Destructive vibrations caused by stochastic external disturbances such as earthquakes, explosions, and fluid-structure interactions pose an insidious threat to various critical infrastructure and mechanical components. Among the most vulnerable and potentially hazardous are large structures, nuclear facilities, aerospace, and naval vehicles. Damage to these systems not only might endanger human lives but also often result in long-term environmental and ecological distress. Hence, reliable models for real-time prediction of the dynamical responses and resulting stresses under stochastic excitations are a critical necessity for the operation, maintenance, and structural health monitoring of these systems. However, most of the aforementioned systems consist of numerous smaller elements of various shapes and physical properties—hence they are referred to as complex systems—which are a great challenge to model and predict. Therefore, the vast majority of existing prediction methods are based on either over-simplistic models that suffer from poor accuracy, or time-consuming computational models that are not applicable for real-time purposes and do not describe the underlying mechanisms that govern the system’s dynamical response.
The current research focuses on a multidisciplinary approach, combining both reduced-order modeling and machine-learning-based methods for the description and prediction of complex dynamical systems. Finally, hybrid vibration mitigation solutions are introduced, which utilize both linear and nonlinear energy absorption techniques for enhanced protection capabilities. The methods presented pave the way towards faster and more accurate forecasting methods as well as more effective vibration mitigation technologies, allowing for enhanced resistance of existing facilities, structures, and mechanical components to a variety of external disturbances in real-time. Thus, they are of great importance in terms of public health, homeland security, and environmental responsibility.
This work is funded by the Fulbright program, the ISEF Foundation, the Israel Academy of Sciences and Humanities, the Shamir Scholarship of the Israeli Ministry of Science, Technology, and Space, and the PMRI -Technion.
