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"Electromagnetic induction"
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Forward Electromagnetic Induction Modelling in a Multilayered Half-Space: An Open-Source Software Tool
Electromagnetic induction (EMI) techniques are widely used in geophysical surveying. Their success is mainly due to their easy and fast data acquisition, but the effectiveness of data inversion is strongly influenced by the quality of sensed data, resulting from suiting the device configuration to the physical features of the survey site. Forward modelling is an essential tool to optimize this aspect and design a successful surveying campaign. In this paper, a new software tool for forward EMI modelling is introduced. It extends and complements an existing open-source package for EMI data inversion, and includes an interactive graphical user interface. Its use is explained by a theoretical introduction and demonstrated through a simulated case study. The nonlinear data inversion issue is briefly discussed and the inversion module of the package is extended by a new regularized minimal-norm algorithm.
Journal Article
Development and Validation of an Electromagnetic Induction-Based Thermal Propagation Test Method for Large-Format Lithium-Ion Battery Systems
This study establishes a standardized framework for thermal propagation test in nickel-7 lithium-ion battery systems through a high-frequency electromagnetic induction heating method. The non-intrusive triggering mechanism enables precise thermal runaway initiation within two seconds through localized eddy current heating (>1200 °C), validated through cell-level tests with 100% success rate across diverse trigger positions. System-level thermal propagation tests were conducted on two identical battery boxes. The parallel experiments revealed distinct propagation patterns influenced by system sealing quality. In the inadequately sealed system (Box 01), flame formation led to accelerated thermal propagation through enhanced convective and radiative heat transfer. In contrast, the well-sealed system (Box 02) maintained an oxygen-deficient environment, resulting in a controlled sequential propagation pattern. The testing methodology incorporating dummy modules proved efficient for validating thermal protection strategies while optimizing costs. This study contributes to a deeper understanding of thermal runaway propagation mechanisms and the development of standardized testing protocols for large-format battery systems.
Journal Article
Extreme multistability and phase synchronization in a heterogeneous bi-neuron Rulkov network with memristive electromagnetic induction
Memristive electromagnetic induction effect has been widely explored in bi-neuron network with homogeneous neurons, but rarely in bi-neuron network with heterogeneous ones. This paper builds a bi-neuron network by coupling heterogeneous Rulkov neurons with memristor and investigates the memristive electromagnetic induction effect. Theoretical analysis discloses that the bi-neuron network possesses a line equilibrium state and its stability depends on the memristor coupling strength and initial condition. That is, the stability of the line equilibrium state has a transition between unstable saddle-focus and stable node-focus via Hopf bifurcation. By employing parameters located in the stable node-focus region, dynamical behaviors related to the memristor coupling strength and initial conditions are revealed by Julia- and MATLAB-based multiple numerical tools. Numerical results demonstrate that the proposed heterogeneous bi-neuron Rulkov network can generate point attractor, period, chaos, chaos crisis, and period-doubling bifurcation. Note that extreme multistability are disclosed with respect to initial conditions of memristor and gated ion concentration. Coexisting infinitely multiple firing patterns of periodic firing patterns with different periodicities and chaotic firing patterns for different memristor initial conditions are demonstrated by phase portrait and time-domain waveform. Besides, the phase synchronization related to the memristor coupling strength and its initial condition is explored, which suggests that the two heterogeneous neurons become phase synchronization with large memristor coupling strength and initial condition. This also reflects that the plasticity of memristor synapse enables adaptive regulation in keeping energy balance between the neurons. What’s more, MCU-based hardware experiments are executed to further confirm the numerical simulations.
Journal Article
Smart Soil Water Sensor with Soil Impedance Detected via Edge Electromagnetic Field Induction
To address the problems in the calibration of soil water content sensors, in this study, we designed a low-cost edge electromagnetic field induction (EEMFI) sensor for soil water content measurement and proposed a normalized calibration method to eliminate the errors caused by the measurement sensor’s characteristics and improve the probe’s consistency, replaceability, and calibration efficiency. The model calibration curve-fitting coefficients of the EEMFI sensors were above 0.98, which indicated a significant correlation. The experimental results of the static and dynamic characteristics showed that the measurement range of the sensor varied from 0% to 100% saturation, measurement accuracy was within ±2%, the maximum value of the extreme difference of the stability test was 1.09%, the resolution was 0.05%, the delay time was 3.9 s, and the effective measurement diameter of the EEMFI sensor probe was 10 cm. The linear fit coefficient of determination of the results was greater than 0.99, and the maximum absolute error of the measurement results with the drying method was less than ±2%, which meets the requirements of soil water content measurement in agriculture and forestry fields. The field experiment results further showed that the EEMFI sensor can accurately respond to changes in soil water content, indicating that the EEMFI sensor is reliable.
