Windage Tray Design Comparison Using Crankcase Breathing Simulation
Bibliographic record
Abstract
The conflicting requirements of better fuel economy, higher performance and lower emissions from an automobile engine have brought many new challenges that require development teams to look beyond conventional test and seek answers from simulations. One of the relatively unexplored areas of development where frictional losses haven't been completely understood is the flow in the crankcase. Here computational engineering can play a significant role in analyzing flow field in a hidden and complex region where otherwise testing has serious limitations. Flow simulation in the crankcase poses significant complexity and provides an opportunity to enhance the understanding of underlying physics by using multi-physics analyses tools available commercially. In this study, air space under the piston and above the oil level in oil pan is simulated. It is known that bay-to-bay breathing and windage holes account for considerable amount of power losses in the crankcase. Therefore, this study is intended to (but not limited to) the estimation of pumping losses (i.e., power required for piston to overcome the resistance offered by air in the crankcase) in addition to gaining insight into flow field to improve breathing between bays. The simulation is carried out with air as fluid and oil is kept stationary to maintain a constant level in the oil pan. Various meshing and mesh moving techniques were employed. This includes, arbitrary sliding interface (ASI) of counter weights and mesh morphing to replicate piston motion. Time dependent momentum and energy equations were solved for air as compressible media. The study found that one of the major components that can have significant effect in reducing pumping losses and oil aeration is the design of windage tray. The windage tray design can be used for effective oil drainage along with reducing the splashing and sloshing of oil in the crankcase. The openings in the windage tray can be optimized for location and size so as to reduce pumping losses as well as oil aeration. This will have positive impact on engine power as well as fuel efficiency. Windage hole size, number and location also helps in determining the flow through drainbacks, and consequently affect the tuning of PCV and makeup air valves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".