Elucidating how electromagnetic fields influence calcium carbonate crystallization is crucial for advancing electromagnetic scale inhibition technology. This study systematically investigates the effect of alternating magnetic fields (AMFs) generated by a wound electromagnetic processor under square wave voltage excitation on CaCO3 crystallization through theoretical derivation, experimental exploration, and scale inhibition application. By establishing a mathematical model of magnetic flux density inside the processor and solving the current response of the excitation system under square wave voltage excitation, the magnetic flux density waveform was obtained. Based on this, three-dimensional trajectories of Ca²⁺ and CO₃²⁻ under Lorentz force were calculated, showing that Lorentz force increases ion collision frequency, enhances radial enrichment, and increases ion kinetic energy. Combined with classical nucleation theory (CNT), these effects synergistically promote CaCO3 nucleation and growth in bulk solution. Magnetic treatment experiments using conductivity and pH as crystallization indicators confirmed that AMFs effectively promote CaCO3 crystallization, with 1 kHz and 300 Gs showing the most significant effect within the experimental range. To validate the practical effectiveness of these parameters, electromagnetic scale inhibition experiments were further conducted, revealing through fouling resistance, XRD (X-ray Diffraction), and SEM (Scanning Electron Microscopy) analysis that magnetic treatment significantly reduces crystallization fouling on heat transfer surfaces. This study provides theoretical basis and experimental reference for optimizing electromagnetic scale inhibition parameters.

Calcium carbonate crystallization fouling on heat transfer surfaces poses a significant challenge in industrial heat exchange systems, reducing thermal efficiency and increasing operational costs. This study presents a multiprocess dynamically coupled mathematical model for describing calcium carbonate crystallization fouling on heat transfer surfaces. The model incorporates the coupling of heat transfer, mass transfer, and chemical reactions during the fouling process, capturing the dynamic interplay among the temperature field, concentration field, and fouling layer within the heat exchange system. Model predictions were validated experimentally, demonstrating an average error of 3.6 % between simulated and experimental fouling resistance values, with wall temperature deviations below 1 % during the stable fouling stage. Using this validated model, numerical simulations were performed to investigate calcium carbonate deposition characteristics under varying operating conditions. The influence of heating power, solution concentration, and circulation flow velocity on system heat and mass transfer was quantified through fouling resistance and wall temperature. Furthermore, the mechanisms through which these parameters affect fouling deposition were elucidated. The results indicate that crystallization fouling can be mitigated while maintaining the required heat transfer performance by optimizing operational conditions, including regulating heating power, reducing ionic concentration in the circulating water, and increasing flow velocity.

During the operation of a wind turbine gearbox, its internal gears undergo spalling due to wear, producing ferromagnetic wear debris that enters the wind turbine gearbox oil (hereafter referred to as 'the oil'). This debris accelerates gear damage and oil deterioration. Consequently, detecting its presence reflects the rates of gear wear and oil quality degradation, making the online monitoring of the ferromagnetic wear debris mass fraction critical for the condition monitoring and early fault warning of wind turbine gearboxes. To address the specific characteristics of ferromagnetic wear debris in oil-namely, a high mass fraction, a strong tendency toward particle agglomeration, and the large flow diameter of tank pipelines-this study proposes a dual-coil differential sensor. This sensor is based on electromagnetic induction and the characteristics of LC resonant circuits, utilizing the root mean square (RMS) value of the excitation current as the output signal. A qualitative model of the sensor was established and verified via simulation, after which an experimental platform was constructed to conduct performance tests. The results demonstrate that within an 8-mm oil pipeline, the sensor achieves a detection limit of 25 ppm and a corresponding measurement accuracy of 25 ppm. For wear debris mass fractions varying continuously within the range of 25-250 ppm, the mean RMS value of the sensor's excitation current exhibits a linear relationship with the corresponding mass fractions (slope: 0.164 mA ppm-1). Furthermore, the measured results yielded a standard deviation of only 0.8 mA.

