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OverviewData Science in Engineering, Volume 9: Proceedings of the 40th IMAC, A Conference and Exposition on Structural Dynamics, 2022, the nineth volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Novel Data-driven Analysis Methods Deep Learning Gaussian Process Analysis Real-time Video-based Analysis Applications to Nonlinear Dynamics and Damage Detection High-rate Structural Monitoring and Prognostics Full Product DetailsAuthor: Ramin Madarshahian , Francois HemezPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2022 ed. Weight: 0.420kg ISBN: 9783031041242ISBN 10: 3031041240 Pages: 156 Publication Date: 06 July 2023 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsChapter 1. Model Updating for Nonlinear Dynamic Digital Twins Using Data-Based Inverse Mapping Models.- Chapter 2. Deep Reinforcement Learning for Active Structure Stabilization.- Chapter 3. Estimation of Structural Vibration Modal Properties Using a Spike-Based Computing Paradigm.- Chapter 4. Environmental-Insensitive Damage Features Based on Transmissibility Coherence.- Chapter 5. Transmittance Anomalies for Model-Based Damage Detection with Finite Element Generated Data and Deep Learning.- Chapter 6. Machine Learning based Condition Monitoring with Multibody Dynamics Models for Gear Transmission Faults.- Chapter 7. Structural Damage Detection Framework Using Metaheuristic Algorithms and Optimal Finite Element Modeling.- Chapter 8. On Aspects of Geometry in SHM and Population-Based SHM.- Chapter 9. A Robust PCA-based Framework for Long-Term Condition Monitoring of Civil Infrastructures.- Chapter 10. Data-Driven Parameter Identification for Turbomachinery Blisks.- Chapter 11. Classification of Rail Irregularities from Axle Box Accelerations using Random Forests and Convolutional Neural Networks.- Chapter 12. Development of a Surrogate Model for Structural Health Monitoring of a UAV Wing Spar.- Chapter 13. On a Description of Aeroplanes and Aeroplane Components using Irreducible Element Models.- Chapter 14. Input Estimation of Four-DOF Nonlinear Building Using Probabilistic Recurrent Neural Network.- Chapter 15. Simulation-Based Damage Detection for Composite Structures with Machine Learning Techniques.- Chapter 16. Synthesizing Dynamic Time-series Data for Structures Under Shock Using Generative Adversarial Networks.- Chapter 17. Multi-Layer Input Deep Learning Applied to Ultrasonic Wavefield Measurements.ReviewsAuthor InformationRamin Madarshahian, Company: Kount, an Equifax company, ID, USA; Francois Hemez, Lawrence Livermore National Laboratory, Livermore, CA, USA Tab Content 6Author Website:Countries AvailableAll regions |
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