Search Results (138)

This work introduces two cooperative dielectric elastomer actuator (DEA) array designs, enabling comparison between a fully soft, wearable-oriented system and a rigid, high-performance platform. The soft silicone-based array achieves strokes up to 1.9 mm and maintains 44% displacement under strong bending, demonstrating suitability for haptic feedback in wearable applications. The rigid prototype, based on thermoformed buckling beams, provides strokes up to 2.8 mm, reduced hysteresis, improved stability, and reproducible fabrication, while allowing fine-tuning of preload conditions. Experiments revealed frequency-dependent coupling, enabling stimulation of defective actuators via neighboring elements and amplification of single-element strokes through cooperative excitation. Furthermore, self-sensing effects were exploited for error detection. These results underline the potential of DEA arrays for decentralized control, fault-tolerant actuation, and future applications in soft robotics and wearable systems. Full article

Background/Objectives: Synaptic plasticity is fundamental to learning and memory, yet classical models such as Hebbian learning and spike-timing-dependent plasticity often overlook the distributed and wave-like nature of neural activity. We present a computational framework grounded in Scale Relativity Theory (SRT), which describes neural propagation along fractal geodesics in a non-differentiable space-time. The objective is to link nonlinear wave dynamics with the emergence of structured memory representations in a biologically plausible manner. Methods: Neural activity was modeled using nonlinear Schrödinger-type equations derived from SRT, yielding complex wave solutions. Synaptic plasticity was coupled through a reaction–diffusion rule driven by local activity intensity. Simulations were performed in one- and two-dimensional domains using finite difference schemes. Analyses included spectral entropy, cross-correlation, and Fourier methods to evaluate the organization and complexity of the resulting synaptic fields. Results: The model reproduced core neurobiological features: localized potentiation resembling CA1 place fields, periodic plasticity akin to entorhinal grid cells, and modular tiling patterns consistent with V1 orientation maps. Interacting waveforms generated interference-dependent plasticity, modeling memory competition and contextual modulation. The system displayed robustness to noise, gradual potentiation with saturation, and hysteresis under reversal, reflecting empirical learning and reconsolidation dynamics. Cross-frequency coupling of theta and gamma inputs further enriched trace complexity, yielding multi-scale memory structures. Conclusions: Wave-driven dynamics in fractal space-time provide a hypothesis-generating framework for distributed memory formation. The current approach is theoretical and simulation-based, relying on a simplified plasticity rule that omits neuromodulatory and glial influences. While encouraging in its ability to reproduce biological motifs, the framework remains preliminary; future work must benchmark against established models such as STDP and attractor networks and propose empirical tests to validate or falsify its predictions. Full article

Piezoelectric actuators, widely used in micro-positioning and active control systems, show important hysteresis characteristics. In particular, the hysteresis contribution is a complex phenomenon that is difficult to model when the input amplitude and frequency are time-dependent. Existing dynamic physical models poorly describe the hysteresis influence of industrial mechatronic devices. This paper proposes a novel hybrid data-driven model based on the Bouc–Wen and backlash hysteresis formulations to appraise and compensate for the nonlinear effects. Firstly, the performance of the piezoelectric actuator was simulated and then tested in a complete representative domain, and then using the committee machine approach. Experimental campaigns were conducted to develop an algorithm that incorporated Bouc–Wen and backlash hysteresis parameters derived via genetic algorithm (GA) and particle swarm optimization (PSO) approaches for identification. These parameters were combined in a committee machine using a set of frequency clusters. The results obtained demonstrated an error reduction of 23.54% for the committee machine approach compared with the complete approach. The root mean square error (RMSE) was 0.42 µm, and the maximum absolute error (MAE) appraisal was close to 0.86 µm in the 150–250 Hz domain via the Bouc–Wen sub-model tuned with the genetic algorithm (GA). Full article

Soft magnetic materials are highly suitable for use as sensors in the monitoring of materials, applications, and processes, with proven effectiveness across various industries. Their ability to be configured as microwires allows excellent integration within composite structures, making them particularly effective for structural health monitoring. Research in this area has enabled the analysis of both hysteresis loops and scattering parameters in transmission and reflection within the microwave frequency range, under conditions such as composite matrix polymerization or when subjecting specimens to different stress states. Consequently, a clear dependence of scattering parameters and impedance on applied stress in composites with magnetic microwire inclusions, which can be monitored, has been demonstrated. However, despite the repeatability of the phenomenon, modeling this behavior is challenging due to the dispersion of results caused by multiple factors and varying conditions that influence outcomes in a conventional environment. This study analyzes the influence of the relative sample position on these measurements and presents results obtained by modifying the position and orientation of microwires through rotation and flipping movements of the test specimen. Full article

