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Based on a Lie symmetry analysis, we construct a closed form solution to the kinematic part of the (partial differential) Cosserat equations describing the mechanical behavior of elastic rods. The solution depends on two arbitrary…

Analysis of PDEs · Mathematics 2016-10-12 Dominik Michels , Dmitry Lyakhov , Vladimir Gerdt , Zahid Hossain , Ingmar Riedel-Kruse , Andreas Weber

In this paper, the modelling strategy of a Cosserat rod element (CRE) is addressed systematically for 3-dimensional dynamical analysis of slender structures. We employ the exact nonlinear kinematic relationships in the sense of Cosserat…

Functional Analysis · Mathematics 2007-05-23 D. Q. Cao , Dongsheng Liu , Charles H. -T. Wang

This paper presents a numerical method for the simulation of fluid-structure interaction specifically tailored to interactions between Newtonian fluids and a large number of slender viscoelastic Cosserat rods. Because of their high…

Soft Condensed Matter · Physics 2022-01-13 S. Tschisgale , J. Fröhlich

We propose a method for the description and simulation of the nonlinear dynamics of slender structures modeled as Cosserat rods. It is based on interpreting the strains and the generalized velocities of the cross sections as basic variables…

Classical Physics · Physics 2022-10-11 G. G. Giusteri , E. Miglio , N. Parolini , M. Penati , R. Zambetti

Most computer algebra systems (CAS) support symbolic integration as core functionality. The majority of the integration packages use a combination of heuristic algebraic and rule-based (integration table) methods. In this paper, we present…

Symbolic Computation · Computer Science 2022-02-08 Shahriar Iravanian , Carl Julius Martensen , Alessandro Cheli , Shashi Gowda , Anand Jain , Yingbo Ma , Chris Rackauckas

This survey paper is aimed to describe a relatively new branch of symbolic dynamics which we call Arithmetic Dynamics. It deals with explicit arithmetic expansions of reals and vectors that have a "dynamical" sense. This means precisely…

Dynamical Systems · Mathematics 2007-05-23 Nikita Sidorov

When neural networks are used to solve differential equations, they usually produce solutions in the form of black-box functions that are not directly mathematically interpretable. We introduce a method for generating symbolic expressions…

Machine Learning · Computer Science 2020-11-05 Maysum Panju , Ali Ghodsi

Symbolic dynamics is a coarse-grained description of dynamics. By taking into account the ``geometry'' of the dynamics, it can be cast into a powerful tool for practitioners in nonlinear science. Detailed symbolic dynamics can be developed…

chao-dyn · Physics 2007-05-23 Bai-lin Hao

In spite of recent progress, soft robotics still suffers from a lack of unified modeling framework. Nowadays, the most adopted model for the design and control of soft robots is the piece-wise constant curvature model, with its consolidated…

Robotics · Computer Science 2018-10-25 Federico Renda , Frederic Boyer , Jorge Dias , Lakmal Seneviratne

There are many approaches to nonlinear SEM (structural equation modeling) but it seems that a rather straightforward approach using Isserlis' theorem has not yet been investigated although it allows the direct extension of the standard…

Computation · Statistics 2021-09-22 Reinhard Oldenburg

The spinning of slender viscous jets can be described asymptotically by one-dimensional models that consist of systems of partial and ordinary differential equations. Whereas the well-established string models possess only solutions for…

Mathematical Physics · Physics 2015-07-02 Walter Arne , Nicole Marheineke , Andreas Meister , Raimund Wegener

This paper presents a geometrically explicit formulation for Cosserat rods that unifies configuration-space and strain-based representations within a single modeling framework. The proposed method uses nodal configurations on the Lie group…

Numerical Analysis · Mathematics 2026-03-12 Lingxiao Xun , Brahim Tamadazte

We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or…

Data Analysis, Statistics and Probability · Physics 2016-08-03 Markus Quade , Markus Abel , Kamran Shafi , Robert K. Niven , Bernd R. Noack

We present a hybrid Eulerian-Lagrangian method for the direct simulation of three-dimensional, heterogeneous structures made of soft fibers and immersed in incompressible viscous fluids. Fiber-based organization of matter is pervasive in…

Computational Physics · Physics 2024-01-19 Arman Tekinalp , Yashraj Bhosale , Songyuan Cui , Fan Kiat Chan , Mattia Gazzola

We describe a neural-based method for generating exact or approximate solutions to differential equations in the form of mathematical expressions. Unlike other neural methods, our system returns symbolic expressions that can be interpreted…

Machine Learning · Computer Science 2020-11-16 Maysum Panju , Kourosh Parand , Ali Ghodsi

We consider a subsystem of the Special Cosserat Theory of Rods and construct an explicit form of its solution that depends on three arbitrary functions in (s,t) and three arbitrary functions in t. Assuming analyticity of the arbitrary…

Soft robots have many advantages over rigid robots thanks to their compliant and passive nature. However, it is generally challenging to model the dynamics of soft robots due to their high spatial dimensionality, making it difficult to use…

Robotics · Computer Science 2024-09-26 Tom Z. Jiahao , Ryan Adolf , Cynthia Sung , M. Ani Hsieh

This paper is concerned with the problem of estimating (interpolating and smoothing) the shape (pose and the six modes of deformation) of a slender flexible body from multiple camera measurements. This problem is important in both biology,…

The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of operators, is a hard problem in machine learning, both…

Machine Learning · Computer Science 2020-06-15 Vernon Austel , Cristina Cornelio , Sanjeeb Dash , Joao Goncalves , Lior Horesh , Tyler Josephson , Nimrod Megiddo

In this work we show how auxiliary variables can be used to give an efficient method involving symbolic manipulation and Picard iteration for approximating solutions of certain Volterra integral equations.

Classical Analysis and ODEs · Mathematics 2016-11-15 Hamid Semiyari , Douglas Shafer
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