arXiv subjects

Daniel Floryan

Publications and source records attributed to Daniel Floryan.

At least 19 recordsLinked to original sources

arXiv2025

Acoustic-Assisted Fabrication of Thin Shells with Spatially Distributed Imperfections

Thin-shell structures, found in biological systems such as beetle carapaces and widely used in aerospace, civil, and mechanical engineering, achieve remarkable strength-to-mass ratio given their slenderness and curved geometries. However, their load-bearing capacity is highly sensitive to geometric imperfections, which are often unavoidable during fabrication and can trigger subcritical buckling. Silicone-based hemispherical domes have served as an experimental modal system to study this phenomenon, yet prior work has largely focused on localized dimples or flat imperfections, failing to capture the spatially distributed nature of real-world imperfection patterns. Here, we introduce an acoustic-assisted method for fabricating thin shells with spatially distributed, vibrational mode-shaped imperfections. Silicone is cast onto a thick elastic mold excited by a speaker, and vibration-induced flow during curing creates thickness variations. High-speed imaging and microCT scanning reveal accumulation of material at the antinodes of the mold's vibrational modes. We show that imperfection geometry can be tuned by acoustic frequency, while their amplitude increases with acoustic volume. Buckling experiments demonstrate significant reductions in critical pressure, offering a scalable platform to study and tune imperfection-sensitive mechanics. Beyond shell mechanics, we offer a scalable and tunable fabrication method for patterning soft materials in applications ranging from morphable surfaces to bioinspired design.

physics.app-ph↗

arXiv2025

Propulsion of a flexible foil in a wavy flow: resonance, antiresonance, and destructive self-interference

Swimming and flying animals demonstrate remarkable adaptations to diverse flow conditions in their environments. In this study, we aim to advance the fundamental understanding of the interaction between flexible bodies and heterogeneous flow conditions. We develop a linear inviscid model of an elastically mounted foil that passively pitches in response to a prescribed heaving motion and an incoming flow that consists of a traveling wave disturbance superposed on a uniform flow. In addition to the well-known resonant response, the wavy flow induces an antiresonant response for non-dimensional phase velocities near unity due to the emergence of non-circulatory forces that oppose circulatory forces. We also find that the wavy flow destructively interferes with itself, effectively rendering the foil a low-pass filter. The net result is that the waviness of the flow always improves thrust and efficiency when the wavy flow is of a different frequency than the prescribed heaving motion. Such a simple statement cannot be made when the wavy flow and heaving motion have the same frequency. Depending on the wavenumber and relative phase, the two may work in concert or in opposition, but they do open the possibility of simultaneous propulsion and net energy extraction from the flow, which, according to our model, is impossible in a uniform flow.

physics.flu-dyn↗

arXiv2025

Effects of symmetry and hydrodynamics on the cohesion of groups of swimmers

When groups of inertial swimmers move together, hydrodynamic interactions play a key role in shaping their collective dynamics, including the cohesion of the group. To explore how these interactions influence group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer. Focusing on symmetric triangular, diamond, and circular group arrangements, we investigate whether passive hydrodynamics alone can promote cohesive behavior, and what role symmetry of the group plays. While small symmetric (and even asymmetric) groups can be cohesive, larger groups typically are not, instead breaking apart into smaller, self-organized subgroups that are cohesive. Notably, we discover circular arrangements of swimmers that chase each other around a circle, resembling the milling behavior of natural fish schools; we call this hydrodynamic milling. Hydrodynamic milling is cohesive in the sense that it is a fixed point of a particular Poincar\'e map, but it is unstable, especially to asymmetric perturbations. Our findings suggest that while passive hydrodynamics alone cannot sustain large-scale cohesion indefinitely, controlling interactions between subgroups, or controlling the behavior of only the periphery of a large group, could potentially enable stable collective behavior with minimal active input.

physics.flu-dyn↗

arXiv2024

Particle Re-Suspension in Two-Phase Dispersed Rayleigh-B\'{e}nard Convection

The process by which particles are entrained by the fluid in Rayleigh-B\'{e}nard convection is studied by means of particle-resolved numerical simulations in a periodic domain at a Rayleigh number of $10^7$. The fluid Prandtl number is 1 and the particle-to-fluid density ratio 1.1. The results show that the horizontal velocity field near the bottom of the cell accumulates particles in heaps, or `dunes', at the base of ascending plumes. The dunes deflect the incoming flow, conferring to it a vertical velocity component which entrains the particles up the dune and into the plume. An experimental observation of this mechanism was briefly reported by Solomatov et al. (Earth Planet. Sc. Lett. 120, 387, 1993) but has not been considered further in the literature. By its very nature, such a process cannot be simulated by the point particle model. The final particle load carried by the convection depends both on the available gravitational energy of the fluid and on the effectiveness of the re-suspension mechanism.

