Dynamic Characterization of Optical Coherence-Based Displacement-Type Weight Sensor

At present, development of manufacturer’s ultrasonic cleaning tank (UCT) to match the requirements from consumers usually relies on computer simulation based on harmonic response analysis (HRA). However, this technique can only be used with single-frequency UCT. For dual frequency, the manufacturer used information from empirical experiment alongside trial-and-error methods to develop prototypes, resulting in the UCT that may not be fully efficient. Thus, lack of such a proper calculational method to develop the dual frequency UCT was a problem that greatly impacted the manufacturers and consumers. To resolve this problem, we proposed a new model of simulation using transient dynamics analysis (TDA) which was successfully applied to develop the prototype of dual frequency UCT, 400 W, 18 L in capacity, eight horn transducers, 28 and 40 kHz frequencies for manufacturing. The TDA can indicate the acoustic pressure at all positions inside the UCT in transient states from the start to the states ready for proper cleaning. The calculation also reveals the correlation between the positions of acoustic pressure and the placement positions of transducers and frequencies. In comparison with the HRA at 28 kHz UCT, this TDA yielded the results more accurately than the HRA simulation, comparing to the experiments. Furthermore, the TDA can also be applied to the multifrequency UCTs as well. In this article, the step-by-step development of methodology was reported. Finally, this simulation can lead to the successful design of the high-performance dual frequencies UCT for the manufacturers.

This paper presents a novel Model-Free Deadbeat Predictive Current Controller (MF-DBPC) tailored for grid connected two-level inverters incorporating resistance-inductance (R-L) filters. Unlike traditional approaches, the MF-DBPC leverages a data-driven model derived solely from current and voltage measurements, eliminating the need for explicit systems parameter inputs. Central to the MF-DBPC’s functionality is an Auto-Regressive with Exogenous Input (ARX) model, complemented by a Recursive Least Squares (RLS) estimator for real-time parameter identification. This strategy offers enhanced adaptability to dynamic system conditions and achieve robustness against parameter mismatches inherent in grid-connected inverter systems. To demonstrate this, two distinct model-free predictive control strategies have been benchmarked: one grounded in the deadbeat control principle and the other utilizing a rolling optimization technique. Simulation analyses demonstrate that the MF-DBPC, driven by the deadbeat principle, yields superior current waveform quality while requiring a sampling frequency five times lower than its rolling optimization technique. Experimental validation further confirms the efficacy of the MF-DBPC across steady-state and dynamic performance metrics. Notably, its robustness against filter inductance mismatches is highlighted, showcasing resilience under challenging real-world conditions.

Origami‐inspired robots hold significant potential in flexible systems, yet their operational speeds remain constrained by the inherent trade‐off between structural compliance and actuation efficiency. This study presents a novel approach by exploiting the transient energy release characteristics of bistable Kresling origami to achieve rapid locomotion. Through parametric modelling of the critical bistable transition, we establish quantitative relationships between geometric parameters and dynamic performance metrics, revealing that optimised configurations enable ultra‐fast rebound within 60 ms. The robot integrates a cable‐driven crank mechanism that synchronises motor rotation with periodic linear actuation, achieving precise control over energy storage–release cycles. A bioinspired differential friction foot design with programmable anchoring sequences facilitates earthworm‐like peristaltic motion. Experimental results demonstrate exceptional crawling speeds up to 375 mm/s (3–4 body lengths/s) across multiple substrates (ceramic, wood, PVC). This work provides a paradigm‐shifting framework for reconciling speed and flexibility in soft robotics, with direct implications for applications requiring rapid reconfiguration in confined environments.

There is a strong demand for the research of electric vehicles (EVs) in automotive industry, because of an increased concern of the energy depletion and environmental pollution problems caused by oil-fueled automotive. The traction motor drive system is one of the core components of EVs, and a motor with superior dynamic performance and high efficiency could significantly reduce energy consumption and improve riding comfort of EVs. Therefore, in order to achieve high dynamic performance and high efficiency of permanent magnet synchronous motor (PMSM), a multi-objective optimization design method for PMSM based on the artificial bee colony algorithm was proposed in this paper. First, based on the magnetic field analytical model of PMSM, the analytical expressions of the key parameters were deduced, namely, mechanical time constant and electrical time constant. Second, the efficiency and electrical and mechanical time constant were defined as optimization objectives. Third, the efficiency and dynamic performance of the original motor and optimized motor were compared applying the finite-element analysis. Furthermore, one prototype machine was manufactured according to the results of optimization. The dynamic performance and efficiency of the prototype had been tested. The experiments show confident results that the efficiency increased about 1% and the mechanical time constant reduced to 31.4% of initial value.

