Evaluation of Electron Beam Welded AISI 415 Stainless Steel
Bibliographic record
Abstract
Sustainable manufacturing for assembly of turbines used in hydro power generation systems is driving the development of advanced technologies targeted to reduce life-cycle costs whilst assuring high performance over the prolonged product life-span. The turbine runner, a critical component in hydro power generation systems, requires weld assembly between the crown, band and blade sub-components. With due consideration of the thick-gauge sections involved, design and fabrication of a turbine runner that would integrate a high energy density technology for assembly, such as vacuum electron beam welding (EBW), has marked potential to achieve deep penetration with a low heat input, thereby rendering a weldment with narrow heat-affected zones (HAZ) and low distortion. In this study, the weldability of thick-gauge section AISI 415 martensitic stainless steels that are widely utilized in hydro turbine manufacturing was investigated by EBW. Particularly, bead-on-plate (BOP) welding of 88 mm-thick AISI 415 plate was carried out using a 42 kW high vacuum EBW system. The characteristics of the weldments, such as fusion zone (FZ) and HAZ microstructures and hardness were evaluated. The microstructural constituents across the weldment for process conditions that rendered near-complete penetration were studied and related to the microhardness evolution.
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 | 0.000 | 0.001 |
| 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 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".