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Record W7055183579

A Comparison Between 7- and 12-Parameter Shell Finite Elements for Large Deformation Analysis

2017· dissertation· en· W7055183579 on OpenAlexfundno aff

Bibliographic record

VenueOakTrust (Texas A&M University Libraries) · 2017
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
FundersHigh Performance Research Computing, Texas A and M UniversityConsejo Nacional de Ciencia y TecnologíaMcGill University
KeywordsFinite element methodShell (structure)ComputationDegrees of freedom (physics and chemistry)Interpolation (computer graphics)Displacement fieldDeformation (meteorology)Displacement (psychology)Transient response
DOInot available

Abstract

fetched live from OpenAlex

In this study two continuum shell finite elements are developed. The first one is based on the first-order shear deformation theory with seven independent parameters and the second one is based on the third-order thickness deformation theory with twelve independent parameters. Continuum shell finite elements are developed and utilized in the numerical simulations of isotropic, laminated composite, and functionally graded structures undergoing large deformations. High-order spectral interpolation of the field variables is used to avoid all forms of numerical locking, allowing the development of robust shell elements in a purely displacement based setting.\n\nThis thesis includes static and transient analysis of various structures using aforementioned two shell elements. This is the first time that the seven-parameter formulation is used to compute a full transient response of shell structures. Deflections and maximum stresses are computed and compared between the two formulations and, in some cases, also with the results obtained using commercial codes ANSYS and ABAQUS. Furthermore, the influence of the variation of the temperature through the thickness for functionally graded shells is studied. In all the simulations, static condensation of degrees of freedom associated with the internal nodes of the element is implemented, which allows us to reduce the computational time and make use of parallel computation when this feature is available. This makes the higher-order elements used computationally competitive with standard finite elements.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
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 communication0.0000.001
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 head0.022
GPT teacher head0.243
Teacher spread0.221 · 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 designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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