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Steffen Plunder

Publications and source records attributed to Steffen Plunder.

7 recordsLinked to original sources

A new comparison principle for discrete Volterra equations with an application to convex sweeping processes with infinite delays

Comparison principles for Volterra equations play a role analogous to maximum principles in PDEs: they provide positivity and stability information on the solution and allow one to control the output of bounded inputs. In the continuous setting, such results often rely on Laplace-transform or spectral methods (see Gripenberg, Londen, and Staffans, Volterra Integral and Functional Equations, 1990). However, these tools are not uniform in the discretization step $h$ hence fail in discrete or semi-discrete approximations. The present note introduces a resolvent-free argument yielding uniform $L^\infty(0,T)$-bounds for non-negative kernels. Compactness is a key ingredient in order to show existence of sweeping processes. While in the classical framework it is well established, adding an infinite distribution of delays complicates greatly the obtaining of such a result. In a first step we show a general energy decay estimate, which is then used to establish compactness. The argument is carried out in the discrete setting and that necessitates the introduction of the new comparison principle. In the classical sweeping process the previous position of the particle lies on the boundary of the constraint set, staying $O(h)$ close to the next projection point ($h$ is the discretization step). Our delay model projects the particle's averaged (by a unit measure kernel) past positions to the constraint set. Numerical simulations show that the projected point can lie at $O(1)$ distance from the convex set's boundary.

math.NA

Boundary geometry controls a topological defect transition that determines lumen nucleation in embryonic development

Topological defects determine the collective properties of anisotropic materials. How their configurations are controlled is not well understood however, especially in 3D. In living matter moreover, 2D defects have been linked to biological functions, but the role of 3D polar defects is unclear. Combining computational and experimental approaches, we investigate how confinement geometry controls surface-aligned polar fluids, and what biological role 3D polar defects play in tissues interacting with extracellular boundaries. We discover a charge-preserving transition between 3D defect configurations driven by boundary geometry and independent of material parameters, and show that defect positions predict the locations where fluid-filled lumina -- structures essential for development -- form within the confined polar tissue of the mouse embryo. Experimentally perturbing embryo shape beyond the transition point, we moreover create additional lumina at predicted defect locations. Our work reveals how boundary geometry controls polar defects, and how embryos use this mechanism for shape-dependent lumen formation. We expect this defect control principle to apply broadly to systems with orientational order.

cond-mat.soft

Macroscopic effects of an anisotropic Gaussian-type repulsive potential: nematic alignment and spatial effects

Elongated particles in dense systems often exhibit alignment due to volume exclusion interactions, leading to packing configurations. Traditional models of collective dynamics typically impose this alignment phenomenologically, neglecting the influence of volume exclusion on particle positions. In this paper, we derive nematic alignment from an anisotropic repulsive potential, focusing on a Gaussian-type potential and first-order dynamics for the particles. By analyzing larger particle systems and performing a hydrodynamic limit, we uncover the effects of anisotropy on both particle density and direction. Our findings reveal that while particle density evolves independently of direction, anisotropy slows down nonlinear diffusion. The direction dynamics are affected by the particles' position and involve complex transport and diffusion processes, with different behaviors for oblate and prolate particles. The key to obtaining these results lies in recent advancements in Generalized Collision Invariants offered by Degond, Frouvelle and Liu (KRM 2022).

math.AP

Cell seeding dynamics in a porous scaffold material designed for meniscus tissue regeneration

We study the dynamics of a seeding experiment where a fibrous scaffold material is colonized by two types of cell populations. The specific application that we have in mind is related to the idea of meniscus tissue regeneration. In order to support the development of a promising replacement material, we discuss certain rate equations for the densities of human mesenchymal stem cells and chondrocytes and for the production of collagen-containing extracellular matrix. For qualitative studies, we start with a system of ordinary differential equations and refine then the model to include spatial effects of the underlying nonwoven scaffold structure. Numerical experiments as well as a complete set of parameters for future benchmarking are provided.

math.NA

Convergence proof for first-order position-based dynamics: An efficient scheme for inequality constrained ODEs

NVIDIA researchers have pioneered an explicit method, position-based dynamics (PBD), for simulating systems with contact forces, gaining widespread use in computer graphics and animation. While the method yields visually compelling real-time simulations with surprising numerical stability, its scientific validity has been questioned due to a lack of rigorous analysis. In this paper, we introduce a new mathematical convergence analysis specifically tailored for PBD applied to first-order dynamics. Utilizing newly derived bounds for projections onto uniformly prox-regular sets, our proof extends classical compactness arguments. Our work paves the way for the reliable application of PBD in various scientific and engineering fields, including particle simulations with volume exclusion, agent-based models in mathematical biology or inequality-constrained gradient-flow models.

math.NA

The mean-field limit for particle systems with uniform full-rank constraints

We consider a particle system with uniform coupling between a macroscopic component and individual particles. The constraint for each particle is of full rank, which implies that each movement of the macroscopic component leads to a movement of all particles and vice versa. Skeletal muscle tissues share a similar property which motivates this work. We prove convergence of the mean-field limit, well-posedness and a stability estimate for the mean-field PDE.

math.AP

Coupled Systems of Differential-Algebraic and Kinetic Equations with Application to the Mathematical Modelling of Muscle Tissue

We consider a coupled system composed of a linear differential-algebraic equation (DAE) and a linear large-scale system of ordinary differential equations where the latter stands for the dynamics of numerous identical particles. Replacing the discrete particles by a kinetic equation for a particle density, we obtain in the mean-field limit the new class of partially kinetic systems. We investigate the influence of constraints on the kinetic theory of those systems and present necessary adjustments. We adapt the mean-field limit to the DAE model and show that index reduction and the mean-field limit commute. As a main result, we prove Dobrushin's stability estimate for linear systems. The estimate implies convergence of the mean-field limit and provides a rigorous link between the particle dynamics and their kinetic description. Our research is inspired by mathematical models for muscle tissue where the macroscopic behaviour is governed by the equations of continuum mechanics, often discretised by the finite element method, and the microscopic muscle contraction process is described by Huxley's sliding filament theory. The latter represents a kinetic equation that characterises the state of the actin-myosin bindings in the muscle filaments. Linear partially kinetic systems are a simplified version of such models, with focus on the constraints.

math.NA