High efficiency and high power density are key targets in modern power conversion. Operating power converters at high switching frequencies enables the use of smaller passive components, which, in turn, facilitate achieving high power density. However, the concurrent increase in switching frequency and power density leads to efficiency and overheating issues. Soft switching techniques are typically employed to minimize switching losses and significantly improve efficiency by reducing power losses. However, the hysteresis behavior of the power electronics devices’ output capacitance, C_OSS, is the cause of regrettable losses in Super-Junction (SJ) MOSFETs, SiC MOSFETs, and GaN HEMTs, which are usually adopted in soft switching-based conversion schemes. This paper reviews the techniques for measuring hysteresis traces and power losses, as well as the understanding of the phenomenon to identify current research trends and open problems. A few studies have reported that GaN HEMTs tend to exhibit the lowest hysteresis losses, while Si superjunction (SJ) MOSFETs often show the highest. However, this conclusion cannot be generalized by comparing the results from different works because they are typically made across devices with different (when the information is reported) breakdown voltages, on-state resistances, die sizes, and test conditions. Moreover, some recent investigations using advanced TCAD simulations have demonstrated that newer Si-SJ MOSFETs employing trench-filling epitaxial growth can achieve significantly reduced hysteresis losses. Similarly, while multiple studies confirm that hysteresis losses increase with increasing dv/dt and decreasing temperature, the extent of this dependence varies significantly with device structure and test methodology. This difficulty in obtaining a general conclusion is due to the lack of proper figures of merit that account for hysteresis losses, making it problematic to evaluate the suitability of different devices in resonant converters. This problem highlights the primary current challenge, which is the development of a standard and automated method for characterizing C_OSS hysteresis. Consequently, significant research effort must be invested in addressing this main challenge and the other challenges described in this study to enable power electronics researchers and practitioners to develop resonant converters properly. Full article

This study addresses the challenge of accurately modeling the dynamic behavior of industrial robots for precision manufacturing applications. Using a comprehensive experimental approach with modal impulse hammer testing and triaxial acceleration measurements, 360 frequency response functions were recorded along orthogonal measurement paths for a KUKA KR10 robot. Two dynamic models with different parameter dimensions (12-parameter and 24-parameter) were developed in Matlab/Simscape, and their parameters were identified using genetic algorithm optimization. The KUKA KR10 features Harmonic Drives at each joint, whose high transmission ratio and zero backlash characteristics significantly influence rotational dynamics and allow for meaningful static structural measurements. Objective functions based on the Frequency Response Assurance Criterion (FRAC) and Root Mean Square Error (RMSE) metrics were employed, utilizing a frequency-dependent weighting function. The performance of the models was evaluated across different robot configurations and frequency ranges. The 24-parameter model demonstrated significantly superior performance, achieving 70% overall average Global FRAC in the limited frequency range (≤200 Hz) compared to 41% for the 12-parameter model when optimized using a representative subset of 9 measurement points. Both models showed substantially better performance in the limited frequency range than in the full spectrum. This research provides a validated methodology for dynamic characterization of industrial robots and demonstrates that higher-dimensional models, incorporating transverse joint compliance, can accurately represent robot dynamics up to approximately 200 Hz. Future work will investigate nonlinear effects such as torsional stiffness hysteresis, particularly relevant for Harmonic Drive systems. 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

Fast steering mirrors (FSMs), actuated by piezoelectric ceramics, play pivotal roles in satellite laser communication, distinguished by their high bandwidth and fast responsiveness, thereby facilitating the precise pointing and robust tracking of laser beams. However, the dynamic performance of FSMs is notably impaired by the hysteresis nonlinearity inherent in piezoelectric ceramics. Under dynamic conditions, rate-dependent hysteresis models and Hammerstein models are predominantly employed to characterize hysteresis nonlinearity. By combining the advantages of these two models, a hysteresis model termed modified Hammerstein-like (MHL) model is proposed. This model integrates an input time delay, a rate-dependent hysteresis term, and a linear dynamic term in a cascaded structure, effectively capturing the dynamic characteristics of hysteresis systems across a broad frequency range. Additionally, a composite control strategy is tailored for the MHL model which consists of a feedforward compensator based on a rate-dependent hysteresis inverse model and a proportional–integral (PI) controller for closed-loop regulation. Experimental results demonstrate the effectiveness of the proposed modeling and composite control methods. Full article

