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Record W4403275622 · doi:10.1061/jsendh.steng-13653

Numerically Stable Integrated Simulation Method for Coupled Dynamic Systems

2024· article· en· W4403275622 on OpenAlex
Shangzhang Wang, Xu Huang, Oh‐Sung Kwon, Bin Wu, Ge Yang

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 Structural Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsHudbay Minerals (Canada)University of Toronto
Fundersnot available
KeywordsComputer scienceDynamic simulationSimulation

Abstract

fetched live from OpenAlex

Compared to monolithic simulation methods, integrated simulation methods allow decomposition of a large and complex system into several subsystems whose behavior can either be numerically or experimentally captured considering unique capabilities of existing analysis tools. Therefore, they have been applied to multi-physics problems and analysis of large-scale complex structural systems. However, there is still a lack of a robust integrated simulation method that can be easily implemented in existing analysis tools and also ensure numerical stability. In this study, a novel integrated simulation method is proposed that not only allows seamless data exchange based on standard input and output of subsystem programs but also can achieve unconditional stability by adjusting the time integration coefficients for the interface layers between the decomposed subsystems. The stability of the proposed method is mathematically evaluated through the energy approach. Numerical evaluations of the accuracy and stability limits of the proposed method are also presented. Two application examples are provided to demonstrate potential applications of the proposed approach.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score0.557

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 communication0.0000.000
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 head0.007
GPT teacher head0.264
Teacher spread0.257 · 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