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Journal of Complex and Multiphysics Engineering Systems
JCMBS
Journal of Complex and Multiphysics Engineering Systems (JCMES)
JDGOD
ISSN (print): 3134-7932
ISSN (online): 3134-7940
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2026: Vol. 1
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Journal of Complex and Multiphysics Engineering Systems (JCMES) is a peer-reviewed, open-access journal that publishes research on the modelling, analysis, and design of engineering systems governed by interacting physical processes. The journal focuses on analytical, computational, and experimental studies that examine how coupled thermal, mechanical, fluid, electromagnetic, chemical, and micro- and small-scale mechanisms affect system behaviour, stability, transport characteristics, and overall performance under realistic operating conditions. It welcomes contributions that present well-founded modelling approaches supported by theoretical development, numerical simulation, experimental validation, or integrated investigation, particularly in areas such as coupled-field interactions, system response and stability, multiscale modelling, the verification and validation of engineering models, and scale-bridging methodologies. Relevant application domains include energy and thermal systems, structural and dynamic systems, fluid transport and process engineering, advanced materials and composites, micro- and nano-electromechanical systems, manufacturing processes, and environmental or subsurface engineering systems. JCMES is published quarterly by Acadlore, with issues released in March, June, September, and December.

  • Professional Editorial Standards - All submissions are evaluated through a standard peer-review process involving independent reviewers and editorial assessment before acceptance.

  • Efficient Publication - The journal follows a defined review, revision, and production workflow to ensure regular, predictable publication of accepted manuscripts.

  • Open Access - JCMES is an open-access journal. All published articles are made available online without subscription or access fees.

Editor(s)-in-chief(1)
hamid mohammad-sedighi
Department of Mechanical Engineering, Shahid Chamran University of Ahvaz, Iran
hmsedighi@gmail.com; h.msedighi@scu.ac.ir | website
Research interests: Nonlinear Dynamics and Vibration; Applied and Computational Mechanics; Structural Stability Analysis; Fluid–Structure Interaction; Nanomechanics and Advanced Engineering Modelling

Aims & Scope

Aims

Journal of Complex and Multiphysics Engineering Systems (JCMES) is an international, peer-reviewed, open-access journal devoted to the study of engineering systems in which multiple physical processes interact and jointly influence system behaviour. The journal publishes research on the modelling, analysis, and design of systems governed by thermal, mechanical, fluid, electromagnetic, chemical, and micro-scale phenomena, particularly where their interaction plays a material role in system performance.

Engineering systems in contemporary practice frequently operate under conditions where more than one physical mechanism is active. Interactions among these mechanisms may affect stability, transport processes, structural response, durability, and overall operational characteristics. JCMES provides a forum for research that examines such interactions in a systematic and technically rigorous manner, with attention to their implications for engineering analysis and design.

The journal is concerned with how interacting physical processes influence system behaviour at the component and system levels. Emphasis is placed on clear physical interpretation, well-defined modelling assumptions, and demonstrable technical contribution. Submissions should extend beyond routine computation or incremental parametric variation and should offer substantive insight into engineering mechanisms, modelling approaches, or system-level understanding.

While particular attention is given to systems involving interacting fields, the journal also considers high-quality studies of engineering field behaviour more generally, including single-field investigations, where the work presents methodological development, improved modelling frameworks, or findings with clear relevance to system performance or design considerations.

Contributions may be theoretical, computational, experimental, or integrative. Regardless of approach, manuscripts are expected to demonstrate analytical consistency, technical depth, and reproducibility of results.

JCMES is published quarterly by Acadlore. All submissions undergo structured peer review to ensure technical soundness and clarity of presentation.

Key features of JCMES include:

  • The journal focuses on engineering systems influenced by interacting physical processes, rather than on isolated disciplinary classifications.

  • It addresses system behaviour arising from coupled mechanisms, multi-scale effects, and interface-driven phenomena across a range of engineering domains.

  • Contributions are expected to integrate sound physical reasoning with appropriate analytical, numerical, or experimental support.

  • Both foundational modelling work and application-oriented studies are considered, provided they demonstrate clear technical substance and clear relevance to engineering system behaviour or design.

  • Particular attention is given to methodological transparency and consistency of analysis.