The degradation of subarctic peatland ecosystems under climate change impacts surrounding landscapes, carbon balance, and biogeochemical cycles. To assess these ecosystems’ responses to climate change, it is essential to consider not only the active-layer thickness but also its thermo-hydraulic conditions. Ground-penetrating radar is one of the leading methods for studying the active layer, and this paper proposes systematically investigating its potential to determine the thermal properties of the active layer. Collected experimental data confirm temperature hysteresis in peat linked to changes in water and ice content, which GPR may detect. Using palsa mires of the Kola Peninsula (NW Russia) as a case study, we analyze relationships between peat parameters in the active layer and search for thermal gradient responses in GPR signal attributes. The results reveal that frequency-dependent GPR attributes can delineate thermal intervals of ±1 °C through disperse waveguides. However, further verification is needed to clarify the conditions under which GPR can reliably detect temperature variations in peat, considering factors such as moisture content and peat structure. In conclusion, our study discusses the potential of GPR for remotely monitoring freeze–thaw processes and moisture distribution in frozen peatlands and its role as a valuable tool for studying peat thermal properties in terms of permafrost stability prediction. Full article

As conductive materials, ionogels have attracted significant attention for their potential applications in flexible wearable electronics. However, preparing an ionogel with mechanical properties akin to human skin while also achieving transparency, adhesion, and low hysteresis through simple processes remains challenging. Here, we introduce a multifunctional ionogel synthesized via a one-step photopolymerization method. By leveraging the good compatibility between the ionic liquid and the polymer network, as well as the hydrogen bonding and chemical crosslinking within the gel network, we achieved an ionogel with high transparency (>98%), stretchability (fracture strain of 19), low hysteresis (<5.83%), strong adhesion, robust mechanical stability, excellent electrical properties, a wide operating temperature range, and a tunable modulus (1–103 kPa) that matches human skin. When used as a conductor in soft actuators, the ionogel enabled a large area strain of 36% and a fast electromechanical conversion time of less than 1 s. The actuator demonstrated good actuation performance with voltage and frequency dependence, electrochemical stability, and outstanding durability over millions of cycles. This study provides a simple and effective method to produce multifunctional ionogels with tailored mechanical properties that match those of human skin, paving the way for their application in flexible wearable electronics. Full article

The dynamic response of pump valve motion directly influences the volumetric efficiency of drilling pumps and serves as a critical factor in performance enhancement. This study presents a coupled fluid–structure interaction (FSI) analysis of a novel secondary cushioned pump valve for drilling systems. A validated 3D transient numerical model, integrating piston–valve kinematic coupling and clearance threshold modeling, was developed to resolve the dynamic interactions between reciprocating mechanisms and turbulent flow fields. The methodology addresses critical limitations in conventional valve closure simulations by incorporating a geometrically adaptive mesh refinement strategy while maintaining computational stability. Transient velocity profiles confirm complete sealing integrity with near-zero leakage (<0.01 m/s), while a 39.3 MPa inter-pipeline pressure differential induces 16% higher jet velocities in suction valves compared to discharge counterparts. The secondary cushioned valve design reduces closure hysteresis by 22%, enhancing volumetric efficiency under rated conditions. Parametric studies reveal structural dominance, with increases in cylindrical spring stiffness lowering discharge valve lift by 7.2% and velocity amplitude by 2.74%, while wave spring optimization (24% stiffness enhancement) eliminates pressure decay and reduces perturbations by 90%. Operational sensitivity analysis demonstrates stroke frequency as a critical failure determinant: elevating speed from 90 to 120 rpm amplifies suction valve peak velocity by 59.87% and initial closing shock by 129.07%. Transient flow simulations validate configuration-dependent performance, showing 6.3 ± 0.1% flow rate deviations from theoretical predictions (Q_{t_max} = 40.0316 kg/s) due to kinematic hysteresis. This study establishes spring parameter modulation as a key strategy for balancing flow stability and mitigating cushioning-induced oscillations. These findings provide actionable insights for optimizing high-pressure pump systems through hysteresis control and parametric adaptation. Full article

