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Record W2334583910 · doi:10.1115/detc2009-87100

3D Predictive Model for Controlled Resistance Welding of Composites for Manufacturing Applications

2009· article· en· W2334583910 on OpenAlexaff
Imad Zammar, Iraj Mantegh, Mojtaba Ahmadi

Bibliographic record

VenueVolume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stress Analysis, and Failure Prevention Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsNational Research Council CanadaCarleton University
Fundersnot available
KeywordsWeldingThermocoupleMaterials scienceTransient (computer programming)Resistive touchscreenFinite element methodHeat transferProcess (computing)VoltageTemperature measurementMechanical engineeringThermal resistanceThermalComposite materialComputer scienceStructural engineeringMechanicsEngineeringElectrical engineeringComputer vision

Abstract

fetched live from OpenAlex

A three-dimensional transient heat transfer model is developed for a sequential joining process (resistance welding) applied on thermoplastic composites. This process involves with moving a voltage source along a heating element that conducts the power throughout a resistive mesh, generating heat and melts and bounds two composite surfaces. The model developed here is used to predict the spatial and temporal variations in the current and temperature over the weld seam for different set of input variables. The model integrates both the resistive and thermal behaviours of components involved. The significance of this modeling approach is that it captures the movement of the electrical connection, simulating a sequential joining process along a continuous weld seam. The modeling results are compared with experimental data obtained by thermocouples and infrared camera, and accurately predict the trend of variations in weld temperature.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.270
Teacher spread0.254 · 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.

Study designSimulation or modeling
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

Citations1
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueVolume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stress Analysis, and Failure Prevention ConferenceSame topicElectronic Packaging and Soldering TechnologiesFrench-language works237,207