SHORT DESIGN PROJECTS FOR AN INTRODUCTORY THERMOFLUIDS ENGINEERING COURSE
Bibliographic record
Abstract
The Faculty of Engineering at Dalhousie University offers a common introductory course that covers the basic principles of thermodynamics and fluid mechanics in a unified manner. This introductory course is a mandatory part of the curriculum for all engineering programs offered at Dalhousie. In this course, students are required to perform six laboratory experiments, and since 2012 students have also completed short, four-week design projects.The short design project helps students to acquire more of the graduate attributes defined by the Canadian Engineering Accreditation Board (CEAB), including design, communication, and team work skills. They also provide students with a well-deserved break from purely theoretical work in lectures and tutorials, and a chance to develop some hands-on abilities.This paper describes the lessons learned from the last three design projects, which were focused on modifications to a Ranque-Hilsch vortex tube, design of a pop-pop boat, and design of a double pipe heat exchanger. The primary challenges have been the limited engineering design experience possessed by students in their third semester of studies, the heavy workload that second-year engineering students already have, and the relatively large class size. Even though there are clear challenges related to integrating a design project into a large second-year class, the results seem to indicate that these design projects provide a positive learning experience for the students.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.121 | 0.034 |
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".