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Record W4403848266 · doi:10.1016/j.cej.2024.156797

CFD-based studies of scaled-up adsorption columns

2024· article· en· W4403848266 on OpenAlexafffund
Henry Steven Fabian-Ramos, Chinmay Baliga, Arvind Rajendran, Petr A. Nikrityuk

Bibliographic record

VenueChemical Engineering Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAdsorptionComputational fluid dynamicsChemical engineeringMaterials scienceChromatographyProcess engineeringChemistryEnvironmental sciencePetroleum engineeringMechanicsEngineeringPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Adsorption is an actively researched process in chemical engineering with advances in various realms. Regarding numerical studies, most research has been focused on lab-scale and pilot-scale packed beds, leaving a gap in the understanding of flow dynamics within industry-scale systems. The present study attempts to address this gap by applying a multidimensional CFD model to industry-sized 2D geometries of adsorption columns. The model is validated using published experimental data of a pilot-scale column containing 41 kg of adsorbent. A column of 1.055 m in diameter and 2.395 m in length is considered along with three inflow distribution modes: plug, jet, and conical inflow. The effect of heat transfer through the wall is also studied by comparing the usage of a constant heat transfer coefficient ( h w ) against a physics-based h w formulation. The evolution across time and space of relevant adsorption variables like composition, temperature, and loading is analysed, where aspects such as irregular spatial distributions, front morphing, radial gradients, and the influence of heat transfer are explored. It is determined that the inflow mode does not have a permanent effect on species distribution at large scales, as the composition fronts revert to a plug-flow configuration at 42% and 32% of the column’s length for the jet and conical cases, respectively. However, the lack of proper radial distribution, along with convective cooling, induces irreversible asymmetries in the temperature fronts that affect adsorption at the latter stages of a DCB experiment. Finally, a constant h w is proven to be an acceptable modelling assumption, as it differs from the physics-based h w approach in less than 6.87% and has negligible impact on the overall adsorption dynamics. • Flow dynamics within three scaled-up geometries of adsorption columns are studied. • The validated CFD model shows accuracy and scalability across small and large setups. • The inflow mode does not permanently affect species distribution. • Convective cooling can irreversibly morph the posterior side of thermal fronts. • The fixed heat transfer approach has ∼ 6% discrepancy but maintains overall accuracy.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.151
Threshold uncertainty score0.695

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.233
Teacher spread0.220 · 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 teacher head, 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

Citations5
Published2024
Admission routes2
Has abstractyes

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