Hybrid Analytical Model Research Articles

A Hybrid Analytical Model of Growth Regulation in Animals

The aim of this study was to build and analyse a model of ontogenetic growth of animals. The model was built based on experimental data and field observations. The growth of pigs was modelled by a non-local hybrid technique. This technique treats time as a discrete variable. In this study the growth of pigs was modelled beginning the stage of the rapid growth up to the maximum weight. The growth was modelled as a dynamic system. It was shown that the trajectory of the growth is neither smooth nor continuous. The main theme in this study is transition to a new growth phenotype. There are two results in this study. At a certain point in animal's ontogeny the trajectory of the growth undergoes a first-order phase transition. In the next stage, during bifurcation, new trajectories of growth emerge; this sequence of events has a biological meaning. The emerged trajectories differ from the initial trajectory, and from each other in essence. In the model, one trajectory of the growth emerges instantly. For other growth trajectory to emerge it takes half a year. In a population of animals, it is a general situation. Individual animals can take on only one of the emerged trajectories. In this study, a two-stage process of a transition to a new ontogenetic trajectory or a new phenotype was revealed. The transition to the new growth phenotype is to consider as the model of the pattern of the systemic regulation of growth.

3-D Hybrid Analytical Prediction Model for Air-Cored Linear-Rotary Induction Machine

This article presents a 3-D hybrid analytical prediction model for an air-cored linear-rotary induction machine (LRIM) in which its columnar movable armature surfaced with the conductor. The analytical magnetic distributions in the conductor and air gap of the LRIM are predicted by employing a group of H-formulations in the conductor and the Laplacian equations with magnetic scalar potential (MSP) in the others in the Cartesian coordinate. The correctness of the magnetic field distributions and the eddy-current distributions is verified by the numerical computational results using the 3-D finite-element method (FEM).

Modified Winding Function Analysis of Synchronous Reluctance Motor for Design Iteration Purposes

This article proposes a hybrid analytical modeling procedure for the performance parameter estimation of synchronous reluctance machine, including its operation in the region of magnetic saturation. The proposed model better estimated the torque profile through improved translation and stepped transition of rotor flux barriers. The non-linear operation is simulated by considering the global saturation and estimating the machine’s operating point on the magnetization curve of the core material. The procedure formulation focuses on improving the accuracy and rapidness of the iterative design process. The obtained results are validated against an already established design analysis technique, finite-element analysis, and the frequency spectrum analysis of practical machine results. With the improved accuracy and the least requirement of simulation runtime and computational resources, the modeling procedure can be utilized as an initial design iteration tool.

An Experimental Approach to Evaluate Film Thickness in Starved Large-Size Spinning Contacts

Abstract In the present work, we evaluate the effects of lubricant starvation on the film thickness of spinning large-size point contacts from an experimental standpoint. This kind of contact is found in roller bearings in which the lubrication of the roller-end/flange contacts may be critical with respect to the system performance. First, the conception and validation of a dedicated experimental setup inducing both test conditions, either independently or combined, is exposed. Then, the work presents novel experimental measurements that corroborate the numerical trends determined in earlier work from the authors and describe the behavior of such contacts from the perspective of its kinematic field. Finally, both maximum and minimum film thicknesses obtained experimentally and numerically are gathered in a chart and compared well with the results given by a hybrid analytical model, combining independently starvation and spinning influences.

Influence of particle shape and material on the acoustic radiation force and microstreaming in a standing wave.

In view of its influence on the acoustic radiation force, we investigate the microstreaming around a small solid elastic particle in an ultrasonic standing wave in dependence of its material properties and shape. The configuration is axisymmetric, making it accessible to numerical methods, such as the finite element method. The results reveal a transition from viscous scattering- to microstreaming-dominated acoustic radiation force that depends on the particle density. When a deviation of the particle shape from a sphere becomes smaller than the viscous boundary layer thickness, we show that the influence of the shape on the viscous contributions to the acoustic radiation force diminishes, allowing the use of theoretical models for a spherical particle. However, extreme asymmetric shape perturbations, such as crowns with sharp edges, can give rise to noticeable viscous contributions for a dense particle that is larger than the viscous boundary layer thickness. We also introduce a hybrid analytical model for the acoustic radiation force on a spherical particle that accounts for the microstreaming and particle compressibility and shows a good agreement with numerical simulations for an arbitrary particle size and density.