Scope

JCMES welcomes original research articles, theoretical studies, systematic reviews, and well-documented experimental or computational investigations in areas including, but not limited to, the following:

Coupled Physical Processes in Engineering Systems

Research addressing systems in which two or more physical mechanisms interact in a manner that materially affects system response.

  • Fluid–structure interaction

  • Thermo-mechanical and thermo-fluid coupling

  • Electro-thermal and magnetohydrodynamic systems

  • Reactive transport and chemically influenced processes

  • Phase change and transformation phenomena

  • Interface and boundary-driven interaction effects

  • Transport processes influenced by interacting fields

System Response, Stability, and Evolution

Studies examining how interacting mechanisms influence system behaviour under operational conditions.

  • Dynamic response and time-dependent behaviour

  • Stability and instability mechanisms

  • Transition and localisation phenomena

  • Mechanically or thermally influenced damage and failure

  • Behaviour influenced by scale-dependent effects

Modelling Frameworks and Scale Bridging

Research developing or refining modelling approaches relevant to engineering systems influenced by interacting processes.

  • Continuum and extended modelling formulations

  • Multiscale modelling strategies

  • Constitutive modelling under coupled conditions

  • Micro- and nano-scale system modelling

  • Homogenisation and scale-bridging approaches

  • Reduced-order modelling approaches supported by sound physical justification

Computational and Experimental Approaches

Methodological contributions supporting the analysis and validation of engineering systems.

  • Multiphysics simulation techniques

  • Finite element, finite volume, lattice-based, and hybrid numerical methods

  • Model verification and validation

  • Experimental investigation of interacting field behaviour

  • Combined computational–experimental studies

Engineering Applications

Applied studies demonstrating interacting physical mechanisms or modelling approaches within practical engineering contexts. Contributions in the following areas are welcome where either clear system-level or modelling relevance is demonstrated:

  • Energy and thermal engineering systems

  • Fluid transport and process systems

  • Structural and dynamic engineering systems

  • Advanced materials and composite structures

  • Micro- and nano-electromechanical systems

  • Manufacturing and process engineering

  • Environmental and subsurface systems

Articles
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Nonlinear plasma evolution in microgravity cannot be reliably characterized under terrestrial gravity because buoyancy-driven convection modifies or suppresses the intrinsic instability mechanisms. Consequently, the predictive design and safe operation of electromagnetically actuated plasma engineering systems require a unified theoretical framework capable of distinguishing gravity-independent behavior from phenomena that emerge only under microgravity conditions. A microgravity nonlinear plasma platform was therefore established as a multi-physics governance framework that defines the physical and mathematical conditions under which nonlinear plasma evolution becomes microgravity-dependent while providing quantitative criteria for operational stability. A dimensionless governance ratio was introduced as the principal classification metric, coupling the electromagnetic control bandwidth with the nonlinear instability growth rate. The framework was further integrated with a three-tier distributed intelligent governance of stabilized plasmas supervisory architecture, through which electromagnetic actuation, thermal-ionization energy balance, and structural boundary response are coordinated across multiple interacting physical domains. Three operating regimes were thereby defined: admissible (R > 10), marginal (1 < R ≤ 10), and runaway (R ≤ 1), each associated with prescribed electromagnetic control actions, a diagnostic latency constraint, and mandatory termination logic. An analytical microgravity threshold was derived. Recent observations from the Plasma Kristall-4 (PK-4) complex plasma facility aboard the International Space Station (ISS) were shown to be consistent with the predicted emergence of field-aligned filamentary structures and anisotropic nonlinear transport under reduced-gravity conditions. Finally, five quantitative and experimentally falsifiable predictions were formulated to establish a systematic validation pathway for future microgravity plasma experiments. Collectively, the proposed framework provides a rigorous theoretical foundation for the analysis, governance, and engineering design of high-energy-density plasma systems operating in microgravity and establishes a general methodology for the development of next-generation plasma propulsion technologies, advanced confinement architectures, and reaction-boundary control systems in coupled multi-physics environments.

