7 research outputs found
EXPERIMENTAL MEASUREMENTS ON NON-NEWTONIAN AND DRAG REDUCTION FLOWS IN PIPES
A laboratory setup was designed for experimental study of non-Newtonian and drag
reducing fluid flow in a square cross section pipe. Aqueous solutions of carboxymethyl cellulose
(CMC) in water were used as the non-Newtonian fluids while dilute solutions of polyethylene
oxide (PEO) in water as the drag reducing fluids. An injection technique was used to overcome
the pump degrading effects on the PEO solutions.
A turbometer was used for flow rate measurements, a pressure transducer for pressure
measurements, Pitot tubes for velocity measurements and Preston tubes for wall shear stress
measurements. The performance and calibration of the previous devices are presented in this paper with
some results compared with theory
Погребение Второй Половины Х В. С Инвентарём «Венгерского Облика» У С. Рованцы из Украины [Pogrebeniye Vtoroy Poloviny KH V. S Inventarom «Vengerskogo Oblika» U S. Rovantsy iz Ukrainy] = Magyar jellegű sír a 10. század második feléből az ukrajnai Rovanci település határából
MEAN FLOW PROPERTIES IN THE DEVELOPING REGION OF A CIRCULAR PIPE FOR TURBULENT FLOW AT MAXIMUM DRAG REDUCTION
Nonlocal stimulation of three-magnon splitting in a magnetic vortex
We present a combined numerical, theoretical and experimental study on stimulated three-magnon splitting in a magnetic disk in the vortex equilibrium state. Our micromagnetic simulations and Brillouin-light-scattering results confirm that three-magnon splitting can be triggered even below threshold by exciting one of the secondary modes by magnons propagating in a waveguide next to the disk. The experiments show that stimulation is possible over an extended range of excitation powers and a wide range of frequencies around the eigenfrequencies of the secondary modes. Rate-equation calculations predict an instantaneous response to stimulation and the possibility to prematurely trigger three-magnon splitting even above threshold in a sustainable manner. These predictions are confirmed experimentally using time-resolved Brillouin-light-scattering measurements and are in a good qualitative agreement with the theoretical results. We believe that the controllable mechanism of stimulated three-magnon splitting could provide a possibility to utilize magnon-based nonlinear networks as hardware for reservoir or neuromorphic computing.
Here, we briefly describe how the archived data for the publication "Nonlocal stimulation of three-magnon splitting in a magnetic vortex", submitted to PRL, is structured.
"rate-equations"
- theoretical data of the temporal evolution of the spin wave modes in Fig. 4
"micromagnetic-simulation"
- MuMax3 simulation recipes (.go files) and sample-layout masks for the
simulations performed for Fig. 2(a,b,c).
- corresponding power spectra obtained with our "mumax3-pwsp" program
- mode profiles for stimulated and spontaneous splitting (Fig. 1(c) and Fig. 2(d))
- dispersion of the spin waves, calculated by micromagetnic simulation, shown in Fig. 1(b)
"experiments"
- electron beam microscopy image of the sample
- intensity spectrum of the waveguide, used to calculate the approximate
frequency/wave-vector region where the waveguide is effective (inset in Fig. 1(c))
- non-time-resolved BLS measurements, including spectra, power sweeps, etc. for
Figs 2,3 in "i3MS" folders, in more detail described by "i3MS_V1_KS_logbook.pdf"
- time-resolved BLS measurements, further explained in the corresponding subfolder
Data publication: Curvilinear spin-wave dynamics beyond the thin-shell approximation: Magnetic nanotubes as a case study
This dataset contains the numerical data for our publication "Curvilinear spin-wave dynamics beyond the thin-shell approximation: Magnetic nanotubes as a case study" published in Physical Review B. The data consists of dispersion, magnetization ground states and mode profiles of spin waves in vortex-state magnetic nanotubes of different thicknesses, and has been calculated with the TetraX micromagnetic modeling package. All calculations are described within each subfolder by a jupyter notebook