Impact of Regular and Irregular Pore Distributions on the Elasticity of Porous Materials: A Microstructure-Free Finite Element Study
Bibliographic record
Abstract
Conventional analytical formulas for predicting the effective Young's modulus of porous materials often rely on simplifying assumptions and do not explicitly incorporate microstructural information. This study investigates the impact of regular versus irregular pore distributions on the stiffness of porous materials using microstructure-free finite element modeling (MF-FEM). After conducting a convergence study, MF-FEM predictions were validated against experimental data and used to assess the accuracy of commonly employed analytical models. The results demonstrate that materials with irregular microstructures exhibit a rapid decrease in Young's modulus, approaching zero at porosities slightly greater than 50%. In contrast, regular microstructures show a more gradual decline, maintaining significant stiffness until the porosity exceeds 90%. Additionally, the study reveals that some analytical formulas align better with irregular microstructures while others are more suited to regular ones, attributable to the underlying assumptions of these models. These findings underscore the necessity of considering pore distribution patterns in modeling to accurately predict the mechanical behavior of porous materials.
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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) | 0.001 | 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".