Computer Aided Engineering Introduction In A Multi Disciplinary Engineering Program
Bibliographic record
Abstract
Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Computer-Aided-Engineering: Introduction in a Multi-disciplinary Engineering Program Introduction Computer-aided engineering (CAE) and computer-aided design (CAD) are taking an increasing role for the practicing engineer in both design and analysis context. For the practicing engineer, it provides an opportunity to explore creative ideas without the initial expense of prototypes and/or pilot facilities. The importance of CAE in engineering education is well established and many engineering programs now include some type of formal education utilizing solid modelling software packages1,2,3. Many studies have shown that the use of CAE software enhances the learning of students at all levels from first year4,5,6 to fourth year7,8. The CAD/CAE software packages themselves tend to be broad based, offer extensive tools for the experienced practitioner and hence they may not be intuitive to the novice user. CAE is not a trivial domain. It is easy to generate results that are incorrect and dangerous9. Therefore, it is essential to know what is going on within a software program and recognize the software’s limitations10. Unfortunately, it is easy for a student or the practitioner to generate impressive pictures with CAE software which display completely erroneous results. Engineering education must develop strategies to ensure that our graduates recognize the power of CAE while respecting the risks and responsibilities associated with its use. The University of Guelph offers fully accredited engineering programs in Biological, Systems and Computing, Environmental, and Water Resources. Each program at Guelph is multidisciplinary blend of traditional engineering disciplines. Design is recognized as the essence of engineering and has been delivered at the School through a core sequence of design courses since the early 1970s11. These core design courses offer all of our students the experience of working in multi-disciplinary teams. The introduction of CAD/CAE tools into the curriculum began in Fall 2000 with a single course and has evolved to be offered in three second year courses. This paper presents the current approach, which has largely been in practice for the past 2 or 3 years. The paper then discusses some of the key attributes that are believed to be important for success and assesses the level of intelligent usage by students in their fourth year capstone design projects. CAD/CAE Delivery in Second Year The participating second year courses are Engineering & Design II and Material Science (fall offerings), and Fluid Mechanics (winter offering). All of these courses are taken by all engineering students at Guelph. Solid modelling is introduced in Engineering and Design II. The basics of finite element modelling related to solid mechanics problems are introduced in Material Science. Computational fluid dynamics is introduced in Fluid Mechanics. Engineering & Design II is the core course supporting CAE. The students, in teams of approximately 10, start in the machine shop dissecting a product. Over the years, the products have ranged from refrigerators, to computers, to the components of a 1986 Honda Prelude. This
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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 | 0.001 |
| 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) | 0.000 | 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".