International Journal of Hydromechatronics (19 papers in press)

Regular Issues

• Research on Magnet Structure Design and Torque Performance Optimisation of Permanent Magnet Synchronous Motors  
  by Zhiqiang Wang, Chenxu Chen, Rui Dong, Xu Zhao, Salvinder Singh Karam Singh, Beilin Han 
  Abstract: Based on the issues of substantial torque fluctuation, severe magnetic leakage, and low efficiency in conventional rectangular embedded permanent magnet synchronous motors (PMSM), this paper introduces an arc-trapezoidal magnet (ATM) structure aimed at enhancing the torque performance of the motor. Through comprehensive simulation analysis and experimental validation, the design parameters are optimised via orthogonal experimental, leading to the identification of the optimal parameter set. Experimental results reveal a 26.8% increase in average motor torque, a 51.2% reduction in torque fluctuation, and a significant improvement in the motor's output torque performance.
  Keywords: permanent magnet synchronous motor; magnet structure design; torque performance optimization; orthogonal experiment design.
  DOI: 10.1504/IJHM.2025.10073599
   
  
• Nonlinear Thermo-Mechanics of Smart Functionally Graded Rotating Disks for Adaptive Hydromechatronics  
  by Pankaj Thakur, Priya Gulial 
  Abstract: This study investigates the nonlinear thermo-mechanical behaviour of functionally graded (FG) hyperbolic rotating disks with rigid shaft inclusions and radially varying density. The disks are composed of Ti-6Al-4V/GFRP composites, with properties following a power-law gradation indexed by m. Using a generalised strain-displacement formulation, non-dimensional equilibrium equations capture axisymmetric deformations under combined thermal and mechanical loading. Numerical results show that material gradation and shaft geometry significantly influence performance. Under isothermal conditions, GFRP-rich disks (m = 0) achieve up to 42% higher yielding angular speed than Ti-6Al-4V-rich disks (m =1.25), while thermal loading reduces this advantage. Radial stress at the bore decreases ~22% in GFRP-rich disks, whereas circumferential stress rises 15%20% in Ti-6Al-4V-rich disks. Radial displacements increase 27%30%, further amplified 16%28% under thermal effects. These findings highlight the trade-off between high-speed capacity and thermo-mechanical stability, providing a framework for optimising FG disks in aerospace, energy storage, and hydromechatronic systems.
  Keywords: functionally graded materials (FGMs); rotating disks; thermo- mechanical coupling; density gradation; smart shaft inclusions.
  DOI: 10.1504/IJHM.2025.10073734
   
  
• Study on the End Correction of Extended-tube Expansion Chamber Hydraulic Pulsation Attenuator with Viscoelastic Materials  
  by Chaozhong Meng, Fan Yang, Jiaxin Yu, Hongjie Fan, Tingyu Liu, Xuepeng Cao 
  Abstract: Water-jet-guided laser (WJGL) systems require ultra-stable hydraulic pressure (<5% pulsation amplitude at 0-1000 Hz). Current viscoelastic-lined pulsation attenuators lack standardized characterization methods, leading to significant errors in impedance modelling. This study proposes a novel end-correction formula incorporating viscoelastic material parameters (sound speed, bulk modulus) for extended-tube expansion chambers (VMETC). Based on the finite element analysis and experimental validation results, the formula demonstrates good universality across 441 parameter combinations, with 71.4% of the combinations exhibiting errors below 5%.
  Keywords: End correction; extended-tube expansion chamber; finite element analysis; electrohydraulic analogue; viscoelastic metamaterials; Impedance modelling.
  DOI: 10.1504/IJHM.2025.10074061
   