Simplified 3-D Hybrid Analytical Modelling of Magnet Temperature Distribution for Surface-mounted PMSM With Segmented Magnets

In this article, a simplified three-dimensional (3-D) hybrid analytical thermal model for surface-mounted permanent magnet (PM) synchronous machines is proposed and applied to investigate the influence of PM segmenting strategies on the spatial PM temperature distributions and hotspots. The developed 3-D hybrid thermal model synergies the lumped-parameter thermal model and analytical method and is able to estimate 3-D spatial temperature distributions and hotspots for both unsegmented and segmented surface-mounted PMs accounting for the uneven PM eddy current loss distributions. Meanwhile, by utilizing the proposed matrix-based post-processing methods, the developed hybrid analytical thermal model has a simple mathematical expression but persists in high estimation accuracy. Finally, the proposed hybrid analytical modelling method is validated by 3-D electromagnetic-thermal coupled FEA and experiments.

A Novel Hybrid Analytical Model of Active Magnetic Bearing Considering Rotor Eccentricity and Local Saturation Effect

To facilitate the active magnetic bearing (AMB) design and analysis, an accurate and fast model that considers both rotor eccentricity and the saturation effect is necessary. In this article, a novel hybrid analytical model (HAM) for effective calculation of the magnetic field of the AMB is proposed. Eccentricity and local saturation are considered in the proposed HAM. In the proposed HAM, the stator and rotor are modeled by elementary subdomains (ESDs) and the air-gap is modeled by magnetic equivalent circuit (MEC). Direct coupling between the solutions in the ESD regions with MEC completes the whole model matrices. Compared to the existing literature, the proposed model considers both the rotor eccentricity and material nonlinearity. The effectiveness and accuracy of the proposed HAM are validated by both the finite element model and experimental results. The results show that the proposed HAM can accurately predict the magnetic quantities of the AMB.

Analytical modelling of one cage rotor induction motor for electric submersible pumps

A new hybrid analytical model (HAM) based on conformal mapping (CM) method and magnetic equivalent circuit (MEC) model is presented in this paper for electromagnetic modelling of cage rotor induction motors (CRIMs) used in electric submersible pumps (ESPs). For every operating point, the iron parts are modelled with a non-linear MEC model to calculate the equivalent virtual currents, which represent the influence of magneto motive force (MMF) drops and MMF sources in stator and rotor cores. The effects of the equivalent virtual currents on the air-gap magnetic field are then considered using the CM method and Hague's solution. This approach for calculating the air-gap field is also used to prepare a 3-D lookup table (3-D LUT) for each element of inductance matrix and derivative of inductance matrix in terms of rotor position. These LUTs are then used for transient modelling and analysis of CRIM under no-load and loading conditions. The accuracy of proposed HAM is validated by comparing the results obtained through HAM with corresponding results obtained from finite element method and experiment set-up.

A new hybrid analytical model for electromagnetic analysis of wound rotor induction motors

AbstractAccurate modeling of slotting and magnetic saturation effects has been two main challenges for analytical modeling of electric machines. In this article, first, different techniques such as sub‐domain (S‐D) model, winding function theory, magnetic equivalent circuit (MEC) model, and conformal mapping (CM) method are introduced to analytical model and analysis of electric machines. These techniques are also compared in terms of their accuracy, and computational complexity. Second, with respect to the comparison results, a new hybrid analytical model is presented for electromagnetic modeling of wound rotor induction motors, which consider the modeling accuracy of slotting and magnetic saturation effect, simultaneously. In this way, the air‐gap region is modeled by using S‐D model, and the iron parts are considered by using MEC model assisted by CMs. In final, the analytical results are verified by comparing with corresponding results obtained through finite element method and experiment set‐up.

