Relativistic Lattice Boltzmann Method

Numerical solver for a relativistic gas in flat space time. See for details the preprint at https://doi.org/10.21203/rs.3.rs-1558550/v

Crowdflow – diluted pedestrian dynamics in the Metaforum building of Eindhoven University of Technology

This is a dataset of pedestrian trajectories recorded on a nearly 24/7 schedule in a landing in the Metaforum building at Eindhoven University of Technology. The data acquisition spanned over a year and, overall, about 250.000 trajectories have been collected. Depth imaging data has been first obtained via an overhead Microsoft Kinect sensor, then ad hoc localization algorithms and PTV-like tracking have been employed to estimate the trajectory of individual heads (cf. publication). The current dataset includes 20.000 trajectories from pedestrians walking undisturbed i.e. in diluted conditions (individuals are walking alone in the facility). There are 10.000 trajectories of pedestrians crossing the landing entering from the left hand side (file: "left-to-right.ssv") and 10.000 trajectories of pedestrians entering in the opposite side (file: "right-to-left.ssv", right-left reference is given according to the publication linked). The purpose of the dataset is to enable ensemble analyses of diluted pedestrian motion. The trajectories are in the following table format: Pid Rstep X Y X_SG Y_SG U_SG V_SG (Pid: unique identifier of a trajectory - Rstep: identifier of the timestep (starts from zero, the first 5 and last 5 samples are eliminated as typically less precise)) - X,Y: position in Cartesian coordinates (in meters) - X_SG,Y_SG: position in Cartesian coordinates after Savizky-Golay smoothing (in meters, cf. paper) - U_SG, V_SG: velocity in Cartesian coordinates after Savizky-Golay smoothing (in meters per second, cf. paper)

Data from numerical simulations of topological structure and dynamics of three-dimensional active nematics

The data in this dataset are the result of numerical simulations aimed at understanding the topology and dynamics of active nematics. In the manuscript a comparison between numerical and experimental results is also presented

Heavy particles in turbulent flows RM-2007-GRAD-2048

Heavy point-wise Lagrangian particle evolution in homogeneous and isotropic turbulent velocity field from a 2048 cubed DNS. Trajectory length: 4720 LAGR_DT Total number of particles per subset: 3184 * 64 [ Subset : Stokes number ] [ St0..2 : 0.0 ][ St3..5 : 0.16 ][ St6..8 : 0.6 ][ St9..11 : 1.0 ][ St12 : 2.0 ][ St13 : 3.0 ][ St14 : 5.0 ] [ St15 : 10.0 ][ St16 : 20.0 ][ St17 : 30.0 ][ St18 : 40.0 ][ St19 : 50.0 ][ St20 : 70.0

Supplementary material from "A multi-component lattice Boltzmann approach to study the causality of plastic events"

Using a multi-component lattice Boltzmann (LB) model, we perform fluid kinetic simulations of confined and concentrated emulsions. The system presents the phenomenology of soft-glassy materials, including a Herschel–Bulkley rheology, yield stress, ageing and long relaxation time scales. Shearing the emulsion in a Couette cell below the yield stress results in plastic topological re-arrangement events which follow established empirical seismic statistical scaling laws, making this system a good candidate to study the physics of earthquakes. One characteristic of this model is the tendency for events to occur in avalanche clusters, with larger events, triggering subsequent re-arrangements. While seismologists have developed statistical tools to study correlations between events, a process to confirm causality remains elusive. We present here, a modification to our LB model, involving small, fast vibrations applied to individual droplets, effectively a macroscopic forcing, which results in the arrest of the topological plastic re-arrangements. This technique provides an excellent tool for identifying causality in plastic event clusters by examining the evolution of the dynamics after ‘stopping’ an event, and then checking which subsequent events disappear.This article is part of the theme issue ‘Fluid dynamics, soft matter and complex systems: recent results and new methods’

Supporting data and movies from A multi-component lattice Boltzmann approach to study the causality of plastic events

The file contains the plotting and analysis scripts and relevant movies for supporting the article

Fluctuations in pedestrian dynamics routing choices

Set of pedestrian trajectories recorded during the GLOW festival in Eindhoven (The Netherlands), between November 9th and 16th 2019. The data has been used in the analysis described in the paper "Fluctuations in pedestrian dynamics routing choices". PNAS Nexus, pgac16

Supplementary material from "The collective effect of finite-sized inhomogeneities on the spatial spread of populations in two dimensions"

The dynamics of a population expanding into unoccupied habitat has been primarily studied for situations in which growth and dispersal parameters are uniform in space or vary in one dimension. Here, we study the influence of finite-sized individual inhomogeneities and their collective effect on front speed if randomly placed in a two-dimensional habitat. We use an individual-based model to investigate the front dynamics for a region in which dispersal or growth of individuals is reduced to zero (obstacles) or increased above the background (hotspots), respectively. In a regime where front dynamics is determined by a local front speed only, a principle of least time can be employed to predict front speed and shape. The resulting analytical solutions motivate an event-based algorithm illustrating the effects of several obstacles or hotspots. We finally apply the principle of least time to large heterogeneous environments by solving the Eikonal equation numerically. Obstacles lead to a slow-down that is dominated by the number density and width of obstacles, but not by their precise shape. Hotspots result in a speedup, which we characterize as function of hotspot strength and density. Our findings emphasize the importance of taking the dimensionality of the environment into account

Massively parallel implementation and approaches to simulate quantum dynamics using Krylov subspace techniques

We have developed an application and implemented parallel algorithms in order to provide a computational framework suitable for massively parallel supercomputers to study the unitary dynamics of quantum systems. We use renowned parallel libraries such as PETSc/SLEPc combined with high-performance computing approaches in order to overcome the large memory requirements to be able to study systems whose Hilbert space dimension comprises over 9 billion independent quantum states. Moreover, we provide descriptions of the parallel approach used for the three most important stages of the simulation: handling the Hilbert subspace basis, constructing a matrix representation for a generic Hamiltonian operator and the time evolution of the system by means of the Krylov subspace methods. We employ our setup to study the evolution of quasidisordered and clean many-body systems, focussing on the return probability and related dynamical exponents: the large system sizes accessible provide novel insights into their thermalization properties

Data and code: Oceanic frontal divergence alters phytoplankton competition and distribution

Data and codes for the publication "Oceanic frontal divergence alters phytoplankton competition and distribution'