Simulation of iron losses in induction machines using an iron loss model for rotating magnetization loci in no electrical steel

Purpose Various iron loss models can be used for the simulation of electrical machines. In particular, the effect of rotating magnetic flux density at certain geometric locations in a machine is often neglected by conventional iron loss models. The purpose of this paper is to compare the adapted IEM loss model for rotational magnetization that is developed within the context of this work with other existing models in the framework of a finite element simulation of an exemplary induction machine. Design/methodology/approach In this paper, an adapted IEM loss model for rotational magnetization, developed within the context of the paper, is implemented in a finite element method simulation and used to calculate the iron losses of an exemplary induction machine. The resulting iron losses are compared with the iron losses simulated using three other already existing iron loss models that do not consider the effects of rotational flux densities. The used iron loss models are the modified Bertotti model, the IEM-5 parameter model and a dynamic core loss model. For the analysis, different operating points and different locations within the machine are examined, leading to the analysis of different shapes and amplitudes of the flux density curves. Findings The modified Bertotti model, the IEM-5 parameter model and the dynamic core loss model underestimate the hysteresis and excess losses in locations of rotational magnetizations and low-flux densities, while they overestimate the losses for rotational magnetization and high-flux densities. The error is reduced by the adapted IEM loss model for rotational magnetization. Furthermore, it is shown that the dynamic core loss model results in significant higher hysteresis losses for magnetizations with a high amount of harmonics. Originality/value The simulation results show that the adapted IEM loss model for rotational magnetization provides very similar results to existing iron loss models in the case of unidirectional magnetization. Furthermore, it is able to reproduce the effects of rotational flux densities on iron losses within a machine simulation.

On the Corrosion of Two Types of Bronzes Under Cavitation

This article contains the results of the experiments concerning the mass loss of two types of bronze in seawater in the cavitation produced by ultrasound generated by a high-frequency generator. The mass loss models are presented for the experimental conditions when the generator worked at different powers - 80 W, 120 W, and 180 W. In all scenarios, the results show that the bronze with Sn has the highest mass loss in the cavitation field.

Analytical Iron Loss Evaluation in the Stator Yoke of Slotless Surface-Mounted PM Machines

<div>One of the attractive benefits of slotless machines is low losses at high speeds, which could be emphasized by a careful stator core loss assessment, potentially available already at the pre-design stage. Unfortunately, mainstream iron loss estimation methods are typically implemented in the finite element analysis (FEA) environment with a constant-coefficients dummy model, leading to weak extrapolations with huge errors. In this paper, an analytical method for iron loss prediction in the stator core of slotless PM machines is derived. It is based on the extension of the 2-D field solution over the entire machine geometry. Then, the analytical solution is combined with variable- or constant-coefficient loss models (i.e., VARCO or CCM), which can be efficiently computed by vectorized post-processing. VARCO loss models are shown to be preferred at a general level.Moreover, the paper proposes a lookup-table-based (LUT) solution as an alternative approach. The main contribution lies in the numerical link between the analytical field solution and the iron loss estimate, with the aid of a code implementation of the proposed methodology. First, the models are compared against a sufficiently dense dataset available from laminations manufacturer for validation purposes. Then, all the methods are compared for the slotless machine case. Finally, the models are applied to a real case study and validated experimentally.</div>

Analytical Iron Loss Evaluation in the Stator Yoke of Slotless Surface-Mounted PM Machines

<div>One of the attractive benefits of slotless machines is low losses at high speeds, which could be emphasized by a careful stator core loss assessment, potentially available already at the pre-design stage. Unfortunately, mainstream iron loss estimation methods are typically implemented in the finite element analysis (FEA) environment with a constant-coefficients dummy model, leading to weak extrapolations with huge errors. In this paper, an analytical method for iron loss prediction in the stator core of slotless PM machines is derived. It is based on the extension of the 2-D field solution over the entire machine geometry. Then, the analytical solution is combined with variable- or constant-coefficient loss models (i.e., VARCO or CCM), which can be efficiently computed by vectorized post-processing. VARCO loss models are shown to be preferred at a general level.Moreover, the paper proposes a lookup-table-based (LUT) solution as an alternative approach. The main contribution lies in the numerical link between the analytical field solution and the iron loss estimate, with the aid of a code implementation of the proposed methodology. First, the models are compared against a sufficiently dense dataset available from laminations manufacturer for validation purposes. Then, all the methods are compared for the slotless machine case. Finally, the models are applied to a real case study and validated experimentally.</div>

