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Substitution of Coke and Energy Saving In Blast Furnaces. Part 5. Problems and Prospects of Low-Coke Blast-Furnace Technology

2013· article· en· W1805494527 on OpenAlexvenueno aff
I. G. Tovarovskiy

Bibliographic record

VenueEnergy science and technology · 2013
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsnot available
Fundersnot available
KeywordsTuyereBlast furnacePulverized coal-fired boilerRacewayCoalCokeWaste managementMetallurgyCoke strength after reactionEnvironmental scienceCoal combustion productsEngineeringMaterials sciencePetroleum cokeMechanical engineering

Abstract

fetched live from OpenAlex

Two most promising known non-traditional blast furnace technologies can be used to minimize the coke rate: 1) the tuyere injection of the hot reducing gases with removal of CO2 from the top gas and 100% oxygen blast; 2) injection of 300-400 kg pulverized coal/thm (PCI-technology). The injection of hot reducing gases (HRG) is limited by the heat balance of the entire Iron & Steel Works since the blast furnace gas will not be supplied to other works in sufficient quantity. The combustion and gasification of significant amount of coal and liquation of coal ash in the tuyere’s raceway are the limitations for the PCI-technology. Lack of resources, low-ash coal for pulverized coal injection—PCI (pulverized coal full—PCF) requires solutions to technical problems of the use of high-ash coals, in particular, partial and full gasification of fuel before entering the tuyere area of BF. Injection of the products of coal gasification (PCG) instead of PCI into the blast furnace tuyeres eliminates these limitations. The advantages of this technology in comparison with traditional PCI injection are as follows: increase in coal rate and decrease in coke consumption; possibility of low grade coals usage; elimination of fine coal grinding; gas desulphurization in the course of coal gasification and the possibility of coal ash fluxing and being removed from the process. The special compact coal gasifiers attached to the blast furnaces tuyeres were developed and tested at industrial scale. The estimated decrease in coke consumption from 565 kg/thm to 305 kg/thm with injection of 300 kg/thm of coal gasification products and 105 kg/thm of oxygen was specified with respect to operation of blast furnaces at Zaporozgstal Iron & Steel Works (90 years of the last century). The study by using a multi-zone mathematical model showed that the temperature-concentration and phase fields of the charge and the gas flow in the furnace change under the influence of the same tendencies that are seen with the injection of pulverized-coal fuel (PCF). The fact that the amount of coal which can be injected could be increased significantly by subjecting it to preliminary gasification and fluidizing the ash in tuyere-mounted gasifiers means that the targeted savings of coke could be realized by replacing coke with either high-grade coals (in the form of PCF) or low-grade coals (in the form of CGPs). In this case, for the best variants of the technology the ratio of the equivalents for the replacement of coke by coal is close to the ratio of the contents of nonvolatile carbon in the high- and low-grade coals (0.65 in the present case). The application of the developed technology for blast furnaces with burden composition of BF-5 “Severstal” and BF-9 AMKR will allow further decrease in coke rate to the minimal level of 180-200 kg/thm. The payback period of capital investments for this technology is estimated in the range of one year.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.004
GPT teacher head0.175
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations2
Published2013
Admission routes1
Has abstractyes

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