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The response function of a network of springs and masses, an elastodynamic network, is the matrix valued function $W(\omega)$, depending on the frequency $\omega$, mapping the displacements of some accessible or terminal nodes to the net…

数学物理 · 物理学 2015-06-01 Fernando Guevara Vasquez , Graeme W. Milton , Daniel Onofrei

We study the properties and stability of networks with arbitrary Laplacian coupling. Classic approaches to studying networked systems require unrealistic assumptions, including homogeneous node dynamics, one-dimensional and undirected…

适应与自组织系统 · 物理学 2026-04-21 Nina Kastendiek , Jakob Niehues , Frank Hellmann

In the dynamic analysis of structural engineering systems, it is common practice to introduce damping models to reproduce experimentally observed features. These models, for instance Rayleigh damping, account for the damping sources in the…

计算工程、金融与科学 · 计算机科学 2015-03-25 Pierre Jehel , Régis Cottereau

We give a complete characterization of the possible response matrices at a fixed frequency of n-terminal electrical networks of inductors, capacitors, resistors and grounds, and of n-terminal discrete linear elastodynamic networks of…

材料科学 · 物理学 2009-11-13 Graeme W. Milton , Pierre Seppecher

Athermal models of disordered fibrous networks are highly useful for studying the mechanics of elastic networks composed of stiff biopolymers. The underlying network architecture is a key aspect that can affect the elastic properties of…

软凝聚态物质 · 物理学 2016-01-20 Albert James Licup , Abhinav Sharma , Fred C. MacKintosh

In the inelastic time history analyses of structures in seismic motion, part of the seismic energy that is imparted to the structure is absorbed by the inelastic structural model, and Rayleigh damping is commonly used in practice as an…

经典物理 · 物理学 2013-09-12 Pierre Jehel , Pierre Léger , Adnan Ibrahimbegovic

In this paper, we present a data-driven approach to identify second-order systems, having internal Rayleigh damping. This means that the damping matrix is given as a linear combination of the mass and stiffness matrices. These systems…

最优化与控制 · 数学 2019-10-03 Igor Pontes Duff , Pawan Goyal , Peter Benner

Elastic structures can be designed to exhibit precise, complex, and exotic functions. While recent work has focused on the quasistatic limit governed by force balance, the mechanics at a finite driving rate are governed by Newton's…

软凝聚态物质 · 物理学 2024-12-17 Marc Berneman , Daniel Hexner

We study the elasticity of random stiff fiber networks. The elastic response of the fibers is characterized by a central force stretching stiffness as well as a bending stiffness that acts transverse to the fiber contour. Previous studies…

软凝聚态物质 · 物理学 2007-10-02 Claus Heussinger , Erwin Frey

We consider a damped linear hyperbolic system modelling the propagation of pressure waves in a network of pipes. Well-posedness is established via semi-group theory and the existence of a unique steady state is proven in the absence of…

数值分析 · 数学 2016-05-11 Herbert Egger , Thomas Kugler

The problem of characterizing the structure of an elastic network constrained to lie on a frozen curved surface appears in many areas of science and has been addressed by many different approaches, most notably, extending linear elasticity…

生物物理 · 物理学 2022-08-31 Yinan Dong , Roya Zandi , Alex Travesset

We study stationary distributions in the context of stochastic reaction networks. In particular, we are interested in complex balanced reaction networks and reduction of such networks by assuming a set of species (called non-interacting…

概率论 · 数学 2024-02-06 Linard Hoessly , Carsten Wiuf , Panqiu Xia

In the first part of this paper, we propose new optimization-based methods for the computation of preferred (dense, sparse, reversible, detailed and complex balanced) linearly conjugate reaction network structures with mass action dynamics.…

动力系统 · 数学 2014-07-15 Matthew D. Johnston , David Siegel , Gábor Szederkényi

Analyzing nonlinear conformational relaxation dynamics in elastic networks corresponding to two classical motor proteins, we find that they respond by well-defined internal mechanical motions to various initial deformations and that these…

生物大分子 · 定量生物学 2007-06-13 Yuichi Togashi , Alexander S. Mikhailov

The need to build a link between the structure of a complex network and the dynamical properties of the corresponding complex system (comprised of multiple low dimensional systems) has recently become apparent. Several attempts to tackle…

混沌动力学 · 物理学 2012-06-18 Michael Small , Kevin Judd , Thomas Stemler

In this paper, we address the problem of dynamic network embedding, that is, representing the nodes of a dynamic network as evolving vectors within a low-dimensional space. While the field of static network embedding is wide and…

社会与信息网络 · 计算机科学 2023-11-17 Ed Davis , Ian Gallagher , Daniel John Lawson , Patrick Rubin-Delanchy

Power system coherency refers to the phenomenon that machines in a power network exhibit similar frequency responses after disturbances, and is foundational for model reduction and control design. Despite abundant empirical observations,…

系统与控制 · 电气工程与系统科学 2025-11-11 Yixuan Liu , Yingzhu Liu , Pengcheng You

We study the role of connectivity on the linear and nonlinear elastic behavior of amorphous systems using a two-dimensional random network of harmonic springs as a model system. A natural characterization of these systems arises in terms of…

软凝聚态物质 · 物理学 2015-05-13 M. Wyart , H. Liang , A. Kabla , L. Mahadevan

Dimension reduction is a common strategy to study non-linear dynamical systems composed by a large number of variables. The goal is to find a smaller version of the system whose time evolution is easier to predict while preserving some of…

动力系统 · 数学 2022-06-23 Marina Vegué , Vincent Thibeault , Patrick Desrosiers , Antoine Allard

The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean…

分子网络 · 定量生物学 2009-11-10 Stuart Kauffman , Carsten Peterson , Björn Samuelsson , Carl Troein
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