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Dynamics representation of mechanical systems for time-stepping problems

2025· article· en· W7106121430 on OpenAlexafffund

Bibliographic record

VenueMechanism and Machine Theory · 2025
Typearticle
Languageen
FieldMathematics
TopicNumerical methods for differential equations
Canadian institutionsMcGill University
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsKinematicsRobustness (evolution)Nonlinear systemInertial frame of referenceControl theory (sociology)Representation (politics)Flexibility (engineering)Mechanical systemPosition (finance)

Abstract

fetched live from OpenAlex

This paper introduces a novel two-stage time-stepping framework for mechanical systems. The method separates the update of configuration and dynamics: configuration is advanced using independent (joint) velocities, while the dynamic equations are formulated using a dependent set of velocities—specifically, the velocity of body-fixed points and the angular velocity of each rigid body. These dependent velocities are projected onto the joint space to ensure that kinematic constraints are satisfied at the position level, eliminating the need for constraint stabilization techniques. A key advantage of this decomposition is that it enables a compact and transparent expression of the nonlinear inertial terms, which can then be integrated either explicitly or implicitly within the same framework. This flexibility makes the approach particularly well suited for time-stepping schemes, including those used in challenging scenarios such as unilateral contact problems. Numerical results illustrate how different integration strategies and velocity representations affect the stability and accuracy of the solution, highlighting the robustness of the proposed method. • New formulation for time stepping. • Separation of dynamics (impulse–momentum), and kinematics (velocity–position) steps. • Constraints are satisfied without stabilization techniques. • Detailed analysis of nonlinear inertial terms in explicit and implicit time stepping. • Well suited for the development of stable time-stepping methods in systems.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.640
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.039
GPT teacher head0.340
Teacher spread0.301 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2025
Admission routes2
Has abstractyes

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