Empirical Numerical Methods Research Articles

Crushing of Single-Walled Corrugated Board during Converting: Experimental and Numerical Study

Corrugated cardboard is an ecological material, mainly because, in addition to virgin cellulose fibers also the fibers recovered during recycling process are used in its production. However, the use of recycled fibers causes slight deterioration of the mechanical properties of the corrugated board. In addition, converting processes such as printing, die-cutting, lamination, etc. cause micro-damage in the corrugated cardboard layers. In this work, the focus is precisely on the crushing of corrugated cardboard. A series of laboratory experiments were conducted, in which the different types of single-walled corrugated cardboards were pressed in a fully controlled manner to check the impact of the crush on the basic material parameters. The amount of crushing (with a precision of 10 micrometers) was controlled by a precise FEMat device, for crushing the corrugated board in the range from 10 to 70% of its original thickness. In this study, the influence of crushing on bending, twisting and shear stiffness as well as a residual thickness and edge crush resistance of corrugated board was investigated. Then, a procedure based on a numerical homogenization, taking into account a partial delamination in the corrugated layers to determine the degraded material stiffness was proposed. Finally, using the empirical-numerical method, a simplified calculation model of corrugated cardboard was derived, which satisfactorily reflects the experimental results.

Wind energy potential and economic analysis with a comparison of different methods for determining the optimal distribution parameters

Abstract Pakistan is one of the countries heavily dependent on hydrocarbon fuel for energy production which is causing a severe climate change; however, wind energy seems to be a long-term solution. Various statistical distributions have been used to draw the analysis of wind data, but the selection of an optimum method has been a challenge. This work is an assessment of wind power potential of a site located near the southern coast of Pakistan. Data collected in two years is analyzed at four heights using three variations of Weibull parameters. Weibull parameters computed through the proposed mean bias error-based artificial intelligence grey wolf optimization were compared with the computations through Rayleigh and Justus’s empirical numerical methods. Root mean square error, determination of coefficient, and mean bias error, are computed to validate and compare the computed results. The wind characteristics like most probable and Maximum energy-carrying wind are found to be in excellent compatibility with most of the wind turbines that could be used on the site. The results obtained along with a brief cost analysis, for eight selected wind turbine systems, show that the considered site is suitable for the production of a wind power project.

Accuracy of determination of stress concentrations by empirical-numerical methods

1. The combined use of experimental methods and the finite elements method to study stress concentrations in individual zones of actual objects makes it possible to improve the accuracy of determination of the maximum stresses compared to the accuracy of a purely experimental determination. 2. The use of displacements as the boundary conditions for calculating the zones by means of the finite elements method places more stringent requirements on the accuracy with which they are assigned compared to the use of boundary conditions in stresses. 3. In several cases, the error of the calculation due to the error of assignment of the boundary conditions is of the same order as that due to the error of the numerical method. Thus, it is important that the examination of individual zones of objects makes it possible to subdivide them finely enough into finite elements and thus makes the problem of selecting an optimum grid less urgent. 4. Approximation of the experimental data on the contour leads to a substantial decrease in the number of points at which it is necessary to determine the stresses or displacements, which in turn reduces the volume of experimental work necessary and simplifies it as well.