Cover Image

Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sharma, Harsh, Najera-Flores, David A., Todd, Michael D., Kramer, Boris
Format:	Preprint
Published:	2024
Subjects:	Computational Engineering, Finance, and Science Dynamical Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Port-Hamiltonian multibody dynamics: Lagrangian formulation, consistent interconnection, structure-preserving simulation and index-reduction
by: Latussek, Lisa, et al.
Published: (2026)

Data repairing and resolution enhancement using data-driven modal decomposition and deep learning
by: Hetherington, A., et al.
Published: (2024)

Port-Hamiltonian formulation and structure-preserving discretization of hyperelastic strings
by: Kinon, Philipp L., et al.
Published: (2023)

PySHRED: A Python package for SHallow REcurrent Decoding for sparse sensing, model reduction and scientific discovery
by: Ye, David, et al.
Published: (2025)

A fluid--peridynamic structure model of deformation and damage of microchannels
by: Wang, Ziyu, et al.
Published: (2025)

Deep learning-based predictive modelling of transonic flow over an aerofoil
by: Chen, Li-Wei, et al.
Published: (2024)

Relevance of the Basset history term for Lagrangian particle dynamics
by: Urizarna-Carasa, Julio, et al.
Published: (2024)

Meshless projection model-order reduction via reference spaces for smoothed-particle hydrodynamics
by: Rodriguez, Steven N., et al.
Published: (2025)

Energy-consistent integration of mechanical systems based on Livens principle
by: Kinon, Philipp L., et al.
Published: (2023)

Multi-scale topology optimization of porous heat sinks with voided lattice structure using a two-layer Darcy-Forchheimer model
by: Saito, Tatsuki, et al.
Published: (2025)

Synthetic Lagrangian Turbulence by Generative Diffusion Models
by: Li, Tianyi, et al.
Published: (2023)

A Lagrangian method for solving the spherical shallow water equations using power diagrams
by: Caplan, Philip, et al.
Published: (2025)

Deep learning modelling of manufacturing and build variations on multi-stage axial compressors aerodynamics
by: Bruni, Giuseppe, et al.
Published: (2023)

Enabling topography-resolving structural dynamic contact simulation
by: Linder, Hendrik D., et al.
Published: (2026)

Mixed formulation and structure-preserving discretization of Cosserat rod dynamics in a port-Hamiltonian framework
by: Kinon, Philipp L., et al.
Published: (2025)

Reduced order modelling of Hopf bifurcations for the Navier-Stokes equations through invariant manifolds
by: Colombo, Alessio, et al.
Published: (2025)

A manifold learning approach to nonlinear model order reduction of quasi-static problems in solid mechanics
by: Scheunemann, Lisa, et al.
Published: (2024)

Model-based deep reinforcement learning for accelerated learning from flow simulations
by: Weiner, Andre, et al.
Published: (2024)

Multiphase Flow Simulation of Blow-by and Fuel-in-Oil Dilution via the Piston Ring Pack Using the CFD Level-Set Method
by: Antony, Patrick, et al.
Published: (2024)

Density-based topology optimization for turbulent fluid flow using the standard k-epsilon RANS model with wall-functions imposed through an implicit wall penalty formulation
by: Bayat, Amirhossein, et al.
Published: (2026)

Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference
by: McQuarrie, Shane A., et al.
Published: (2025)

Extreme Event Precursor Prediction in Turbulent Dynamical Systems via CNN-Augmented Recurrence Analysis
by: Agarwal, Rahul, et al.
Published: (2025)

C(NN)FD -- a deep learning framework for turbomachinery CFD analysis
by: Bruni, Giuseppe, et al.
Published: (2023)

Beyond development: Challenges in deploying machine learning models for structural engineering applications
by: Esteghamati, Mohsen Zaker, et al.
Published: (2024)

STONet: A neural operator for modeling solute transport in micro-cracked reservoirs
by: Haghighat, Ehsan, et al.
Published: (2024)

Accelerated Computational Fluid Dynamics Simulations of Microfluidic Devices by Exploiting Higher Levels of Abstraction
by: Takken, Michel, et al.
Published: (2023)

Circularity of Thermodynamical Material Networks: Indicators, Examples, and Algorithms
by: Zocco, Federico
Published: (2022)

Topological Separation of Vortices
by: Zafar, Adeel, et al.
Published: (2024)

A weakly compressible SPH method for RANS simulation of wall-bounded turbulent flows
by: Wang, Feng, et al.
Published: (2025)

Investigate the efficiency of incompressible flow simulations on CPUs and GPUs with BSAMR
by: Liu, Dewen, et al.
Published: (2024)

Hydrodynamics of bubble flow through a porous medium with applications to packed bed reactors
by: Nagrani, Pranay P., et al.
Published: (2023)

Data-Assisted Non-Intrusive Model Reduction for Forced Nonlinear Finite Elements Models
by: Cenedese, Mattia, et al.
Published: (2023)

Development of a Cost-Effective Simulation Tool for Loss of Flow Accident Transients in High-Temperature Gas-cooled Reactors
by: Liu, Bo, et al.
Published: (2025)

Fast Surrogate Models for Adaptive Aircraft Trajectory Prediction in En route Airspace
by: Pepper, Nick, et al.
Published: (2026)

Bayesian Model Selection for Complex Flows of Yield Stress Fluids
by: Rinkens, Aricia, et al.
Published: (2026)

On the use of high order central difference schemes for differential equation based wall distance computations
by: Kakumani, Hemanth Chandra Vamsi, et al.
Published: (2021)

Gaussian Field Representations for Turbulent Flow: Compression, Scale Separation, and Physical Fidelity
by: Shenoy, Dhanush Vittal, et al.
Published: (2026)

Physics-Informed Machine Learning Approach in Augmenting RANS Models Using DNS Data and DeepInsight Method on FDA Nozzle
by: Geshani, Hossein, et al.
Published: (2025)

Lightweight equivariant model for efficient machine learning interatomic potentials
by: Yang, Ziduo, et al.
Published: (2023)

A Diffusion MRI model for axonal damage quantification based on axial diffusivity reduction in axons: a Monte Carlo simulation study
by: Sharma, Nand
Published: (2024)