A Review of Empirical Methods to Estimate Relative Permittivity

A. J. Rubin; C.L. Ho

Found an issue? Give us feedback

https://doi.org/10.1...arrow_drop_down

https://doi.org/10.1109/icgpr....

Article . 2018 . Peer-reviewed

Data sources: Crossref

https://dx.doi.org/10.1109/icg...

Other literature type

Data sources: Microsoft Academic Graph

A Review of Empirical Methods to Estimate Relative Permittivity

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jun 2018Publisher:IEEEJournal:2018 17th International Conference on Ground Penetrating Radar (GPR)

Authors: A. J. Rubin; C.L. Ho;

doi: 10.1109/icgpr.2018.8441646

A Review of Empirical Methods to Estimate Relative Permittivity

- Summary
- Metrics

Abstract

Four empirical models to estimate the relative permittivity of soil are tested based on a new database of relative permittivity measurements on soils. The selected models are Topp et. al. CRIM, SMDM, and GRMDM. The new database of relative permittivity measurements consists of 124 measurements on five different soils measured at a range of porosities and saturations. The effectiveness, positive attributes, and negative attributes of each model are discussed.

Related Organizations

University of Massachusetts Amherst
United States

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	1
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average