Journal Article
Electromagnetic induction effects on electrical activity within a memristive Wilson neuron model
Neurons can exhibit abundant electrical activities due to physical effects of various electrophysiology environments. The electromagnetic induction flows can be triggered by changes in neuron membrane potential, which can be equivalent to a memristor applying on membrane potential. To imitate the electromagnetic induction effects, we propose a three-variable memristor-based Wilson neuron model. Using several kinetic analysis methods, the memristor parameter- and initial condition-related electrical activities are explored intensively. It is revealed that the memristive Wilson neuron model can display rich electrical activities, including the asymmetric coexisting electrical activities and antimonotonicity phenomenon. Finally, using off-the-shelf discrete components, an analog circuit on a hardware level is implemented to verify the numerically simulated coexisting electrical activities. Studying these rich electrical activities in neurons can build the groundwork to widen the neuron-based engineering applications.
Journal Article
Abiotic water quality control on mangrove distribution in estuarine river channels assessed by a novel boat-mounted electromagnetic-induction technique
Due to climate change impacts and the resulting sea-level rise, saline waters have been found further inland in tropical riverine estuaries such as the Godineau wetland, Trinidad. The saline water intrusion could constrain mangrove vegetation distribution. We investigated the surface water quality of two river channels (2 km and 6 km), emanating from a tropical wetland and from forest/agriculture at high-tide, respectively. Using a novel boat-mounted geophysical approach, spatially exhaustive river/estuarine salinity data was collected. Water quality parameters - salinity, pH and dissolved oxygen (DO) - were compared with vegetation surveyed along the course of the rivers to determine relationships between plant zonation and water quality. Our findings showed similar trends for salinity and apparent electrical conductivity, which were higher in the 2 km channel (27.10 to 31.80 dS/m) than in the 6 km channel (17.80 to 27.10 dS/m), while pH and DO levels were lower in the 2 km channel than in the 6 km channel due to higher levels of decomposition in the stagnant shorter channel. Red mangrove (Rhizophora mangle) was found in areas with little oxygen, high salinities and high acidity, making it more adaptable to conditions resulting from saline intrusion. Therefore, to replace the mangrove that has been lost due to die-off, the red mangrove maybe used in viable restoration efforts for the protection of inland areas from floods, as well as to provide ecosystem goods and services.
Journal Article
Dynamical effects of memristive electromagnetic induction on a 2D Wilson neuron model
Electromagnetic induction plays a crucial impact on the firing activity of biological neurons, since it exists along with the mutual effect between membrane potential and ions transport. Flux-controlled memristor is an available candidate in characterizing the electromagnetic induction effect. Different from the previously reported literature, a non-ideal flux-controlled memristor with cosine mem-conductance function is employed to determine the periodic magnetization and leakage flux processes in neurons. Thereafter, a three-dimensional (3D) memristive Wilson (m-Wilson) neuron model is constructed under the consideration of this kind of electromagnetic induction. Numerical simulations are performed by multiple numerical tools, which demonstrate that the 3D m-Wilson neuron model can generate abundant firing activities. Interestingly, coexisting firing activities, antimonotonicity, and firing frequency regulation are discovered under special parameter settings. Furthermore, a PCB-based analog circuit is designed and hardware measurements are executed to verify the numerical simulations. These explorations in numerical and hardware surveys might provide insights to regulate the firing activities by appropriate electromagnetic induction.
Journal Article
Flow measurement by electromagnetic induction
This book describes of basic principles of electromagnetic induction measurements and consolidates the outcomes of recent research. It encompasses pipeline electromagnetic flow meters, electromagnetic flow meters, multiphase flow electromagnetic flowmeters and flow field of electromagnetic induction reconstruction. Though theoretical in nature it does draw on experimental data and includes new research findings, especially in the areas of multiphase flow and flow reconstruction. With a focus on theory and computation in flow measurement by electromagnetic induction including traditional flowmeters in closed conduits, velocity probe, two-phase flow, velocity reconstruction and dry calibration it will be an invaluable resource for researchers and practising engineers. The book uses MATLABª to introduce efficient numerical methods to model and simulate flows, sensor construction and geometry, and the effect of pipe materials. Part of IOP Series in Sensors and Sensor Systems.
eBook
Ground-Penetrating Radar and Electromagnetic Induction: Challenges and Opportunities in Agriculture
Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.
Journal Article