Search Results (43)

Determination of single-valued BH curve and power loss curve of electric steels is an important parameter in the design of electrical machines and transformers. This paper proposes a correction procedure for the measurement of anhysteretic BH curve and power losses, based on the finite element model (FEM) and SST apparatus. A 3D finite element model (FEM) of the SST (Single Sheet Tester) was developed with respect to the IEC 60404-3 standard. The measurement results obtained with a standardized SST apparatus are fed to its FEM and used to iteratively correct initial BH and power loss curves, obtained using magnetic equivalent circuits theory. The proposed iterative correction procedure is based on the steepest descent algorithm, while the stopping criteria were based on the difference between simulated and measured global variables (power loss, induced voltage, and primary current). After correction, root mean squared errors were decreased from 1.85 A/m to 42.88 × 10⁻³ A/m for the BH curve, and from 44.5 × 10⁻⁴ W/kg to 7.28 × 10⁻⁴ W/kg for the power loss curve. Full article

Today, numerous advanced options exist for analyzing and measuring magnetic hysteresis loops and core loss across a broad spectrum of applications. Most of these systems are compact and ready to use, fulfilling the measurement and data processing requirements for laminated iron cores according to the standards. However, modeling newly developed materials with complex structures or the high-frequency behavior of iron cores, and the computation of dynamic hysteresis properties’ temperature dependence, are still challenging problems in the field. Moreover, these standardized measurement tools are relatively expensive, and most of them represent a black box that impedes research and further development. This paper presents the development of a cheap and accessible measurement system that is explicitly designed for recording the hysteresis properties of 3D-printed iron cores. The paper presents a comprehensive overview of the design process, components, circuitry, and simulations integral to this project. The paper presents a completed circuit simulation conducted using LTspice and validation of the prototype’s measurement performance. The measurements obtained with the proposed system show good agreement with those of the reference setup, demonstrating its accuracy and practical applicability. Full article

This study investigates the electromagnetic analysis and optimal design of outer rotor type brushless DC (BLDC) motors for fan filter applications. The primary objective is to develop a method that integrates three-dimensional (3D) structural effects with efficient two-dimensional (2D) equivalent analysis. This study proposes a 2D equivalent analysis method that addresses the unique features of outer rotor type BLDC motors, particularly the permanent magnet (PM) overhang structure. This approach transforms the operating point on the B–H curve to facilitate accurate modeling in a 2D framework, overcoming traditional analysis limitations. An analytical method using spatial harmonics is introduced to derive essential electromagnetic quantities, namely flux linkage and back electromotive force (EMF). The method compensates for slot effects using the Carter coefficient, ensuring precise evaluation of circuit parameters and electromagnetic losses. To optimize motor performance, a multi-objective optimization technique is implemented using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), aiming to maximize both efficiency and power density. The research validates the proposed analytical approach against the finite element analysis method (FEM) results to confirm its accuracy. Full article

A three-dimensional model of a three-phase linear induction motor (LIM) is analyzed by using hybrid finite element–boundary element (FEM-BEM) analysis. Two models with aluminum rotors are considered, one with back iron and the other without back iron. The outer boundary is chosen arbitrarily in free space to enclose the motor. The problem domain is divided into rectangular brick elements. The FEM is applied for the interior region, and the BEM is applied for the outer surface. The iron parts can be simulated either as constant permeability regions or regions with the actual magnetization B-H curve. The electromagnetic field problem is solved in terms of the magnetic vector potential. Performance parameters such as propulsion force, levitation force, and dissipated power are then obtained. A comparison of the results with the available measurements from cited references shows agreement within 4–5% for the model without back iron and 9–14% for the model with back iron. It also shows the significant impact of the hybrid FEM-BEM in comparison with the FEM. Full article