physics.flu-dyn↗

arXiv2024

On instabilities in neural network-based physics simulators

When neural networks are trained from data to simulate the dynamics of physical systems, they encounter a persistent challenge: the long-time dynamics they produce are often unphysical or unstable. We analyze the origin of such instabilities when learning linear dynamical systems, focusing on the training dynamics. We make several analytical findings which empirical observations suggest extend to nonlinear dynamical systems. First, the rate of convergence of the training dynamics is uneven and depends on the distribution of energy in the data. As a special case, the dynamics in directions where the data have no energy cannot be learned. Second, in the unlearnable directions, the dynamics produced by the neural network depend on the weight initialization, and common weight initialization schemes can produce unstable dynamics. Third, injecting synthetic noise into the data during training adds damping to the training dynamics and can stabilize the learned simulator, though doing so undesirably biases the learned dynamics. For each contributor to instability, we suggest mitigative strategies. We also highlight important differences between learning discrete-time and continuous-time dynamics, and discuss extensions to nonlinear systems.

cs.LG↗

arXiv2024

Group cohesion and passive dynamics of a pair of inertial swimmers with three-dimensional hydrodynamic interactions

When swimming animals form cohesive groups, they can reap several benefits. Our understanding of collective animal motion has traditionally been driven by models based on phenomenological behavioral rules, but more recent work has highlighted the critical importance of hydrodynamic interactions among a group of inertial swimmers. To study how hydrodynamic interactions affect group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer. In a group of two model swimmers, we observe several dynamical phases, including following, divergence, collision, and cohesion. Our results illustrate when cohesive groups can passively form through hydrodynamic interactions alone, and when other action is needed to maintain cohesion. We find that misalignment between swimmers makes passive cohesion less likely; nevertheless, it is possible for a cohesive group to form through passive hydrodynamic interactions alone. We also find that the geometry of swimmers critically affects the group dynamics due to its role in how swimmers sample the velocity gradient of the flow.

physics.flu-dyn↗

arXiv2023

Self-similar, spatially localized structures in turbulent pipe flow from a data-driven wavelet decomposition

This study aims to extract and characterize structures in fully developed pipe flow at a friction Reynolds number of $\text{Re}_\tau = 12\,400$. To do so, we employ data-driven wavelet decomposition (DDWD) [D.~Floryan and M.~D.~Graham, PNAS 118, e2021299118 (2021)], a method that combines features of proper orthogonal decomposition and wavelet analysis in order to extract energetic and spatially localized structures from data. We apply DDWD to streamwise velocity signals measured separately via a thermal anemometer at 40 wall-normal positions. The resulting localized velocity structures, which we interpret as being reflective of underlying eddies, are self-similar across streamwise extents of 40 wall units to one pipe radius, and across wall-normal positions from $y^+=350$ to $y/R=1$. Notably, the structures are similar in shape to Meyer wavelets. Projections of the data onto the DDWD wavelet subspaces are found to be self-similar as well, but in Fourier space; the bounds of self-similarity are the same as before, except streamwise self-similarity starts at a larger length scale of $450$ wall units. The evidence of self-similarity provided in this study lends further support to Townsend's attached eddy hypothesis, although we note that the self-similar structures are detected beyond the log layer and extend to large length scales.

physics.flu-dyn↗

arXiv2022

A fundamental limit on energy savings in controlled channel flow, and how to beat it

We derive a limit on energy savings in controlled channel flow. For flow in a channel driven by pressure, shear, or any combination of the two, and controlled via wall transpiration or spanwise wall motion, the uncontrolled laminar state requires the least net energy (accounting for the energetic cost of control). Thus, the optimal control solution is to laminarize the flow. Additionally, we raise the possibility of beating this limit. By simultaneously applying wall transpiration and spanwise wall motion, we show that it may be possible to attain sustained sub-laminar energy expenditure in a controlled flow. We provide a necessary design criterion for net energy savings.

