Systematic Assessment of Rigid Internal Combustion Engine Dynamic Coupling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Accurate estimation of engine vibrations is essential in the design of new engines, engine mounts, and the vehicle frames to which they are attached. Mount force prediction has traditionally been simplified by assuming that the reciprocating dynamics of the engine can be decoupled from the three-dimensional motion of the block. The accuracy of the resulting one-way coupled models decreases as engine imbalance and cylinder-to-cylinder variations increase. Further, the form of the one-way coupled model must be assumed a priori, and there is no mechanism for generating an intermediate-complexity model if the one-way coupled model has insufficient fidelity. In this paper, a new dynamic system model decoupling algorithm is applied to a Detroit Diesel Series 60 in-line six-cylinder engine model to test one-way coupling assumptions and to automate generation of a proper model for mount force prediction. The algorithm, which identifies and removes unnecessary constraint equation terms, is reviewed with the aid of an illustrative example. A fully coupled, balanced rigid body model with no cylinder-to-cylinder variations is then constructed, from which x, y, and z force components at the left-rear, right-rear, and front engine mounts are predicted. The decoupling algorithm is then applied to automatically generate a reduced model in which reciprocating dynamics and gross block motion are decoupled. The amplitudes of the varying components of the force time series are predicted to within 8%, with computation time reduced by 55%. The combustion pressure profile in one cylinder is then changed to represent a misfire that creates imbalance. The decoupled model generated by the algorithm is significantly more robust to imbalance than the traditional one-way coupled models in the literature; however, the vertical component of the front mount force is poorly predicted. Reapplication of the algorithm identifies constraint equation terms that must be reinstated. A new, nondecoupled model is generated that accurately predicts all mount components in the presence of the misfire, with computation time reduced by 39%. The algorithm can be easily reapplied, and a new model generated, whenever engine speed or individual cylinder parameters are changed.
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.
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 it