A major challenge for practical magnetic energy harvesting (MEH) applications is achieving stable harvested power with high power density under a wide range of temperature variation. The amount of power harvested from the MEH is sensitive to ambient temperature because the characteristics of the magnetic material are greatly affected by temperature. From a practical point of view, previous studies have limitations because they do not consider thermal effects at all. In this paper, a novel control algorithm form maximum harvesting power in MEH is proposed by considering dynamic changes in temperature for the first time. In order to tackle this problem, a temperature-dependent B-H curve model is proposed, which considers the effect of temperature variation on the magnetic core. This study is the first to integrate thermal effects at the design stage of MEH. Theoretical analysis using the proposed B-H curve model demonstrates that the nonlinear behavior of magnetic materials can be accurately predicted under varying temperature conditions. Based on the above analysis, it was possible to extract the maximum harvested power while predicting shifts in the magnetic saturation point across a wide temperature range. Experimental results validate the effectiveness of the proposed design method, achieving a 26.5% higher power density compared to conventional methods that neglect thermal effects. Full article

The saturation model of the transformer is one of the core tools of multi-physics simulation. By combining it with multi-physics simulation, researchers can more comprehensively evaluate the performance of a transformer in actual applications. Geomagnetically induced currents (GIC) induce DC bias in transformers, leading to core saturation and a host of adverse effects. Traditional transformer models often struggle to accurately capture the behavior of the core under nonlinear saturation conditions. To address these challenges, a saturable transformer unified magnetic-equivalent (UMEC) model that directly takes the B-H magnetization curve to represent a transformer’s core nonlinear characteristics is proposed. The saturable transformer model is based on the model of a magnetic circuit of the transformer core. An estimation method to obtain a transformer’s essential parameters for saturation simulation is presented. GIC effects on transformer saturation are also studied through the proposed saturable transformer and estimation method. Full article

The current transformer (CT)-based energy harvesting method has gained considerable attention for low-power devices. Accurate estimation of the B-H curve is essential to develop a high-performance CT, as it closely relates to the electromagnetic behavior of CT material. However, the existing estimation methods for the B-H curve face several drawbacks, which include process complexity and a high cost. This study presented an intuitive method to estimate the B-H curve based on the experimentally obtained resistance-voltage data. The performance of the CT core is obtained based on the estimated B-H curve, which exhibited an error of only 2.6% when compared to the experimental results for the most accurate case. Additionally, we analyzed split-core performance deterioration caused by the presence of an air gap. The air gap formation of the split core was closely related to the surface roughness, which significantly influenced core performance. The air gap range that minimizes the reduction in performance is predicted and validated through simulations and experiments. This research highlights a straightforward approach to obtaining the B-H curve of magnetic CT core material. We believe that this study provides the design guidelines needed to develop a high-performance CT core, including considerations for core geometry and the recommended air gap range. Full article

Bighorn sheep (BHS) populations have been reported to experience high levels of morbidity and mortality following infection with Mycoplasma ovipneumoniae. This contrasts with the subclinical presentation in domestic sheep (DS). Understanding this difference requires baseline knowledge of pre- and post-infection immune responses of both species. The present study identifies differences in leukocyte phenotypes between adult BHS and DS before and after intranasal inoculation with 1 × 10⁸ Mycoplasma ovipneumoniae. Prior to inoculation, BHS were confirmed to have a higher abundance of leukocyte CD14 and serum concentrations of IL-36RA. In contrast, DS had a higher leukocyte abundance of CD16 in addition to previously observed integrin markers and CD172a, as well as greater serum TNF-α concentrations. Within 15 days of inoculation, BHS displayed signs of mild respiratory disease and M. ovipneumoniae DNA was detected on nasal swabs using a quantitative PCR; meanwhile, DS exhibited few to no clinical signs and had levels of M. ovipneumoniae DNA below the standard curve threshold. Immunologic markers remained relatively consistent pre- and post-inoculation in DS, while BHS demonstrated changes in the peripheral leukocyte expression of CD172a and CD14. Circulating serum IL-36RA decreased and CXCL10 increased within BHS. These findings highlight significant differences in cellular immunity between BHS and DS, raised and housed under similar conditions, prior to and following inoculation with M. ovipneumoniae. Full article

