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UID:0-267@aerospace.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20210407T163000

DTEND;TZID=Asia/Jerusalem:20210407T173000

DTSTAMP:20230525T064159Z

URL:https://aerospace.technion.ac.il/events/modeling-prediction-and-mitiga
 tion-of-nonlinear-complex-dynamical-systems-under-stochastic-disturbances/

SUMMARY:Modeling\, Prediction\, and Mitigation of Nonlinear Complex Dynamic
 al Systems Under Stochastic Disturbances
DESCRIPTION:Lecturer:Maor Farid\n Faculty:Mechanical Engineering\, MIT\; Me
 chanical Engineering\, Technion\n Institute:Mechanical Engineering\, MIT\;
  Mechanical Engineering\, Technion\n Location:https://technion.zoom.us/j/9
 3324438721\n Zoom: \n Abstract: \n Details: \n Destructive vibrations caus
 ed by stochastic external disturbances such as earthquakes\, explosions\, 
 and fluid-structure interactions pose an insidious threat to various criti
 cal infrastructure and mechanical components. Among the most vulnerable an
 d potentially hazardous are large structures\, nuclear facilities\, aerosp
 ace\, and naval vehicles. Damage to these systems not only might endanger 
 human lives but also often result in long-term environmental and ecologica
 l distress. Hence\, reliable models for real-time prediction of the dynami
 cal responses and resulting stresses under stochastic excitations are a cr
 itical necessity for the operation\, maintenance\, and structural health m
 onitoring of these systems. However\, most of the aforementioned systems c
 onsist of numerous smaller elements of various shapes and physical propert
 ies—hence they are referred to as complex systems—which are a great ch
 allenge to model and predict. Therefore\, the vast majority of existing pr
 ediction methods are based on either over-simplistic models that suffer fr
 om poor accuracy\, or time-consuming computational models that are not app
 licable for real-time purposes and do not describe the underlying mechanis
 ms that govern the system’s dynamical response.\nThe current research fo
 cuses on a multidisciplinary approach\, combining both reduced-order model
 ing and machine-learning-based methods for the description and prediction 
 of complex dynamical systems. Finally\, hybrid vibration mitigation soluti
 ons are introduced\, which utilize both linear and nonlinear energy absorp
 tion techniques for enhanced protection capabilities. The methods presente
 d pave the way towards faster and more accurate forecasting methods as wel
 l as more effective vibration mitigation technologies\, allowing for enhan
 ced resistance of existing facilities\, structures\, and mechanical compon
 ents to a variety of external disturbances in real-time. Thus\, they are o
 f great importance in terms of public health\, homeland security\, and env
 ironmental responsibility.\nThis 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.\nZoom Meeting
CATEGORIES:Seminars
LOCATION:https://technion.zoom.us/j/93324438721

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