Dielectric properties of water and ice: a unified treatment

Волков, А. А.; Васин, А. А.

doi:10.1080/00150193.2019.1569989

Cited by 8 publications

(3 citation statements)

References 16 publications

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“…Most of the relaxation phenomena of water molecules occur in the radiofrequency and microwave regions of the electromagnetic spectrum. Water is a polar molecule that forms tetrahedral structures with hydrogen bonds that are continually formed and destroyed because the hydrogen bond formation energy is of the order of average thermal energy at room temperature [24,25]. Currently, the most accepted dynamical model of water is the "wait and switch" model.…”

Section: Introductionmentioning

confidence: 99%

Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis

Santillán-Rodríguez,

Sáenz-Hernández,

Grijalva-Castillo

et al. 2024

AgriEngineering

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Glyphosate is an herbicide used worldwide with harmful health effects, and efforts are currently being made to develop sensors capable of detecting its presence. In this work, an array of four interdigitated microwave sensors was used together with the multivariate statistical technique of principal component analysis, which allowed a well-defined pattern to be found that characterized waters for agricultural use extracted from the Bustillos lagoon. The variability due to differences between the samples was explained by the first principal component, amounting to 86.3% of the total variance, while the variability attributed to the measurements and sensors was explained through the second principal component, amounting to 13.2% of the total variance. The time evolution of measurements showed a clustering of data points as time passed, which was related to microwave–sample interaction, varied with the fluctuating dynamical structure of each sample, and tended to have a stable mean value.

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Section: Introductionmentioning

confidence: 99%

Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis

Santillán-Rodríguez,

Sáenz-Hernández,

Grijalva-Castillo

et al. 2024

AgriEngineering

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“…The identification of runway ice and snow contaminants by the above detection methods still has certain shortcomings, as the relative dielectric constants of ice and water are relatively close to each other, which can lead to large measurement errors. In response to this problem, scholars found that the relative dielectric constants of ice and water vary greatly at different detection frequencies [13], and therefore proposed a capacitive sensor based on multi-frequency detection. Troiano et al designed a columnar capacitance sensor that can be embedded in the runway to determine the condition of the road surface by measuring the capacitance value at two different frequencies, while developing a recognition algorithm, and indoor experimental results showed that the sensor recognition accuracy was greatly improved [14].…”

Section: Introductionmentioning

confidence: 99%

Design of an active detection system for ice and snow pollutants and freezing temperature on runway

Chen,

Gao,

Yang

et al. 2023

Meas. Sci. Technol.

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This paper studied the problem of ice and snow pollutants identification and freezing temperature detection under winter runway operation, and designed an active detection system for runway ice and snow pollutants and freezing temperature. The temperature change trend during the liquid freezing process was researched, and the freezing temperature detection model based on sequence segmented linear fitting and inflection point identification was proposed in combination with active cooling technology. The differences in dielectric properties of runway snow and ice cover are studied, and a multi-frequency detection-based forked-finger planar capacitive sensor was identified for snow and ice pollutants detection considering practical application scenarios. A finite element simulation model of the forked-finger planar capacitive sensor was established, to optimize the structural parameters of the sensor and verify the feasibility of the capacitor sensor. Finally, the detection device and control system were designed and fabricated, and built an experimental platform for system test. The field experimental results showed that the system has good reliability and stability, and the error of freezing temperature detection model is less than 0.3 °C. At the same time, it can identify three types of pollutants, including water, ice and ice–water mixture, with an accuracy of 89%.

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“…The electrical conductivity of ice is affected by the content of impurities, intra-ice ions, and gas bubbles produced by the deposition of sea salt and acids emitted into the atmosphere by volcanic eruptions [15,[20][21][22]. The dielectric constant is related to ice chemistry variations, ice fabrics, and the pressure and temperature of ice [23,24]. All these factors result in the corresponding attenuation of electromagnetic waves propagating within the ice.…”

Section: Introductionmentioning

confidence: 99%

Airborne Radio-Echo Sounding Data Denoising Using Particle Swarm Optimization and Multivariate Variational Mode Decomposition

Chen,

Liu,

Luo

et al. 2023

Remote Sensing

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Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode decomposition (VMD) algorithm. It processes data encompassing multiple channels. Determining the most effective component combination of the penalty parameter (α) and the number of intrinsic mode functions (IMFs) (K) is fundamental and affects the decomposition results. α and K in traditional MVMD are provided by subjective experience. We integrated the particle swarm optimization (PSO) algorithm to iteratively optimize these parameters—specifically, α and K—with high precision. This was then combined with the four quantitative parameters: energy entropy, signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and root-mean-square error (RMSE). The RES signal decomposition results were judged, and the most effective component combination for noise suppression was selected. We processed the airborne RES data from the East Antarctic ice sheet using the combined PSO–MVMD method. The results confirmed the quality of the proposed method in attenuating the RES signal noise, enhancing the weak signal of the ice base, and improving the SNR. This combined PSO–MVMD method may help to enhance weak signals in deeper parts of ice sheets and may be an effective tool for RES data interpretation.

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Dielectric properties of water and ice: a unified treatment

Cited by 8 publications

References 16 publications

Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis

Glyphosate Pattern Recognition Using Microwave-Interdigitated Sensors and Principal Component Analysis

Design of an active detection system for ice and snow pollutants and freezing temperature on runway

Airborne Radio-Echo Sounding Data Denoising Using Particle Swarm Optimization and Multivariate Variational Mode Decomposition

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