Computational Structural mechanics: From aeronautics to Shape memory alloys
Bibliographic record
Abstract
Typically, the structure of any project is as follows: proposal of the problem, justifying the \nresearch, development of the project and conclusions regarding the original problem. But \nsometimes setbacks appear, unexpected turns that impede the normal line of the project. \nThis paper suffered several setbacks favoring a totally different structure to a conventional \none: it is composed of three sub-projects, of which two of them do not share the conclusions \nto the original problem. \nThe first sub-project, Chapter 2, presents Preliminary design of a trolley for dismantling an \naircraft at the end of life. The aeronautic private enterprise Avianor, in their quest to be a \nworld leader in recycling aircraft, wanted a trolley to completely dismantle the plane in order \nto try to reuse all the aircraft¿s components and materials. Thus Avianor contacted the ¿Ecole \nde Technologie Superieure¿ in Montreal (Canada) and both established the guidelines to \nachieve a detailed design of the trolley. Unfortunately, a short time after beginning the \nproject, Avianor did not wish to continue and the research only became the preliminary \ndesign of the trolley. \nThe second sub-project, Chapter 3, describes the modelling and optimization of the \nstructure of the material for orthopedic implants using numerical tools. After ending the \nfirst project, I was relocated by my tutor, the Dr. Terriault, to an entirely new field: the porous \nsuperelastic metal alloys for medical purposes within the branch of orthopedics. In this new \nproject, the aim was to design porous structures and optimize them to obtain maximum \ncompatibility with living tissue. In the absence of the manufacturing machine for the \nsuperelastic metal alloys due to economic reasons, an alternative plastic material during the \nstudy development was necessary. Regrettably, this material did not reproduce superelasticity \nbehavior so this project had to stop too. However, when the manufacturing machine of the \nsuper alloy is available, the project development will continue. \nThe third sub-project, Chapter 4, shows the Unit cell analysis of the superelastic behavior \nof open-cell tetrakaidecahedral shape memory alloy foam under quasi-static loading. In \nthe previous project, one of the structures that were studied was the tetrakaidecahedral \ngeometric. This structure is of great interest in the area of shape memory alloys, and luckily, \nat this moment the department was performing a research project whose geometry and \nmethodology resembles the ones of the latter. I started to successfully collaborate in this \nproject. It is worth to say that the results of this work have been sent to a JCR journal, \n¿Computational Material Science¿. The title of the paper is ¿Unit cell analysis of the \nsuperelastic behavior of open-cell tetrakaidecahedral shape memory alloy foam under quasistatic \nloading¿.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".