There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

At the watershed scale, soil moisture is the major control for rainfall–runoff response, especially where saturation excess runoff processes dominate. From the ecological point of view, the pools of soil moisture are fundamental ecosystem resources providing the transpirable water for plants. In drylands particularly, soil moisture is one of the major controls on the structure, function, and diversity in ecosystems. In terms of the global hydrological cycle, the overall quantity of soil moisture is small, ∼0.05%; however, its importance to the global energy balance and the distribution of precipitation far outweighs its physical amount. In soils it governs microbial activity that affects important biogeochemical processes such as nitrification and CO2 production via respiration. During the past 20 years, technology has advanced considerably, with the development of different electrical sensors for determining soil moisture at a point. However, modeling of watersheds requires areal averages. As a result, point measurements and modeling grid cell data requirements are generally incommensurate. We review advances in sensor technology, particularly emerging geophysical methods and distributed sensors, aimed at bridging this gap. We consider some of the data analysis methods for upscaling from a point to give an areal average. Finally, we conclude by offering a vision for future research, listing many of the current scientific and technical challenges.

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Soil Moisture Measurement for Ecological and Hydrological Watershed-Scale Observatories: A Review

Thermoelectric generators: A review of applications

Simulation of large deformation and post-failure of geomaterial in the framework of smoothed particle hydrodynamics (SPH) are presented in this study. The Drucker–Prager model with associated and non-associated plastic flow rules is implemented into the SPH code to describe elastic–plastic soil behavior. In contrast to previous work on SPH for solids, where the hydrostatic pressure is often estimated from density by an equation of state, this study proposes to calculate the hydrostatic pressure of soil directly from constitutive models. Results obtained in this paper show that the original SPH method, which has been successfully applied to a vast range of problems, is unable to directly solve elastic–plastic flows of soil because of the so-called SPH tensile instability. This numerical instability may result in unrealistic fracture and particles clustering in SPH simulation. For non-cohesive soil, the instability is not serious and can be completely removed by using a tension cracking treatment from soil constitutive model and thereby give realistic soil behavior. However, the serious tensile instability that is found in SPH application for cohesive soil requires a special treatment to overcome this problem. In this paper, an artificial stress method is applied to remove the SPH numerical instability in cohesive soil. A number of numerical tests are carried out to check the capability of SPH in the current application. Numerical results are then compared with experimental and finite element method solutions. The good agreement obtained from these comparisons suggests that SPH can be extended to general geotechnical problems. Copyright © 2008 John Wiley & Sons, Ltd.

Lagrangian meshfree particles method (SPH) for large deformation and failure flows of geomaterial using elastic–plastic soil constitutive model

Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review

This paper presents the evaluation of the performance, in terms of uncertainty, of a tool designed to estimate the main parameters of a model of a photovoltaic panel (PVP) under real and/or simulated working conditions. The presented tool permits the characterization of the panel, and it is useful to predict its behavior in whatever working condition; in this way, it is possible to compare the actual and expected performance to prevent any decrease in the output power, so permitting the replacement of the monitored module before it goes out of order or its efficiency falls under a given threshold. The well-known two-diode model is used to estimate the parameters of the electrical equivalent circuit of the PVP and to simulate the I -V and P-V characteristic curves in any given environmental condition of irradiance and/or temperature. The model and the estimation algorithm are implemented with MATLAB functions, whereas data acquisition and result presentation are managed by a LabVIEW graphics user interface. The presented tool has been validated against an experimentally characterized PVP. The environmental parameters of the model such as irradiance and temperature have been set (with their respective uncertainties) during simulations or directly measured during the outdoor tests, whereas the others parameters have been evaluated using a best-fit algorithm on the measured data. The estimation is based on the minimization of a new objective function and on a modified expression of the model resistances, which differ from those mentioned in the available literature. After a review of the state of the art, this paper provides the description of the estimation technique and its validation by means of simulations and experiments. Some results are also provided to illustrate the performance of the proposed test method.

Characterization and Testing of a Tool for Photovoltaic Panel Modeling

Measurement of chlorophyll concentration is gaining more-and-more importance in evaluating the status of the marine ecosystem. For wide areas monitoring a reliable architecture of wireless sensors network is required. In this paper, we present a network of smart sensors, based on ISO/IEC/IEEE 21451 suite of standards, for in situ and in continuous space–time monitoring of surface water bodies, in particular for seawater. The system is meant to be an important tool for evaluating water quality and a valid support to strategic decisions concerning critical environment issues. The aim of the proposed system is to capture possible extreme events and collect long-term periods of data.

A Smart Sensor Network for Sea Water Quality Monitoring

This paper describes a theoretical approach to evaluate the uncertainty on the series and shunt resistances estimated by the seven-parameter (double diode) model of a photovoltaic (PV) cell using data commonly provided by panel manufacturers, measured environmental parameters, and semiempirical equations. After a brief survey on the state of the art and the treatment of the double-diode model, the procedure proposed by the authors, to estimate the unknown parameters, is illustrated. The theoretical expression of the uncertainty, which affects the estimation of the series and shunt resistances (namely, and ) of a PV cell, is then derived. A statistical analysis performed by means of a Monte Carlo simulation is in agreement with the theoretical expression of the uncertainty.

Uncertainty Analysis in Photovoltaic Cell Parameter Estimation

The paper deals with the problem of measuring the moisture of agricultural soils by an accurate, on-site, real-time method. The idea is to estimate the moisture by measuring the speed of sound in the medium: the main issue is therefore to determine a precise relationship between the two quantities. To this purpose, the Brutsaert's model for elastic waves in porous media is applied, taking into consideration different kinds of soil of common interest in agriculture. The authors have derived the speed-moisture curves, the conditions for the actual validity of the curves, and the suitable sound frequency for performing the measurement, for a wide range of agricultural soils in different physical conditions. The paper results are therefore the basis to realize an inexpensive and accurate moisture sensor for farmers.

An acoustic method for soil moisture measurement

In this paper, the use of the fast Fourier transform (FFT) test to measure the integral nonlinearity (INL) of analog-to-digital (A/D) converters is examined. The derived INL is a linear combination of Chebyshev polynomials, where the coefficients are the spurious harmonics of the output spectrum. The accuracy of the test is examined theoretically, in simulations and in practical devices, particularly for the critical (and typical) case when sudden jumps are present in the actual INL. The examined methodology appears to be very convenient when the device under test has high resolution (16-20 bits) and a smoothed approximation of the INL is sufficient, as the FFT test is in this case thousands of times faster than the customary histogram test and static nonlinearity test.

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Filippo Attivissimo

Papers

Characterization and Testing of a Tool for Photovoltaic Panel Modeling

A Smart Sensor Network for Sea Water Quality Monitoring

Uncertainty Analysis in Photovoltaic Cell Parameter Estimation

An acoustic method for soil moisture measurement

FFT test of A/D converters to determine the integral nonlinearity