Symbolic Formulation of Multibody Dynamic Equations for Wheeled Vehicle Systems on Three-Dimensional Roads
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">A method to improve the computational efficiency of analyzing wheeled vehicle systems on three-dimensional (3-D) roads has been developed. This was accomplished by creating a technique to incorporate the tire on a 3-D road in a multibody dynamics model of the vehicle with an approach that formulates the governing equations using symbolic formulation. For general handling analysis performed on the vehicle, the tire forces and moments are determined using a tire model that represents the tire as a set of mathematical expressions. Since these expressions need numerical values to determine the forces and moments, a symbolic solution does not exist. Therefore, the evaluation of the tire forces and moments needs to be done during simulation. However, symbolic operations can be used when the governing equations are formulated to develop an efficient method to evaluate these forces.</div><div class="htmlview paragraph">A method to automatically construct the procedures necessary to evaluate the tire forces and moments has been developed. This approach includes a technique to automatically generate an optimized road model procedure that calculates the contact point between the tire and the ground. The method is based on the thin disk tire model with variable radius, resulting in two non-linear equations that define the point of contact. The road model procedure is developed and optimized during automated formulation of the equations of motion.</div><div class="htmlview paragraph">The road model procedure was implemented in the DynaFlexPro software package by creating a simulation code structure to evaluate the tire forces and moments during simulation. The structure was included in a tire/road component that is a linear graph representation of the tire and a three-dimensional (3-D) road. A vehicle system was analyzed on two different road profiles performing a cornering maneuver using DynaFlexPro and repeated in MSC.ADAMS to test the accuracy of the approach. Good agreement was achieved between the symbolic computing method presented here, and the purely numerical algorithm along with significant improvements in the simulation time.</div></div>
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".