  
• Towards General Embodied Intelligence: Integrating Large Language Models, Knowledge Bases, and Reasoning Capabilities to Build the Next Generation of AI Agents  
  by Fujiang Yuan, Xia Huang, Lusheng Wang, Jun Ding, Zhen Tian, Yuxin Wang, Shaojie Gu, Yuki Funabora, Yanhong Peng, Zebing Mao 
  Abstract: The convergence of large language models (LLMs), structured knowledge bases (KBs), and reasoning ability (RA) presents a promising trajectory toward general embodied intelligence (GEI). This paper reviews the evolution of LLM-centered intelligent systems, emphasizing their integration with knowledge representation, logical reasoning, and physical embodiment. We analyze LLM architectures, pre-training methods, and inference mechanisms, along with their interaction with external knowledge sources and structured reasoning frameworks. Furthermore, we examine embodied AI paradigms wherein agents learn and act in physical environments. A unified framework is proposed to illustrate the synergy among LLMs, KBs, RA, and embodiment, supporting perception, reasoning, and action. To advance toward GEI, we identify five key challenges: efficient LLM deployment, closed-loop knowledge integration, hybrid symbolic-neural reasoning, perception-action grounding, and continual learning. This survey provides a comprehensive roadmap for developing adaptive, multimodal agents capable of operating in complex, dynamic settings.
  Keywords: Embodied intelligence; large language model; knowledge base; reasoning ability; general embodied intelligence.
  DOI: 10.1504/IJHM.2025.10074893
   
  
• Density Determination of Low Viscous Fluid Utilising Frequency Response of PZT-Steel Cantilever Sensor  
  by Shivanku Chauhan, Abhinav Sharma, Mohd. Zahid Ansari 
  Abstract: This work presents a study on density estimation of low-viscosity fluids using the frequency response of a lightweight and portable PZT-steel cantilever sensor. A coupled numerical model is developed to simulate the sensors behaviour when partially immersed in different fluidic environments. In addition, an analytical frequency-density relation is formulated for inviscid fluids and further improved by introducing a correction shape factor to account for partial immersion. The density estimated using the developed frequency-density relationship, together with the experimental frequency response of the PZT-steel cantilever sensor, closely matches the actual density values of different fluidic media (liquid paraffin, water, and glycerin), with a deviation of only 2%3%. The results confirm that the PZT-steel cantilever exhibits high sensitivity and accuracy in density measurement across different fluid media. Compared with conventional density metres, the proposed cantilever-based approach offers a compact, low-cost, and accurate alternative for fluid characterisation.
  Keywords: Density; Fluidic media; Numerical modeling; PZT-Steel cantilever sensor; Resonant frequency.
  DOI: 10.1504/IJHM.2025.10075125
   
  
• Unveiling the Operational Mechanisms of Magnetorheological Transmission: Experimental Characterisation of Key Dynamic, Thermal and Torque Behaviours  
  by Xiankang Huang, Zuzhi Tian, Haopeng Li, Fei Chen, Gege Liu, Shuyou Wang 
  Abstract: This study experimentally investigates five key characteristics of magnetorheological (MR) transmission devices. The zero-field tests reveal speed-dependent no-load torque that decreases over time due to centrifugal particle migration. Static characteristics show a linear current-torque relationship with negligible hysteresis, ensuring high controllability. Dynamic response is dominated by mechanical factors (> 97%), with current withdrawal being 1.5x slip speeds as reduced Mason number mitigates shear-thinning effects. Temperature tests show only 3.2% torque reduction at 100C, as viscosity decrease partially offsets magnetisation loss. These comprehensive findings provide fundamental insights into MR transmission mechanisms, offering valuable guidance for optimising device performance in applications requiring precise torque control and thermal stability.
  Keywords: magnetorheological transmission; zero-field characteristic; static characteristic; dynamic characteristic; torque characteristic; temperature characteristic.
  DOI: 10.1504/IJHM.2025.10075884
   
  
• Research Progress on Control Mechanisms and Strategies in Electrohydrodynamic Jet Printing  
  by Ziwei Zhao, Wei Chen, Yingjie Zhu, Yuxuan Tang, Ke Wu, Jiankui Chen 
  Abstract: Electrohydrodynamic jet (e-jet) printing is a high-resolution micro/nanoscale fabrication technique driven by high-voltage electric fields, offering programmable patterning and high material utilisation efficiency. As e-jet printing advances from laboratory studies toward early industrial commercialisation, achieving stable and precise process control has become a critical challenge. This review systematically analyses the influence of process parameters on printing behaviour and summarises empirical forward-control strategies that enable diverse micro/nanoscale structures through predefined parameter selection. In addition, inverse control approaches are reviewed, in which optimal process parameters are derived from target printing outcomes. Key control objectives, including droplet volume, jetting frequency, andsuch as machine learning, are also highlighted. Furthermore, open-loop and closed-loop control frameworks, along with representative e-jet printing equipment, are reviewed. This work provides a comprehensive overview of control strategies in e-jet printing laying a technological foundation for multifunctional device fabrication. landing position, are discussed in detail. Advanced control methodologies,
  Keywords: Electrohydrodynamic jet printing; Printing parameter; Control Strategies; Micro/nanoscale manufacturing.
  DOI: 10.1504/IJHM.2025.10076573
   