Active magnetic bearings (AMBs), pivotal in high-speed rotating machinery for their frictionless operation and precise control, demand power amplifiers with exceptional dynamic performance and minimal current ripple. However, conventional amplifier designs often overlook eddy current effects, a critical oversight given the high-frequency switching inherent to pulse-width modulation (PWM). These induced eddy currents distort output waveforms, amplify ripple, and degrade system bandwidth. This paper bridges this critical gap by proposing a comprehensive methodology to model, quantify, and mitigate eddy current impacts on three-level half-bridge power amplifiers. A novel mutual inductance-embedded circuit model was developed, integrating winding–eddy current interactions under PWM operations, while a discretized transfer function framework dissects frequency-dependent ripple amplification and phase hysteresis. A voltage selection criterion was analytically derived to suppress nonlinear distortions, ensuring stable operation in high-precision applications. A Simulink simulation model was established to verify the accuracy of the theoretical model. Experimental validation demonstrated a 212% surge in steady-state ripple (48 mA to 150 mA at 4 A DC bias) under a 20 kHz PWM operation, aligning with theoretical predictions. Dynamic load tests (400 Hz) showed a 6.28% current amplitude reduction at 80 V DC bus voltage compared to 40 V, highlighting bandwidth degradation. This research provides a paradigm for optimizing AMB power electronics, enhancing precision in next-generation high-speed systems. Full article

This study investigates the fatigue durability of Plexus MA300 methacrylic adhesive, which is employed in structural joints of metals, plastics, and composites. Cast adhesive specimens were subjected to cyclic tensile loads at a frequency of 5 Hz with a stress ratio R = 0.1. Six load levels were tested. Hysteresis loops were recorded during testing and analyzed in detail. Significant differences in fatigue fracture characteristics were observed depending on load level. Specimens subjected to high loads exhibited a characteristic radial structure with a distinct crack initiation point, whereas specimens tested at lower loads showed more uniform, matte fracture surfaces. Hysteresis loop analysis revealed phenomena typical for polymers: creep and damping causing energy dissipation. Various fatigue approaches were compared: stress-based, strain-based, energy-based, and stiffness-based. The highest coefficient of determination (R²) was obtained for the model based on strain energy density, indicating its superior utility in predicting the fatigue life of the tested adhesive. The obtained results contribute to the understanding of the fatigue behavior of methacrylic adhesives and provide practical data for structural joint design involving this material class. Full article

In this study, the role of blood perfusion in modulating the thermal response of tumors during magnetic nanoparticle hyperthermia was investigated through computational modeling. The thermal dissipation of 15 nm magnetite nanoparticles was estimated using micromagnetic simulations of their hysteresis loops under a magnetic field of 20 mT and a frequency of 100 kHz. These calculations provided precise energy loss parameters, serving as inputs to simulate the temperature distribution in a tumor embedded within healthy tissue. Temperature-dependent blood perfusion rates, derived from experimental models, were integrated to differentiate the vascular dynamics in normal and cancerous tissues. The simulations were conducted using a bioheat transfer model on a 2D axisymmetric tumor geometry with magnetite nanoparticles dispersed uniformly in the tumor volume. Results showed that tumor tissues exhibit limited blood perfusion enhancement under hyperthermic conditions compared to healthy tissues, leading to localized heat retention favorable for therapeutic purposes. The computational framework validated these findings by achieving therapeutic tumor temperatures (41–45 °C) without significant overheating of surrounding healthy tissues, highlighting the critical interplay between perfusion and energy dissipation. These results demonstrate the efficacy of combining nanoparticle modeling with temperature-dependent perfusion for optimizing magnetic nanoparticle-based hyperthermia protocols. Full article

A stochastic energetics framework is applied to examine how periodically shifting the frequency of a time-dependent oscillating temperature gradient affects heat transport in a nanoscale molecular model. We specifically examine the effects that frequency switching, i.e., instantaneously changing the oscillation frequency of the temperature gradient, has on the shape of the heat transport hysteresis curves generated by a particle connected to two thermal baths, each with a temperature that is oscillating in time. Analytical expressions are derived for the energy fluxes in/out of the system and the baths, with excellent agreement observed between the analytical expressions and the results from nonequilibrium molecular dynamics simulations. We find that the shape of the heat transport hysteresis curves can be significantly altered by shifting the frequency between fast and slow oscillation regimes. We also observe the emergence of features in the hysteresis curves such as pinched loops and complex multi-loop patterns due to the frequency shifting. The presented results have implications in the design of thermal neuromorphic devices such as thermal memristors and thermal memcapacitors. Full article