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Sauro Succi

Publications and source records attributed to Sauro Succi.

At least 73 records · Page 4Linked to original sources
arXiv2024

Lattice Boltzmann simulation of deformable fluid-filled bodies: progress and perspectives

With the rapid development of studies involving droplet microfluidics, drug delivery, cell detection, and microparticle synthesis, among others, many scientists have invested significant efforts to model the flow of these fluid-filled bodies. Motivated by the intricate coupling between hydrodynamics and the interactions of fluid-filled bodies, several methods have been developed. The objective of this review is to present a compact foundation of the methods used in the literature in the context of lattice Boltzmann methods. For hydrodynamics, we focus on the lattice-Boltzmann method due to its specific ability to treat time and spatial-dependent boundary conditions and to incorporate new physical models in a computationally efficient way. We split the existing methods into two groups with regard to the interfacial boundary: fluid-structure and fluid-fluid methods. The fluid-structure methods are characterised by the coupling between fluid dynamics and mechanics of the flowing body, often used in applications involving membranes and similar flexible solid boundaries. We further divide fluid-structure-based methods into two subcategories, those which treat the fluid-structure boundary as a continuum medium and those that treat it as a discrete collection of individual springs and particles. Next, we discuss the fluid-fluid methods, particularly useful for the simulations of fluid-fluid interfaces. We focus on models for immiscible droplets and their interaction in a suspending fluid and describe benchmark tests to validate the models for fluid-filled bodies.

cond-mat.soft↗
arXiv2024

Three Carleman routes to the quantum simulation of classical fluids

We discuss the Carleman approach to the quantum simulation of classical fluids, as applied to i) Lattice Boltzmann (CLB), ii) Navier-Stokes (CNS) and iii) Grad (CG) formulations of fluid dynamics. CLB shows excellent convergence properties, but it is plagued by nonlocality which results in an exponential depth of the corresponding circuit with the number of Carleman variables. The CNS offers a dramatic reduction of the number Carleman variables, which might lead to a viable depth, provided locality can be preserved and convergence can be achieved with a moderate number of iterates also at sizeable Reynolds numbers. Finally it is argued that CG might combine the best of CLB and CNS.

physics.flu-dyn↗
arXiv2024

Measuring arrangement and size distributions of flowing droplets in microchannels through deep learning

In microfluidic systems, droplets undergo intricate deformations as they traverse flow-focusing junctions, posing a challenging task for accurate measurement, especially during short transit times. This study investigates the physical behavior of droplets within dense emulsions in diverse microchannel geometries, specifically focusing on the impact of varying opening angles within the primary channel and injection rates of fluid components. Employing a sophisticated droplet tracking tool based on deep-learning techniques, we analyze multiple frames from flow-focusing experiments to quantitatively characterize droplet deformation in terms of ratio between maximum width and height and propensity to form liquid with hexagonal crystalline order. Our findings reveal the existence of an optimal opening angle where shape deformations are minimal and crystal-like arrangement is maximal. Variations of fluid injection rates are also found to affect size and packing fraction of the emulsion in the exit channel. This paper offers insights into deformations, size and structure of fluid emulsions relative to microchannel geometry and other flow-related parameters captured through machine learning, with potential implications for the design of microchips utilized in cellular transport and tissue engineering applications.

physics.flu-dyn↗
arXiv2024

High-order thread-safe lattice Boltzmann model for HPC turbulent flow simulations

We present a highly-optimized thread-safe lattice Boltzmann model in which the non-equilibrium part of the distribution function is locally reconstructed via recursivity of Hermite polynomials. Such a procedure allows the explicit incorporation of non-equilibrium moments of the distribution up to the order supported by the lattice. Thus, the proposed approach increases accuracy and stability at low viscosities without compromising performances and amenability to parallelization with respect to standard lattice Boltzmann models. The high-order thread-safe LB is tested on two types of turbulent flows, namely the turbulent channel flow at $Re_τ=180$ and the axisymmetric turbulent jet at $Re = 7000$, it delivers results in excellent agreement with reference data (both DNS, theory, and experiments) and a) achieves peak performances ($\sim 5 \; TeraFlop/s$ and an arithmetic intensity of $\sim 7\; FLOP/byte$ on single GPU) by significantly reducing the memory footprint, b) retains the algorithmic simplicity of standard lattice Boltzmann computing and c) allows to perform stable simulations at vanishingly low viscosities. Our findings open attractive prospects for high-performance simulations of realistic turbulent flows on GPU-based architectures. Such expectations are confirmed by the excellent agreement among lattice Boltzmann, experimental, and DNS reference data.