Fouling on heat transfer surfaces significantly reduces heat transfer efficiency. This study innovatively introduces air nanobubbles (NBs) into the heat transfer fluid at distinct stages (initiation, growth, transition, and stabilization) of CaCO3 crystalline fouling formation on the heat transfer surface. By analyzing the fouling resistance and fouling layer morphology images of the heat transfer surface, the conductivity of the working fluid, as well as the X-ray diffraction patterns and scanning electron microscopy images of fouling samples, the fouling inhibition characteristics and mechanisms of NBs were investigated. The results demonstrate that NBs can effectively reduce the formation of fouling on the heat transfer surface, with a maximum fouling inhibition rate of 89.1% achieved at the initial stage. NBs can simultaneously decrease fouling resistance and conductivity, promoting the CaCO3 formation in the bulk phase of the working fluid rather than depositing on the heat transfer surface. By controlling the timing of NBs introduction, the crystal phase proportion of CaCO3 can be regulated. In the early stages of fouling formation, NBs exhibit significant effects in crystal phase regulation and fouling prevention, while in the late stages, they remove the already-formed fouling through shear action. This study confirms that NBs are a green, eco-friendly, and highly efficient novel strategy for reducing fouling, demonstrating significant engineering application potential in extending the service life of heat exchange equipment, enhancing heat transfer performance, and reducing energy consumption and carbon emissions.

In order to investigate the deposition characteristics of particle-crystallization composite fouling on rough surface, three random rough surfaces with different roughness levels were constructed. Molecular dynamics simulations were employed to study the deposition characteristics of SiO2 particle and CaCO3 in aqueous solutions on random rough surface. This study focuses on the initial stage of composite fouling formation. The results reveal that for a Ca2+ concentration of 0.48 mol/L, as surface roughness increases, so does the density of the water molecule layer near the surface at the margins, as well as the number of adsorbed ions. The deposition time of the mixed clusters on the surface shortens. The deposition of composite fouling becomes more stable as the surface roughness increases because the interaction potential energy between the surface and Ca2+ ions rises. When the calcium carbonate concentration increases to 0.72 mol/L, the deposition process of composite fouling remains unchanged. But more ions are adsorbed onto the surface and particle, causing the volume of the mixed clusters to increase and the deposition time to shorten. The deposited mixed clusters bind more tightly to the surface. This study reveals the deposition characteristics of composite fouling on realistic Cu surface and provides theoretical support for the prevention of fouling in heat exchangers.

The relevant experimental data of the fouling formation process of a heat exchanger were obtained through the fouling monitoring experimental platform. Whereafter, with regard to the conventional particle swarm optimization (PSO) algorithm, this study commenced from the iteration formula and innovatively presented an optimization approach for improving the inertia weight, thereby obtaining the improved particle swarm optimization (IPSO) algorithm. The wavelet neural network (WNN) was optimized through the application of the IPSO–WNN algorithm, resulting in the development of the IPSO–WNN model. Utilizing this model, a predictive model for fouling thermal resistance was constructed, incorporating input variables such as conductivity, pH, dissolved oxygen, average wall temperature, and bulk temperature, while the output variable represented fouling thermal resistance. Comparative analyses demonstrated that the IPSO–WNN model exhibited superior prediction accuracy and robust generalization capabilities to that of the conventional WNN and PSO–WNN models, as evidenced by significantly lower values across all indicators, including MAPE, MAE, and RMSE. The IPSO algorithm effectively optimized the initial parameters of the WNN, addressing the challenge of local minimum and enhancing the model’s overall capacity to identify optimal solutions. This model effectively captures the dynamic trends of fouling thermal resistance during its growth stage and approaches the asymptotic value in the stable stage. Precise prediction models for heat exchanger fouling contribute valuable insights for its prediction in practical industrial applications.

This research innovatively proposed the method of applying excitation current to characterize the calcium carbonate fouling state on the heat transfer surface under the action of an alternating magnetic field. This characterization method can simply and effectively characterize calcium carbonate fouling through excitation current as a physical signal, breaking the limitations of conventional characterization methods of water quality parameters. The feasibility of the research was demonstrated through theoretical deduction, simulation analysis, and experimental verification. The detailed expression of the RLC circuit current response under the excitation of a square-wave AC voltage was solved using the harmonic analysis method. Furthermore, by constructing an equivalent circuit simulation model, the error between the simulation results and the calculated results was obtained to be approximately 1 %, which confirmed the accuracy of the obtained solution results. Based on the expression of excitation current and the magnetization effect theory, the variation in medium density impacts the self-inductance coefficient of the excitation coil by the permeability, subsequently influencing the excitation current. And the mechanism of excitation current characterizing the fluid medium's state change was deduced. Before reaching resonance, the excitation current increases with higher density and decreases with lower density for relatively strong paramagnetic fluids. Finally, the excitation current trend collected during the experiments was analyzed in relation to the state of the fluid medium. The experimental results showed that the current realized the characterization for the fouling state.

