Hysteresis Model Research Articles

Design, experiment and modeling of a damper based on magnetic gradient pinch mode MR valve

Abstract In this study, a novel Magnetorheological (MR) damper designed based on the Magnetic Gradient Pitch Mode MR (MGPMR) valve, is investigated analytically and experimentally. The prototype and experimental platform are designed and established to characterize the dynamic force- displacement/velocity properties under board ranges of excitation and current conditions with the consideration of the effect of design parameters, which mainly includes the number of the non-magnetic rings and the diameter of the flow channel. The experimental data shows that the tunable damping range is positive correlation with the number of non-magnetic rings and negative correlation with the diameter of flow channel. Therefore, an analytical model, which considers the hysteresis damping model of the MGPMR valve, ideal gas model, and the hysteresis friction of seals, is established to describes the dynamic force- displacement/velocity properties of the MGPMR damper with 4 non-magnetic rings and 7mm diameter of the MGPMR valve. The proposed hysteresis damping model of the MGPMR valve consists of the tangential hyperbolic hysteresis model, tunable viscous damping, and fluid inertial together with the identified model parameters. The validity of the proposed model of MGPMR damper is demonstrated through a comparison between the simulation and experiment results showing good agreement of the hysteresis loops and output force-displacement/velocity characteristics under wide range of excitation and currents conditions.

A New and Easy Method to Determine the Energy Stored in Urban Areas: A Case Study of Mexico City

Urban areas present different climates from those of their rural surroundings. Energy balance and especially energy storage play important roles in the resulting climate since more than 50% of the net radiation is absorbed in densely urbanized areas. A simple model of energy storage in the urban fabric is presented, fed with the air temperature of a given area and its thermal properties; it can estimate heat storage (QS) with good results. The proposed QST energy storage model was compared with QS results obtained from two sites in Mexico City, Escandón (objective hysteresis model, QSOHM) and ENP7 (residual, QSRES), and one site in Marseille, France (thermal mass scheme, QSTMS). The comparison between QST and QSOHM showed that r2 = 0.71, while in ENP7 (QN > 0), QSRES and QST were 116.5 Wm−2 and 142 Wm−2, corresponding to 49% and 60% of the QN, respectively. The results obtained using the QSTMS model in Marseille and QST in Escandón showed similar behavior, with RMSEs of 109 and 101 Wm−2, respectively, in a daily period. Although it is difficult to discern which method is better, it is possible to affirm that the presented method is quite accurate, easier to use, and inexpensive.

Seismic Performance of Shaped Steel Reinforced High‐Strength Concrete Walls: Cyclic Loading Test and Analytical Modeling

ABSTRACTThe thickness of the bottom shear walls in tall and super‐tall structures is often designed too large to meet the limit requirements of axial compression ratios, which increases the weight and cost of the structure. To address this issue, high‐strength concrete (HSC) and shaped steel are combined to form composite shear wall members. This paper focuses on seismic performance and analytical hysteresis model of steel reinforced HSC shear walls (SRHCW) under high axial compressive load. Firstly, the reversed cyclic test was conducted to investigate the influence of concrete strength and the steel ratio on the seismic performance of SRHCWs by comparing the failure mechanism, hysteretic curves, stiffness degradation, ductility, energy dissipation, and steel bar strain variation of each specimen. Then, a hysteresis model for SRHCWs was established, and the model can be used for the nonlinear analysis and seismic performance evaluation of SRHCWs. Finally, the accuracy of the proposed hysteresis model was evaluated by the experimental data. The experimental results show that under high axial compression ratio, the interstory drift ratio capacity of SRHCWs can reach 3.03% showing excellent deformation performance. The wall specimens built with different strength concrete and shaped steel ratios exhibited similar strength, deformation, and initial stiffness, indicating that the steel ratio of the wall can be effectively reduced by upgrading the concrete strength of the wall specimens while ensuring its seismic performance. The analytical model can well predict the hysteresis force–deformation curves of SRHCWs under high axial load ratios.