  
• Negative Stiffness-Enhanced Elastic Metamaterials for Extreme-Environment Low-Frequency Vibration Damping  
  by Zhiwei Song, Shiteng Rui, Shaokun Yang, Zimeng Zhou, Jiuhui Wu 
  Abstract: Low-frequency vibration is ubiquitous in cooling towers and ships, parts of structure are exposed to extreme environments such as high temperatures and seawater corrosion. Local resonance is effective for low-frequency vibration, but the prevailing approach of providing damping and stiffness through viscoelastic materials like rubber limits the range of applications. Here, we present a novel integrated material-structure-function design paradigm for elastic metamaterials. Introducing a negative stiffness (NS) structure into the locally resonant cell (LRC) enables vibration energy dissipation through non-viscoelastic and non-plastic mechanisms, thereby endowing the integrally fabricated 316L stainless steel-based metamaterials (NS-LRC) with the potential to serve in extreme environments. By coupling multiple resonators in parallel within each cell, sub-wavelength and lightweight characteristics are achieved, along with excellent low-frequency vibration damping performance. We analyze the mechanical behavior and hysteresis curves of the NS structure through mechanical property tests and systematically verify the effectiveness of the vibration damping scheme using elastic wave band gaps, energy flow, and vibration damping experiments. This device shows promise for low-frequency vibration damping and wave reduction applications in extreme environments, with significant engineering applications.
  Keywords: Vibration damping; Elastic metamaterials; Severe service conditions; Negative stiffness; locally resonant cell; Multiple resonators coupling.
  DOI: 10.1504/IJHM.2025.10076811
   
  
• Transmission Systems Using PDC And PMU in Machine Learning for Enhanced Efficiency, Fault Detection and Diagnosis  
  by A. Sekar, D. Sri Vidhya, S. Jaividhya, R. Gopalakrishnan 
  Abstract: The primary issue in contemporary transmission systems is ensuring operational efficiency and reliability and facilitating rapid and precise fault detection. Traditional fault detection techniques are not real time responsive as they do not reflect intricate temporal dynamics and spatial-temporal dependencies of wide-area power systems. To overcome this limitation, this paper suggests an intelligent phasor-based fault detection (IPFD) model that enhances the accuracy, efficiency, and robustness of the detection system. This framework uses synchronised data of phasor measurement units (PMUs) and phasor data concentrators (PDCs) and then preprocessing phases to remove noise, and normalise the data. Adaptive spectral-spatial decomposition (ASSD) is used to extract features, which minimise dimensionality and yet important fault features to be effectively classified. The method is tested in a digital twin setting with OPAL-RT and PSCAD in the conditions of real faults. Performance and transmission system efficiency are confirmed by the results.
  Keywords: Transmission Networks; Phasor Measurement Units (PMU); Spatial-Temporal Learning; Digital Twin Technology; Adaptive Spectral-Spatial Decomposition (ASSD); Fault Detection.
  DOI: 10.1504/IJHM.2025.10076881
   