A Hybrid Analytic Model for the Effective Prediction of Different Stages in Chronic Kidney Ailments

Chronic kidney disease (CKD) is a gradual loss of kidney function over the period of time and it is irrevocable once functionality reaches the critical state. Detecting the various stages of CKD helps to reduce the progression of the disease. Accurate prediction of CKD stages is one of the urgent needs in the medical industry and it can be effectively done by adopting machine learning (ML) techniques. The primary objective of the present research is to develop an effective classification model for the accurate prediction of CKD stages based on the patient’s health profile as well as the clinical test reports. Here, a hybrid ML strategy is employed that integrates random forest (RF) and AdaBoost (AB) techniques through a voting classifier (VC). The standard CKD dataset with 400 tuples and 25 parameters is used for the proposed investigation. The modification of diet in renal disease (MDRD) equation is used to extract an additional feature known as “estimated Glomerular Filtration Rate (eGFR)” for the prediction of the CKD stage. Pre-processing is carried out on the CKD dataset to fill the missing values by considering the skewness of the parameters and the issue of data leakage is also well addressed. Medically important features are considered and Correlation analysis is carried out to select the appropriate features for the model building process. The proposed Hybrid Ensemble Model (HEM) aids in lowering the bias and variance. HEM model efficiency is assessed using the performance metrics such as cross validation score (CVS), accuracy, precision, recall, F1 measure, Mean Squared Error (MSE), bias and variance and it is compared with the state-of-the-art classification schemes. The outcomes of the analysis reveal that the proposed HEM ensures that the CKD stage prediction is more accurate with 99.16%, 100%, 100% in reduced feature set I, set II, set III and with cross validation score of 97.85%, 99.28%, and 99.64% with reduced features set I, set II and set III respectively.

A Novel Asymmetric-PM Hybrid-Magnetic-Circuit Variable Flux Memory Machine for Traction Applications

In this paper, a novel asymmetric-permanent- magnet hybrid-magnetic-circuit variable flux memory machine (AH-VFMM) is proposed. The low coercive force (LCF) permanent magnets (PMs) are located on one biased side of the hybrid magnetic circuit branch, forming an AH configuration. Compared to its conventional symmetric-PM hybrid-magnetic-circuit (SH) counterpart, the proposed design benefits from the reduced usage of high coercive force (HCF) rare-earth magnet, alleviating the magnetic saturation to improve the flux regulation (FR) range, while the excellent load demagnetization withstand (LDW) capability can be still maintained. The topology evolution and operating principle of the proposed machine are introduced and described, respectively. Then, based on the combination of the magnetic equivalent circuit (MEC) method and Schwarz-Christoffel (SC) transformation, a hybrid analytical model is established to quantitatively reveal the mechanism of FR range extension, and facilitate the initial design of the machine. The electromagnetic characteristics of the proposed machine under different magnetization states (MSs) are investigated and compared with those of the conventional SH counterpart. Finally, an AH-VFMM prototype is manufactured, and the experimental measurements are carried out to verify the validity of the proposed design.

A New Hybrid Analytical Model Based on Winding Function Theory for Analysis of Unbalanced Two-Phase Induction Motors

The purpose of this paper is to present a new hybrid analytical model (HAM) based on winding function theory (WFT) for electromagnetic analysis of performance of one typical unbalanced two-phase induction motor (UTPIM). Different indexes of electromagnetic modeling such as winding distribution, slotting effect, and magnetic saturation can be accurately considered by using the proposed HAM. For obtaining this new hybrid technique, the winding function theory is reformulated for considering the magnetic saturation in addition to the influence of slotting and winding distribution. The conformal mappings (CMs) are used to accurately calculate the slotted air-gap length. The magnetic equivalent circuit (MEC) model is used to consider the magneto-motive force (MMF) drop in iron parts of stator and rotor due to the excitation of one phase-winding. The obtained results of CMs and MEC are then utilized in reformulated WFT to calculate the inductances of respective phase-winding. Transient analysis is then done to calculate the indexes of performance such as air-gap magnetic field, phase currents, electromagnetic torque, and rotor speed by using the lookup table of inductances while considering different capacitors in auxiliary phase. In each step, the accuracy of analytical results is verified by comparing with corresponding results obtained through FEM.

People's expectations and experiences of big data collection in the Saudi context.