physics.flu-dyn↗

arXiv2022

Propulsive performance of oscillating plates with time-periodic flexibility

We use small-amplitude inviscid theory to study the swimming performance of a flexible flapping plate with time-varying flexibility. The stiffness of the plate oscillates at twice the frequency of the kinematics in order to maintain a symmetric motion. Plates with constant and time-periodic stiffness are compared over a range of mean plate stiffness, oscillating stiffness amplitude, and oscillating stiffness phase for isolated heaving, isolated pitching, and combined leading edge kinematics. We find that there is a profound impact of oscillating stiffness on the thrust, with a lesser impact on propulsive efficiency. Thrust improvements of up to 35% relative to a constant-stiffness plate are observed. For large enough frequencies and amplitudes of the stiffness oscillation, instabilities emerge. The unstable regions may confer enhanced propulsive performance; this hypothesis must be verified via experiments or nonlinear simulations.

physics.flu-dyn↗

arXiv2021

Data-driven discovery of intrinsic dynamics

Dynamical models underpin our ability to understand and predict the behavior of natural systems. Whether dynamical models are developed from first-principles derivations or from observational data, they are predicated on our choice of state variables. The choice of state variables is driven by convenience and intuition, and in the data-driven case the observed variables are often chosen to be the state variables. The dimensionality of these variables (and consequently the dynamical models) can be arbitrarily large, obscuring the underlying behavior of the system. In truth, these variables are often highly redundant and the system is driven by a much smaller set of latent intrinsic variables. In this study, we combine the mathematical theory of manifolds with the representational capacity of neural networks to develop a method that learns a system's intrinsic state variables directly from time series data, and also learns predictive models for their dynamics. What distinguishes our method is its ability to reduce data to the intrinsic dimensionality of the nonlinear manifold they live on. This ability is enabled by the concepts of charts and atlases from the theory of manifolds, whereby a manifold is represented by a collection of patches that are sewn together -- a necessary representation to attain intrinsic dimensionality. We demonstrate this approach on several high-dimensional systems with low-dimensional behavior. The resulting framework provides the ability to develop dynamical models of the lowest possible dimension, capturing the essence of a system.

cs.LG↗

arXiv2020

Discovering multiscale and self-similar structure with data-driven wavelets

Many materials, processes, and structures in science and engineering have important features at multiple scales of time and/or space; examples include biological tissues, active matter, oceans, networks, and images. Explicitly extracting, describing, and defining such features are difficult tasks, at least in part because each system has a unique set of features. Here, we introduce an analysis method that, given a set of observations, discovers an energetic hierarchy of structures localized in scale and space. We call the resulting basis vectors a "data-driven wavelet decomposition". We show that this decomposition reflects the inherent structure of the dataset it acts on, whether it has no structure, structure dominated by a single scale, or structure on a hierarchy of scales. In particular, when applied to turbulence---a high-dimensional, nonlinear, multiscale process---the method reveals self-similar structure over a wide range of spatial scales, providing direct, model-free evidence for a century-old phenomenological picture of turbulence. This approach is a starting point for the characterization of localized hierarchical structures in multiscale systems, which we may think of as the building blocks of these systems.

physics.flu-dyn↗

arXiv2019

Large-amplitude oscillations of foils for efficient propulsion

Large-amplitude oscillations of foils have been observed to yield greater propulsive efficiency than small-amplitude oscillations. Using scaling relations and experiments on foils with peak-to-peak trailing edge amplitudes of up to two chord lengths, we explain why this is so. In the process, we reveal the importance of drag, specifically how it can significantly reduce the efficiency, and how this effect depends on amplitude. The scaling relations and experimental data also reveal a fundamental tradeoff between high thrust and high efficiency, where the drag also plays a crucial role.

physics.flu-dyn↗

arXiv2019

Distributed flexibility in inertial swimmers

We study a linear inviscid model of a passively flexible swimmer with distributed flexibility, calculating its propulsive performance and optimal distributions of flexibility. The frequencies of actuation and mean stiffness ratios we consider span a large range, while the mass ratio is fixed to a low value representative of swimmers. We present results showing how the trailing edge deflection, thrust coefficient, power coefficient, and efficiency vary with frequency, mean stiffness, and stiffness distribution. Swimmers with distributed flexibility have the same qualitative features as those with uniform flexibility. Significant gains in thrust can be made, however, by tuning the stiffness such that a resonant response is triggered, or by concentrating stiffness towards the leading edge if resonance cannot be triggered. To minimize power, the opposite is true. Meaningful gains in efficiency can be made at low frequencies by concentrating stiffness away from the leading edge, since doing so induces efficient travelling wave kinematics. We also speculate on the effects of a finite Reynolds number in the form of streamwise drag. The drag adds an offset to the net thrust produced by the swimmer, causing efficiency-maximizing distributions of flexibility to tend towards thrust-maximizing ones, representative of what is found in nature.