The r-process is one of the processes that produces heavy elements in the Universe. One of its possible astrophysical sites is the neutron star–black hole (NS-BH) merger. We first show that the neutrons can degenerate before and during the r-process in these mergers. Previous studies assumed neutrons were non-degenerate and the related rates were calculated under Maxwell–Boltzmann approximations. Hence, we corrected the related rates with neutron degeneracy put in the network code and calculated with the trajectories of NS-BH mergers. We show that there are differences in the nuclei distributions. The heating rates and the temperature at most can be two times larger. The change in heating rates and temperature can affect the light curves of the kilonovae. However, this has little effect on the final abundances. Full article

Direct current (DC) bias induced by the DC transmission and geomagnetically induced current is a critical factor in the abnormal operation of electrical equipment and is widely used in the field of power transmission and distribution system state evaluation. As the main affected component, the vector magnetization state of a transformer core under DC bias has rarely been studied, resulting in inaccurate transformer operation state estimations. In this paper, a dynamic vector hysteresis model that considers the impact of rotating and DC-biased fields is introduced into the numerical analysis to simulate the distribution of magnetic properties, iron loss and temperature of the transformer core model and a physical 110 kV single-phase autotransformer core. The maximum values of B, H and iron loss exist at the corners and T-joint of the core under rotating and DC-biased fields. The corresponding maximum value of the temperature increase is found in the main core limb area. The temperature rise of the 110 kV transformer core under various DC-biased conditions is measured and compared with the FEM (Finite Element Method) results of the proposed model and the model solely based on the magnetization curve B||H. The calculation error of the temperature rise obtained by the improved model is approximately 3.76–15.73% and is much less than the model solely based on magnetization curve B||H (approximately 50.71–66.92%). Full article

Low-cost sensors (LCSs) of Geekcreit PM₁/PM_2.5/PM₁₀ (based on a PMS5003 sampler) and BOHU BH-1 models A3 and B3 (based on a Pando G7 sampler) were compared for different aerosol size ranges using a research-grade instrument (Grimm 1.109) under controlled laboratory conditions. An aerosol generator was utilized to produce various sizes of monodispersed particulate matter (PM), which was introduced into a laboratory smoke chamber under resistance heating/cooling and/or varying RH conditions. In addition, the accuracy of the air temperature (T) and relative humidity (RH) sensors of the LCSs were assessed against calibrated, laboratory-grade instruments. The study LCSs showed generally accurate readings for PM_2.5, irrespectively of the slow T and/or RH changes, which provided apt conditions for accurate calibration slopes (S) and low intercepts/bias (b) of the linear fits. On the other hand, PM₁ and PM₁₀ readings slightly deviated from those observed with the reference monitor, likely due to the lower detection efficacy of the LCSs towards fine and coarse PM. Varying RH influenced the S and b values, showing its impact on the detection efficacy of LCSs. Under low/medium RH, homoscedastic calibration curves of PM_x were found, whereas rather heteroscedastic calibration plots were observed at high RH. For T calibration, low RH in the smoke chamber provided more reproducible conditions in terms of lower measurement bias for LCSs as recorded against a calibrated, reference-grade thermometer. Full article

This paper deals with the electromagnetic characterization of a laminated toroidal ferromagnetic core made through additive manufacturing, specifically using the laser powder bed fusion process. The continuing demand for increasingly efficient, lightweight, and higher performance electric machines is creating huge challenges in the design and realization of new electric motor solutions. The constant improvements in additive manufacturing technologies have prompted researchers to investigate the possibility of adopting these production techniques for the manufacture of high-value electric motors. For these reasons, this paper investigates the ferromagnetic characteristics of an additively manufactured core made with FeSi6.5 powder. The BH curve and the specific iron losses of the processed material have been measured so that they can be compared with a commercial lamination, and have the possibility of carrying out more precise finite element simulations. Full article