  
• Multi-Objective Trajectory Planning and Optimisation of Excavators Based on Energy Consumption Analysis  
  by Zhaoyuan Yao, Wenli Zhang, Qihuai Chen, Tianliang Lin 
  Abstract: The realization of automatic excavator operation has become a key component in the intelligent development of construction machinery. Trajectory planning and optimization is the core technologies for achieving automated excavator operations, with its primary objective being to ensure a smooth and continuous operation process while achieving low energy consumption, high efficiency. Therefore, a comprehensive trajectory planning and optimisation framework is proposed in this paper, based on energy consumption analysis. This framework aims to effectively balance time, energy consumption, and bucket fill rate during excavator operations. Initially, the kinematic model, dynamic model, and excavation resistance model of the excavator are established to provide a theoretical foundation for subsequent trajectory planning and optimisation. Subsequently, the proposed models are analysed and validated. Finally, the excavation path for channel excavation is optimised using five non-uniform rational B-spline curves, with an improved chaotic adaptive particle swarm optimisation algorithm employed to solve the multi-objective optimisation problem.
  Keywords: excavator; autonomous operation; dynamic model; trajectory planning and optimization.
  DOI: 10.1504/IJHM.2025.10077065
   
  
• Matrix sensitivity-based adaptive nonlinear iterative compensation controller for the force control system of hydraulic legged robots  
  by Kaixian Ba, Jinbo She, Linyang Chen, Bao Xu, Yuan Wang, Xiaolong He, Xinrong Li, Ning Liu, Guoliang Ma, Bin Yu 
  Abstract: With the growing demand for tasks requiring effective force interaction between robots and their environments, the need for enhanced force control performance in hydraulic drive unit (HDU) has escalated. However, the inherent nonlinearities and coupling effects in HDU pose substantial challenges to achieving precise force control. This paper introduces a theory of matrix sensitivity control and proposes a matrix sensitivity-based adaptive nonlinear iterative compensation controller (MSANIC). Initially, the matrix sensitivity visually displays the implicit relationship between control input compensation quantities and predicted output state variations in non-linear systems. Secondly, the real-time optimal model parameters of the feedforward compensation controller were determined, and adaptive control of the feedforward compensation controller was achieved. Finally, comparative experiments verified the superior performance of the proposed force control method, demonstrating its ability to significantly reduce error oscillations. This research provides a theoretical refer-ence for the stable motion control of the legged robot.
  Keywords: Force control; hydraulic drive unit (HDU); hydraulic legged robot; matrix sensitivity; nonlinear iterative compensation.
  
  
• Design, Modelling and Verification of Powerful Electro-hydrostatic Actuators with Impact Absorption for Heavy-Load Joints Application  
  by Huipeng Zhao, Junjie Zhou, Shanxiao Du, Yi Wu, Sanxi Ma, Wenbo Liao, Hui Liu 
  Abstract: This study proposes a joint electro-hydrostatic actuator (JEHA), designed to enable heavy-load wheel-legged robots to jump over obstacles and absorb impact when landing The JEHA can operate in four-quadrant with high-power density To further analyze its inherent impedance and energy consumption, an improved spring-damping model for the JEHA was formulated considering the oil as an elastic element, and the internal leakage and pressure losses as damping effects The experimental results demonstrate that the JEHA enables a 70 kg single-leg mechanism to achieve jumping and exhibits outstanding joint performance, including high torque output, high-speed operation, and enhanced safety features Notably, its inherent impedance reduced landing impact forces by 47% And the safe reverse operation under impact demonstrated potential energy recovery This study highlights the ability of JEHA to combine high power output with superior impact absorption, promising a novel solution for heavy-load robots requiring robust and efficient interaction with challenging environments.
  Keywords: Electro-hydrostatic actuator; heavy-load robots; modeling analysis; impact absorption; energy recovery.
  DOI: 10.1504/IJHM.2025.10077424
   
  
• Communication Delay Effects and Mitigation in Renewable Energy Systems AC Grid and DC Grid: a Comprehensive Review  
  by Nissi Solomon, Kalyan Dusarlapudi 
  Abstract: As renewable energy becomes a bigger part of today's power systems, strong communication networks are essential to manage and coordinate distributed energy resources in real time However, delays in communication-whether from data transmission, processing, or protocol inefficiencies can seriously impact the stability and performance of both AC and DC power grids. This paper explores how these delays affect renewable energy systems, comparing the unique challenges faced by AC and DC grid configurations. It looks at key issues like frequency regulation in AC systems and voltage control in DC microgrids, and how these are influenced by time-varying delays. A range of solutions is reviewed, from smarter communication protocols and delay-aware control methods to the use of AI, edge computing, and hybrid networks. Real-world examples and simulations help show what works in practice. Finally, the paper highlights promising future directions, including the roles of 5G, blockchain, and AI in building more delay-resilient energy systems.
  Keywords: Communication Delay; Renewable Energy System; AC Grid; DC Grid,; Delay Mitigation Techniques; Distributed Energy Resources (DER).
  DOI: 10.1504/IJHM.2025.10077450
   
