Proceedings of the 11th International Conference on Mechanics and Materials in Design (M2D2026)
Bibliographic record
Abstract
M2D2017 is the seventh international gathering of a prestigious series of conferences coordinated by the International Scientific Committee of Mechanics and Materials in Design. This series of conferences is wholy devoted to advances in mechanics, materials, structural integrity and design. M2D2017 is sponsored by the University of Porto, the University of Toronto and the University of Algarve. The conference attracted over 230 participants with 360 accepted submissions from 40 countries out of 416 submissions. These papers were presented in June 11-15, 2017 in the magnificent city of Albufeira/Algarve, Portugal. The conference themes which address novel and advanced topics in Mechanics and Materials in Design focused on computational mechanics, experimental mechanics, fatigue and fracture mechanics, composite and advanced materials, nanotechnologies and nanomaterials, tribology and surface engineering, mechanical design and prototyping, biomechanical applications, civil engineering applications, impact ant crashworthiness, energy and thermo-fluid systems, and industrial engineering and management. The conference also included an Open Forum on The Challenges Facing Engineering Education, where an expert panel with over 100 years of collective and active researchers and educators addressed the roles of professors that they meet, the obligations of their stakeholders and current challenges facing engineering education. We believe that the meeting offered our delegates a forum for the dissemination of their recent work in mechanics and materials and their applications in engineering design, fostered research that integrates mechanics and materials in the design process, and promoted exchange of ideas and international co-operation among scientists and engineers in this important field of engineering. We are particularly indebted to the authors and special guests for their presentations. Each of the more than 360 contributions offered opportunities for thorough discussions with the authors. Particularly, we acknowledge the excellent contributions of the participants, their innovative ideas and research directions, the novel modeling and simulation techniques, and the invaluable critical discussions. We are also indebted to the outstanding keynote speakers who highlighted the conference themes with their contributions. We also take this opportunity to thank the members of the International Scientific Committee, the members of the Advisory Committee and the reviewers for their time, effort and helpful suggestions. We offer our sincere gratitude to the symposia organisers for their efforts and valuable contributions to the success of the event, and the local organising committee for attending to the conference demands and delegates needs. All in all, M2D2017 was a great success and the credit must go to all the participants for their significant contributions and lively discussions, the keynote speakers for bridging the gap between the different disciplines and the organizing committee for an absolutely superb organization of the meeting in this magnificent city. To all of you, we offer our gratitude. Given the rapidity with which science is advancing in all areas of mechanics and materials, the next conference in this series (Integrity, Reliability and Failure - IRF2018) will take place in Lisbon, the capital city of Portugal, in July 2018. Undoubtedly, we expect IRF2018 to be as stimulating and interesting as M2D2017, as evidenced by the excellent contributions offered in this current event. We look forward to seeing all of you in Lisbon in 2018.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.186 | 0.077 |
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".