Current transformer hysteresis modelling for condition assessment under standard and non-standard operation

Current transformer hysteresis modelling for condition assessment under standard and non-standard operation

Evaluation of Hysteresis Models for Estimating the Characteristics of High Pressure Solenoid Valves for Mechanical Ventilation

Abstract The flow control of inspiratory valves for mechanical ventilation is a crucial element of the overall functionality as it mainly governs precision and safety. However, control tuning can be challenging as the widely used magnetic actuation principle comes with a hysteresis shaped characteristic. As a result, the production of ventilators is highly dependent on specific valves and therefore vulnerable if supply chains are interrupted as during the pandemic. An approach which is capable of providing a reliable control for a variety of standard solenoid valves would be beneficial. Therefore, this work examines different models of hysteresis and their precision when being applied to actual measurement data of high pressure solenoid valves as a foundation for a following model-based control approach which can be either feedback or feedforward. Regarding the precision, the Prandtl-Ishlinskii (PI) model outperformed alternative approaches (MAEbelow2.5 L/ min) for the chosen parameters which is why the model is described for fitting both the forward and inverse case.

Testing and simulation of the hysteresis characteristics of magnetostrictive materials under harmonic excitation

As various power electronic devices are widely used in the power grid, the current flowing through the drive winding of the magnetostrictive actuator inevitably contains harmonic components. The flux density within the hysteresis material is non-sinusoidal with harmonic components, which distorts the hysteresis characteristics of the material and affects the accurate calculation of losses. This paper builds a harmonic magnetic performance testing platform for magnetostrictive materials to test and analyze the magnetic properties under different excitation conditions (magnetic density amplitude, harmonic order, and harmonic content). To complete the mathematical description of the static hysteresis model containing closed minor hysteresis loops, two pinning coefficients k1(Bn,kTHD) and k2(Bn,kTHD), which are related to the degree of harmonic distortion, are used to express the rate of change of the irreversible magnetization components. Fractional order derivative and harmonic frequency-dependent terms are used to characterize the eddy losses and excess losses mathematically. Finally, the dynamic hysteresis model under harmonic excitation is developed. Comparative analysis of model calculation results and experimental test data shows that the model can not only accurately simulate the distorted hysteresis characteristics but also predict the loss of magnetostrictive materials. This research is of significance to the optimal design and temperature rise analysis of magnetostrictive devices.

On the hysteretic bending behavior of slack metallic cables

Short and slack stranded metallic cables are encountered in several technical applications to connect different structures or different parts of the same structural system. A couple of relevant examples are provided by flexible-bus conductors used in high-voltage electrical substations or passive damping devices installed on overhead electrical lines, such as Bretelle dampers. Bending behavior of metallic cables is nonlinear and non-holonomic due to the onset and propagation of relative sliding phenomena between the wires. While taut suspended cables have been widely studied in the literature under the classic assumptions of small sag and perfect flexibility, whenever dealing with short and slack cables, the aforementioned hypotheses typically cease to be valid, and the bending stiffness contribution plays a significative role in the determination of the overall structural response. In the present paper, two different modeling strategies for the description of the bending behavior of short and slack stranded cables are presented. The first (discrete bending model) describes the cable as a composite structural element made of wires, which are individually modeled as curved elastic thin rods interacting through normal and tangential contact forces. The second (phenomenological bending model), instead, relies on a description of the cable bending process based on an application of the well-known Bouc-Wen hysteresis model. Applications of the proposed models are presented both at the cross-sectional and at the structural levels. The systematic comparison between theoretical and experimental results allows to assess the performance of the two proposed bending models when used with “nominal” values of the model parameters, which are estimated only on the base of the knowledge of the material and geometric properties of the strand. Moreover, a back-analysis of the model parameters is carried out to get an insight on internal mechanical parameters of the cable and on the overall cross-sectional bending response (e.g. bending stiffness values).

