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Old and recent experiments show that there is a direct response to the heating power of transport observed in modulated ECH experiments both in tokamaks and stellarators. This is most apparent for modulated experiments in the Large Helical Device (LHD) and in Wendelstein 7 advanced stellarator (W7-AS). In this paper we show that: (1) this power dependence can be reproduced by linear models and as such hysteresis (in flux) has no relationship to hysteresis as defined in the literature; (2) observations of 'hysteresis' (in flux) and a direct response to power can be perfectly reproduced by introducing an error in the estimated deposition profile as long as the errors redistribute the heat over a large radius; (3) non-local models depending directly on the heating power can also explain the experimentally observed Lissajous curves (hysteresis); (4) how non-locality and deposition errors can be recognized in experiments and how they affect estimates of transport coefficients; (5) from a linear perturbation transport experiment, it is not possible to discern deposition errors from non-local fast transport components (mathematically equivalent). However, when studied over different operating points non-linear-non-local transport models can be derived which should be distinguishable from errors in the deposition profile. To show all this, transport needs to be analyzed by separating the transport in a slow (diffusive) time-scale and a fast (heating/non-local) time-scale, which can only be done in the presence of perturbations.

The heat flux is one of the key parameter used to quantify and understand transport in fusion devices. In this paper, a new method is introduced to calculate the heat flux including its confidence with high accuracy based on perturbed measurements such as the electron temperature. The new method is based on ideal filtering to optimally reduce the noise contributions on the measurements and piece-wise polynomial approximations to calculate the time derivative. Both methods are necessary to arrive at a heat flux and effective diffusion coefficient with high accuracy. The new methodology is applied to a measurement example using electron cyclotron resonance heating block-wave modulation at the Large Helical Device showing the merit of the newly developed methodology.

In this paper, techniques for optimal input design are used to optimize the waveforms of perturbative experiments in modern fusion devices. The main focus of this paper is to find the modulation frequency for which the accuracy of the estimated diffusion coefficient is maximal. Mathematically, this problem can be formulated as an optimization problem in which the Fisher information matrix is maximized. First, this optimization problem is solved for a simplified diffusion model, while assuming a slab geometry and a semi-infinite domain. Later, the optimization is repeated under more general conditions such as a cylindrical geometry, finite domain, and simultaneous estimation of multiple transport coefficients. Based on the results of these optimizations, guidelines are offered to select the modulation frequency and to determine the optimality of the corresponding experiment.

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods.

The use of temperature-time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater-surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1-D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature-time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater-surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time-variable fluxes from periodic and nonperiodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations.

The successful application of impedance spectroscopy in daily practice requires accurate measurements for modeling complex physiological or electrochemical phenomena in a single frequency or several frequencies at different (or simultaneous) time instants. Nowadays, two approaches are possible for frequency domain impedance spectroscopy measurements: (1) using the classical technique of frequency sweep and (2) using (non-)periodic broadband signals, i.e. multisine excitations. Both techniques share the common problem of how to design the experimental conditions, e.g. the excitation power spectrum, in order to achieve accuracy of maximum impedance model parameters from the impedance data modeling process. The original contribution of this paper is the calculation and design of the D-optimal multisine excitation power spectrum for measuring impedance systems modeled as 2R-1C equivalent electrical circuits. The extension of the results presented for more complex impedance models is also discussed. The influence of the multisine power spectrum on the accuracy of the impedance model parameters is analyzed based on the Fisher information matrix. Furthermore, the optimal measuring frequency range is given based on the properties of the covariance matrix. Finally, simulations and experimental results are provided to validate the theoretical aspects presented., QC 20120807

The successful application of impedance spectroscopy in daily practice requires accurate measurements for modeling complex physiological or electrochemical phenomena in a single frequency or several frequencies at different (or simultaneous) time instants. Nowadays, two approaches are possible for frequency domain impedance spectroscopy measurements: (1) using the classical technique of frequency sweep and (2) using (non-)periodic broadband signals, i.e. multisine excitations. Both techniques share the common problem of how to design the experimental conditions, e.g. the excitation power spectrum, in order to achieve accuracy of maximum impedance model parameters from the impedance data modeling process. The original contribution of this paper is the calculation and design of the D-optimal multisine excitation power spectrum for measuring impedance systems modeled as 2R-1C equivalent electrical circuits. The extension of the results presented for more complex impedance models is also discussed. The influence of the multisine power spectrum on the accuracy of the impedance model parameters is analyzed based on the Fisher information matrix. Furthermore, the optimal measuring frequency range is given based on the properties of the covariance matrix. Finally, simulations and experimental results are provided to validate the theoretical aspects presented., Peer Reviewed, Postprint (published version)

Respiratory diseases, which include diseases of the lung, pleura, bronchial tree, trachea, upper respiratory tract and of the respiratory muscles and nerves, are a common and important cause of illness and death among the population. Experimental evidences have shown that tissue lesions have different electrical properties compared with normal tissue. Therefore, lung tissues lesions may be differentiated from lung normal tissue by comparing the tissue passive electrical properties. The manuscript reports a feasibility study for minimally invasive in vivo human lung tissue tetrapolar bioimpedance measurements using a catheter during the bronchoscopy procedure based on multisine Electrical Impedance Spectroscopy (EIS) at 10 kHz - 1 MHz., Peer Reviewed, Postprint (published version)

Classicalmeasurements ofmyocardium tissue electrical impedance for characterizing the morphology of myocardium cells, as well as cell membranes integrity and intra/extra cellular spaces, are based on the frequency-sweep electrical impedance spectroscopy (EIS) technique. In contrast to the frequency-sweep EIS approach, measuring with broadband signals, i.e., multisine excitations, enables to collect, simultaneously, multiple myocardium tissue impedance data in a short measuring time. However, reducing the measuring time makes the measurements to be prone to the influence of the transients introduced by noise and the dynamic time-varying properties of tissue. This paper presents a novel approach for the impedance-frequency-response estimation based on the local polynomial method (LPM). The fast LPM version presented rejects the leakage error’s influence on the impedance frequency response when measuring electrical bioimpedance in a short time. The theory is supported by a set of validation measurements. Novel preliminary experimental results obtained from real-time in vivo healthy myocardium tissue impedance characterization within the cardiac cycle using multisine excitation are reported., Peer Reviewed, Postprint (published version)

Electrical Impedance Spectroscopy (EIS) is a powerful tool to collect data from many biological materials in a wide variety of applications. Body composition fluid or tissue and organ state monitoring are just some examples of these applications. While the classical EIS is based on frequency sweep, the EIS technique using broadband excitations allows to acquire simultaneous impedance spectrum data. The strength and weakness of broadband EIS relies on the fact that it enables multiple Electrical Bio-Impedance (EBI) data collection in a short measuring time but at the cost of losing impedance spectrum accuracy. In general, there is a relationship between the broadband excitation time/frequency properties and the final EBI's accuracy obtained. This paper studies the influence of the multisine broadband excitation amplitude's design over the EBI accuracy by means of the resultant Noise-to-Signal Ratio (NSR) obtained when measuring with a custom impedance analyzer. Theory has been supported by a set of validation experiments., Peer Reviewed, Postprint (published version)