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Record W2163734601 · doi:10.1109/jmems.2008.921673

Passive Reduced-Order Macromodeling Algorithm for Microelectromechanical Systems

2008· article· en· W2163734601 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Microelectromechanical Systems · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicModel Reduction and Neural Networks
Canadian institutionsWestern UniversityUniversity of Calgary
FundersCMC Microsystems
KeywordsKrylov subspaceMicroelectromechanical systemsFinite element methodReduction (mathematics)DiscretizationModel order reductionSubspace topologyPassivityAlgorithmOrder (exchange)Computer scienceApplied mathematicsMathematicsControl theory (sociology)Mathematical analysisEngineeringPhysicsIterative methodGeometryElectrical engineeringStructural engineering

Abstract

fetched live from OpenAlex

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, we present a passive reduced-order macromodeling algorithm for second-order dynamic systems of linear microelectromechanical systems (MEMS) devices. The proposed reduction algorithm is based on congruent transformations. The system equations of MEMS devices, given by finite-element methods (FEMs), are converted to state-space forms that are compatible with passive Krylov subspace methods. To achieve this, a modified matrix equation is proposed for second-order MEMS dynamics. In addition, the generalized procedure is provided for first-order heat transfer problems and second-order structure dynamic problems to ensure that the discretized FEM system satisfies all the necessary conditions to guarantee the passivity of the reduced-order system. Finally, numerical examples are provided to demonstrate the validity of the proposed passive reduction technique. <formula formulatype="inline"><tex>$\hfill$</tex> </formula>[2006-0224] </para>

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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