Prediction of Crack-Opening Stress Levels for Service Loading Spectra
Bibliographic record
Abstract
The fatigue lives of automotive components subjected to variable amplitude service loading are assumed to be dominated by a process of small crack growth. It is generally accepted that crack closure is responsible for most of the variation in fatigue crack growth rates and fatigue lives. This investigation examined the effect of different types and magnitudes of service loadings on crack closure behavior. Three different Society of Automotive Engineers (SAE) standard service load histories with different mean stresses were applied to notched specimens of a 2024-T351 aluminum alloy. The three spectra are the SAE Grapple Skidder history, which has a positive mean stress, the SAE Log Skidder history which has a zero mean stress, and the inverse of the SAE Grapple Skidder history which has a negative mean stress. A curve of maximum stress in the history versus fatigue life was constructed for each spectrum. The crack-opening stress (COS) levels were measured at frequent intervals in order to capture the behavior of the opening stress for each spectrum, for each of a set of scaled histories with different maximum stress ranges. A crack growth analysis based on a fracture mechanics approach was used to model the fatigue behavior of the aluminum alloy specimens for the given load spectra and stress ranges. The crack growth analysis was based on an effective strain-based intensity factor, a crack growth rate curve obtained during closure-free loading cycles, and a local notch strain calculation based on Neuber's rule. The COS levels were modeled assuming that the COS follows an exponential build-up formula that is a function of the difference between the current crack opening stress and the steady state crack opening stress of the given cycle unless this cycle is below the intrinsic stress range, or the maximum stress is below zero. However, the build-up only occurs when the crack-opening steady state stress level for the given cycle is higher than the previously calculated crack opening stress. The modeled crack opening stress level was in good agreement with the measured crack opening stress. The average of the measured crack opening stresses and those calculated using the model were nearly the same for all the histories examined. When these average crack-opening stresses were used in the life prediction model they gave predictions as good as those obtained by modeling COS on a cycle by cycle basis. In the interest of simplifying the use of COS in design the average COS was correlated with the frequency of occurrence of the cycle reducing the COS to the average level. The use of a COS level corresponding to the one in 200 cycle gave a conservative estimate of average COS for all the histories.
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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) | 0.001 | 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 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".