Variable-resolution building exposure modelling for earthquake and tsunami scenario-based risk assessment: an application case in Lima, Peru

We propose the use of variable resolution boundaries based on central Voronoi tessellations (CVTs) to spatially aggregate building exposure models for risk assessment to various natural hazards. Such a framework is especially beneficial when the spatial distribution of the considered hazards presents intensity measures with contrasting footprints and spatial correlations, such as in coastal environments. This work avoids the incorrect assumption that a single intensity value from hazards with low spatial correlation (e.g. tsunami) can be considered to be representative within large-sized geo-cells for physical vulnerability assessment, without, at the same time, increasing the complexity of the overall model. We present decoupled earthquake and tsunami scenario-based risk estimates for the residential building stock of Lima (Peru). We observe that earthquake loss models for far-field subduction sources are practically insensitive to the exposure resolution. Conversely, tsunami loss models and associated uncertainties depend on the spatial correlations of the hazard intensities as well as on the resolution of the exposure models. We note that for the portfolio located in the coastal area exposed to both perils in Lima, the ground shaking dominates the losses for lower-magnitude earthquakes, whilst tsunamis cause the most damage for larger-magnitude events. For the latter, two sets of existing empirical flow depth fragility models are used, resulting in large differences in the calculated losses. This study, therefore, raises awareness about the uncertainties associated with the selection of fragility models and spatial aggregation entities for exposure modelling and loss mapping.

Empirical path loss models for 5G wireless sensor network in coastal pebble/sand environments

Propagation modeling of small/big pebbles and air-dry/wet sand environments for wireless sensor networks has not been extensively studied in the 5G frequency band. This study is necessary for the proper coverage planning and efficient operation of wireless sensors in various applications such as monitoring summer sporting activities, and environmental/ground surveillance on coastal pebble/sand environments, or tracking pebble mobility and including the rescue of the flood-type avalanche in Gravel-Bed Rivers. In this study, empirical path loss models are proposed for wireless sensor networks in pebble/sand environments at two discrete frequencies, namely 3.5 and 4.2 GHz. The theoretical models and proposed models are compared to indicate the accuracy of proposed models in predicting the path loss in these environments. Additionally, R-squared and RMSE values of eight different generated models are calculated in the range of 0.931–0.877 and 2.284–2.837, respectively. These comparisons indicate that empirical model parameters have a significant effect on the path loss model.

Optimal Design of a Flyback Microinverter Operating under Discontinuous-Boundary Conduction Mode (DBCM)

The flyback converter has been widely used in Photovoltaic microinverters, operating either in Discontinuous, Boundary, or Continuous Conduction Mode (DCM, BCM, CCM). The recently proposed hybrid DBCM operation inherits the merits of both DCM and BCM. In this work, the necessary analytical equations describing the converter operation for any given condition under DBCM are derived, and are needed due to the hybrid nature of the modulation strategy during each sinusoidal wave. Based on this analysis, a design optimization sequence used to maximize the weighted efficiency of the inverter under DBCM is then applied. The design procedure is based on a power loss analysis for each converter component and focuses on the appropriate selection of the converter parameters. To achieve this, accurate, fully parameterized loss models of the converter components are implemented. The power loss analysis is then validated by applying the optimization methodology to build an experimental prototype operating in DBCM.

Photoevaporation versus core-powered mass-loss: model comparison with the 3D radius gap

The EUV/X-ray photoevaporation and core-powered mass-loss models are both capable of reproducing the bimodality in the sizes of small, close-in exoplanets observed by the Kepler space mission, often referred to as the ‘radius gap’. However, it is unclear which of these two mechanisms dominates the atmospheric mass-loss which is likely sculpting the radius gap. In this work, we propose a new method of differentiating between the two models, which relies on analysing the radius gap in 3D parameter space. Using models for both mechanisms, and by performing synthetic transit surveys we predict the size and characteristics of a survey capable of discriminating between the two models. We find that a survey of ≳ 5000 planets, with a wide range in stellar mass and measurement uncertainties at a $\lesssim 5{{\ \rm per\ cent}}$ level is sufficient. Our methodology is robust against moderate false positive contamination of $\lesssim 10{{\ \rm per\ cent}}$. We perform our analysis on two surveys (which do not satisfy our requirements): the California Kepler Survey and the Gaia-Kepler Survey and find, unsurprisingly, that both data-sets are consistent with either model. We propose a hypothesis test to be performed on future surveys which can robustly ascertain which of the two mechanisms formed the radius gap, provided one dominates over the other.