Experimental and numerical investigation of cavitation in marine Diesel injectors
Bibliographic record
Abstract
To further increase the efficiency and decrease emissions of large two-stroke marine Diesel engines, the understanding of the fuel injection, spray breakup and the resulting combustion plays a vital role. Investigations have shown that the strongly asymmetrically and eccentrically arranged nozzle bores of the fuel injectors can lead to undesirable spray deflections that provoke increased component temperatures, emissions and fuel consumption. In order to investigate the origin of these spray deviations, transparent nozzles have been used to qualitatively visualize the in-nozzle flow under realistic geometrical and fuel pressure conditions. Three different, 0.75 mm diameter, single-hole nozzle geometries that represent typical geometrical characteristics have been used in cavitating nozzle flow experiments. The optical measurement technique Shadowgraphy has been applied to visualize the in-nozzle flow over the complete fuel injection process. The experiments have been performed with Diesel fuel at a rail pressure of 50 MPa with ambient back-pressure and temperature. Impingement measurements have been executed to compare the nozzle performance and validate CFD simulations using URANS with cavitation modeling in order to provide qualitative and quantitative support to the experimental results. The volume of fluid (VOF) method has been applied to simulate the multiphase flow with High Resolution Interface Capturing (HRIC). The cavitation model is based on a flash-boiling method with rapid heat transfer between the liquid and vapor phases. A Homogeneous Relaxation Model (HRM) has been utilized to describe the rate at which the instantaneous quality, the mass fraction of vapor in a two-phase mixture, will approach its equilibrium value. The numerical modeling of the cavitation inside the nozzle bore and the evaluated momentum flux have been compared to the experimental findings and show good agreement for the qualitative comparison of the cavitation patterns and differences of less than 6% for the quantitative momentum flux comparison.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".