physics.flu-dyn↗
arXiv2024

Revisiting the Lindemann's criterion from a minimal viscosity perspective

A revisiting of the Lindemann criterion under the recently established minimal viscosity formulation is proposed which uncovers intriguing insights into the melting process. The approach suggests that melting involves competition between the electron rest energy and the thermal one caused by temperature increase when considering a defect-free crystal structure. However, when accounting for the role of vacancies in the melting process, the analysis suggests that the key competing factors are the thermal energy and the one needed for vacancy migration. The estimated value of the Lindemann constant, in this case, is close to the reported values and with recent simulations studying the correlation between Born and Lindemann melting criteria.

cond-mat.other↗
arXiv2024

Lattice Boltzmann-Carleman quantum algorithm and circuit for fluid flows at moderate Reynolds number

We present a quantum computing algorithm for fluid flows based on the Carleman-linearization of the Lattice Boltzmann (LB) method. First, we demonstrate the convergence of the classical Carleman procedure at moderate Reynolds numbers, namely for Kolmogorov-like flows. Then we proceed to formulate the corresponding quantum algorithm, including the quantum circuit layout and analyze its computational viability. We show that, at least for moderate Reynolds numbers between 10 and 100, the Carleman-LB procedure can be successfully truncated at second order, which is a very encouraging result. We also show that the quantum circuit implementing the single time-step collision operator has a fixed depth, regardless of the number of lattice sites. However, such depth is of the order of ten thousands quantum gates, meaning that quantum advantage over classical computing is not attainable today, but could be achieved in the near-mid term future. The same goal for the multi-step version remains however an open topic for future research.

quant-ph↗
arXiv2023

Quantum computing for fluids: where do we stand?

We present a pedagogical introduction to the current state of quantum computing algorithms for the simulation of classical fluids. Different strategies, along with their potential merits and liabilities, are discussed and commented on.

physics.comp-ph↗
arXiv2023

Modeling realistic multiphase flows using a non-orthogonal multiple-relaxation-time lattice Boltzmann method

In this paper, we develop a three-dimensional multiple-relaxation-time lattice Boltzmann method (MRT-LBM) based on a set of non-orthogonal basis vectors. Compared with the classical MRT-LBM based on a set of orthogonal basis vectors, the present non-orthogonal MRT-LBM simplifies the transformation between the discrete velocity space and the moment space, and exhibits better portability across different lattices. The proposed method is then extended to multiphase flows at large density ratio with tunable surface tension, and its numerical stability and accuracy are well demonstrated by some benchmark cases. Using the proposed method, a practical case of a fuel droplet impacting on a dry surface at high Reynolds and Weber numbers is simulated and the evolution of the spreading film diameter agrees well with the experimental data. Furthermore, another realistic case of a droplet impacting on a super-hydrophobic wall with a cylindrical obstacle is reproduced, which confirms the experimental finding of Liu \textit{et al.} [``Symmetry breaking in drop bouncing on curved surfaces," Nature communications 6, 10034 (2015)] that the contact time is minimized when the cylinder radius is comparable with the droplet cylinder.

physics.flu-dyn↗
arXiv2023

Single Relaxation Time and Multiple Revised Matrix Lattice Boltzmann Simulations of Forced Isotropic Turbulence

The single relaxation time (SRT) and the revised matrix (RM) lattice Boltzmann models are compared for simulations of three dimensional forced isotropic turbulence with resolutions of 128^3 and 256^3, respectively. The forcing technique by Guo et al. (2002) is applied with the two models using the same parameters and conditions. Some new aspects and results have been confirmed such as the superiority of the MRT model to simulate forced turbulence and using the Courant-Friedichs-Lewy condition (CFL) (Courant et al., 1967) by multiplying the velocity input with the coefficient CFL < 1.0 to overcome the stability problem and divide the output velocity data by the same CFL. The initial velocity field is chosen as u(x; 0) = 0 and the force is injected at low wave-numbers with a fixed forcing amplitude to 10^-4 for all cases. The single relaxation time is set to 0.503 in all SRT simulations. Results show that the obtained turbulent velocity fields yield universal characteristics as proven in previous theoretical, experimental and numerical studies. The Taylor Reynolds number for the simulations are found as SRT: R = 62 and MRT : R = 65 for 1283 and SRT: R= 107 and MRT: R = 82 for the case of 2563, respectively. To test the weak incompressibility for the SRT model in comparison to the MRT model, the density probability distribution function (PDF) is depicted and it is found that ? is almost unity at all timesteps for the MRT case, while a clear disturbance about unity is observed for the SRT case.