This paper is to study the effect of CaCO3 precipitated crystal scale mixed with different particles on the scaling characteristics under the action of electromagnetic field. The simulation of industrial field experiments, based on the electromagnetic water treatment dynamic experimental bench, change the type of particles, concentration, magnetic field strength, according to the experimental results of the thermal resistance and scale inhibition rate curve under different working conditions, through the scanning electron microscope microscopy analysis of the fouling samples, to study the effect of CaCO3 fouling mixed with different particles in the role of the magnetic field on the effect of the law on the deposition characteristics. The results show that: electromagnetic field on MgO particles dirt and CaCO3 dirt deposition have inhibition effect; CaCO3 and different concentrations of CaCO3 crystalline particles mixed, CaCO3 particles, the more the electromagnetic field on the formation of CaCO3 precipitation scale inhibition effect is not obvious; CaCO3 precipitation scale and MgO particles mixed in the magnetic field can significantly enhance the effect of the field of the inhibition of the scale, magnetic field Under the action of the magnetic field, as the content of MgO particles increases, the scale inhibition effect on the dirt is first enhanced and then weakened until it tends to be about 0. Scanning electron microscopy analyses showed that the morphology and degree of aggregation of calcium carbonate fouling crystals were influenced by MgO particles under the action of electromagnetic fields, and CaCO3 fouling was transformed from regular ortho-hexahedra to acicular aragonite and amorphous CaCO3, which made the stripping phenomenon more significant. Comprehensive experimental results and scanning electron microscopy analyses of fouling samples show that the mixture of CaCO3 solution with a small amount of MgO particles can be an effective means to inhibit the precipitation of crystalline fouling under the environment of alternating electromagnetic field. This study provides theoretical guidance for the application of alternating magnetic field in the future, and provides new ideas and methods for solving the problem of crystalline fouling in industry.

Crystallization fouling of a heat exchanger surface under an alternating magnetic field was studied by using self-designed annular channel electromagnetic anti-fouling experiment platform to obtain experimental data including conductivity, induced current and fouling resistance in various magnetic induction intensities. The magnetic induction intensity of 300 Gs exhibited the best fouling inhibition effect, and the fouling inhibition rate was 78.89%. The induced current (first proposed in the research) was related to the change of magnetic in-duction intensity and salt concentration, which could directly reflect the characteristics of fouling resistance and alternating magnetic field. Based on the strong correlation between conductivity, induced current and fouling resistance, support vector regression (SVR) optimized by improved grey wolf algorithm (IGWO) was proposed to predict fouling resistance with conductivity and induced current as input variables, fouling resistance as output variable. Keeping other experimental conditions constant, the fouling resistance on the heat exchanger surface under the same and different magnetic induction intensities was predicted. Prediction results indicated that, the mean absolute percentage error was 3.24% for the former, 7.88% (300 Gs) and 4.04% (100 Gs) for the latter. IGWO-SVR had the highest prediction accuracy and the strongest generalization capability compared with support vector regression (SVR) and SVR optimized by genetic algorithm (GA-SVR), which demonstrated that IGWO-SVR was highly adaptable to predict fouling resistance in various situations.

In this study, the influence of an axial-electromagnetic field treatment device (AEFTD) with a solenoid structure using different electromagnetic frequencies on calcium carbonate (CaCO3) crystallization fouling on the tube side of a shell-and-tube heat exchanger was investigated. The experimental results indicated that the application of the AEFTD could effectively reduce fouling resistance and decelerate the growth rate of CaCO3 fouling. The opposite trend between fouling resistance and the outlet temperature of an experimental fluid indicated that the application of the AEFTD could enhance heat transfer. Meanwhile, the crystal morphologies of the fouling samples were analyzed by means of scanning electron microscopy (SEM). The axial-electromagnetic field favored the formation of vaterite as opposed to calcite. Non-adhesive vaterite did not easily aggregate into clusters and was suspended in bulk to form muddy fouling that could be carried away by turbulent flow. Furthermore, the anti-fouling mechanism of the axial-electromagnetic field is discussed in detail. The anti-fouling effect of the AEFTD on CaCO3 fouling exhibited extreme characteristics in this study. Therefore, the effectiveness of the AEFTD is contingent upon the selection of the electromagnetic parameters.

