Use of ultrasound in petroleum residue upgradation
Bibliographic record
Abstract
Abstract Conventional processes for the upgradation of residual feedstocks, viz., thermal cracking and catalytic cracking are carried out in the temperature range of 400–520°C. Such high temperatures can in principle be substituted by acoustic cavitation. In the present work, two vacuum residues, namely, Arabian mix vacuum residue (AMVR) and Bombay high vacuum residue (BHVR) and one asphalt, viz., Haldia asphalt (HA) were subjected to acoustic cavitation for different reaction times from 15 min to 120 min at ambient temperature and pressure. An attempt has been made to seek a performance comparison of two devices of acoustic cavitation, namely, ultrasonic bath and ultrasonic horn with regard to their ability to upgrade the petroleum residues to lighter, more value‐added products mainly the hydrocarbons boiling in the range of gas oil fraction. Another attempt has been made to study the effect of ultrasound on the upgradation of the residue when it is emulsified in water with the help of different surfactants. For all the cases, a kinetic model has been developed based on the constituents of the residue so as to get an insight into the reaction mechanism. The study revealed that ultrasonic horn is more effective in bringing about the upgradation than ultrasonic bath and that the acoustic cavitation of the aqueous emulsified hydrocarbon mixture could reduce the asphaltenes content to a greater extent than the acoustic cavitation of non‐emulsified hydrocarbon mixture. The reduction in asphaltenes content of BHVR was found to be more followed by AMVR followed by HA. The variation in the rate constants was found to be feed specific and the rate constants for the conditions of maximum conversion of asphaltenes to gas oil for AMVR, BHVR and HA were found to be 0.29 × 10−4 s−1, 1.4 × 10−4 s−1 and 0.23 × 10−4 s−1, respectively.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".