  
• Measurement and Mapping of Acoustic Pressure and Standing Wave in an Ultrasonic Medium: Effect of Power and Frequency  
  by Muhammad Shafiq Mat Shayuti, Tuan Mohammad Yusoff Shah Tuan Ya, Mohamad Zaki Abdullah 
  Abstract: Sonication is an emerging technique in green processes, but complication arises when non-uniform cavitation in acoustic field goes under-comprehended, especially in combinations of various ultrasonic power & frequency. As acoustic pressure is the indicator for cavitation activity, this report explores the impact of varying ultrasound power & frequency towards the acoustic pressure within a bath reactor. Result indicates that 25 to 60 kHz sonication thrusted by 30 to 120 W power generated 174 kPa-783 kPa of acoustic pressure corresponding to shockwaves & microjets from cavitation bubbles implosion, with higher frequencies required more power to achieve comparable acoustic pressure. Furthermore, the ratio of standing wave to traveling wave regions was discovered to be influenced by attenuating acoustic pressure, where visibly vigorous bubble activity correlated with stronger acoustic pressure readings. This qualitative observation, supported by acoustic pressure measurements, suggests that regions of intense cavitation can be indirectly identified by pressure mapping.
  Keywords: acoustic pressure; frequency; mapping; power; standing wave; ultrasonic bath.
  DOI: 10.1504/IJHM.2025.10077452
   
  
• Robustness of the injection characteristics for a hydraulically-actuated fuel system  
  by Qi Lan, Zixin Wang, Yun Bai, Ying Xu, Yong Wang, Xinming Yan, Dehao Kong, Chuan Ma 
  Abstract: This study investigated the injection characteristics robustness in a hydraulically-actuated fuel system under parameter drift caused by harsh operating conditions. Utilizing Monte-Carlo method integrated with Latin hypercube sampling, 1000 parameter samples were analysed to derive frequency distribution histograms and quantify robustness via statistical indicators. Key structural parameters influencing fuel injection quantity (FIQ), opening delay time (ODT), and closing delay time (CDT) were evaluated. Regression models linking normalized parameters to robustness metrics reveals that nozzle hole diameter predominantly affects FIQ robustness (43.4%58.1% contribution). ODT robustness is strongly governed by control and outlet orifice diameters (combined > 86% contribution). CDT mean and kurtosis correlate with nozzle hole and inlet orifice diameters, while outlet orifice diameter dominates CDT standard deviation (74.1% contribution). CDT skewness is sequentially influenced by outlet orifice, nozzle hole, control orifice, and inlet orifice diameters. These findings provide quantitative insights into optimising parameter design for enhanced injection consistency.
  Keywords: Hydraulic-driven fuel system; Injection characteristics; Robustness indicators; Monte-Carlo method; Quantitative analysis.
  DOI: 10.1504/IJHM.2026.10077633
   
  
• Data-Driven Suitability Mapping for Optimised Electric Vehicle Charging Infrastructure: A Comprehensive Literature Review  
  by Nissisolomon Rudrapogu 
  Abstract: The rapid growth of electric vehicle (EV) adoption has led to an increased demand for efficient and accessible electric vehicle charging stations (EVCS). This paper reviews the literature on data-driven methods for selecting EVCS locations and mapping facility suitability, focusing on the use of geographic information systems (GIS), machine learning (ML), and multi-criteria decision-making (MCDM) approaches. It explores current optimisation techniques, including models like analytic hierarchy process (AHP), fuzzy AHP, stepwise weight assessment ratio analysis (SWARA), and predictive models such as random forest. The review identifies common trends in the application of synthetic data generation, micro-simulations, and digital twins for estimating EV charging demand. Key contributions of the paper include the systematic categorisation of methodologies used for EVCS planning, a critique of hybrid GIS-ML-MCDM frameworks, and an assessment of gaps related to data sparsity, privacy, and multi-period adaptive planning. The findings highlight the importance of integrating GIS spatial analysis with explainable ML models and robust decision-support factors to enhance the resilience and transparency of EVCS infrastructure planning. The study provides valuable insights for policymakers and researchers, offering a roadmap for the sustainable deployment of EVCS and supporting the transition to cleaner urban transportation.
  Keywords: Electric Vehicle Charging Infrastructure (EVCS); Geographic Information Systems (GIS); Machine Learning (ML); Multi-Criteria Decision-Making (MCDM); Hybrid Models and Optimization.
  DOI: 10.1504/IJHM.2025.10077634
   
