Effects of Steel Fibers and Iron Filings on Thermal and Mechanical Properties of Concrete for Energy Storage Application

An experimental study on the thermal properties of iron filings and steel-fiber-reinforced concrete for solar/thermal energy storage application is presented in this report. It takes into account the results of measurements of thermal conductivity, thermal resistivity, thermal diffusivity and the results of compressive strength, density as well as energy storage capacity calculated from the knowledge of the above measured parameters. The experimental testing method is described as well: based upon the linear heat source theory, it requires the use of a special probe to be inserted into the sample. The experimentation was forwarded to test concrete aggregate mixtures with three different sizes and same quantity of steel fibers;two different quantities of iron filings and one plain concrete. The measurements were carried out from the pouring time of cubic samples and were ended up when hardened conditions were achieved. The results indicate that the steel fibers and iron filings have influence on the thermal and mechanical properties of the concretes tested, thus the iron filings and steel fibers reinforced concrete is suitable for better solar/thermal energy storage due to an increase in storage capacity over plain concrete.

Numerical modeling and optimization of process parameters in continuous extrusion process through response surface methodology, artificial neural network & genetic algorithm

The product of high complex profile,high strength,high productivity and excellent material properties with infinite length can be produced by Continuous Extrusion(CE)process.The numerical simulation of Aluminum(AA 1100)feedstock material at different wheel velocities,product diameter,feedstock temperature,die temperature and friction condition has been carried out using 3D simulation tool Design Environment for Forming(DEFORM-3D)in this paper.The development of mathematical model is carried out to investigate the influence of wheel velocity,extrusion ratio,feedstock temperature,die temperature and friction conditions on total load required for the deformation and extrusion of feedstock material through Response Surface Methodology(RSM).The statistical significance of mathematical model is verified through analysis of variance(ANOVA).The most optimum value of extrusion load has been found to be 136.4 kN through iterative process of Genetic Algorithm(GA)using Artificial Neural Network(ANN).The optimized value of input process variables for minimum value of extrusion load obtained has been found to be 13 Revolutions per Minute(RPM)as wheel velocity,5 mm as product diameter,0.95 as friction condition,650◦C as feedstock temperature and 550◦C as die temperature.This paper with proposed methodology will be helpful for industries working in the area of CE in terms of minimizing energy consumption during production process of bus bars,tubes,wires,cables,sheets,plates,strips,etc.

Lattice Boltzmann Modeling of Viscous Elementary Flows

A lattice Boltzmann method is developed for modeling viscous elementary flows.An adjustable source term is added to the lattice Boltzmann equation,which can be tuned to model different elementary flow features like a doublet or a point source of any strength,including a negative source(sink).The added source term is dimensionally consistent with the lattice Boltzmann equation.The proposed model has many practical applications,as it can be used in the framework of the potential flow theory of viscous and viscoelastic fluids.The model can be easily extended to the three dimensional case.The model is verified by comparing its results with the analytical solution for some benchmark problems.The results are in good agreement with the analytical solution of the potential flow theory.