Call for papers/Topics

Full Articles/ Reviews/ Shorts Papers/ Abstracts are welcomed in the following research fields:

Deformable and Rigid-Body Mechanics: High-fidelity structural analysis applying advanced Newtonian physics to analyze loads, internal forces, shear, and moments under dynamic conditions.
Advanced Fluid Dynamics: Experimental, analytical, and computational modeling utilizing the Navier-Stokes equations and dimensionless parameters (Reynolds, Froude, and Mach numbers) to predict fluid-structure interactions.
Multiphysics Engineering: The study of coupled systems simultaneously involving mechanical, thermal, electrical, and chemical reactions (e.g., modern welding flux, acoustic-thermal boundaries).

Advanced Clean Fuel Technologies: Breakthroughs in bioenergy, biofuels, and hydrogen production/storage systems.
Electrochemical and Thermal Energy Storage: Optimization of fuel cells, electrolyzers, membrane reactors, and advanced grid batteries.
Carbon Capture, Utilization, and Storage (CCUS): Engineering scalable chemical and mechanical networks to isolate and convert carbon emissions.

Kinematics, Dynamics, and Control Theory: Foundations of physical robot motion, gait mimicking, and path-planning automation.
Embedded Microprocessors and Sensors: Next-generation hardware, edge-processing distance sensors, and motor-actuation controllers.
Hardware-in-the-Loop (HIL) Testing: Physical hardware simulation under virtual constraints to isolate system behaviors before deployment.

4. Smart Engineering Systems and Industry 4.0

Cyber-Physical Systems (CPS): Seamlessly embedding physical machinery with digital communication networks, enabling real-time self-diagnosis.
Industrial Internet of Things (IoT): Large-scale sensory mesh networks feeding structural and process telemetry data into centralized clouds.
Digital Twins and Virtual Reality (VR): Real-time digital mirroring of complex operational assets to run risk-free simulations and optimize engineering designs.

Model-Based Systems Engineering (MBSE): Transitioning from document-based systems to digital, centralized system modeling languages (e.g., SysML) to track complete system lifecycles.
Axiomatic Design and Robust Design Methodologies: Formalized mathematical frameworks to evaluate system complexity, error mitigation, and quality metrics over time.
Multi-Objective Refactoring & System Optimization: Algorithmic workflows engineered to handle multi-domain trade-offs, such as maximizing structural integrity while minimizing weight and economic cost.

Generative Design Algorithms: The convergence of AI and quantum-parametric design spaces to automatically engineer optimized geometric and material solutions.
Predictive Maintenance Frameworks: Implementing neural networks, support vector machines, and decentralized federated learning models to predict catastrophic equipment failures without data privacy breaches.
Trustworthy and Explainable AI (XAI): Developing tracing mechanics to ensure algorithmic accountability and human-interpretable outputs within automated engineering tasks.

Life-Cycle Assessment (LCA) Systems: Engineering software and metrics to evaluate the complete carbon and waste footprint of a system from raw material extraction to decommissioning.
Smart Grid Integration: Combining process engineering, renewable sources (wind, solar), and smart load distribution algorithms to accommodate decentralized energy architecture.
Circular Economy Engineering Manufacturing: Systems designed specifically for modular disassembly, material upcycling, and zero-waste production lifecycles.