Deeper Understanding Of Physical Processes Research Articles

Theoretical justification of faraday's experimental law

So far, the fundamental laws of nature can only be obtained experimentally. Among them is Faraday's law of electromagnetic induction in mathema-tical representation as Maxwell's second law of the elec-tric field. Theoretically, it is impossible to obtain it on the basis of the laws of electrodynamics. Therefore, in the work, a bold attempt is made to theoretically obtain its analogue in the gravitational field, and then, on the basis of electromechanical analogies, to return to the electric field. What has been successfully done. But before that, there was a need to mathematically rehabili-tate the electromechanical analogies themselves, the reputation of which had suffered in the process of the reverse extension of the law from electricity to gravity under the name of gravito(electro)magnetism. Such immersion in the world of two disciplines - electricity and mechanics − is fundamental for a deeper understanding of physical processes, and at the same time for their quantitative detection.

Physical approach to analysis of induction motor braking under machinery load

The mechanical braking process of induction motors during short interruptions, and full switching off is studied in the paper. The approximate approach to solving a differential equation is used for the theoretical analysis of the braking process. The comparison of this approach with the exact solution shows its good accuracy. The used procedure is simple for a deep understanding of physical processes. It is shown that good results could be obtained for both full-stopping and braking due to sags if the right collocation point is chosen. This approach could be used for the study of different transients in electric motors and drives. It helps beginner students to understand clearly the main features of transients. However, it is also useful for experienced engineers who can easily obtain design formulas.

Stochastic simulation model for the 3D morphology of composite materials in Li–ion batteries

Battery technology plays an important role in energy storage. In particular, lithium–ion (Li–ion) batteries are of great interest, because of their high capacity, long cycle life, and high energy and power density. However, for further improvements of Li–ion batteries, a deeper understanding of physical processes occurring within this type of battery, including transport, is needed. To provide a detailed description of these phenomena, a 3D representation is required for the morphology of composite materials used in Li–ion batteries. In this paper, we develop a stochastic simulation model in 3D, which is based on random marked point processes, to reconstruct real and generate virtual morphologies. For this purpose, a statistical technique to fit the model to 3D image data gained by X-ray tomography is developed. Finally, we validate the model by comparing real and simulated data using image characteristics which are especially relevant with respect to transport properties.