Purpose To analyze the dynamic response of the lumbosacral vertebrae structure of a scoliosis spine and a kyphosis spine under whole-body vibration. Methods Typical Lenke4 (kyphosis) and Lenke3 (scoliosis) spinal columns were used as research objects. A finite element model of the lumbosacral vertebrae segment was established and validated based on CT scanning images. Modal, harmonic response, and transient dynamic analyses were performed on the lumbar-sacral scoliosis model using the finite element software abaqus. Results The first four resonance frequencies of kyphosis spine extracted from modal analysis were 0.86, 1.45, 8.51, and 55.71 Hz. The first four resonance frequencies of scoliosis spine extracted from modal analysis were 0.76, 1.45, 10.51, and 63.82 Hz. The scoliosis spine had the maximum resonance amplitude in the transverse direction, while the kyphosis spine had the maximum resonance amplitude in the anteroposterior direction. The dynamic response in transient analysis exhibited periodic response over time at all levels. Conclusion The scoliosis and kyphosis deformity of the spine significantly complicates the vibration response in the scoliosis and kyphosis areas at the top of the spine. Scoliosis and kyphosis patients are more likely to experience vibrational spinal diseases than healthy people. Besides, applying vertical cyclic loads on a malformed spine may cause further rotation of scoliosis and kyphosis deformities.

Model predictive control (MPC) emerges as an attractive alternative for the control of modular multilevel converters (MMCs) owing to its superior dynamic performance and ease of implementation. Nevertheless, conventional MPC's performance could be further improved by reducing dependence on weighting factors, switching frequency, and computational burden. To achieve these objectives, an arm‐current sensorless MPC is developed for a grid‐interfacing MMC in this article. The MPC is integrated with an arm‐current sensorless reduced switching frequency voltage balance algorithm that requires only switching vectors (where number of submodules per arm) to optimize the cost function. This method does not require knowledge of arm‐current direction to decide the charging and discharging state of the submodule capacitors. The developed control not only reduces the switching frequency of devices but also eliminates the need to sense the arm currents. As a result, it reduces the system's cost, complexity, computational burden, switching losses and provides a more reliable control method for MMCs with superior dynamic performance. Further, the effect of parameter mismatch on the developed MPC's dynamic performance and stability is studied. The developed MPC's effectiveness is validated through both simulation and experimental results and also compared with existing methods under different conditions.

Financial time series forecasting plays a critical role in investment decision-making, risk management, and portfolio optimization. Traditional forecasting models, including statistical approaches and deep learning-based architectures, often focus on maximizing predictive accuracy but fail to incorporate dynamic risk-adjusted performance metrics. The Sharpe ratio, a widely used measure of risk-adjusted return, is typically applied post-forecasting, limiting its potential to guide predictive models during training. To address this limitation, this study proposes an adaptive Sharpe ratio-based temporal fusion transformer (AS-TFT) that integrates risk-aware forecasting mechanisms to optimize financial predictions while considering return volatility. Experimental evaluations on stock indices, cryptocurrency prices, and commodity markets demonstrate that the AS-TFT outperforms conventional forecasting methods in terms of both predictive accuracy and portfolio returns. The results highlight the importance of integrating risk-adjusted financial performance metrics within deep learning-based forecasting architectures, offering a practical and scalable solution for financial decision-making.

Daylight performance metrics provide a promising approach for the design and optimization of lighting strategies in buildings and their management. Smart controls for electric lighting can reduce power consumption and promote visual comfort using different control strategies, based on affordable technologies and low building impact. The aim of this research is to assess the energy efficiency of these smart controls by means of dynamic daylight performance metrics, to determine suitable solutions based on the geometry of the architecture and the weather conditions. The analysis considers different room dimensions, with variable window size and two mean surface reflectance values. DaySim 3.1 lighting software provides the simulations for the study, determining the necessary quantification of dynamic metrics to evaluate the usefulness of the proposed smart controls and their impact on energy efficiency. The validation of dynamic metrics is carried out by monitoring a mesh of illuminance-meters in test cells throughout one year. The results showed that, for most rooms more than 3.00 m deep, smart controls achieve worthwhile energy savings and a low payback period, regardless of weather conditions and for worst-case situations. It is also concluded that dimming systems provide a higher net present value and allow the use of smaller window size than other control solutions.

Dynamic transport characteristics and performance response of commercial-size polymer electrolyte membrane fuel cell stack: An experimental study

Dynamic response characteristics of solenoid valves directly determined their performances. Among numerous parameters, the influence of magnetic isolation ring (MIR) on solenoid valve performance is crucial. Previous optimization studies have not conducted a systematic exploration and analysis of MIR. In this paper, a model of an AC solenoid valve considering the position of the MIR is proposed, and the model’s accuracy was verified by simulation and experiments. The electromagnetic force, response time, and magnetic field distribution at different positions of the MIR were analyzed, and the effect of the position of MIR on dynamic response characteristics of the solenoid valve was clarified. The results show that the MIR affects the dynamic response characteristics of the solenoid valve by changing the magnetic circuit. With the positive translation of the position of the MIR along the Z-axis, the electromagnetic force first increases and then decreases, and the response time first decreases and then increases. The position range of MIR with excellent dynamic response performance was obtained from the comprehensive consideration of response time and electromagnetic force. Finally, the optimization design for the dynamic response performance of the solenoid valves is realized.

