Negative stiffness honeycomb structure as automobile leaf spring: A numerical investigation
Bibliographic record
Abstract
The leaf spring is one of the main components in an automobile which carries the weight of the vehicle and passenger as well as absorbs the vibration and shock produced due to road irregularities. The weight, natural frequency, stress developed, energy absorption, fatigue life, etc. are the key factors that need to be considered to design a leaf spring. Towards that, a novel design integrating a Negative Stiffness Honeycomb Structure (NSHS) in the leaf spring is proposed. The proposed design and the traditional leaf spring are analyzed using the commercially available Finite Element Method (FEM) software Abaqus. Both the traditional and NSHS models were created using Solidworks and modal, harmonic, structural, and transient analyses were performed. It is found that the natural frequency of the NSHS leaf spring is well above the frequency produced due to road irregularities although it is lower than the traditional spring. The total weight of the NSHS spring structure is reduced significantly by 30.73% compared to the traditional spring. Structural analysis shows a lower stress development and higher energy absorption capacity for the NSHS leaf spring. Transient analysis reveals lower mean stress in the proposed NSHS spring. The fatigue life is also found to be 82.78 % higher in the proposed design. The NSHS-incorporated novel leaf spring design may be an excellent alternative to the traditional leaf spring.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".