Dr. Arnold J.T. Mathijssen, 8 July 2019
Collective functionality in active fluids: Hydrodynamic communication, bacterial active carpets, and ciliary mucus clearance Arnold JTM Mathijssen Stanford University, Dept. of Bioengineering, 443 Via Ortega, Stanford, California, USA amath@stanford.edu The vast majority of life forms make grand achievements through co-operative efforts, by assembling in dense schools, herds, charms, flocks, teams & parliaments, despite the depletion of resources in these crowded and dynamic environments. Such trade-offs occur not only at the organismic scale, but also between individual cells, and even among the molecular motors that constitute these. Here, we will explore some of the biophysical mechanisms that enable this multi-scale organisation. I will first focus on reliable communication in ultra-fast biology, […]
KAPSEL-4.00 released, 1 April 2019
We are happy to announce that KAPSEL4.00 has been released. Please download from below. KAPSEL HP: kapsel-dns.com/ New options for phase separating solvents (implemented by AIST team) New pair potential with Hamaker constant (implemented by AIST team) New options for micro-swimmers with the rotrel term (implemented by KyotoU team)
Dr. Norihiro Oyama, 31 Jan 2019
Speaker: Dr. Oyama (MathAM-OIL) Title: Avalanche Interpretation of the Power-law of the Energy Spectrum in Three-Dimensional Dense Granular Flow Abstract: Molecular dynamics simulations on dense granular packings under a very slow simple shear flow have revealed that the statistical properties of the non-affine velocity field are consistent with those of classical turbulence of viscous fluid. However, such observations have been limited to two-dimensional systems and knowledge about three dimensional systems is still missing[1]. In this work[2], we conducted direct numerical simulations on three-dimensional dense granular flow and found that the statistical property is not turbulent-like in three dimension. We propose a new understanding from the perspective of avalanche dynamics. This […]
Dr. Stoyan Nedeltchev, 30 Jan 2019
New Methods for Extraction of Important Information from Various Time Series in Bubble Columns Stoyan Nedeltchev Visiting Lecturer at Department of Chemical Engineering Tokyo Institute of Technology (Japan) In this presentation will be demonstrated that useful information can be extracted from various time-dependent signals based on new methods employing the concept of reconstruction of the time series into numerous state vectors. This reconstruction technique is part of the nonlinear chaos theory (Schouten and Van den Bleek, Chem. Eng. J. 53, 75-87, 1993). The development of new methods for extraction of useful and hidden information from various time-dependent signals (differential pressure and gas holdup fluctuations as well as X-ray scans) is […]