VoxHenry: FFT-Accelerated Inductance Extraction for Voxelized Geometries

Abdulkadir C. Yucel*, Ioannis P. Georgakis, Athanasios G. Polimeridis, Hakan Bagci, Jacob K. White

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


VoxHenry, a fast Fourier transform (FFT)-accelerated integral-equation-based simulator for extracting frequency-dependent inductances and resistances of structures discretized by voxels, is presented. VoxHenry shares many features with the popular inductance extractor, FastHenry. Just like FastHenry, VoxHenry solves a combination of the electric volume integral equation and the current continuity equation, but with three distinctions that make VoxHenry suitable and extremely efficient for analyzing voxelized geometries: 1) it leverages a carefully selected set of piecewise-constant and piecewise-linear basis functions; 2) it exploits FFTs to accelerate the matrix-vector multiplications during the iterative solution of system of equations; and 3) it employs a sparse preconditioner to ensure the rapid convergence of iterative solution. VoxHenry is capable of accurately computing frequency-dependent inductances and resistances of arbitrarily shaped and large-scale structures on a desktop computer. The accuracy, efficiency, and applicability of VoxHenry are demonstrated through inductance analysis of various structures, including square and circular coils as well as arrays of RF inductors (situated over ground planes).

Original languageEnglish (US)
Pages (from-to)1723-1735
Number of pages13
JournalIEEE Transactions on Microwave Theory and Techniques
Issue number4
StatePublished - Apr 2018


  • Fast Fourier transform (FFT)
  • FastHenry
  • inductance extraction
  • magneto-quasistatic analysis
  • parasitic extraction
  • partial element equivalent circuit
  • volume integral equation (VIE)
  • voxelized geometries

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Radiation
  • Electrical and Electronic Engineering


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