Design, quality and quality assurance of solid recovered fuels for the substitution of fossil feedstock in the cement industry – Update 2019
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Production, quality and quality assurance, as well as co-incineration of solid recovered fuels in cement industry, have become state-of-the-art in the European cement industry. At the global level, average thermal substitution rate is about 17%, whereby, only 13% in Canada and in the USA 16%, while in the European Union 28 it is about 44% (i.e. 11,300,000 t waste fuels utilised in 2016). In Austria, thermal substitution rate was ca. 80% in 2017, which was worldwide the highest one. Regarding solid recovered fuels for the cement industry, two types are relevant, namely solid recovered fuels PREMIUM Quality and solid recovered fuels MEDIUM Quality. In the case study shown, solid recovered fuels PREMIUM Quality from 11 and solid recovered fuels MEDIUM Quality from nine different solid recovered fuels production plants have been investigated. Investigations consist of sorting and sieving analyses (for PREMIUM), as well as physical–chemical analyses (for both solid recovered fuels types) according to the (inter)national standards (i.e. Austrian ‘ÖNORM’, European ‘EN’ standards and CEN TC 343 guidelines). The results gained from the first investigation were published in 2014 and here, results of further investigations are updated for 2016 and 2018 and confronted with legal and market relevant requirements. During the investigation, not enough parallel samples could be investigated and therefore no adequate scientific statistical analyses could be elaborated but a more practical indicative interpretation has been made. Finally, it can be confirmed, that all investigated solid recovered fuels fulfil the Austrian legal and international solid recovered fuels and co-incineration market requirements.
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.
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 | 0.015 | 0.000 |
| 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 | 0.001 |
| 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 it