Forced convective heat transfer and CaCO3 deposition experiments were performed to investigate fouling inhibition characteristics of a variable frequency electromagnetic field on the CaCO3 fouling of a heat transfer surface and three indicators, namely, fouling resistance, conductivity, and scanning electron microscope (SEM), were analyzed. Experimental results indicated that the variable frequency electromagnetic field could effectively inhibit the CaCO3 fouling deposition on the heat transfer surface and slow down the growth rate of CaCO3 fouling by influencing aqueous solution and fouling forming ions. Moreover, the variable frequency electromagnetic field could reduce the conductivity of the test fluid, increase both the total precipitation and the bulk precipitation, and promote the CaCO3 crystallization in aragonite rather than calcite to form muddy soft fouling that was readily washed off by the fluid flow. An evaluation model was proposed to better define the fouling inhibition effect of the variable frequency electromagnetic field in the whole period of CaCO3 deposition. The fouling inhibition characteristics of the variable frequency electromagnetic field presented an extremum feature. The minimum fouling resistance was 1.1 x 10(-4) m(2)center dot K/W obtained at 1 kHz, during which the fouling inhibition rate was 64.7% and the average growth rate of CaCO3 fouling dramatically decreased by 61.0% compared with that of the blank test. This work can provide sound theoretical guidance for future application of electromagnetic fouling inhibition technology in the heat transfer enhancement. (c) 2022 Elsevier Ltd. All rights reserved.

Experiments were performed to investigate the influence of an alternating magnetic field with different magnetic induction intensities on the calcium carbonate (CaCO3) fouling of a heat transfer surface. Experimental results indicated that the alternating magnetic field could effectively inhibit the fouling deposition on the heat transfer surface by prolonging the fouling induction period and slowing down the growth rate of CaCO3 fouling. Moreover, the fouling inhibition characteristics of the alternating magnetic field presented a multi-extremum feature. The fouling inhibition effectiveness depended on the selection of operating parameters in the alternating magnetic field. The most significant period was 300 Gs in this work, during which the fouling inhibition rate was 91.57%. Meanwhile, the fouling induction period increased by 132.3% and the growth rate decreased by 38.8% compared with the blank test. According to the scanning electron microscopy and particle size distribution, the morphology of CaCO3 particles exhibited changes with the alternating magnetic field. The smaller crystal size and terrace-ledge-kink growth were two reasons that impeded CaCO3 fouling from adhering easily on the heat transfer surface. This work can provide a sound theoretical guidance for future alternating magnetic field system design and application in fouling inhibition. (C) 2021 Elsevier Ltd. All rights reserved.

基于自制的电磁抑垢动态模拟实验台,分析不同磁场强度下(0,100,150,200和250Gs)的交变电磁场对碳酸钙溶液污垢热阻、电导率、pH和溶解氧的影响,并运用灰色关联分析法研究了各水质参数与污垢热阻之间的关联特性.研究结果表明:在200Gs磁场强度下,污垢热阻的诱导期最长,达到10000min.说明该磁场强度的交变电磁场对污垢热阻的影响显著;并且,电导率较pH、溶解氧与污垢热阻有更大的关联度,关联度为0.5504.说明相对pH和溶解氧,电导率与污垢热阻的关联性更密切,更能反映污垢热阻的变化.通过对交变电磁场作用下水质参数与污垢热阻进行关联分析,能够为污垢热阻与多水质参数间数学模型的建立选取合适的参数提供理论及实验依据.

以电磁抑垢动态模拟实验台为基础,分析了磁场强度为0与200Gs时电磁场对污垢形成过程中电导率、pH值及溶解氧3种水质参数的影响,并运用数理统计方法分析了各水质参数与污垢热阻的关联特性.对其相关分析和偏相关分析的结果表明:无论是否施加电磁场,电导率与污垢热阻的相关系数均最大,pH值次之,溶解氧最小,即电导率对换热器的污垢热阻影响显著;相比未施加电磁场的情况,电磁场处理后各水质参数与污垢热阻的关联程度有所减小.通过对电磁场处理后的污垢热阻与水质参数进行关联分析,为选取参数建立水质参数与污垢热阻之间数学模型及分析电磁抑垢机理、制定有效的防垢抑垢对策提供了实验依据和理论参考.

To investigate the effects of magnetic induction intensity, magnetic field treatment time, and solution concentration on the magnetic memory time of CaCO3 solution, an orthogonal experiment was carried out to establish a L-16(4(5)) orthogonal table, and 16 groups of experimental results were obtained on the basis of a self-made electromagnetic water treatment experimental platform. Range and variance analyses were carried out. Experimental results indicated that the main factor affecting the magnetic memory time of CaCO3 solution is the magnetic induction intensity and the effect is significant. The magnetic field treatment time and solution concentration have little effect on the magnetic memory time. In addition, optimum experimental conditions were obtained. When a CaCO3 solution of 2 mmol/L concentration was treated for 36 h with a magnetic induction intensity of 300 Gs, the longest magnetic memory time (about 5600 min) was observed. These research results provide the theoretical basis for the selection of subsequent experimental parameters.

