Marco Bittelli

Use of dielectric spectroscopy to estimate ice content in frozen porous media

[1]xa0We investigate the use of dielectric spectroscopy to estimate ice content in frozen porous media. A dielectric mixing model was used to determine the volumetric fractions of the different phases, based on knowledge of the bulk and single-phase dielectric permittivities. Measurement of the dielectric permittivities at two different frequencies with an impedance analyzer is required to infer ice content. One of the frequencies (25 kHz) has to be close to the relaxation frequency of ice; the other frequency (158 kHz or higher) must be well above the relaxation frequency of ice to obtain a different permittivity value of the ice phase. The theory was tested with three soil samples containing different amounts of clay. Dielectric permittivities of the soil samples were determined between 0.1 and 200 kHz, and in the temperature range of −30°C to +5°C. Ice content was successfully determined for a loamy sand sample. However, surface phenomena at low frequencies (such as double-layer polarization, surface conduction, and Maxwell-Wagner type effects) made ice content estimation using our proposed methods unfeasible in silty loam and clay samples, which had 13% and 46% clay by weight, respectively.

A Nonlinear Dynamics Approach for Incorporating Wind-Speed Patterns into Wind-Power Project Evaluation

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind—the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

Dielectric data analysis: recovering hidden relaxations by fourth-order derivative spectroscopy

Complex materials exhibit a dielectric behavior that can shed light on their chemophysical structure through a comprehension of the physical mechanisms originating that behavior. For the interpretation of a complex dielectric shape, where multiple relaxations are present (and usually described by semi-empirical functions), a correct interpretation of each simple relaxation is necessary. The separation of often closely overlapped relaxation curves requires the verification of the meaningfulness of such multiple relaxations and to determine their number and relative magnitudes, in other words to resort to a fitting procedure. However, often the physical interpretation of the fitting parameters is not straightforward, and their physical meaning is arguable. The application of even-order derivative spectroscopy is here demonstrated to be able to detect the presence and location of multiple dielectric relaxations, acting on the experimental data without any a priori hypothesis.

Analysis of Hydro-meteorological Monitoring Data Collected in Different Contexts Prone to Shallow Landslides of the Oltrepò Pavese (Northern Italy)

Open image in new window This work presents the results of the continuous monitoring of two slopes of the Oltrepo Pavese (northern Apennines, north-western Italy), representative of different contexts usually affected by shallow landslides. The first monitored site is representative of high gradient slopes with silty soils. The second one represents slopes with low-medium slope gradient and clayey soils. Hydrological monitoring allowed to identify the responses of the soils to different rainy or dry periods, focusing in particular on the conditions which could predispose landslides triggering. As demonstrated by monitoring and by slope stability analyses through a simplified physically-based model, increase in pore water pressure during most intense rainfalls in wet periods, sometimes with development of perched water table, can promote slope instability.

Monitoring and Modelling of Soil–Atmosphere Interaction on a Slope Affected by Shallow Landslides

A long-term field monitoring proves very helpful to understand the effect of climatic variables on the hydrological response of a shallow soil and the role of atmospheric features in the triggering mechanism of rainfall-induced landslides. In this work, field measurements of the soil saturation in a sample slope, coming from 18 months continuous monitoring of soil water content, are presented. The experimental data are compared with the seasonal trends of the soil saturation resulting from the application of a simplified empirical model, based on rainfall and air temperature input data. The performance of the model is evaluated for two different soil depths, in order to establish a future application of this method to predict time trends of the saturation for large scale slope stability analyses.

Rainfall-Induced Landslides: Slope Stability Analysis Through Field Monitoring

Rainfall-induced shallow landslides are hazardous phenomena that could cause several damages to infrastructures and people. To understand the hydrological and mechanical triggering conditions of shallow landslides in an area of Oltrepo Pavese (Northern Apennines, Italy) a field monitoring was conducted. In this work the results of 16 months monitoring are shown, focusing on the hydrological behaviour of the studied materials as function of rainfall and its effect on slope stability.