This study conducts the thermodynamics analysis of creeping viscous nanofluid influenced by metachronical waves in an inclined ciliated tube and investigates the effects of magnetic field, porous medium and Hall current. Moreover, heat transport analysis is performed to consider the viscous dissipation phenomena. Thermal conductivity of the fluid is made more effective by adopting water-based titanium dioxide nanoparticles. [Formula: see text] is chosen as it has many remarkable implications in nanobio-sensing, medical implants, drug delivery and antibacterial fields. The governing equations are formulated which are converted into ordinary differential system by taking into account the similarity variables. The analytical solution are obtained for momentum, pressure gradient and energy profiles. It is found that the entropy generation is an increasing function of the Eckert number, Prandtl number and dimensionless temperature difference. Both Darcy and Eckert numbers enhance the energy of flow system. The fluid velocity drops quickly with increasing magnetic parameter.
Methods based on electromagnetic time reversal (EMTR) have recently demonstrated promising results. In particular, EMTR, as a correlation estimator metric, has offered a quantitative definition for fault location candidates. As the correlation estimator already obtains the system transfer functions by simulating fault occurrences, these functions are subsequently correlated with the fault-generated transfer function. Therefore, it is necessary to explore the analysis related to the pre-fault processing of this metric. Firstly, the impact of fault impedance mismatch between the fault occurrence and fault estimation stages was investigated, and a simple approach is presented after observing the fault locations’ error. Secondly, it was noticed that the existing correlation estimator approach does not accurately identify fault types; therefore, a pseudo approach was developed to address this issue. Finally, the spatial step considered during the fault estimation stage was investigated. It is demonstrated that larger spatial steps result in inaccuracies in fault location. The smaller spatial steps improved the performance, but increased the memory burden on the data storage devices, especially when simple and pseudo approaches must be employed. The memory issue was resolved by presenting a hybrid approach that makes use of regression analysis. A single-phase and a three-phase lossy transmission line system were used to illustrate the proposed analyses.
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