Skip to content
DraconiticResearch
Search Sources API
201,818 studies31 sourcesUpdated 48 min ago
PreprintCC BY 4.0arXiv

Stochastic Geometrically Exact Beams: Continuous-Time Geometric Principles and Variational Discretizations

Abstract

Geometrically exact beams naturally arise in physical phenomena and engineering practice for modeling flexible structures, such as soft robotic manipulators and DNA structures. To the best of our knowledge, there appear to be no geometric integrators for stochastic geometrically exact beams in a variational formulation. In this paper, we introduce variational principles for the dynamics of stochastic geometrically exact beams, in both continuous- and discrete-time settings. By introducing perturbations via stochastic potentials and stochastic kinematics, we derive the equations of motion from a variational viewpoint. The resulting stochastic geometric integrators simultaneously discretize time and space in a parallel manner, which provides a distributed computational framework for solving the stochastic dynamics of complex beam systems. In particular, the proposed integrators are shown to be a stochastic extension of the well-known deterministic staggered leapfrog scheme for the wave equation, and also a stochastic extension of Yee's scheme for spatially one-dimensional computational electromagnetism. Numerical results are shown to demonstrate the effectiveness of the proposed approaches.

Related

  1. Pressure-robustness by commuting interpolation operators for Stokes discretizations with continuous pressures
    Philip L. Lederer, Theresa Vock
    arXivPreprintarXiv licenceFull textNumerical analysis & scientific computingarXiv
  2. Metric gradient flows and variational principles
    Alberto Domínguez Corella
    arXivPreprintarXiv licenceFull textAnalysis & PDEsarXiv
  3. Generic variational principles for supinf problems with constraints
    D. Gaumont, D. Kamburova, J. P. Revalski
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsOptimisation & controlarXiv
  4. A new perspective in linear Cauchy Elasticity: variational minimum principles for statics, dynamics, and heterogeneous materials
    Amit Acharya
    arXivPreprintCC BY 4.0Full textAnalysis & PDEsOptimisation & controlarXiv
  5. Rough variational principles and applications to adjoint systems
    Ruiao Hu, Melvin Leok
    arXivPreprintCC BY 4.0Full textNumerical analysis & scientific computingOptimisation & controlarXiv
BibTeX
@misc{du2026stochastic,
  title = {{Stochastic Geometrically Exact Beams: Continuous-Time Geometric Principles and Variational Discretizations}},
  author = {Minghang Du and François Gay-Balmaz and Tianzhi Li and Donghua Shi},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.14717},
  eprint = {2610.14717},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.14717},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Stochastic Geometrically Exact Beams: Continuous-Time Geometric Principles and Variational Discretizations
AU  - Minghang Du
AU  - François Gay-Balmaz
AU  - Tianzhi Li
AU  - Donghua Shi
PY  - 2026
DA  - 2026/10/10
PB  - arXiv
DO  - 10.48550/arxiv.2610.14717
UR  - https://arxiv.org/abs/2610.14717
AB  - Geometrically exact beams naturally arise in physical phenomena and engineering practice for modeling flexible structures, such as soft robotic manipulators and DNA structures. To the best of our knowledge, there appear to be no geometric integrators for stochastic geometrically exact beams in a variational formulation. In this paper, we introduce variational principles for the dynamics of stochastic geometrically exact beams, in both continuous- and discrete-time settings. By introducing perturbations via stochastic potentials and stochastic kinematics, we derive the equations of motion from a variational viewpoint. The resulting stochastic geometric integrators simultaneously discretize time and space in a parallel manner, which provides a distributed computational framework for solving the stochastic dynamics of complex beam systems. In particular, the proposed integrators are shown to be a stochastic extension of the well-known deterministic staggered leapfrog scheme for the wave equation, and also a stochastic extension of Yee's scheme for spatially one-dimensional computational electromagnetism. Numerical results are shown to demonstrate the effectiveness of the proposed approaches.
ER  -