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#forces

ett innlegg1 deltaker0 innlegg i dag
Mark

We see the enemy’s intentions and attempts to advance, and it is important that each of these attempts is being thwarted thanks to the resilience of our units and active defense. #Russian army has fallen far short of its command’s expectations for this summer

#Kyiv has claimed success in holding off a Russian advance into northeastern Sumy Oblast

#Ukrainian #forces allegedly pinning down about 50,000 #RussianTroops in the sector.

kyivindependent.com/russias-su

The Kyiv Independent · Russia's summer offensive has fallen 'far short of expectations,' Zelensky saysAv Dmytro Basmat
#RussianAggression#StandWithUkraine
Rxiv mechanobio

📰 "Static friction of liquid marbles"
arxiv.org/abs/2506.20116 #Physics.Flu-Dyn #Cond-Mat.Soft #Adhesion #Forces

arXiv.orgStatic friction of liquid marblesLiquid marbles, droplets coated with a granular layer, are highly mobile as particles prevent capillary adhesion with the substrate. Yet, they exhibit static friction due to their granular shell, which resists rolling until it yields. This friction depends on the shell geometry and increases exponentially with grain density, indicating a logistic dependence of interparticle compressive forces on surface coverage, confirmed by yielding measurements in granular rafts. These results reveal the shell's dual role, and establish liquid marbles as a model system for probing granular raft mechanics.
Rxiv mechanobio

📰 "Effective interface forces to model boundary effects in a finite-size metamaterial through the reduced relaxed micromorphic model"
arxiv.org/abs/2504.21697 #Physics.App-Ph #Forces #Cell

arXiv.orgEffective interface forces to model boundary effects in a finite-size metamaterial through the reduced relaxed micromorphic modelWe use the reduced relaxed micromorphic model (RRMM) to capture the effective "bulk" dynamical response of finite size metamaterial specimens made out of a Labyrinthine unit cell. We show that for small finite-size specimens, boundary effects can play a major role, so that the RRMM needs an enrichment to capture the metamaterial's bulk response, as well as the boundary effects. A benchmark test is introduced to show that different metamaterial/ homogeneous material interfaces can drive completely different responses even if the bulk metamaterial remains the same. We show with no remaining doubts that the concept of "interface forces" must necessarily be introduced if one wants to model finite-size metamaterials in a homogenized framework.
Rxiv mechanobio

📰 "Chirality across scales in tissue dynamics"
arxiv.org/abs/2506.12276 #Physics.Bio-Ph #Cond-Mat.Soft #Dynamics #Forces #Cell

arXiv.orgChirality across scales in tissue dynamicsChiral processes that lack mirror symmetry pervade nature from enantioselective molecular interactions to the asymmetric development of organisms. An outstanding challenge at the interface between physics and biology consists in bridging the multiple scales between microscopic and macroscopic chirality. Here, we combine theory, experiments and modern inference algorithms to study a paradigmatic example of dynamic chirality transfer across scales: the generation of tissue-scale flows from subcellular forces. The distinctive properties of our microscopic graph model and the corresponding coarse-grained viscoelasticity are that (i) net cell proliferation is spatially inhomogeneous and (ii) cellular dynamics cannot be expressed as an energy gradient. To overcome the general challenge of inferring microscopic model parameters from noisy high-dimensional data, we develop a nudged automatic differentiation algorithm (NADA) that can handle large fluctuations in cell positions observed in single tissue snapshots. This data-calibrated microscopic model quantitatively captures proliferation-driven tissue flows observed at large scales in our experiments on fibroblastoma cell cultures. Beyond chirality, our inference algorithm can be used to extract interpretable graph models from limited amounts of noisy data of living and inanimate cellular systems such as networks of convection cells and flowing foams.
Rxiv mechanobio

