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L. Urankar

Researcher at Siemens

Publications -  8
Citations -  331

L. Urankar is an academic researcher from Siemens. The author has contributed to research in topics: Vector potential & Elliptic integral. The author has an hindex of 8, co-authored 8 publications receiving 317 citations.

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Vector potential and magnetic field of current-carrying finite arc segment in analytical form, Part III: Exact computation for rectangular cross section

TL;DR: In this paper, the vector potential and magnetic field of a circular arc segment of a current-carrying conductor of arbitrary cross section and arbitrary azimuthal length were derived, based on known functions such as Jacobian elliptic functions, complete and incomplete elliptic integrals of the first, second, and third kind.
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Vector potential and magnetic field of current-carying finite arc segment in analytical form, part II: Thin sheet approximation

TL;DR: In this article, the vector potential and magnetic field of a conic cylinder segment of arbitrary azimuthal and axial length, and carrying a constant peripheral current, were derived.
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Vector potential and magnetic field of current-carrying finite arc segment in analytical form, part IV: General three-dimensional current density

TL;DR: In this article, analytical expressions for the components of the vector potential and magnetic field derived in Part II [1] and in Part III [2] for azimuthal constant current density are now extended to general three-dimensional constant vector current density.
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Vector potential and magnetic field of current-carrying circular finite arc segment in analytical form. V. Polygon cross section

TL;DR: In this article, analytical expressions for the components of the vector potential and magnetic field of a circular-arc segment of a current-carrying conductor of polygonal cross section and arbitrary azimuthal length are derived.
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Boundary Element Solution of Biomagnefic Problems

TL;DR: In this article, a boundary element formulation for biomagnetic problems is described and an analytical element integration and tuning of the boundary element method (BEM) forward solution for implementation in the inverse problem algorithm results in a far better relationship between accuracy and computational effort.