Search results for "NEURAL NETWORK"
showing 10 items of 1385 documents
Dynamics of Singlet Oxygen Molecule Trapped in Silica Glass Studied by Luminescence Polarization Anisotropy and Density Functional Theory
2020
The support from M-ERANET project “MyND” is acknowledged. A.A., M.M-S., and L.R. were supported by the Research Council of Lithuania (Grant M-ERA.NET-1/2015). The authors thank A. Pasquarello for providing the structures of the amorphous SiO 2 matrix for our computational work and K. Kajihara (Tokyo Metropolitan University) for valuable advice in PL kinetics measurements.
Using Dynamic Light Scattering Experimental Setup and Neural Networks For Particle Sizing
2017
Abstract Using a Lorentzian function fit as reference, a basic experiment was designed for processing Dynamic Light Scattering time series, allowing to estimate the average particle size of a suspension. For fitting the averaged power spectrum of the time series, several neural network configurations were tested in order to compare the results with the reference. The results of this comparison revealed a good match, serving as a proof of concept for using neural networks as an alternative for DLS time series processing.
Using a neural network for predicting the average grain size in friction stir welding processes
2009
In the paper the microstructural phenomena in terms of average grain size occurring in friction stir welding (FSW) processes are focused. A neural network was linked to a finite element model (FEM) of the process to predict the average grain size values. The utilized net was trained starting from experimental data and numerical results of butt joints and then tested on further butt, lap and T-joints. The obtained results show the capability of the AI technique in conjunction with the FE tool to predict the final microstructure in the FSW joints.
Continuous dynamic recrystallization phenomena modelling in friction stir welding of aluminium alloys: A neural-network-based approach
2007
The current paper focuses on the continuous dynamic recrystallization phenomena (CDRX) occurring in friction stir welding processes of AA6082 T6 aluminium alloys. In particular, in order to predict the average grain size, a properly trained neural network is linked to the finite element method (FEM) model of the process. The utilized net, which takes as inputs the local values of strain, strain rate, and temperature, was trained starting from experimental data and numerical results. The obtained results show the capability of the artificial intelligence (AI) technique in conjunction with the FE tool to predict the final microstructure in the joint section.
Prediction and analysis of high velocity oxy fuel (HVOF) sprayed coating using artificial neural network
2019
Abstract Thermal spray comprises a group of coating processes for coating manufacturing in which metallic or nonmetallic materials are deposited in a molten or semi-molten condition. Most often, the coating properties are significantly influenced by the operating parameters. However, obtaining a comprehensive modeling or analytical analysis of the thermal spray process is too difficult to be practical due to the complex chemical and thermodynamic reactions. Accordingly, the present study aims at applying an artificial neural network (ANN) model to predict the HVOF sprayed Cr3C2−25NiCr coatings and analyze the influence of operating parameters regardless of the intermediate process. The proce…
Mechanical and microstructural properties prediction by artificial neural networks in FSW processes of dual phase titanium alloys
2012
Abstract Friction Stir Welding (FSW), as a solid state welding process, seems to be one of the most promising techniques for joining titanium alloys avoiding a large number of difficulties arising from the use of traditional fusion welding processes. In order to pursue cost savings and a time efficient design, the development of numerical simulations of the process can represent a valid choice for engineers. In the paper an artificial neural network was properly trained and linked to an existing 3D FEM model for the FSW of Ti–6Al–4V titanium alloy, with the aim to predict both the microhardness values and the microstructure of the welded butt joints at the varying of the main process parame…
Using Dynamic Light Scattering for Monitoring the Size of the Suspended Particles in Wastewater
2019
Abstract A coherent light scattering experiment on wastewater samples extracted from several stages of water processing within a wastewater processing plant was carried out. The samples were allowed to sediment while they were the subject of a Dynamic Light Scattering (DLS) measurement. The recorded time series were processed using an Artificial Neural Network based DLS procedure to produce the average diameter of the particles in suspension. The method, using a single physical procedure for monitoring the variation of the average diameter in time, indicates the dominant type of suspensions in water.
Interaction of Lamb modes with two-level systems in amorphous nanoscopic membranes
2007
Using a generalized model of interaction between a two-level system (TLS) and an arbitrary deformation of the material, we calculate the interaction of Lamb modes with TLSs in amorphous nanoscopic membranes. We compare the mean free paths of the Lamb modes with different symmetries and calculate the heat conductivity $\kappa$. In the limit of an infinitely wide membrane, the heat conductivity is divergent. Nevertheless, the finite size of the membrane imposes a lower cut-off for the phonons frequencies, which leads to the temperature dependence $\kappa\propto T(a+b\ln T)$. This temperature dependence is a hallmark of the TLS-limited heat conductance at low temperature.
Dynamics of nanoparticles in a supercooled liquid
2008
The dynamic properties of nanoparticles suspended in a supercooled glass forming liquid are studied by x-ray photon correlation spectroscopy. While at high temperatures the particles undergo Brownian motion the measurements closer to the glass transition indicate hyperdiffusive behavior. In this state the dynamics is independent of the local structural arrangement of nanoparticles, suggesting a cooperative behavior governed by the near-vitreous solvent.
Secondary relaxation in the glass-transition regime of ortho-terphenyl observed by incoherent neutron scattering.
1992
We report on incoherent-neutron-scattering measurements in the supercooled regime of the van der Waals liquid ortho-terphenyl. A secondary localized relaxational process on the picosecond time scale is found. In accordance with mode-coupling theories of the glass transition, the relaxational dynamics around a critical temperature ${\mathit{T}}_{\mathit{c}}$ decomposes into two time regimes.