Rapid shaft sinking / Mechanisiertes Abteufen von Schächten
Bibliographic record
Abstract
Abstract In 2011 Herrenknecht designed a shaft sinking machine suitable for applications in frozen ground or soft to medium hard rock up to 120 Mpa, with variable shaft diameters as well as geometries. The target was to develop a machine that will provide safe working conditions for the personnel and exceed the shaft sinking rates of conventional systems. Two prototypes were manufactured and assembled at the Herrenknecht works in Schwanau during winter/spring 2012. In early summer of 2012, cutting trials were performed with the aim of achieving the maximal possible cutting rate performance. After successful completion of the cutting trials, the machines where shipped to Canada and assembled at the site. In November 2012, the first machine was lowered into the shaft and first cutting cycles where performed before Christmas 2012. Assembly and commissioning of the second machine follows in early 2013. Die Herrenknecht AG hat im Jahr 2011 eine Maschine für das maschinelle Abteufen von Schächten in gefrorenem Boden oder weichem bis mittelhartem Gestein mit einer Druckfestigkeit von bis zu 120 MPa entwickelt. Ein großes Ziel dieser Entwicklung war, die Arbeitsbedingungen für das Personal im Schacht sicherer zu gestalten sowie die Schachtabteufgeschwindigkeit konventioneller Anlagen zu übertreffen. Zwei Prototypen wurden hergestellt und im Zeitraum Winter 2011 bis Frühjahr 2012 auf dem Werksgelände der Herrenknecht AG in Schwanau montiert. Schneidversuche fanden im Frühjahr 2012 mit dem Ziel statt, die maximal mögliche Schneidleistung zu ermitteln. Nach erfolgreichem Abschluss der Schneidversuche wurden die Maschinen nach Kanada ausgeliefert und am Standort aufgebaut. Im November 2012 wurde die erste Maschine in den Vorschacht abgesenkt und die ersten Schneidzyklen noch vor Weihnachten 2012 durchgeführt. Aufbau und Inbetriebnahme der zweiten Maschine erfolgte im Sommer 2013.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".