physics.flu-dyn↗
arXiv2023

Extreme flow simulations reveal skeletal adaptations of deep-sea sponges

Since its discovery, the deep-sea glass sponge Euplectella aspergillum has attracted interest in its mechanical properties and beauty. Its skeletal system is composed of amorphous hydrated silica and is arranged in a highly regular and hierarchical cylindrical lattice that begets exceptional flexibility and resilience to damage. Structural analyses dominate the literature, but hydrodynamic fields that surround and penetrate the sponge have remained largely unexplored. Here we address an unanswered question: whether, besides improving its mechanical properties, the skeletal motifs of E. aspergillum underlie the optimization of the flow physics within and beyond its body cavity. We use extreme flow simulations based on the 'lattice Boltzmann' method, featuring over fifty billion grid points and spanning four spatial decades. These in silico experiments reproduce the hydrodynamic conditions on the deep-sea floor where E. aspergillum lives. Our results indicate that the skeletal motifs reduce the overall hydrodynamic stress and support coherent internal recirculation patterns at low flow velocity. These patterns are arguably beneficial to the organism for selective filter feeding and sexual reproduction11,12. The present study reveals mechanisms of extraordinary adaptation to live in the abyss, paving the way towards further studies of this type at the intersection between fluid mechanics, organism biology and functional ecology.

physics.flu-dyn↗
arXiv2023

Logarithmic, Fractal and Volume-Law Entanglement in a Kitaev chain with long-range hopping and pairing

Thanks to their prominent collective character, long-range interactions promote information spreading and generate forms of entanglement scaling, which cannot be observed in traditional systems with local interactions. In this work, we study the asymptotic behavior of the entanglement entropy for Kitaev chains with long-range hopping and pairing couplings decaying with a power law of the distance. We provide a fully-fledged analytical and numerical characterization of the asymptotic growth of the ground state entanglement in the large subsystem size limit, finding that the truly non-local nature of the model leads to an extremely rich phenomenology. Most significantly, in the strong long-range regime, we discovered that the system ground state may have a logarithmic, fractal, or volume-law entanglement scaling, depending on the value of the chemical potential and on the strength of the power law decay.

quant-ph↗
arXiv2023

Shapes and dynamic regimes of a polar active fluid droplet under confinement

Active droplets are artificial microswimmers built from a liquid dispersion by microfluidic tools and showing self-propelled motion. These systems hold particular interest for mimicking biological phenomena, such as some aspects of cell locomotion and collective behaviors of bacterial colonies, as well as for the design of droplet-based biologically inspired materials, such as engineered tissues. Growing evidence suggests that geometrical confinement crucially affects their morphology and motility, but the driving physical mechanisms are still poorly understood. Here we study the effect of activity on a droplet containing a contractile polar fluid confined within microfluidic channels of various sizes. We find a surprising wealth of shapes and dynamic regimes, whose mechanics is regulated by a subtle interplay between contractile stress, droplet elasticity and microchannel width. They range from worm-like and cell-like shaped droplets displaying an oscillating behavior within wider channels to bullet-shaped droplets exhibiting rectilinear motion in narrower slits. Our findings support the view that geometrical confinement can provide a viable strategy to control and predict the propulsion direction of active droplets. It would be of interest to look for analogues of these motility modes in biological cells or in synthetic active matter.

cond-mat.soft↗
arXiv2023

Learning of viscosity functions in rarefied gas flows with physics-informed neural networks

