Dielectric data in volcanic ash at weather radar wavelengths (centimeter range) are extremely sparse and are crucial for radar sensing of ash clouds and for imaging of volcanic terrains. This study extends previous data to include a wavelength range of 1.5-7.5 cm and volcanic ash compositions of 50-75 % silica. The real part of the complex permittivity, , of volcanic ash is 6 ± 0.5 (1σ) for all wavelengths. The imaginary part, , ranges from 0.08 to 0.27. Both and show higher values at lower SiO 2 concentration. It is safe to assume in any weather radar applications that the reflectivity factor is K = |( − 1)/( + 2)| 2 = 0.39 ± 0.02 (1σ), regardless of composition or wavelength. The results will help quantify radar observations of volcanic clouds.
We present a simple density theory based on first principles that predicts the shielding effectiveness of composite matrix materials at filler loadings near or above the percolation threshold. Such a model has practical applications in electromagnetic interference and radio frequency interference, and is validated here for Fortafil 243 carbon fiber within nylon 6,6. In brief, the theory predicts that the most important parameter on the shielding effectiveness of a sample is the carbon fiber volume percent. At very high filler loadings, experimental results show a weak dependence on the frequency of the wave to be shielded, which may be attributed to enhanced reflection from multiple, coherent scatterers (carbon fiber network). These effects are not considered in our model. Nevertheless, advantages of this model are ease of use and improved predictive capabilities when compared to models previously reported in the literature. Our model performs very well over an electrical resistivity range from 10 15 ohm-cm (at low filler loading levels below the percolation threshold) down to 10 -1 ohm-cm (at high filler loading levels well above the percolation threshold), and can be used to determine filler loadings needed to provide a certain level of shielding of electromagnetic waves. POLYM. COMPOS., 26: 671-678, 2005.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.