Weakly electric fish generate electric current and use hundreds of voltage sensors on the surface of their body to navigate and locate food. Experiments (von der Emde and Fetz 2007 J. Exp. Biol. 210 3082-95) show that they can discriminate between differently shaped conducting or insulating objects by using electrosensing. One approach to electrically identify and characterize the object with a lower computational cost rather than full shape reconstruction is to use the first order polarization tensor (PT) of the object. In this paper, by considering experimental work on Peters' elephantnose fish Gnathonemus petersii, we investigate the possible role of the first order PT in the ability of the fish to discriminate between objects of different shapes. We also suggest some experiments that might be performed to further investigate the role of the first order PT in electrosensing fish. Finally, we speculate on the possibility of electrical cloaking or camouflage in prey of electrosensing fish and what might be learnt from the fish in human remote sensing.

This analysis explored the computational process of heat transfer analysis in a thin-film MHD flow embedded in the hybrid nanoparticles, which combine the spherical copper and alumina dispersed in ethylene glycol as the conventional heat transfer Newtonian fluid model over a stretching sheet. The nonlinear ordinary differential equations (ODEs) was attained by transforming partial differential equation (PDEs) as governing equations when implementing the similarity transformations technique. The resulting nonlinear ODEs have been utilized by using the Keller box method. The natures of the thin-film flow and heat transfer through the various values of the pertinent parameters: unsteadiness, nanoparticle volume fraction, thin-film thickness, magnetic interaction and intensity suction/injection are deliberated. The approximate results for velocity and temperature distributions and physical quantities in terms of local skin friction and Nusselt number have been obtained and analyzed via graphs and tables. As a consequence, the suction expresses a more prodigious effect on the hybrid nanofluid rather than injection fluid for all the investigation parameters. It is worth acknowledging that the existence of the nanoparticles and MHD in the viscous hybrid nanofluid tends to enhance the temperature profile but decay the particle movement in the thin-film flow. It is perceived that the velocity and temperature profiles decline for the growth of the unsteadiness, thin-film thickness and suction/injection parameters.

This paper studies the heat transfer in the blood fluid-based copper and alumina nanoparticles over an unsteady permeable stretching sheet. The model is governed by the governing equations consist of a series of ODEs that are reduced from PDEs by implementing the similarity transformations subjected to mixed boundary conditions. The results of the transformed equations has been obtained by using the Keller-box method in MATLAB software. This paper focuses on the characteristics of thin-film flow and heat transfer through the governing parameters; unsteadiness parameter, nanoparticles volume fraction, Casson parameter, and intensity of suction. From this study, it is observed that the behavior of both fields for nanofluid is lower than hybrid nanofluid under the suction effect. It is noticed that enhance the physical parameters increase the velocity field of the fluid. Further, increase the physical parameter also deteriorate the temperature field except for nanoparticles volume fraction.

This paper explores the mathematical model of thin-film flow and heat transfer utilizing hybrid nanofluid along with the two-dimensional time dependent stretching sheet. The influence of several parameters towards the model are discussed and solved by the method of collocation, namely bvp4c solver that can find in MATLAB software. In this paper, we focused on the effect of parameters are unsteadiness parameter λ, thermocapillarity number M, constant mass transfer parameter S, and concentration of    towards the model.  The numerical results have been obtained and shown in table and graph form. The effect of thermocapillarity number M and concentration of  are explored and graphically portrayed through the velocity, temperature and concentration profile.

One of the important parameters in developing dry ice blasting nozzle is the high-speed dry ice pellets. However, many studies focus primarily only on its performance without considering the noise emission that comes from an operating nozzle. In this method, the central composite optimization tool has been used. The two-way mass momentum and energy exchange are successfully modeled using the two-way mass momentum model. As an attempt to theoretically verify the model accuracy, a comparison is conducted on the density, pressure, temperature, as well as Mach number ratios corresponding to various ratios of nozzle area. In return, the smallest value of the convergent angle results in the highest velocity of 516.75 m s −1 , as well as the highest level of the acoustic power level of 144.36 dB. Besides, one of the vital influencing factors on the emitted acoustic power level is the turbulence intensity, which can achieve a maximum of 1% intensity for an angle of 20° at the throat section. Besides, the same negative sensitivity of around − 0.99% is provided by the velocity and acoustic power level, which is highly responsive toward the convergent angle variation. Furthermore, the optimum nozzle convergent angle for the minimization of the acoustic power level and maximization of the velocity is 7.03°. The novelty of this research lies in the findings on the effective convergent angle of the dry ice blasting nozzle that accelerates the particle flow and minimizes the noise emission from the operating nozzle.