physics.flu-dyn↗

arXiv2019

Connections between resonance and nonlinearity in swimming performance of a flexible heaving plate

We investigate the role of resonance in finite-amplitude swimming of a flexible flat plate in a viscous fluid. The role of resonance in performance remains unclear for two reasons: i) a lack of definition of resonance for the fully-coupled fluid-structure interaction system in a viscous flow, and ii) the presence of nonlinear effects, which makes it difficult to disentangle resonant and non-resonant mechanisms in finite-amplitude swimming. We address point i) and provide an unambiguous definition for system resonance by computing global linear stability modes of the fully-coupled fluid-structure interaction system that account for the viscous fluid, the plate, and the coupling between them. We then resolve point ii) by considering high-fidelity nonlinear simulations of systematically increased amplitude. By comparing the results for different amplitudes with one another and with the linear stability modes, we separate linear and/or resonant effects from nonlinear and/or non-resonant effects. Resonant behavior is observed over a wide range of plate stiffnesses, with peaks in trailing-edge motion and thrust occurring near the resonant frequency defined by the global linear analysis. The peaks broaden and weaken with increasing heave amplitude, consistent with an increased damping effect from the fluid. At the same time, non-resonant mechanisms are present at large heave amplitudes. The input power exhibits qualitatively different dynamics at large heave amplitudes compared to smaller heave amplitudes, where resonance dominates. Moreover, leading-edge separation is present for stiff plates at large heave amplitudes, which can drastically alter the performance characteristics from what one would expect through linear predictions.

physics.flu-dyn↗

arXiv2019

Swimmers' wake structures are not reliable indicators of swimming performance

The structure of swimmers' wakes is often assumed to be an indicator of swimming performance, that is, how momentum is produced and energy is consumed. Here, we discuss three cases where this assumption fails. In general, great care should be taken in deriving any conclusions about swimming performance from the wake flow pattern.

physics.flu-dyn↗

arXiv2019

Efficient cruising for swimming and flying animals is dictated by fluid drag

Many swimming and flying animals are observed to cruise in a narrow range of Strouhal numbers, where the Strouhal number ${St = 2fA/U}$ is a dimensionless parameter that relates stroke frequency $f$, amplitude $A$, and forward speed $U$. Dolphins, sharks, bony fish, birds, bats, and insects typically cruise in the range $0.2 < St < 0.4$, which coincides with the Strouhal number range for maximum efficiency as found by experiments on heaving and pitching airfoils. It has therefore been postulated that natural selection has tuned animals to use this range of Strouhal numbers because it confers high efficiency, but the reason why this is so is still unclear. Here, by using simple scaling arguments, we argue that the Strouhal number for peak efficiency is largely determined by fluid drag on the fins and wings.

physics.flu-dyn↗

arXiv2018

Clarifying the relationship between efficiency and resonance for flexible inertial swimmers

We study a linear inviscid model of a passively flexible swimmer, calculating its propulsive performance, eigenvalues, and eigenfunctions with an eye towards clarifying the relationship between efficiency and resonance. The frequencies of actuation and stiffness ratios we consider span a large range, while the mass ratio is mostly fixed to a low value representative of swimmers. We present results showing how the trailing edge deflection, thrust coefficient, power coefficient, and efficiency vary in the stiffness-frequency plane. The trailing edge deflection, thrust coefficient, and power coefficient show sharp ridges of resonant behaviour for mid-to-high frequencies and stiffnesses, whereas the efficiency does not show resonant behaviour anywhere. For low frequencies and stiffnesses, the resonant peaks smear together and the efficiency is high. In this region, flutter modes emerge, inducing travelling wave kinematics which make the swimmer more efficient. We also consider the effects of a finite Reynolds number in the form of streamwise drag. The drag adds an offset to the net thrust produced by the swimmer, causing resonant peaks to appear in the efficiency (as observed in experiments in the literature).

physics.flu-dyn↗

arXiv2018

Bio-inspired underwater propulsors

Here we present a general overview of bio-inspired propulsion. We identify the major types of aquatic swimmers (oscillatory, undulatory, pulsatile, and drag-based) and break down their mechanisms for thrust production (drag-based, lift-based, added mass, and momentum injection). For each swimmer, we (1) discuss wake characteristics; (2) derive expressions for thrust and efficiency; and (3) design a specific bio-inspired aquatic vehicle concept. This document will be a book chapter, which at the moment is unpublished.

physics.flu-dyn↗