فهرست مطالب s. deswal

Present work is concerned with the analysis of transient wave phenomena in a piezo-thermoelastic medium with diffusion, fiber reinforcement and two-temperature, when an elastic wave is made incident obliquely at the traction free plane boundary of the considered medium. The formulation is applied under the purview of generalized theory of thermoelasticity with one relaxation time. The problem is solved analytically and it is found that there exists four coupled quasi waves: qP (quasi-P ), qMD (quasi mass diffusion), qT (quasi thermal) and qSV (quasi-SV ) waves propagating with different speeds in a two-dimensional model of the solid. The amplitude ratios, phase velocities and energy ratios for the reflected waves are derived and the numerical computations have been carried out with the help of MATLAB programming. Effect of presence of diffusion is analyzed theoretically, numerically and graphically. The number of reflected waves reduce to three in the absence of diffusion as qMD wave will disappear in that case which is physically admissible. Influence of piezoelectric effect, two temperature and anisotropy is discussed on different characteristics of reflected waves such as phase velocity and reflection coefficients. It has been verified that there is no dissipation of energy at the boundary surface during reflection. Thus, the energy conservation law holds at the surface. Finally, all the reflection coefficients are represented graphically through 3D plots to estimate and highlight the effects of frequency and angle of incidence.

This study aims to examine the ability of free floating aquatic plants to remove phosphorus and to predict the reduction of phosphorus from rice mill wastewater using soft computing techniques. A mesocosm study was conducted at the mill premises under normal conditions, and reliable results were obtained. Four aquatic plants, namely water hyacinth, water lettuce, salvinia, and duckweed were used for this study. The growth of all the plants was inhibited in rice mill wastewater due to low pH, high chemical oxygen demand, high conductivity, and high phosphorus concentration. Subsequently, a 1:1 ratio of mill water to tap water was used. A control was maintained to assess the aquatic plant technology. In this study, the aquatic plants reduced the total phosphorus content up to 80 % within 15 days. A comparison between three modeling techniques e.g. Artificial neural network (ANN), Random forest (RF) and M5P has been done considering the reduction rate of total phosphorus as predicted variable. In this paper, the data set has been divided in two parts, 70 % is used to train the model and residual 30 % is used for testing of the model. Artificial neural network shows promising results as compared to random forest and M5P tree modelling. The root mean square error (RMSE) for all the three models is observed as 0.0162, 0.0204 and 0.0492 for ANN, RF and M5P tree, respectively.