NUMSTAT 2026 Special Issue

About the Special Issue

Modern engineering systems are increasingly complex, nonlinear, data-rich, and computationally demanding. Their modelling, analysis, prediction, identification, monitoring, testing, and control require the integration of advanced numerical methods, statistical modelling, computational mechanics, uncertainty quantification, experimental measurements, system identification, and emerging data-driven techniques.

Recent advances in artificial intelligence, scientific machine learning, physics-informed modelling, sensing technologies, reduced-order modelling, and digital twins are creating new opportunities for understanding complex engineering dynamical systems. At the same time, experimental investigations, vibration measurements, sensing, model validation, and hybrid experimental–computational approaches remain essential for ensuring that theoretical and computational developments provide physically meaningful and reliable predictions.

Selected high-quality papers presented at NUMSTAT 2026, to be held on 31 October–1 November 2026 at the ABV-Indian Institute of Information Technology & Management (ABV-IIITM), Gwalior, India, will be considered for this Special Issue of the Journal of Vibration Testing and System Dynamics (JVTSD).

The aim of this Special Issue is to bring together original, high-quality research presenting recent theoretical, numerical, statistical, computational, experimental, and data-driven developments in vibration and engineering dynamics. Particular emphasis will be placed on contributions that integrate numerical simulation, statistical analysis, experimental data, sensor measurements, uncertainty quantification, and modern artificial intelligence and machine-learning approaches.

All submissions must demonstrate a clear and substantive connection to vibration, dynamical systems, structural dynamics, system identification, vibration testing, condition monitoring, sensing and measurement, or closely related areas within the scope of JVTSD. General numerical, statistical, computational, or machine-learning methodologies will be considered only when the manuscript demonstrates a substantive application or contribution to these areas.

Experimental investigations and hybrid experimental–computational studies are particularly encouraged. Contributions involving measurements, sensing, experimental validation, vibration testing, condition monitoring, or the integration of experimental data with numerical and data-driven models are especially welcome.

Authors of selected high-quality papers presented at NUMSTAT 2026 may be invited to submit full journal manuscripts for consideration. An invitation to submit does not guarantee acceptance for publication. All manuscripts will undergo the standard peer-review and editorial process of JVTSD, and acceptance for presentation at NUMSTAT 2026 will be independent of the journal's publication decision.

Potential Topics

Topics of interest include, but are not limited to:

• Numerical methods for vibration and dynamical systems
• Computational methods for structural dynamics and vibration analysis
• Nonlinear dynamics and computational modelling
• Finite element and related numerical methods for dynamic systems
• Computational mechanics and coupled dynamical systems
• Flow-induced vibration and fluid–structure interaction
• Thermo-mechanical and multiphysics dynamical systems
• Vibration testing and experimental dynamics
• Experimental–computational methods and model validation
• System identification and parameter estimation
• Statistical methods for vibration and dynamical systems
• Uncertainty quantification in structural and dynamical systems
• Structural reliability and probabilistic analysis of dynamical systems
• Stochastic dynamics and random vibration
• Signal processing for vibration and dynamic measurements
• Sensing, measurement, and condition monitoring
• Data-driven modelling of dynamical systems
• Scientific machine learning for vibration and dynamics
• Artificial intelligence and machine learning for fault diagnosis and prognostics
• Physics-informed and hybrid physics–data models for dynamical systems
• Reduced-order modelling of engineering dynamical systems
• Digital twins for structural and dynamical systems
• Predictive maintenance, fault detection, and health monitoring
• Optimisation and control of vibration and complex dynamical systems
• Network dynamics and complex engineering systems

Important Dates