Working Groups
The Workshop offers a venue for reviewing and discussing the latest advances in the fields of structural control and monitoring.
Working Group 1: Digital Twins and Hybrid Simulation
Digital twins are fusions of computational models and data, and form a virtual digital duplicate of a complex system and its environement. They aim at accounting for the treatment of uncertainties, as well as at improving the predictive capability. Within such a context, hybrid simulation is particulalry helpful, for obtaining a core insight of subsystems and their effects on the system level.
The first Working Group (WG) will trigger a dialogue on these emerging areas and focus on diverse topics, such as:
- Uncertainty Quantification
- Verification & Validation
- Nonlinear Substructuring and Hybrid Simulation
- Life-Cycle Performance
Working Group 2: Structural Vibration Control
Engineering vibration has traditionally comprised a very active research area, motivated by the abundance of associated technological applications. In this domain, the safety margins associated with the protection of humans, machines and structures, from undesired/uncontrolled motions of diverse frequency characteristics dictate design.
The attenuation of engineering vibration is treated using a mix of passive, active and semi-active methods. This WG will foster discussions on topics that include, among others:
- Modern theoretical developments for structural control
- Smart actuators, materials and devices
- Linear and nonlinear metamaterials
- Fault-tolerant control
- Benchmark problems and applications
Working Group 3: Structural Health Monitoring
Structural Health Monitoring capitalizes on the multiplicity of data conveyed by modern sensing technologies which allow for extraction of diverse information on the response and operational environments of structures and infrastructures. Proper utilization of SHM data, able to account for the underlying epistemic and aleatory uncertainties, allows for condition-based maintenance, life-cycle and remaining useful lifetime assessment, and optimization of operational/control conditions.
A major challenge in carrying out these tasks stems from the uncertainties that are underlying not only the data, but also the system models, which are often fused into the estimation and assessment process. This WG will foster discussions on topics that include, among others:
- Development in contact, embedded and non-contact (remote) sensing
- Theoretical developments for SHM and identification methodologies
- Fusion of data and models in Hybrid or Grey Box modeling tools for simulations of increased confidence/ digital twinning
- Machine Learning and Artificial intelligence schemes, including physics-constrained deep learning, in particular with relation to the handling of time series data
- Field applications on data extracted from full-scale systems