MétaCan
Menu
Back to cohort
Record W2086035193 · doi:10.5139/jksas.2013.41.8.597

Thermomechanical Analysis of Composite Structures in Pyrolysis and Ablation Environments

2013· article· en· W2086035193 on OpenAlex
Youn Gyu Choi, Sung Jun Kim, Eui Sup Shin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Korean Society for Aeronautical & Space Sciences · 2013
Typearticle
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsPyrolysisMaterials scienceEndothermic processAblationComposite numberComposite materialShrinkageFinite element methodCoupling (piping)Structural engineeringAdsorptionChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

본 논문에서는 열분해 및 삭마 환경의 복합재 구조물에 대한 열기계적 연계 해석을 수행하였다. 열분해 과정의 재료 밀도 감소, 기공 가스 확산, 흡열 반응 에너지와 삭마 과정에서의 표면 침식 효과 등을 고려하였다. 상용 유한요소 코드에 교차 연계 알고리듬을 적용하여 완전 연계된 열 해석 및 구조 해석 인터페이스를 구성하였다. 수치 실험을 통해서 탄소/페놀릭 복합재료의 기본적인 열분해 및 삭마 특성을 분석하였다. 특히, 화학적 및 기계적 삭마에 영향을 미치는 주요 인자에 따른 표면 침식량 등을 비교하였다. 또한, 열분해 과정의 수축 또는 팽창 변형도가 재료의 열기계적 거동에 미치는 영향도 검토하였다. A coupled thermomechanical analysis of composite structures in pyrolysis and ablation environments is performed. The pyrolysis and ablation models include the effects of mass loss, pore gas diffusion, endothermic reaction energy, surface recession, etc. The thermal and structural analysis interface is based upon a staggered coupling algorithm by using a commercial finite element code. The characteristics of the proposed method are investigated through numerical experiments with carbon/phenolic composites. The numerical studies are carried out to examine the surface recession rate by chemical and mechanical ablation. In addition, the effects of shrinkage or intumescence during the pyrolysis process are shown.

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.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.247
Teacher spread0.236 · 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