Performance of Coatings for Underbody Structural Components
Bibliographic record
Abstract
<div class="htmlview paragraph">The Auto/Steel Partnership established the Light Truck Frame Project Group in 1996 with two objectives: (a) to develop materials, design and fabrication knowledge that would enable the frames on North American OEM (original equipment manufacturer) light trucks to be reduced in weight, and (b) to improve corrosion resistance of frames on these vehicles, thereby allowing a reduction in the thickness of the components and a reduction in frame weight. To address the issues relating to corrosion, a subgroup of the Light Truck Frame Project Group was formed. The group comprised representatives from the North American automotive companies, test laboratories, frame manufacturers, and steel producers. As part of a comprehensive test program, the Corrosion Subgroup has completed tests on frame coatings. Using coated panels of a low carbon hot rolled and pickled steel sheet and two types of accelerated cyclic corrosion tests, seven frame coatings were tested for corrosion performance. The coatings included those that are currently in use for frames, such as the hot-melt waxes and E-coat, as well as those for potential future applications. One type of cyclic test was a proving ground corrosion trailer test (100 cycles) carried out on a test track at the General Motors Proving Ground test facility. The second type of cyclic test was based on the SAE J2334 laboratory corrosion test (80 cycles), modified to include a bake step at an elevated temperature (93°C, 121°C or 149°C) and an exposure to shot blast in the cycle. The modifications were designed to simulate corrosion under conditions of exposure of the coating to elevated temperatures from the automotive exhaust system and the damage to the coating by the road gravel impact. Both tests revealed differences in the performance of the frame coatings. Details of the test cycles, procedures for the evaluation of corrosion and the reasons for the performance differences are presented in this paper.</div>
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".