Modeling the Motion of a Saw Ginning Machine

The dynamic characteristics of a saw gin as a subsystem with lumped and distributed parameters are considered in the paper. On the basis of investigation of the machine assembly, graphs are drawn that allow establishing the maximum values of the angle of relative rotation and the angle of rotation of the saw cylinder shaft under torsion.     

Phase-Field Modeling of Nugget Zone for a AZ31-Mg-Alloy Friction Stir Weld

This work presents simulation of microstructure evolution in the nugget zone (NZ) of a AZ31-Mg-alloy friction stir weld. The process parameters (tool geometrical characteristics, rotational speed, travel speed, applied load) have been correlated with the resulting microstructural features in the NZ of the weld (grain size and population) with the aid of the MICRESS software, which provides the ability to simulate both nucleation and grain growth during dynamic recrystallization phenomena evolving in the NZ during the weld thermal cycle. The input parameters of the developed model include the tool geometry, the welding conditions as well as the recrystallization energy, the grain boundary mobility and specific material properties. NZ microstructure obtained by simulation shows good agreement with experimental measurements for both grain population and size.     

The Role of Excitation Photons Energy in the Photoinduced Carrier Dynamics in InGaAs/InAlAs Superlattice Heterostructures

Technical Physics Letters - The influence of excitation photons energy on the relaxation times of photoexcited carriers is studied. The involved relaxation mechanisms are evaluated and the...     

Influence of the Chemical Composition and Local Atomic Packing of Nanostructured MoSx and MoSex Solid Lubricant Coatings on Their Tribological Properties under Complicated Conditions

Technical Physics Letters - We present the results of a comparative investigation of the friction and wear characteristics of MoSx and MoSex coatings in an oxidizing medium (argon–air...     

Study of the Density of Interface States at the Insulator/In0.52Al0.48As Interface

Technical Physics Letters - The C–V characteristics of Au/Al2O3/In0.52Al0.48As and Au/SiO2/In0.52Al0.48As metal–insulator–semiconductor structures have been studied. It has been...     

Detailed study on fusion characteristics of rigid poly(vinyl chloride) nanocomposites: The comparison of using multiple regression analysis and artificial neural network

Fusion behavior of poly(vinyl chloride) (PVC) compounds plays an important role in the development of physical properties of processed material. The fusion characteristics in PVC processing are governed by material variables that affect the fusion with some interactions. In this research, the aim was to characterize the effects of formulation ingredients on fusion characteristics of PVC. Four material parameters, including the contents of nanoclay (NC), azodicarbonamide, calcium stearate, and processing aid, are proposed as affecting variables. The fusion time (FT) as well as fusion factor (FF) are considered fusion indicators and are experimentally determined in some different levels of affecting parameters. The multivariable regression analysis (MRA) and the Artificial Neural Network (ANN) modeling are considered as two analytical methods. The regression analysis result for the FT denotes, in part, significant linear and quadratic effects of NC and also its significant interactions with azodicarbonamide and calcium stearate, whereas that of FF indicates only a linear effect of NC. ANN modeling is performed with a three‐layer (input, hidden, and output) neural network. The results of the comparison of the MRA and ANN predictions with experimental values are reported as the correlation coefficient (R²), mean‐square error, and mean absolute percentage error for both FF and FT parameters. The obtained values clearly denote that the ANN results are more precise and especially more general than those of MRA. However, in the case of FT, improvement of the ANN modeling is much greater than that of FF. J. VINYL ADDIT. TECHNOL., 21:147–155, 2015. © 2014 Society of Plastics Engineers