📰 "$\mathcal{H}$-HIGNN: A Scalable Graph Neural Network Framework with Hierarchical Matrix Acceleration for Simulation of Large-Scale Particulate Suspensions"
arxiv.org/abs/2505.08174 #Physics.Comp-Ph #Forces #Matrix

arXiv.org$\mathcal{H}$-HIGNN: A Scalable Graph Neural Network Framework with Hierarchical Matrix Acceleration for Simulation of Large-Scale Particulate SuspensionsWe present a fast and scalable framework, leveraging graph neural networks (GNNs) and hierarchical matrix ($\mathcal{H}$-matrix) techniques, for simulating large-scale particulate suspensions, which have broader impacts across science and engineering. The framework draws on the Hydrodynamic Interaction Graph Neural Network (HIGNN) that employs GNNs to model the mobility tensor governing particle motion under hydrodynamic interactions (HIs) and external forces. HIGNN offers several advantages: it effectively captures both short- and long-range HIs and their many-body nature; it realizes a substantial speedup over traditional methodologies, by requiring only a forward pass through its neural networks at each time step; it provides explainability beyond black-box neural network models, through direct correspondence between graph connectivity and physical interactions; and it demonstrates transferability across different systems, irrespective of particles' number, concentration, configuration, or external forces. While HIGNN provides significant speedup, the quadratic scaling of its overall prediction cost (with respect to the total number of particles), due to intrinsically slow-decaying two-body HIs, limits its scalability. To achieve superior efficiency across all scales, in the present work we integrate $\mathcal{H}$-matrix techniques into HIGNN, reducing the prediction cost scaling to quasi-linear. Through comprehensive evaluations, we validate $\mathcal{H}$-HIGNN's accuracy, and demonstrate its quasi-linear scalability and superior computational efficiency. It requires only minimal computing resources; for example, a single mid-range GPU is sufficient for a system containing 10 million particles. Finally, we demonstrate $\mathcal{H}$-HIGNN's ability to efficiently simulate practically relevant large-scale suspensions of both particles and flexible filaments.
Rxiv mechanobio

📰 "Controlling the morphologies and dynamics in three-dimensional tissues"
arxiv.org/abs/2505.06168 #Physics.Bio-Ph #Cond-Mat.Soft #Dynamics #Forces #Cell

arXiv.orgControlling the morphologies and dynamics in three-dimensional tissuesA number of factors, such as, cell-cell interactions and self-propulsion of cells driven by cytoskeletal forces determine tissue morphologies and dynamics. To explore the interplay between these factors in controlling the dynamics at the tissue scale, we created a minimal three dimensional model in which short-range repulsive elastic forces account for cell-cell interactions. Self-propulsion is modeled as active uncorrelated random stochastic forces, with strength $μ$, that act on individual cells and is the only source of cell motility. Strikingly, variations in polydispersity in cell sizes ($Σ$) and cell elasticity ($E$), results in the formation of a variety of distinct ``phases", driven entirely by $μ$. At low $E$, the tissue behaves like a liquid, at all values of $Σ$, whereas at high $E$ and $Σ$, it has the characteristics of a glass. The tissue crystallizes at low $Σ$ provided $E$ exceeds a critical value. Over a narrow range of $E$ and $Σ$, that lies between the boundaries of the liquid and glass phase, the effective viscosity increases like in a glass as the cell density increases and saturates as the cells are compressed beyond a certain value, creating the viscosity saturation (VS) phase. The VS phase does not form in systems at finite temperature in which the dynamics satisfies the Fluctuation Dissipation Theorem. In the glass phase, the tissue exhibits aging (relaxation times depend on the waiting time) behavior at high $E$ values. Our findings provide a framework for designing tissues with tunable material properties by controlling the physical characteristics of cells.
Rxiv mechanobio

📰 "Effective interface forces to model boundary effects in a finite-size metamaterial through the reduced relaxed micromorphic model"
arxiv.org/abs/2504.21697 #Physics.App-Ph #Forces #Cell

arXiv.orgEffective interface forces to model boundary effects in a finite-size metamaterial through the reduced relaxed micromorphic modelWe use the reduced relaxed micromorphic model (RRMM) to capture the effective "bulk" dynamical response of finite size metamaterial specimens made out of a Labyrinthine unit cell. We show that for small finite-size specimens, boundary effects can play a major role, so that the RRMM needs an enrichment to capture the metamaterial's bulk response, as well as the boundary effects. A benchmark test is introduced to show that different metamaterial/ homogeneous material interfaces can drive completely different responses even if the bulk metamaterial remains the same. We show with no remaining doubts that the concept of "interface forces" must necessarily be introduced if one wants to model finite-size metamaterials in a homogenized framework.
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