Neuro-enhanced fractional hysteresis modeling and identification by modified Newton-Raphson optimizer

The modeling and parameter identification of a system with hysteresis remains a difficult task. This paper aims to develop a hysteretic model by combining with a fractional Backlash-like model and cascade forward neural network, and proposed a modified Newton-Raphson-based optimizer parameter identification method to precisely capture the nonlinear behavior of piezoelectric platform. There are three contributions in this paper. Firstly, leveraging the definition of fractional calculus, a fractional Backlash-like model is proposed, whose rate dependence is proved theoretically. Secondly, a hybrid fractional Backlash-like model is established by combining fractional Backlash-like model with cascade forward neural network to enhance the fitting and generalization ability of the model. Thirdly, a modified Newton-Raphson-based optimizer enhances the original Newton-Raphson-based optimizer by incorporating a dynamic reverse learning strategy, a Q-learning strategy, a new adaptive coefficient, and local exploitation based on Levy flight, with theoretical analysis demonstrating improvements in convergence, diversity, and accuracy. The ablation test results show that the accuracy of the proposed modeling method is more than 40% less than that of the root mean square error obtained by the classic Backlash-like model. In addition, compared with the traditional Newton-Raphson-based optimizer, dandelion optimizer, particle swarm optimization and african vultures optimization algorithm, the modified algorithm shows significant advantages in accuracy, convergence speed and robustness under all test frequencies. The root mean square error obtained was reduced by more than 20%. These results show that the proposed method provides a powerful research idea for efficient and accurate hysteresis system modeling and parameter identification.

An asymmetric hysteresis model for metal-rubber isolators under dynamic loading and its application to nonlinear vibration simulation

An asymmetric hysteresis model for metal-rubber isolators under dynamic loading and its application to nonlinear vibration simulation

Modeling of magnetic hysteresis parameters in foraminiferal shells of the Mid-Atlantic Ridge

The composition and magnetic properties of foraminifers from bottom sediments of the Mid-Atlantic Ridge and their artificial analogues obtained by hydrothermal synthesis have been studied. The presence of magnetic hysteresis and theoretical modeling of hysteresis characteristics made it possible to assume the presence of grains of nonstoichiometric magnetite in single and low-domain states.

Impact resistance characteristics of pipeline system covered with W-shape elastic-porous metallic damper

As a novel elastic-porous damping material fabricated through entangled wire mesh, W-shape elastic-porous metallic damper (W-EPMD) is considered an ideal damping element for coated pipeline system due to the micro dry friction between metal wires, which induces energy dissipation. The complex interwoven cellular formations of metallic wire mesh pose challenges in characterizing its dynamic characteristics. In this work, the dynamic properties of the pipeline system covered with W-EPMD under various impact conditions, including the acceleration response and impact isolation coefficient, were investigated by numerical simulations and experimental analysis. Constitutive models used to characterize the hysteresis behavior of W-EPMD were introduced, comprising Yeoh and Bergström-Boyce models, and parameter identification were conducted through quasi-static experiments. The reliability of the established numerical model was confirmed through drop impact experiments. The results demonstrate that there is a maximum discrepancy of 9.1 % between the simulation predictions and experimental results of the stress-strain curve. The impact isolation coefficient of the pipeline system covered with W-EPMD exhibits a fluctuating trend with the rise of the pulse peak, while the maximum compression of W-EPMD steadily increases. During the pipeline impact process, the increased density of W-EPMD reduces the impact resistance of the pipeline system, while excessively low density leads to over-compression and structural damage to W-EPMD. Furthermore, the discrepancy of the acceleration response between experimental and numerical results under various excitation signals remain within 6 %, demonstrating that the hysteresis model effectively characterizes the impact resistance characteristics of the pipeline system covered the W-EPMD.

Reinforcement Learning-Based Adaptive Optimal Control for Nonlinear Systems With Asymmetric Hysteresis.