With the continuous push for high areal density, the conventional trailing shield perpendicular writer design faces an increasing challenge in maintaining sufficient writability while scaling down the dimensions of the write pole and the shield. In this work, we investigate an improved trailing shield design with the tapered write gap (TWG). It has been found that the TWG design has two unique recording characteristics that enable better extendibility: 1) flux concentration and 2) self-compensation. Both modeling and experimental results show that the TWG design has superior dynamic performance (DP) than conventional trailing shield design, while the sigma of DP parameters induced by the wafer/back-end variations is reduced.

The virtual prototype is a computer simulation model of the physical product that can be analyzed like a real machine. This paper studies the helical milling unit based on the virtual machine tool. The helical milling unit is first designed according to the kinematics of the helical milling. The main parts of the equipment include rotating mechanism, orbital agency and radial offset organization. Based on the feasibility analysis of the structure, the three-dimensional geometrical model is built in the Solidworks software. The key parts in the model are separated from the device and introduced into the finite element analysis (FEA) software, according to the cutting loads tested from experiment, static and dynamic modal analysis and harmonic response analysis are carried out for the key parts of this device. The results show that the static and dynamic stiffness can meet design requirement.

This study investigates an aerodynamic optimization framework inspired by marine biological morphology, utilizing the sailfish profile as a basis for airfoil configuration. Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. Parametric studies revealed that pivotal factors including installation angle significantly influenced the fluid dynamic performance metrics of lift generation and pressure drag. Response surface methodology was employed to establish predictive models for these critical performance indicators, effectively reducing computational resource consumption and experimental validation costs. The refined bio-inspired configuration demonstrated multi-objective performance improvements compared to the baseline configuration, validating the computational framework’s effectiveness for hydrodynamic profile optimization studies. Furthermore, a coaxial dual-rotor vertical axis turbine configuration was developed, integrating centrifugal and axial-flow energy conversion mechanisms through a shared drivetrain system. The centrifugal rotor component harnessed tidal current kinetic energy while the axial-flow rotor module captured wave-induced potential energy. Transient numerical simulations employing dynamic mesh techniques and user-defined functions within the Fluent environment were conducted to analyze rotor interactions. Results indicated the centrifugal subsystem demonstrated peak hydrodynamic efficiency at a 25° installation angle, whereas the axial-flow module achieves optimal performance at 35° blade orientation. Parametric optimization revealed maximum energy extraction efficiency for the centrifugal rotor occurs at λ = 1.25 tip-speed ratio under Re = 1.3 × 105 flow conditions, while the axial-flow counterpart attained optimal performance at λ = 1.5 with Re = 5.5 × 104. This synergistic configuration demonstrated complementary operational characteristics under marine energy conversion scenarios.

Visual Recognition systems are widely used in fields such as autonomous driving and intelligent security. However, testing these systems faces challenges including restricted scenarios, limited evaluation dimensions, and poor cross-platform compatibility. This paper proposes a universal simulation test platform for Visual Recognition systems, constructing a standardized testing framework through dynamic and static scene simulation, scalable data generation, multi-dimensional monitoring, and hardware-compatible architecture. Specific innovations include: 1) Dynamic and static scene simulation technology, which invokes image generation models (such as foreground-background fusion models) through extensible model management interfaces and uses path clipping technology to generate diversified test data; 2) A multi-dimensional monitoring system that integrates dynamic performance metrics (such as latency jitter and memory peak values) with traditional monitoring indicators; 3) Modular hardware-compatible design, integrating a simulation operation board to support model performance analysis on heterogeneous platforms such as GPUs and FPGAs. Based on this platform, application verification was conducted using several typical models and datasets. Experiments show that the platform can effectively complete multi-dimensional monitoring and testing of Visual Recognition systems under different scenarios and hardware architectures, providing strong data support and technical backing for system performance and quality evaluation, as well as further improvements.

This paper proposes a modified perturb and observe based fuzzy type-2 maximum power point controller. In this study the fuzzy type-2 controller has been used to drive the variable step size of classical perturb and observe algorithm in order to track the maximum power point of the proton exchange membrane fuel cell power system. The proposed controller has been validated using the Matlab/Simulink environment where the whole fuel cell power system composed of 7 kW proton exchange membrane fuel cell powering a resistive load via a DC-DC boost converter controlled using the proposed controller have been implemented. The developed model has been investigated in case of temperature variation. Comparative simulation results obtained using the classical perturb and observe algorithm, the fuzzy type- 1 algorithm and the proposed fuzzy type-2 algorithm prove the superiority of the proposed controller to track effectively the maximum power regarding used dynamic and static performance metrics.