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Rotating machinery commonly operates under coupled mechanical and electrical excitations, where closely spaced vibration frequencies can generate complex dynamic responses and interfere with accurate fault diagnosis. The beating phenomenon represents a critical form of amplitude modulation in rotating systems and serves as a valuable diagnostic indicator for identifying resonance interactions, electromechanical coupling, and instability mechanisms in industrial equipment. This study investigates the dynamic characteristics of beating phenomena in industrial rotating machinery through analytical modeling, vibration signal analysis, and industrial case studies. A mathematical formulation based on sinusoidal superposition was developed to describe the interaction between adjacent frequency components and the resulting amplitude modulation behavior. Time-domain and frequency-domain analyses were performed to evaluate the relationship between beat frequency, modulation envelope, and vibration response characteristics. Two industrial case studies involving a centrifugal pump and a variable-frequency-drive-driven induction motor were examined using vibration monitoring data, fast Fourier transform (FFT) analysis, envelope analysis, and MATLAB-based numerical simulations. The results demonstrated that closely spaced frequency components generated periodic amplitude modulation and produced distinct beating patterns in both the time and frequency domains. In the pump system, the interaction between vibration components at 202.875 Hz and 202.785 Hz produced a measurable beat response that was strongly associated with unstable vibration behavior. In the variable-frequency-drive-driven motor, interference between the 2X and 2LF components was identified as the primary source of beating and abnormal vibration amplification. The implemented corrective actions, including the elimination of unintended current paths and the installation of an insulated bearing, significantly reduced vibration severity and restored stable operating conditions. The findings indicate that beating behavior is strongly associated with coupled electromechanical interactions and provides valuable diagnostic information for identifying closely spaced excitation sources, bearing degradation, and modulation-induced instabilities in rotating equipment. Furthermore, the combined application of FFT analysis, envelope analysis, and vibration condition monitoring enables the reliable identification of fault-related modulation effects and enhances diagnostic accuracy in complex industrial machinery. The proposed analytical and monitoring framework offers an effective approach for vibration-based condition monitoring, early fault detection, and reliability enhancement in complex industrial machinery systems.

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Industry 4.0 transforms modern manufacturing systems through the integration of cyber-physical systems, the Industrial Internet of Things, artificial intelligence (AI), machine learning (ML), and digital twin (DT) technologies. Autonomous industrial control remains a critical challenge in complex engineering environments because conventional control architectures often struggle to handle nonlinear dynamics, distributed decision-making, system uncertainties, and real-time operational variability. This review investigates the role of AI-, ML-, and DT-enabled autonomous control systems in improving adaptive intelligence, predictive capability, operational optimization, and resilient decision-making within smart industrial environments. A comprehensive technical review was conducted to examine recent developments in intelligent system modeling, predictive analytics, adaptive and self-learning control, real-time anomaly detection, multi-objective optimization, quality control, and energy-efficient industrial operations. The architectures and operational mechanisms of the AI–ML–DT-integrated control frameworks were analyzed from the perspective of complex cyber-physical industrial systems. The interrelationships among distributed sensing, intelligent data processing, virtual simulation, and autonomous control layers were also evaluated to identify current technological capabilities and implementation limitations. The analysis showed that the integration of AI, ML, and DT technologies significantly improved predictive maintenance performance, adaptive process control, fault diagnosis accuracy, operational flexibility, and energy optimization in Industry 4.0 environments. The reviewed studies demonstrated that DT-assisted virtual environments enabled safe real-time optimization and intelligent decision validation before physical deployment. The results also revealed that autonomous control architectures enhanced the resilience and self-adaptive capability of industrial systems operating under dynamic and uncertain conditions. However, several limitations were identified, including interoperability constraints, model synchronization challenges, computational complexity, cybersecurity risks, and scalability issues in distributed industrial networks. This study demonstrates that the convergence of AI, ML, and DT technologies establishes an important foundation for next-generation autonomous cyber-physical industrial systems. The proposed review provides a comprehensive engineering perspective for understanding intelligent industrial control architectures and offers valuable insights into the development of scalable, adaptive, and energy-efficient autonomous manufacturing systems for future Industry 4.0 applications.
Open Access
Research article
Multiphysics Modeling and Sensitivity Analysis of Temperature-Dependent Rayleigh Waves in Rotating Magneto-Thermoelastic Semiconductor Systems with Hall Current Effects
maaz ali khan ,
maheen bibi ,
adnan jahangir ,
afzal rahman ,
usman riaz ,
sohail rahman ,
shahid iqbal ,
shahid zaheer
|
Available online: 06-18-2026

