Mechanical characteristics of electric arc coatings sputtered on St3 steel and D16 aluminum alloy
Bibliographic record
Abstract
Electric arc coatings (EAC), sprayed with the Fe–Cr–Si–Mn–B–C cored wires (CW) alloying system with an exothermic charge based on boron carbide powder, is investigated. The content of boron in the FCW varied within 0–2 mass% to obtain a microhardness of coatings in the range of 500–1000 HV0.3 for the restoration of lightly and heavily loaded parts of units. The chromium content in the CW varied within 6–17 mass% to form coatings on parts that operate in technological and corrosive environments. Since the performance characteristics of the coatings, also depend on the substrate material and the air jet pressure during their deposition, they were sprayed onto aluminium and steel sub-strates at subsonic (0.6 MPa, 300 m/s) and super¬sonic (1.2 MPa, 600 m/s) air jet pressures. The supersonic speed was achieved due to the nozzle system of coating spraying using double Laval nozzles. The ratio of residual tensile stresses of the first kind σres to their cohesive strength σs (σres/σs) was used as an indicator of the resistance of coatings to cracking. It was shown that cracks began to form in coatings for which σres/σs > 0.75, while at σres/σs > 0.85, a network of cracks was formed in the coatings. It was found that σres in the coatings sputtered on an aluminium substrate was lower than in those sputtered on steel, which is due to the higher coefficient of thermal expansion of D16 aluminium alloy than of St3 steel.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".