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Record W7043831030

UND Engineering team scores international victory in UAS design

2014· article· en· W7043831030 on OpenAlexaboutno aff

Bibliographic record

VenueUND Scholarly Commons (University of North Dakota) · 2014
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsVictoryPayload (computing)Competition (biology)ChampionshipNinthWorld classLaunched
DOInot available

Abstract

fetched live from OpenAlex

UND Engineering team scores international victory in UAS design A team of University of North Dakota engineering students recently won a major international competition, nailing down the lead with an impressive unmanned aircraft system (UAS) that they designed and built from scratch. Eighteen teams of student engineers competed for the world championship at the 22nd annual ASME (American Society of Mechanical Engineers) Student Design Competition finals, held in Montreal as part of at this year's International Mechanical Engineering Congress & Exhibition. The UND team, comprising, Christopher Borseth, Thief River Falls, Minn.; Aric Glaser; Alex Heyd, East Grand Forks; Scott McDaniel, Darlington, Wisc.; and Daniel Smith, Grand Forks; are all juniors in the Department of Mechanical Engineering, part of the UND College of Engineering & Mines. A press report about UND's win noted that their victorious UAS weighed in at a "massive" 78.4 pounds, nearly twice as much as their nearest competitor. "This year's student competition was given the following challenge: we had to design, build and fly an original UAS, navigate the machine through high and low gate, complete a targeted payload drop (on a simulated forest fire), and return to the start through a hula hoop," Borseth said. "We figured the best option in this competition would be a quadcopter, and we built ours with eight motors, two on the end of each arm, driving counter-rotating propellers. Before the world final, we added another arm with a motor on each end, for a total of 10 motors." The main objective required to capture the title: the heaviest payload. "The group was so successful because they had a strong team that worked well together, had good ideas, and, most importantly, put in the time to continually make improvements and test their prototype," said Dustin McNally, a mechanical engineering faculty member and the team's advisor. "They also received funding from the department and college, which was critical for this competition," McNally said. "They had to design a flying vehicle, and the components can be quite expensive. It is very difficult to control and fly these designs when they are loaded with a lot of weight, and UND's team spent a lot of time maximizing their payload while still being able to complete the course and maneuver satisfactorily." "The students learned how to go through the engineering design steps to evaluate and optimize their design instead of jumping to conclusions and hoping that an idea will work," McNally said. "So they were sure to test everything completely before relying on it." Another thing the team learned in class was that even small details can take a lot of time so budgeting their time and being motivated was also very important. "This combination of having a good team, using the engineering design process to optimize their design and ensuring that it all gets done on time was critical to their success," McNally said. At the International and District level, McNally noted, there were teams that should have done better than they did because their prototypes looked competitive. "UND came through as a clear winner at each level of the competition as the team had put so much quality effort into the right areas," McNally said. Juan Miguel Pedraza University & Public Affairs writer

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.218
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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