Big data and machine learning technologies facilitate various business intelligence activities for businesses. However, personal data collection can generate adverse effects on consumers. Big data collection can compromise people’s sense of autonomy, harming digital privacy, transparency and trust. This research investigates personal data collection, control, awareness, and privacy regulation on people’s autonomy in Saudi. This study used a hybrid analytical model that incorporates symmetrical and asymmetrical analysis via fuzzy set qualitative comparative analysis (fsQCA) to analyze consumer sense of autonomy regarding big data collection. The symmetrical shows that ‘Control’ had the most significant influence on people’s autonomy, followed by ‘Big data collection’ and ‘Awareness’. The fsQCA shows 84% of the variation, explaining the people’s autonomy.

Estimation of 3-D Magnet Temperature Distribution Based on Lumped-Parameter and Analytical Hybrid Thermal Model for SPMSM

This paper presents a hybrid analytical thermal model by utilizing the synergies of the lumped-parameter thermal model (LPTM) and the analytical thermal model to estimate the 3-dimensional (3-D) permanent magnet (PM) temperature distribution as well as the hotspot for surface-mounted PM synchronous machines (SPMSMs). The hybrid analytical thermal model is firstly developed based on 2-dimensional analytical models in radial-circumferential and radial-axial planes, and then extended to three dimensions, in which the uneven distributions of PM eddy current loss are taken into account. The analytical solutions are obtained by solving the Poisson's equations under the Dirichlet and the convection boundary conditions, which are extracted from the synergized LPTM. The proposed hybrid thermal model is applied to a totally enclosed SPMSM and validated by the 3-D electromagnetic-thermal coupled finite element method and experiments.

Transmissivity and groundwater flow exert a strong influence on drainage density

Abstract. The extent to which groundwater flow affects drainage density and erosion has long been debated but is still uncertain. Here, I present a new hybrid analytical and numerical model that simulates groundwater flow, overland flow, hillslope erosion and stream incision. The model is used to explore the relation between groundwater flow and the incision and persistence of streams for a set of parameters that represent average humid climate conditions. The results show that transmissivity and groundwater flow exert a strong control on drainage density. High transmissivity results in low drainage density and high incision rates (and vice versa), with drainage density varying roughly linearly with transmissivity. The model evolves by a process that is defined here as groundwater capture, whereby streams with a higher rate of incision draw the water table below neighbouring streams, which subsequently run dry and stop incising. This process is less efficient in models with low transmissivity due to the association between low transmissivity and high water table gradients. A comparison of different parameters shows that drainage density is most sensitive to transmissivity, followed by parameters that govern the initial slope and base level. The results agree with field data that show a negative correlation between transmissivity and drainage density. These results imply that permeability and transmissivity exert a strong control on drainage density, stream incision and landscape evolution. Thus, models of landscape evolution may need to explicitly include groundwater flow.

Estimation of Two- and Three-dimensional Spatial Magnet Temperature Distributions for Interior PMSMs Based on Hybrid Analytical and Lumped-parameter Thermal Model

A hybrid analytical and lumped-parameter thermal model is proposed in this paper to estimate the transient and steady-state two- and three-dimensional (2/3-D) spatial magnet temperature distributions for an interior permanent magnet synchronous machine (IPMSM). On the basis of a lumped-parameter thermal model (LPTM), the magnet analytical thermal models (ATMs) are synergized to establish the hybrid thermal model. By utilizing the transient or steady-state boundary conditions calculated by the LPTM, the ATMs are obtained by solving the heat conduction equations to estimate the spatial magnet temperature distributions in the 2-D horizontal-vertical and axial-vertical planes, which can also be extended to the 3-D temperature distribution by utilizing the multi-slice method. Meanwhile, the non-uniform magnet eddy current loss is also considered. Finally, both electromagnetic-thermal coupled finite element analysis method and experiments are used for verification based on a totally enclosed IPMSM.

