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Record W2065673153 · doi:10.1115/imece2011-63741

Deformation and Stress Analysis of the Fullerene by Super Element

2011· article· en· W2065673153 on OpenAlexaff
Masoud Nasiri Sarvi, Mohammad Taghi Ahmadian, Ahmad Barari

Bibliographic record

VenueVolume 2: Biomedical and Biotechnology Engineering; Nanoengineering for Medicine and Biology · 2011
Typearticle
Languageen
FieldChemistry
TopicFullerene Chemistry and Applications
Canadian institutionsLakeridge Health
Fundersnot available
KeywordsFullereneMaterials scienceNano-Deformation (meteorology)Ball (mathematics)Stress (linguistics)Finite element methodBearing (navigation)Boundary element methodDiscrete element methodElement (criminal law)Computer scienceNode (physics)Structural engineeringComposite materialNanotechnologyMechanicsEngineeringGeometryArtificial intelligencePhysicsMathematics

Abstract

fetched live from OpenAlex

Accurate prediction of static and dynamic response of nano structures is one of the important interests of scientists in the last decade. Nano bearing as an important part of nano machines has been extensively implemented in recognizing and disassembling cancerous cells and building molecular support structures for strengthening bones. For this reason, Molecular Dynamic Method and some experimental methods are implemented in this area. As nano ball bearing is one of the most important components of nano machines, a large number of studies are concentrated to analyze it statically and dynamically. In this paper, a Fullerene is simulated by a spherical super element whose stress, deformation and natural frequency are calculated. The Fullerene is considered to be the C60 which is properly similar with a 66 surface-node spherical super element. In this study the mechanical properties of the fullerene and boundary conditions of the nano ball bearing under loading are introduced and stress and natural frequency of a fullerene under concentrated load is presented with two different strategies, super element and conventional elements. Compatible findings of these two methods validate and confirm the results. Findings indicate that applying 1 super element for the simulation of the fullerene leads to same results as implementing 154764 conventional 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.494

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 studies0.0000.001
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueVolume 2: Biomedical and Biotechnology Engineering; Nanoengineering for Medicine and BiologySame topicFullerene Chemistry and ApplicationsFrench-language works237,207