An experimental assessment of lawnmower blade loading
Bibliographic record
Abstract
An experimental study of the loading to which a lawnmower blade is subjected during normal operation has been performed. The blade of a consumer-grade walk-behind electric lawnmower was instrumented with strain gauge bridges and strain data were collected using a slip ring assembly and personal-computer-based data acquisition system with integral amplifier. Blade strains were monitored over a range of grass-cutting conditions. It was found that blade strain was dependent principally upon the rotational speed, with no perceptible effect due to cutting conditions, other than the indirect effect due to blade speed changes. The measured strains also compared well with calculated strains, particularly at low speeds. At higher speeds, there were small differences between measured and calculated strains and these differences are attributed to the effects of blade deflection. The results of this study suggest that blade stresses can be accurately calculated using models which include only the effects of rotation. Relative to other possible types of loading (i.e. aerodynamic and grass impacts), rotational effects are easily modelled. At higher speeds, models should include the effects of large-displacement non-linearities to account for the effects of blade deflection. These findings will enable engineers and designers to perform analyses that will minimize the repetitive and often extended empirical testing in arriving at a final mower blade design. Where empirical testing is required, these results indicate that such testing should be based on blade rotation rather than on static fixtures in which cyclic deflection of the blade is applied.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".