Abstract

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Surface acoustic wave propagation in semiconductor systems is strongly influenced by coupled thermal, electromagnetic, and mechanical interactions, particularly under high-frequency operating conditions encountered in advanced microelectronic and sensing devices. Existing thermoelastic wave models generally neglect the simultaneous interaction of Hall current effects, rotational dynamics, temperature-dependent material behavior, and non-Fourier thermal relaxation, which limits their capability for accurately characterizing multiphysics wave phenomena in semiconductor media. This study investigates Rayleigh surface wave propagation in a rotating magneto-thermoelastic silicon semiconductor half-space by developing a unified multiphysics framework incorporating Hall current effects and a multi-dual-phase-lag heat conduction model with temperature-dependent material properties. The coupled governing equations were transformed into dimensionless form and analytically solved using normal-mode analysis to derive the secular equation governing Rayleigh-type surface waves. Numerical simulations were performed using experimentally validated silicon parameters to evaluate the phase velocity, attenuation coefficient, penetration depth, and specific heat loss under different thermal, electromagnetic, and rotational conditions. A variance-based global sensitivity analysis based on Sobol indices was additionally conducted to quantify the relative influence of the governing multiphysical parameters on wave behavior. The results showed that rotational effects increased phase velocity and penetration depth, whereas temperature-dependent thermal softening reduced wave propagation capability and enhanced attenuation. Hall current effects and magnetic field intensity exhibited competing influences on wave kinematics and damping characteristics. The sensitivity analysis revealed that electromagnetic parameters primarily governed wave kinematics, while the thermal softening parameter dominated thermodynamic energy dissipation behavior. Nearly uniform sensitivity distributions were observed for phase velocity and penetration depth, indicating strong multiphysical coupling among thermal, elastic, and electromagnetic fields within the semiconductor system. The results indicate that the proposed framework provides a physically consistent and quantitatively interpretable platform for analyzing coupled wave propagation phenomena in semiconductor engineering systems. The developed model offers practical guidance for the design and optimization of surface acoustic wave devices, semiconductor sensors, and thermo-electromagnetic microelectronic systems operating under complex coupled-field environments.

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This study presents a detailed numerical study of the melting behavior and thermal performance of a paraffin-based cooling layer integrated beneath a photovoltaic (PV) solar panel to improve its electrical efficiency and thermal stability. Since excessive temperature rise is one of the major factors responsible for reducing the performance and lifespan of PV systems, the development of efficient passive cooling technologies has become increasingly important in modern renewable energy applications. In the present study, paraffin-based phase change material (PCM) is employed as a thermal energy storage medium owing to its capability to absorb the excess heat produced by the PV panel during operation. To improve conductive heat transport and quicken the melting process, ternary hybrid nanoparticles composed of Al$_2$O$_3$, TiO$_2$, and Ag are dispersed into the paraffin, while porous metal foam is incorporated inside the PCM container to provide highly conductive pathways for thermal diffusion. The simultaneous incorporation of hybrid nanoparticles and porous metal foam markedly improves the thermal response of the cooling layer, thereby enhancing the system’s ability to regulate the operating temperature of the PV panel under working conditions. The numerical simulations are carried out using the Galerkin method, while adaptive mesh refinement and an implicit solution technique are employed to accurately capture the transient melting behavior and phase transition process within the PCM enclosure. The obtained results indicate that integrating porous metal foam together with ternary nanoparticles significantly enhances the overall thermal performance of the cooling system. The liquid fraction (LF) of the PCM increases by approximately 33.11%, indicating a significant enhancement in the melting rate and thermal energy absorption capability. Furthermore, the enhanced cooling configuration reduces the PV panel temperature by nearly 1.98% compared with the conventional case. As a consequence of the improved thermal regulation, the electrical efficiency of the PV panel increases by about 20.87% relative to the uncooled PV system. These findings confirm that integrating nano-enhanced PCM with porous metal foam provides a highly promising passive cooling strategy for improving the performance, reliability, and energy conversion efficiency of next-generation PV systems.