The prediction non-equilibrium transport phenomena in disordered media is a difficult problem for conventional numerical methods. An example of a challenging problem is the prediction of gas flow fields through porous media in the rarefied regime, where resolving the six-dimensional Boltzmann equation or its numerical approximations is computationally too demanding. Physics-informed neural networks (PINNs) have been recently proposed as an alternative to conventional numerical methods, but remain very close to the Boltzmann equation in terms of mathematical formulation. Furthermore, there has been no systematic study of neural network designs on the performance of PINNs. In this work, PINNs are employed to predict the velocity field of a rarefied gas flow in a slit at increasing Knudsen numbers according to a generalized Stokes phenomenological model using an effective viscosity function. We found that activation functions with limited smoothness result in orders of magnitude larger errors than infinitely differentiable functions and that the AdamW is by far the best optimizer for this inverse problem. The design was found to be robust from Knudsen numbers ranging from 0.1 to 10. Our findings stand as a first step towards the use of PINNs to investigate the dynamics of non-equilibrium flows in complex geometries.

physics.flu-dyn↗
arXiv2023

Multiscale Hybrid Modeling of Proteins in Solvent: SARS-CoV2 Spike Protein as test case for Lattice Boltzmann -- All Atom Molecular Dynamics Coupling

Physiological solvent flows surround biological structures triggering therein collective motions. Notable examples are virus/host-cell interactions and solvent-mediated allosteric regulation. The present work describes a multiscale approach joining the Lattice Boltzmann fluid dynamics (for solvent flows) with the all-atom atomistic molecular dynamics (for proteins) to model functional interactions between flows and molecules. We present, as an applicative scenario, the study of the SARS-CoV-2 virus spike glycoprotein protein interacting with the surrounding solvent, modeled as a mesoscopic fluid. The equilibrium properties of the wild-type spike and of the Alpha variant in implicit solvent are described by suitable observables. The mesoscopic solvent description is critically compared to the all-atom solvent model, to quantify the advantages and limitations of the mesoscopic fluid description.

physics.comp-ph↗
arXiv2023

From quantum foam to graviton condensation: the Zel'dovich route

Based on a previous ansatz by Zel'dovich for the gravitational energy of virtual particle-antiparticle pairs, supplemented with the Holographic Principle, we estimate the vacuum energy in a fairly reasonable agreement with the experimental values of the Cosmological Constant. We further highlight a connection between Wheeler's quantum foam and graviton condensation, as contemplated in the quantum $N$-portrait paradigm, and show that such connection also leads to a satisfactory prediction of the value of the cosmological constant. The above results suggest that the "unnaturally" small value of the cosmological constant may find a quite "natural" explanation once the nonlocal perspective of the large $N$-portrait gravitational condensation is endorsed.

physics.gen-ph↗
arXiv2023

Models of polymer solutions in electrified jets and solution blowing

Fluid flows hosting electrical phenomena make the subject of a fascinating and highly interdisciplinary scientific field. In recent years, the extraordinary success of electrospinning and solution blowing technologies for the generation of polymer nanofibers has motivated vibrant research aiming at rationalizing the behavior of viscoelastic jets under applied electric fields or other stretching fields including gas streams. Theoretical models unveiled many original aspects in the underpinning physics of polymer solutions in jets, and provided useful information to improve experimental platforms. This article reviews advances in the theoretical description and numerical simulation of polymer solution jets in electrospinning and solution blowing. Instability phenomena of electrical and hydrodynamic origin are highlighted, which play a crucial role in the relevant flow physics. Specifications leading to accurate and computationally viable models are formulated. Electrohydrodynamic modeling, theories for the jet bending instability, recent advances in Lagrangian approaches to describe the jet flow, including strategies for dynamic refinement of simulations, and effects of strong elongational flow on polymer networks are reviewed. Finally, the current challenges and future perspectives of the field are outlined and discussed, including the task of correlating the physics of the jet flows with the properties of realized materials, as well as the development of multiscale techniques for modelling viscoelastic jets.

physics.flu-dyn↗
arXiv2023

Thread-safe lattice Boltzmann for high-performance computing on GPUs

We present thread-safe, highly-optimized lattice Boltzmann implementations, specifically aimed at exploiting the high memory bandwidth of GPU-based architectures. At variance with standard approaches to LB coding, the proposed strategy, based on the reconstruction of the post-collision distribution via Hermite projection, enforces data locality and avoids the onset of memory dependencies, which may arise during the propagation step, with no need to resort to more complex streaming strategies. The thread-safe lattice Boltzmann achieves peak performances, both in two and three dimensions and it allows to sensibly reduce the allocated memory ( tens of GigaBytes for order billions lattice nodes simulations) by retaining the algorithmic simplicity of standard LB computing. Our findings open attractive prospects for high-performance simulations of complex flows on GPU-based architectures.

cs.DC↗