This article investigates the adaptive optimal tracking problem for a class of nonlinear affine systems with asymmetric Prandtl-Ishlinskii (PI) hysteresis nonlinearities based on actor-critic (A-C) learning mechanisms. Considering the huge obstacles arising from the uncertainty of hysteresis nonlinearity in actuators, we develop a scheme for the conflict between the construction of Hamilton functions and hysteresis nonlinearity. The actuator hysteresis forces the input into a hysteresis delay, thus preventing the Hamilton function from getting the current moment's input instantly and thus making optimization impossible. In the first step, an inverse model is constructed to compensate for the hysteresis model with a shift factor. In the second step, we compensate for the control input by designing a feedback controller and incorporating the estimation and approximation errors into the Hamilton error. Optimal control, the other part of the actual control input, is obtained by taking partial derivatives of the Hamiltonian function after the nonlinearities have been circumvented. At the end, a simulation is given to validate the developed solution.

Dynamic Hysteresis Model and Loss Prediction of GO Silicon Steel Under DC-Biased High-Frequency Excitation

Dynamic Hysteresis Model and Loss Prediction of GO Silicon Steel Under DC-Biased High-Frequency Excitation

Dynamic Hysteresis Model of GO Silicon Steel Considering Skin Effect and Saturation Effect

Dynamic Hysteresis Model of GO Silicon Steel Considering Skin Effect and Saturation Effect

An asymmetric pinching damaged hysteresis model for glubam members: Parameter identification and model comparison

The performance of glue laminated bamboo (glubam) members is governed by the nonlinear response at their joints, where high deformation levels and stress concentrations are developed. Numerous phenomenological models are presently employed to describe the hysteresis behavior of these joints, while these models always have an excessive number of parameters, and the physical interpretation of these parameters is often challenging. Moreover, some hysteresis models cannot capture all hysteresis features such as asymmetry, pinching, and damage. Consequently, this paper introduces a novel phenomenological-based hysteretic model named Asymmetric Pinching Damaged (APD) model, and implemented it in Abaqus by combining connector and spring elements in series or parallel. This model encompasses asymmetry, pinching, and strength degradation for bamboo joint components, with parameters that possess clear physical meanings and are readily comprehensible. This study also presented a parameter identification framework coupling the Parallel Genetic Algorithm (PGA) and Bayesian Neural Network (BNN). By merging the FE modeling and optimizing algorithms with the interactive application of ABAQUS and Python software platforms, the integrated identification framework is capable of performing multi-threaded parallel computation of finite element models considering the BNN-based uncertainty quantification, thus greatly improving the efficiency of parameter identification.

Experimental study on seismic performance of bridge pier with new HRB650E high-strength steel bar

To facilitate the application of high-strength steel in reinforced concrete bridge structures, this study explores the seismic performance of full-scale HRB650E high-strength reinforced concrete bridge piers. Initially, monotonic tensile tests were conducted on HRB400 and HRB650E steel rebars with the same slenderness ratio to analyze the differences in their mechanical properties. Subsequently, quasi-static cyclic tests were carried out on four square full-scale RC bridge piers to examine the influence of new high-strength rebars, stirrup ratios, and axial load ratios on the seismic performance. Based on the experimental results, a hysteresis model suitable for HRB650E reinforced concrete columns was developed. The findings indicate that the HRB650E steel bar exhibited lower uniform elongation and fracture elongation compared to HRB400 steel bar. The displacement at which HRB650E piers reached crack damage was 36 % higher than that of HRB400 piers, and they also showed lower residual displacements at all load levels. The maximum lateral load capacity and the ductility coefficient of HRB650E piers increased significantly compared to HRB400 piers. While the initial secant stiffness of both types was comparable, HRB650E piers exhibited a slower rate of stiffness degradation, resulting in higher secant stiffness at the ultimate state. They also demonstrated 35 % higher cumulative energy dissipation at the ultimate state. When the stirrup ratio of HRB650E piers was increased from 1.1 % to 1.7 %, there was a slight reduction in residual displacement, a small increase of the yield strength, and a minor improvement in the maximum lateral load capacity. Furthermore, a higher stirrup ratio was observed to improve energy dissipation levels at all loading stages. Increasing the axial load ratio of HRB650E piers from 0.1 to 0.2 allowed the piers to withstand greater deformations at the same repairable ultimate state, with significant increases in yield strength, maximum lateral load capacity, initial secant stiffness, and secant stiffness at the ultimate state, but a small increase in the cumulative energy dissipation. The hysteresis model for HRB650E RC columns, based on experimental data, exhibited good computational accuracy.