Detection of Behavioral Patterns Employing a Hybrid Approach of Computational Techniques

As far as the present state is concerned in detecting the behavioral pattern of humans (subject) using morphological image processing, a considerable portion of the study has been conducted utilizing frontal vision data of human faces. The present research work had used a side vision of human-face data to develop a theoretical framework via a hybrid analytical model approach. In this example, hybridization includes an artificial neural network (ANN) with a genetic algorithm (GA). We researched the geometrical properties extracted from side-vision human-face data. An additional study was conducted to determine the ideal number of geometrical characteristics to pick while clustering. The close vicinity of minimum distance measurements is done for these clusters, mapped for proper classification and decision process of behavioral pattern. To identify the data acquired, support vector machines and artificial neural networks are utilized. A method known as an adaptive-unidirectional associative memory (AUTAM) was used to map one side of a human face to the other side of the same subject. The behavioral pattern has been detected based on two-class problem classification, and the decision process has been done using a genetic algorithm with best-fit measurements. The developed algorithm in the present work has been tested by considering a dataset of 100 subjects and tested using standard databases like FERET, Multi-PIE, Yale Face database, RTR, CASIA, etc. The complexity measures have also been calculated under worst-case and best-case situations.

2‐D analytical on‐load electromagnetic model for double‐layer slotted interior permanent magnet synchronous machines

A fast hybrid analytical model is presented to predict the on-load performance of double-layer interior permanent-magnet synchronous machines (IPMSMs) considering both iron bridges saturation and slotting effects. The saturation of the iron bridges is defined by a constant flux in the magnetic equivalent circuit method. The slotting effect is defined by a flux path function and virtual surface currents (VSCs) in one-dimensional (1-D) and two-dimensional (2-D) analytical methods, respectively. For the no-load condition, double-layer IPMSMs are modelled via surface-mounted permanent magnet synchronous machines with two types of the permanent magnet model and the Magnetic Islands method are used to calculate the armature reaction. The effect of the stator slots is considered by using VSCs. To increase the computation speed in the 2-D analytical method, the amount of VSC is calculated by 1-D analysis. The 1-D and 2-D analytical results for a double-layer IPMSM are compared with those of finite element analysis and experimental set-up.

Analytical Modeling of High-Torque-Density Spoke-Type Permanent Magnet In-Wheel Motor Accounting for Rotor Slot and Eccentric Magnetic Pole

In this article, a hybrid analytical model combining the subdomain method and the lumped-parameter magnetic circuit method (LMCM) is presented for the analysis of a high-torque-density spoke-type permanent magnet in-wheel motor considering rotor slot and eccentric magnetic pole. In the proposed model, the air-gap field distribution is derived using the subdomain method, while the saturation and the axial flux leakage of the iron core are considered by LMCM. The rectangular-shaped spoke magnets, eccentric magnetic poles, and rotor slots are approximated by multiple layers of arc-shaped subdomains. The magnetic equivalent circuit (MEC) of the stator and rotor is established, and the nonlinearity of the iron core is taken into account. Based on the developed hybrid analytical model, electromagnetic performance, such as cogging torque, electromagnetic torque, flux linkage, and back electromotive force, are obtained. The analytical results are verified by the finite-element method, and its application in the optimization process is investigated. Finally, a 1800-Nm high-torque prototype machine is manufactured and tested, and the results validate the accuracy and efficiency of the analytical method.

Analytical investigation on wave attenuation performance of a floating breakwater with nonlinear stiffness

Floating breakwaters play an important role in protecting harborage and marine structures from wave impact. Traditional floating breakwaters (FBs) are not applicative for their ineffectiveness in low frequency waves attenuation. Based on the idea of reducing equivalent stiffness, this paper proposes a FB with nonlinear stiffness to improve the wave attenuation performance. The eigenfunction expansion matching method (EEMM) and multi-harmonic balance method (MHBM) are corporately applied to solve the new model involving nonlinear coupling problem of water waves and floating structures. A pile restrained FB with quasi-zero-stiffness (QZS) is taken as an example to verify the feasibility of the hybrid analytical model and to reveal the wave attenuation mechanism of the nonlinear breakwater. The comparison between nonlinear FB and linear FB shows that nonlinear FB can effectively widen the attenuation frequency bandwidth. The conception of nonlinear floating breakwater proposed in this study provides a new technical idea for attenuating low frequency waves and the hybrid solution method adopted in this paper may be extensible to other wave-structure nonlinear coupling problems.