The luminous intensity measurements of airport navigational lighting should be performed in accordance with the recommendations of the European Aviation Safety Agency (EASA), which allows for the determination of the possibility of further operation or the need to replace particular lamps. This article presents a device and method for measuring the light main beam of in-pavement airport lamps used on runways and taxiways. During the measuring process in the laboratory dark room, the proposed system automatically prepares reports as heatmaps presenting angular relationships of light distribution. Photometric measurements were made using a BH1750 illuminance sensor, which was compared to a certified Sonopan L-200P luxmeter. The measurement stability of different BH1750 modes was investigated for different airport lamp power source thresholds. Due to distortions in spectral characteristic of BH1750, polynomial corrections were proposed. The functionality of the device was presented for the exemplary assessment of used and refurbished runway in-pavement airport lamps to compare their parameters change. The research results and device implementation were possible through scientific cooperation with the Poznań-Ławica Airport. Full article

The concept of being readily biodegradable is crucial in evaluating the potential effects of chemical substances on ecosystems and conducting environmental risk assessments. Substances that readily biodegrade are generally associated with lower environmental persistence and reduced risks to the environment compared to those that do not easily degrade. The accurate development of quantitative structure–activity relationship (QSAR) models for biodegradability prediction plays a critical role in advancing the design and creation of sustainable chemicals. In this paper, we report the results of our investigation into the utilization of classification and regression trees (CARTs) in classifying and selecting features of biodegradable substances based on 2D molecular descriptors. CARTs are a well-known machine learning approach renowned for their simplicity, scalability, and built-in feature selection capabilities, rendering them highly suitable for the analysis of large datasets. Curvature and interaction tests were employed to construct efficient and unbiased trees, while Bayesian optimization (BO) and repeated cross-validation techniques were utilized to improve the generalization and stability of the trees. The main objective was to classify substances as either readily biodegradable (RB) or non-readily biodegradable (NRB). We compared the performance of the proposed CARTs with support vector machine (SVM), K nearest neighbor (kNN), and regulated logistic regression (RLR) models in terms of overall accuracy, sensitivity, specificity, and receiver operating characteristics (ROC) curve. The experimental findings demonstrated that the proposed CART model, which integrated curvature–interaction tests, outperformed other models in classifying the test subset. It achieved accuracy of 85.63%, sensitivity of 87.12%, specificity of 84.94%, and a highly comparable area under the ROC curve of 0.87. In the prediction process, the model identified the top ten most crucial descriptors, with the SpMaxB(m) and SpMin1_Bh(v) descriptors standing out as notably superior to the remaining descriptors. Full article

The reverse magnetization behavior for bulk composite alloys containing Mn-Al-C and α-Fe nanoparticles (NPs) has been investigated by hysteresis loops, recoil, and first-order reversal curves (FORC) analysis. The effect of adding different percentages of α-Fe (5, 10, 15, and 20 wt. %) on the magnetic properties and demagnetization behavior of Mn-Al-C nanostructured bulk magnets was investigated. The fabricated nanocomposites were characterized by XRD and VSM for structural analysis and magnetic behavior investigations, respectively. The demagnetization curve of the sample Mn-Al-C-5wt. % α-Fe showed a single hard magnetic behavior and showed the highest increase in remanence magnetization compared to the sample without α-Fe, and therefore this combination was selected as the optimal composition for FORC analysis. Magnetic properties for Mn-Al-C-5 wt. % α-Fe nanocomposite were obtained as M_s = 75 emu/g, M_r = 46 emu/g, H_c = 3.3 kOe, and (BH)_max = 1.6 MGOe, indicating a much higher (BH)_max than the sample with no α-Fe. FORC analysis was performed to identify exchange coupling for the Mn-Al-C-0.05α-Fe nanocomposite sample. The results of this analysis showed the presence of two soft and hard ferromagnetic components. Further, it showed that the reverse magnetization process in the composite sample containing 5 wt. % α-Fe is the domain rotation model. Full article