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High operating temperatures are a major limitation for photovoltaic (PV) systems, as they reduce electrical efficiency and long-term reliability. Effective thermal regulation is therefore essential to maintain stable performance under strong solar irradiation. In this study, a numerical investigation is conducted to examine the thermal performance of a PV panel integrated with a paraffin-based cooling system positioned beneath the module. To improve the low thermal conductivity of paraffin, ternary nanoparticles together with metal foam are introduced into the phase change material (PCM). This hybrid enhancement significantly improves heat transfer, increases thermal diffusion, and accelerates the melting process. The transient melting behavior is modeled using the Galerkin finite element method, which ensures accurate prediction of temperature variation and phase change dynamics. The liquid fraction (LF) is increased by about 68.93%, indicating faster melting and improved energy absorption. In addition, the temperature distribution inside the PCM is enhanced by approximately 5.71%. Compared with a conventional uncooled PV system, the proposed configuration reduces the PV panel temperature ($T_{\mathrm{PV}}$) by 8.53%, while increasing electrical efficiency by 17.16%. Overall, the study demonstrates that combining ternary nanoparticles with metal foam inside PCM provides a strong synergistic cooling effect. This integrated approach offers a more effective thermal management strategy than traditional single-enhancement methods, leading to improved PV performance, higher efficiency, and better thermal stability under real operating conditions.

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This research delves into the combined influences of a magnetic field and thermodiffusion phenomena on a rotating, pre-stressed two-dimensional microelongated thermoelastic layer. The investigation employs the Moore-Gibson-Thompson (MGT) model as its theoretical framework. To gain a deeper understanding of the system’s behavior, an analytical solution is derived. This solution, built upon the harmonic wave method, is specifically tailored for a half-space model. The primary aim of this analytical approach is to characterize the nature of wave propagation within the material when subjected to mechanical wave loading conditions. The study meticulously examines the behavior of this complex microelongated thermoelastic system, paying close attention to the interplay between the magnetic field, thermodiffusion, and the material’s inherent properties. The findings of this investigation are presented in a graphical format, allowing for a clear and intuitive visualization of the system’s response. The material chosen for this illustrative purpose is aluminum-epoxy, a composite material commonly used in various engineering applications. The analysis of the derived solution reveals that the system exhibits stability. This stability is an important characteristic, indicating that the system’s response remains bounded and predictable under the applied conditions. Furthermore, the study identifies wave damping as a significant factor influencing the wave propagation behavior. This wave damping is attributed to two primary sources: the inherent material properties of the aluminum-epoxy composite and the specific boundary conditions imposed on the half-space model. These factors collectively contribute to the attenuation of the waves as they propagate through the microelongated thermoelastic layer.

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Forest residues generated from logging operations, forest maintenance, and wood-processing activities represent an increasingly important secondary biomass resource for sustainable material engineering. The heterogene-ous composition of these residues, together with their high lignocellulosic content, creates significant opportunities for their integration into wood-based composites and bio-derived adhesive systems. However, variability in species, morphology, moisture sensitivity, and chemical composition still limits their large-scale and standardized industrial utilization. This review investigates the valorization pathways of forest management residues within engineered wood-based material systems, with particular emphasis on wood–plastic composites, fiberboards, veneer-based products, and bio-adhesives derived from lignin and tannin fractions. The reviewed studies were identified through a structured survey of recent scientific literature focusing on the processing, classification, physicochemical characteristics, and engineering applications of forest biomass residues. Different utilization strategies were examined according to the geometrical form of the biomass, including fibers, particles, powders, and chemically extracted constituents used for adhesive formulation. The reviewed literature showed that forest residues were successfully incorporated into thermoplastic and thermosetting composite systems, where they contributed to stiffness enhancement, material lightweighting, and partial substitution of petroleum-derived constituents. Lignin- and tannin-based bio-adhesives also demonstrated promising potential for reducing formaldehyde dependence in wood panel manufacturing, although challenges related to reactivity, water resistance, and compositional variability remained significant. The findings further indicated that hybrid biomass systems, adhesive-free densified boards, and integrated biorefinery approaches have progressively expanded the technological possibilities for circular biomass utilization. The study demonstrates that forest residues can serve as multifunctional feedstocks for sustainable wood-based engineering materials when supported by appropriate material selection, traceability, and process integration strategies. The review also provides critical insights into the current limitations, scalability challenges, and future research directions associated with the transition toward low-emission and circular lignocellulosic material systems.

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