Dynamic modeling of variable speed left ventricular assist devices coupled to the cardiovascular system.

Most of the modeling of the Left Ventricular Assist Devices (LVADs) coupled with the cardiovascular system is based on the assumption of constant rotational speed. Compared with the traditional inertial model, the validated hysteresis model can take into account the unsteady characteristics of LVADs, but it fails to work under the condition of variable speed modulation. This study takes into consideration the impact of speed variations on the unsteady hysteresis effects. The time constant in the hysteresis model is treated as a time-varying parameter, thereby developing a new model applicable to variable speed modulation. Under sinusoidal speed modulation at various phases, a comparative analysis was undertaken among the steady-state model, inertial model, and the new model. Transient Computational Fluid Dynamics (CFD) simulations and existing experimental results are used for validation. The new model provides a more accurate method for the predicting the characteristics of LVAD in the coupled model under varying pump speeds, and exhibits higher linearity in the work done by the left ventricle and the blood pump, and , which is aligning closely with the experimental results. This enhancement renders it applicable for proactive control predictions and passive control validations.

Neural Network Architectures and Magnetic Hysteresis: Overview and Comparisons

The development of innovative materials, based on the modern technologies and processes, is the key factor to improve the energetic sustainability and reduce the environmental impact of electrical equipment. In particular, the modeling of magnetic hysteresis is crucial for the design and construction of electrical and electronic devices. In recent years, additive manufacturing techniques are playing a decisive role in the project and production of magnetic elements and circuits for applications in various engineering fields. To this aim, the use of the deep learning paradigm, integrated with the most common models of the magnetic hysteresis process, has become increasingly present in recent years. The intent of this paper is to provide the features of a wide range of deep learning tools to be applied to magnetic hysteresis context and beyond. The possibilities of building neural networks in hybrid form are innumerable, so it is not plausible to illustrate them in a single paper, but in the present context, several neural networks used in the scientific literature, integrated with various hysteretic mathematical models, including the well-known Preisach model, are compared. It is shown that this hybrid approach not only improves the modeling of hysteresis by significantly reducing computational time and efforts, but also offers new perspectives for the analysis and prediction of the behavior of magnetic materials, with significant implications for the production of advanced devices.

Improved active vibration control of a cantilever beam using MFC actuators with Hammerstein model-based hysteresis modeling and VSS-FxLMS control algorithm

This study aims to enhance active vibration control in a cantilever beam using macro fiber composite (MFC) actuators. To address the challenge of accurately modeling the complex hysteresis behavior of MFC actuators, an advanced hysteresis modeling technique is employed, integrating a non-symmetric Bouc–Wen model with an Auto-Regressive model with eXogenous inputs (ARX). The parameter estimation of this model is optimized using an adaptive mutation factor, and multiple mutation strategy differential evolution (AmFMMDE) algorithm. Additionally, a Variable Step Size Filtered-x Least Mean Square (VSS-FxLMS) algorithm with step size adaptation based on normalized error change is utilized for effective vibration control. This approach shows promising potential for practical engineering applications requiring precise and efficient active vibration control.

Modelling of water sorption hysteresis of cement-based materials based on pore microstructure

This paper presents a model for predicting water sorption isotherms of cement-based materials. In this model, hysteresis contributions of interlayer pores and gel/capillary pores are calculated separately. The hysteresis model of gel/capillary pores is achieved in four steps: (i) quantification of the pore network, (ii) determination of the criterion of saturation/desaturation of pores, (iii) derivation of the two-dimensional volumetric density distribution function, (iv) calculation of the real-time water content of gel/capillary pores. The hysteresis of interlayer pores is represented by an empirical model based on experiments. The reliability of the model is verified by comparing the model predictions and the experimental data in the literatures. Furthermore, three subjects were discussed: the influence of pore network on hysteresis, the hysteretic behavior of water in pores, the interaction of hysteresis mechanisms.