Second law analysis (entropy generation) for the steady two-dimensional laminar forced convection flow, heat and mass transfer of an incompressible viscous fluid past a nonlinearly stretching porous (permeable) wedge is numerically studied. The effects of viscous dissipation, temperature jump, and first-order chemical reaction on the flow over the wedge are also considered. The governing boundary layer equations for mass, momentum, energy and concentration are transformed using suitable similarity transformations to three nonlinear ordinary differential equations (ODEs). Then, the ODEs are solved by using a Keller’s box algorithm. The effects of various controlling parameters such as wedge angle parameter, velocity ratio parameter, suction/injection parameter, Prandtl number, Eckert number, temperature jump parameter, Schmidt number, and reaction rate parameter on dimensionless velocity, temperature, concentration, entropy generation number, and Bejan number are shown in graphs and analyzed. The results reveal that the entropy generation number increases with the increase of wedge angle parameter, while it decreases with the increase of velocity ratio parameter. Also, in order to validate the obtained numerical results of the present work, comparisons are made with the available results in the literature as special cases, and the results are found to be in a very good agreement.

Identification plays an important role in relation to control objects and processes as it enables the control system to be properly tuned. The identification methods described in this paper use the Stochastic Gradient Descent algorithms, which have so far been successfully presented in machine learning. The article presents the results of the Adam and AMSGrad algorithms for online estimation of the Dielectric Electroactive Polymer actuator (DEAP) parameters. This work also aims to validate the learning by batch methodology, which allows to obtain faster convergence and more reliable parameter estimation. This approach is innovative in the field of identification of control systems. The researchwas supplemented with the analysis of the variable amplitude of the input signal. The dynamics of the DEAP parameter convergence depending on the normalization process was presented. Our research has shown how to effectively identify parameters with the use of innovative optimization methods. The results presented graphically confirm that this approach can be successfully applied in the field of control systems.