0.1 Overview of intersection problems 10.2 Intersection problem classification 10. 2. 1 Classification by dimension 10.2.2 Classification by type of geometr 10.2.3 Classification by number system 10.3 Point /point\intersection
Lecture 2 Differential geometry of curves 2.1 Definition of curves 2.1.1 Plane curves Implicit curves f(, y)=0 Example:x2+y2=a2 It is difficult to trace implicit curves It is easy to check if a point lies on the curve Multi-valued and closed curves can be represented
Lecture 6 B-splines(Uniform and Non-uniform) 6.1 Introduction The formulation of uniform B-splines can be generalized to accomplish certain objectives These include Non-uniform parameterization Greater general flexibility Change of one polygon vertex in a Bezier curve or of one data point in a cardinal(or interpolatory) spline curve changes entire curve(global schemes) Remove necessity to increase degree of Bezier curves or construct composite Bezier curves
Lecture 1 Introduction and classification of geometric modeling forms 1.1 Motivation Geometric modeling deals with the mathematical representation of curves, surfaces, and solids necessary in the definition of complex physical or engineering objects. The associated field of computational geometry is concerned with the development, analysis, and computer implemen tation of algorithms encountered in geometric modeling. The objects we are concerned with in engineering range from the simple
Aircraft Dynamics First note that it is possible to develop a very good approximation of a key motion of an aircraft(called the Phugoid mode) using a very simple balance between the kinetic and potential energies Consider an aircraft in steady, level fight with speed Uo and height ho
LECTURE+ 12 RIGID BODY OYNAAICS 工 MPLICAT IONsF GENERAL ROTATIONAL OYWMICS EJLER's EQUATIN of MOTION TORQVE FREE SPECIAL CASES. PRIMARY LESSONS: 30 ROTATONAL MOTION MUCH MORE COMPLEX THAN PLANAR (20) EULER'S E.o.M. PROVIOE STARTING POINT FoR ALL+ OYwAmIcs SOLUTINS To EvlER's EQuATIONS ARE COMPLEX BUT WE CAN OEVE LOP GooO GEOMETRIC VISUALIZATION TOOLS
Spring 2003 Derivation of lagrangian equations Basic Concept: Virtual Work Consider system of N particles located at(, x2, x,,.x3N )with 3 forces per particle(f. f, f..fn). each in the positive direction
NUMERICAL SOLUTION GIEN A COMPLEX SET of OYNAMICS (t)=F(x) WHERE F() COULD BE A NONLINEAR FUNCTION IT CAN BE IMPOSS IBLE To ACTVALLY SOLVE FoR ( ExACTLY. OEVELOP A NUMERICAL SOLUTION. CANNED CoDES HELP US THIS TN MATLAB BUT LET US CONSDER THE BASiCS
