Introduces generalized, extended, mixed, and hybrid principles variational methods of approximation, Hamilton's principle, and Lagrange's equations of motion and approximate solutions to problems in structural mechanics by use of variational theorems. Prerequisite: Instructor permission.Īnalyzes the derivation, interpretation, and application to engineering problems of the principles of virtual work and complementary virtual work related theorems, such as the principles of the stationary value of the total potential and complementary energy, Castigliano's Theorems, theorem of least work, and unit force and displacement theorems. