Lecture
Symmetrical Lurking and Inertia Tensor
In course
DEMO: ad deserunt excepteur culpa
Sunt minim est dolore enim. Dolor laborum consectetur quis non ea. Consequat nostrud culpa sit id ut anim non incididunt laborum consequat tempor sit. Eiusmod tempor et occaecat ullamco.
Description
This lecture covers the concept of symmetrical lurking, including points related to constant directed moments, precession, and face moments. It also delves into the inertia tensor, discussing its properties, relationship with axes, and moments of inertia. The slides provide detailed equations and examples to illustrate these concepts.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on MediaspaceInstructor
exercitation pariatur
Sunt ipsum qui ullamco aliquip. Tempor laboris quis ipsum veniam esse duis. Duis tempor minim Lorem dolore excepteur Lorem officia nisi irure.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related lectures (30)
Angular Momentum Transfer Theorem
Explores angular momentum transfer theorem, inertia tensor, and principal moments of inertia.
Wheel and Thread: Static Equilibrium and Rolling Motion
Covers the static equilibrium and motion of a wheel using a thread.
General Mechanics: Inverted Classroom
Covers general mechanics in an inverted classroom setting, including quizzes on spheres and cylinders rolling without slipping.
Solid Dynamics: Rotational Motion
Explores the dynamics of rigid bodies, including moment of inertia and rotational motion concepts, illustrated with practical examples.
Understanding Chaos in Quantum Field Theories
Explores chaos in quantum field theories, focusing on conformal symmetry, OPE coefficients, and random matrix universality.