Kinetic Model of Steam Gasification of Biomass in a Bubbling Fluidized Bed Reactor
Bibliographic record
Abstract
A simple kinetic model is developed for biomass gasification in a bubbling fluidized bed (BFB) with steam as the fluidizing gas. The biomass pyrolysis is described by a two-step kinetic model in which the primary pyrolysis is modeled by three parallel first-order reactions producing noncondensable gas, tar (bio-oil), and char, and the secondary pyrolysis is modeled by a first-order reaction representing homogeneous thermal cracking of tar. In addition to the yields of pyrolysis products that are often modeled as lumped species, the proportions of major compounds in the pyrolysis gas are predicted based on CHO elemental balances. By incorporating homogeneous and heterogeneous biomass gasification reactions, a seamless kinetic model of a BFB gasifier is developed. An ideal reactor model is used for the BFB gasifier assuming perfectly mixed solids and plug flow of the gas phase. This predictive model is a useful tool to relate biomass gasification product yields and composition to key process operating parameters such as biomass ultimate analysis, reactor temperature, and steam-to-biomass ratio. Predictions of the gasifier model are in good agreement with experimental data from the literature.
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 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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".