A Circular Inclusion with Circumferentially Inhomogeneous Non-Slip Interface in Plane Elasticity
Bibliographic record
Abstract
A rigorous solution is presented for a problem associated with a circular inclusion embedded within an infinite matrix in plane elastostatics. The bonding at the inclusion–matrix interface is assumed to be imperfect. Specifically, the jump in the normal displacement is assumed to be proportional to the normal traction with the proportionality parameter taken to be circumferentially inhomogeneous. In addition, we assume that displacements in the tangential direction are continuous. This type of interface is generally referred to as an inhomogeneous non‐slip interface. Using the principle of analytic continuation, the basic boundary‐value problem for four analytic functions is reduced to a first‐order differential equation for a single analytic function defined inside the circular inclusion. The resulting closed‐form solutions include a finite number of unknown constants determined by analyticity requirements and certain other supplementary conditions. The method is illustrated using several specific examples of a particular class of inhomogeneous non‐slip interface. The results from these calculations are compared with the corresponding results when the interface imperfections are homogeneous. These comparisons indicate that the circumferential variation of interface damage has a significant effect on even the average stresses induced within a circular inclusion.
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".