Motion is the essence of any mechanical system. Analyzing a system''s dynamical response to distinct motion parameters allows for increased understanding of its performance thresholds and can in turn provide clear data to inform improved system designs.Modeling of Complex Dynamic Systems: Fundamentals and Applications equips readers with significant insights into nonlinear vibration phenomenology through a combination of advanced mathematical fundamentals and worked-through modeling experiments. To guide them in determining novel stabilization characteristics for complex moving objects, coupled structures, as well as the stochastic stability of mechanical systems, the technical and methodological analysis is accompanied by industry-relevant practical examples, contributing much sought-after applicable knowledge.The book is intended for use by postgraduate students, academic researchers, and professional engineers alike.- Connects three areas of theoretical and applied mechanics – nonlinear vibrations, dynamics of moving objects, and stochastic stability of structures, while also reviewing literature- Compares classical dynamic models with the authors'' proposed modeling methodologies to analyze mechanical systems affected by parametric instabilities- Discusses new technical solutions powered by AI and ML to introduce possible further research directions

Motion is the essence of any mechanical system. Analyzing a system''s dynamical response to distinct motion parameters allows for increased understanding of its performance thresholds and can in turn provide clear data to inform improved system designs.Modeling of Complex Dynamic Systems: Fundamentals and Applications equips readers with significant insights into nonlinear vibration phenomenology through a combination of advanced mathematical fundamentals and worked-through modeling experiments. To guide them in determining novel stabilization characteristics for complex moving objects, coupled structures, as well as the stochastic stability of mechanical systems, the technical and methodological analysis is accompanied by industry-relevant practical examples, contributing much sought-after applicable knowledge.The book is intended for use by postgraduate students, academic researchers, and professional engineers alike.- Connects three areas of theoretical and applied mechanics – nonlinear vibrations, dynamics of moving objects, and stochastic stability of structures, while also reviewing literature- Compares classical dynamic models with the authors'' proposed modeling methodologies to analyze mechanical systems affected by parametric instabilities- Discusses new technical solutions powered by AI and ML to introduce possible further research directions

Motion is the essence of any mechanical system. Analyzing a system''s dynamical response to distinct motion parameters allows for increased understanding of its performance thresholds and can in turn provide clear data to inform improved system designs.Modeling of Complex Dynamic Systems: Fundamentals and Applications equips readers with significant insights into nonlinear vibration phenomenology through a combination of advanced mathematical fundamentals and worked-through modeling experiments. To guide them in determining novel stabilization characteristics for complex moving objects, coupled structures, as well as the stochastic stability of mechanical systems, the technical and methodological analysis is accompanied by industry-relevant practical examples, contributing much sought-after applicable knowledge.The book is intended for use by postgraduate students, academic researchers, and professional engineers alike.- Connects three areas of theoretical and applied mechanics – nonlinear vibrations, dynamics of moving objects, and stochastic stability of structures, while also reviewing literature- Compares classical dynamic models with the authors'' proposed modeling methodologies to analyze mechanical systems affected by parametric instabilities- Discusses new technical solutions powered by AI and ML to introduce possible further research directions