  
• Effect of the Diameter of the Diaphragm Hydrolic Diode Connecting Fitting on its Diodicity  
  by Sergey Kaigorodov, Egor Dorofeev 
  Abstract: The object of the study in the presented manuscript is hydraulic diodes. Analysis of scientific and technical literature showed that the use of hydrodiodes as an analogue of check valves has a number of advantages, but does not ensure the complete absence of reverse fluid flow. By studying the geometric and design parameters of hydrodiodes, it is possible to reduce the amount of reverse fluid flow, thereby increasing the efficiency of the hydrodiodes. The article contains a set of theoretical and experimental studies aimed at determining the effect of the diameter of the connecting nipple on the diode capacity of the hydraulic diode. As a result of the studies, recommendations were developed for selecting the diameter of the connecting nipple, ensuring the best efficiency of the hydrodiode.
  Keywords: diaphragm hydrolic diode; diodicity; diameter of the connecting fitting.
  DOI: 10.1504/IJHM.2025.10077789
   
  
• Aerodynamic Behaviour of seal-Rotor System with Multivariate Working Fluid and System Parameters via Nonlinear Whirl Model  
  by Heyong Si, Zhenkui Yu, Lihua Cao, Dongchao Chen 
  Abstract: The seal dynamic pressure performance affected by fluid properties and rotor motion affected by system parameters have a strong interference coupling effect. A nonlinear whirl model of the seal-rotor system considering the spatiotemporal gas-solid coupling effect between seal aerodynamic effect and rotor dynamics behaviour was established to restore the actual rotor motion. The co-simulation of seal flow and rotor dynamics was achieved via mesh deformation and user-defined function (UDF). Then the seal dynamics were calculated by differential theory, and the first-order quantitative numerical values were obtained. Finally, a comparative analysis was conducted on the different working fluids and different system parameters. The results indicated that the nonlinear whirl model can more accurately reproduce the rotor motion state and seal flow field change. Supercritical carbon dioxide (SCO2) has a stronger aerodynamic effect. The rotor elastic recovery stiffness, pressure ratio, and rotational speed have a significant influence on seal dynamic characteristics, while the impact of unbalanced mass eccentricity is relatively weak.
  Keywords: Multivariate working fluid; Seal-rotor system; Dynamic behavior; Aerodynamic performance; Nonlinear whirl model.
  
  
• Optimising Pavement Crack Sealing with a Depth-Informed Reinforcement Learning Framework and Synthetic Crack Trajectory Modelling  
  by Jinchao Wang, Edwin K.P. Chong, Chenxi Li, Yihai Fang, Xin Wang 
  Abstract: Pavement crack sealing is a critical maintenance activity essential for extending roadway service life and ensuring traffic safety Traditional crack sealing methods, often modelled as the Traveling Salesman Problem, focus on minimising travel distance but overlook crack depth variations and sealing continuity This often results in inefficient material usage and inconsistent pavement quality To address these limitations, this study presents a depth-informed reinforcement learning (RL) framework for autonomous and continuous crack sealing, with the Automatic Crack Generation Model (ACGM) as its key component ACGM generates realistic synthetic crack maps and optimal sealing trajectories by simulating natural crack propagation patterns, eliminating the need for costly manual expert demonstrations and providing a robust, scalable foundation for RL training Experimental results demonstrate that the proposed approach outperforms conventional TSP-based methods, achieving a 17% reduction in material waste, a 12% decrease in operational time, and improved surface uniformity.
  Keywords: Crack Sealing; Reinforcement Learning; Behavior Cloning; Depth-informed Path Planning,.