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Record W7043386139

Studies of the Torrefaction of Sugarcane Bagasse and Poplar Wood

2017· other· en· W7043386139 on OpenAlexaboutno aff

Bibliographic record

VenueAmericanae (AECID Library) · 2017
Typeother
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsTorrefactionBagasseThermogravimetric analysisBiomass (ecology)Inert gasDecompositionWood dryingWater contentMoisture
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, the main physical and chemical characteristics of sugarcane bagasse and poplar wood submitted to a thermo-chemical torrefaction process were studied. The materials were dried at a temperature of 105°C for 12 hours, to a moisture content of about 5%. The sugarcane bagasse was torrefied in TGA and in a custom designed thermogravimetric reactor for the evaluation of big particles in the temperature ranges of 200-300°C. With TGA tests, kinetic parameters representative of the material decomposition were obtained, and with large particles tests, the degradation was compared when the amount and particle size of material increases. The products of all torrefied tests were characterized and compared. Poplar wood was torrefied in a custom thermogravimetric reactor in order to determine its kinetic parameters and in a two-stage rotary reactor by varying the operating parameters. These experimental tests with poplar were carried out in the circulating fluidized bed laboratory of Dalhousie University, Halifax, Canada. In the rotary reacctor, the biomass is dried in the first stage, and then torrefied in the second. Torrefaction process is carried out under volatiles atmosphere generated during the process, without inlet of inert gases. Fine particles, between 0.5 and 1 mm in diameter were used in this study, and characterized before and after torrefaction. A characterization of the biomass being torrefied was performed using two novel scooper devices for sample capture from inside reactor, specially designed for this research. These two devices allow to capture biomass samples being torrefied and measuring their temperatures in different axial positions of the reactor. Two phenomenological models were constructed: a two-dimensional model for torrefaction of a biomass particle and a two-stage rotary reactor model. Both were duly validated and great information was obtained from them. A kinetic scheme involving secondary reactions to the interior of the biomass particle was used and validated with experimental information. Four phases were considered in the model: Biomass, water, char and gases, and for each of them it was possible to obtain distributions of their volumetric fractions at any time in the process. In addition, temperature distributions, velocities of volatiles generated and pressures can be obtained. A vertical reactor was designed and built in order to evaluate the behavior of large particles in torrefaction process. With this reactor, it is possible to follow the mass and temperature of the particle during the process. In addition, it is possible to capture volatiles and separate them into condensables and non-condensables throught a condensation unit which operates at -15°C and capture the condensable portion of the volatiles stream. With this reactor, it is possible to perform a complete characterization of all torrefation products such as liquid, gas and solid. This reactor was designed and built by the TAYEA group, specifically for the realization of this research work.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.213
Teacher spread0.204 · 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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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