design challenges not present with the use of other structural materials such as steel and aluminum. The natural variation in the physical properties of wood members requires that the specified strengths and resistances used for design calculations be based on the quantities measured for the fifth percentile of all wood materials tested. The result is that design may be unnecessarily conservative and subsequently inefficient.\n\nThe same properties that cause uncertainty surrounding the physical properties of biological materials also create difficulty in applying non-destructive evaluation techniques. Strain measurement is one particular technique that is extremely valuable for materials of known and consistent stress-strain relationships, but whose usefulness is diminished when applied to biological materials.\n\nTo demonstrate the need for more accurate strain measurement in light-framed structures, the predictive calculations and structural modelling of a post-framed building was compared to its demonstrated performance. The analysis did not adequately reflect the actual performance of the building, and it was determined that additional monitoring of light-framed buildings through systems such as strain measurement was required to gain a better understanding of the performance characteristics in order to optimize evaluation techniques.\n\nThis project aimed to develop a system that accurately measures strain in dimensional lumber of different types, which in turn will enable researchers to enhance monitoring the performance of light-frame structures and optimize design analysis and structural modelling techniques. The development of a methodology that provides a practical means by which to perform in-situ testing of post-frame buildings and decreases the complexity of post-frame building monitoring will contribute to the advancement of design and analysis techniques.\n\nIn the calibration phase of the project, metal foil resistance strain gages were mounted onto wooden specimens with dimensions of 5 x 13 x 40 mm, 5 x 40 x 100 mm, and 2 x 20 x 50 mm, and acrylic specimens with dimensions of 3 x 25 x 75 mm. These specimens were then subjected to loading in an ATS universal testing machine in the Physical Properties Lab at the University of Manitoba. Stress-strain curves were developed based upon the observed stress and strain levels. These calibrated gages were then mounted on to a 38 x 89 mm specimen of S-P-F dimensional lumber which represented a typical light-framed building material. This assembly was then subjected to a similar loading procedure as the calibrated gage and stress-strain curves were generated once again.\n\nThe slopes of the stress-strain curves developed from the two phases of the project were compared to determine if a consistent correlation existed. The three sizes of wood specimens did not demonstrate a consistent correlation. However, the acrylic specimen demonstrated consistent correlation amongst two groups of three with correlation coefficients within a forty percent range in one group and within a nine percent range in the other group. This suggests that further experimental refinements could produce the desired results.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".