Визначення особливості спрямування та розподілу інтерметалевої фази в евтектиці матеріалу зварного шва після електронно-променевого зварювання сплавів титану та ніобію
Bibliographic record
Abstract
This paper reports a study whose object was material of the weld. The nature of changes in the microstructure of the weld material, which are caused by changes in the supplied energy, alloying elements and heat removal from the melt area, was investigated. Welding was performed with an electron beam at Uacc=60 kV, Ieb=90 mA, with an elliptical sweep of 3×4 mm. The speed of electron beam movement veb was varied from 7 to 15 mm·s-1. The temperature of the experimental welded samples T0 was varied from 300 K to 673 K. Ti-TiB alloy (a microcomposite alloy with reinforcing TiB fibers) was welded with Ti-TiB alloys, T110, and with niobium. One of the tasks of welding this alloy was to preserve and optimize the structure of this type in the weld. Grinding of boride fibers, loss of their initial orientation, and formation of a dendritic or cellular microstructure was observed in the weld. Using the methods of raster electron microscopy and micro-X-ray spectral analysis, the microstructure of the weld material was investigated and the dimensional characteristics of TiB fibers under different welding conditions were determined. The analysis of changes in the microstructure of the weld material, the average length ᶏ and the thickness ȩ of the boride fibers in the material of the joints made at different velocities of electron beam movement and initial temperatures T0 was carried out. It was established that the growth of the ratio ȩ/ᶏ from 0.04–0.07 to 0.1–0.27 is accompanied by significant changes in the microstructure and the mechanism of formation of eutectic phases. It is shown that the process that determines the formation of the microstructure of the weld material was the eutectic breakdown with the determining influence of the temperature gradient, crystallization rate, supercooling, concentration inhomogeneities, and alloying impurities.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.008 |
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".