Dynamic simulation experiments were conducted on calcium carbonate fouling formation in shell and tube heat exchangers by using a self-designed online evaluation experimental platform of the electromagnetic anti-fouling effect to obtain the experimental data of conductivity, pH, dissolved oxygen and fouling resistance with the electromagnetic anti-fouling treatment (EAT). And the Elman neural network (Elman NN) was optimized using the genetic algorithm (GA) to derive the GA–Elman neural network (GA–Elman NN). On the basis of GA–Elman NN, a fouling resistance prediction model was established with conductivity, pH, and dissolved oxygen as the input variables and fouling resistance as the output variable. Prediction results indicated that GA–Elman NN improved the weight and threshold, overcame the drawback of falling into the local minimum, and strengthened the capability of finding the optimal solution, thereby improving the prediction accuracy significantly. Moreover, the GA–Elman NN prediction model presented enhanced generalization capability. The mean absolute percent error was 6.07%, and the total error was 8.78% with the experimental system uncertainty. These values indicate that the GA-Elman NN prediction model possesses the high prediction accuracy and is rational and feasible in predicting fouling resistance.

Based on the online electromagnetic scale suppression dynamic simulation table designed by our team, the magnetic induction intensity in the cavity of single- and multi-layer winding electromagnetic water processor is simulated and analyzed by using numerical simulation. The relationship between the magnetic induction intensity of the inner cavity and the number of turns of the coil, wire diameter, and inner diameter and the effect of the segment on the intensity of the magnetic induction in the inner cavity are analyzed. According to the Bio–Savarts law, the formula for calculating the magnetic induction intensity in the cavity of multi-layer winding electromagnetic water processor is derived. Moreover, the structural parameters of the processor are determined based on the simulation results of the Maxwell equations. According to the simulation results, we make a new multi-layer winding electromagnetic water processor, which will be used on the online electromagnetic scale suppression dynamic simulation table in the future.

The absorbance values of specific configuration solutions under different magnetic treatment conditions are studied using the UV method based on the circulating dynamic simulation experiment platform for the anti‐scaling of electromagnetics. Additionally, the relationship between the absorbance value and solution concentration is determined. Moreover, the nucleation rate of CaCO 3 is calculated using the absorbance value. The influence of the specific magnetic field on nucleating rate is analyzed. Subsequently, the magnetic memory effect and time of CO 3 −2 and water are studied. Results show that the magnetic treatment changes the nucleation rate of CaCO 3 and the critical oversaturation of the solution by acting on CO 3 −2 . This treatment also can promote the dissolution of CaCO 3 in water by changing the properties of water. These two aspects all exert memory effects; however, their respective memory times are different. Moreover, the results show that the magnetic treatment can reduce the critical oversaturation of the CaCO 3 solution and accelerate the nucleation rate. Furthermore, the memory time of the magnetic field acting on CO 3 −2 and the properties of water are 45 min and 78 h, respectively.

Four indicators, namely, conductivity, fouling induction period (FIP), scanning electron microscopy, and particle size distribution, were adopted in this study based on an online evaluation experimental platform of the electromagnetic anti-fouling effect and an electromagnetic anti-fouling treatment (EAT) device to investigate the anti-fouling effect of axial alternating electromagnetic field with different magnetic induction intensities (i.e., 0, 10, 15, 17.5, 20, 22.5, and 25 mT) on calcium carbonate (CaCO3) fouling in the U-shaped circulating cooling water heat exchange tube. The function model for FIP and magnetic induction intensity was established. Experimental results indicate that the anti-fouling effect was related to the magnetic induction intensity at a specified electromagnetic frequency (i.e., 1 kHz). Moreover, the magnetic induction intensity of 20 mT was considered an inflection point, in which the axial alternating electromagnetic field exhibited the best anti-fouling effect. The following results were obtained at 20 mT in this study. The conductivity increased by 84.87 mu s/cm in average compared with that of the no treatment group. FIP reached a maximum of 10,536 min. The average diameter of CaCO3 particles decreased to 4.04 mu m. In summary, EAT can effectively prevent and mitigate CaCO3 fouling, and the magnetic induction intensity of 20 mT was found to be the best magnetic induction intensity for the EAT device in the current experiment. (C) 2017 Elsevier Ltd. All rights reserved.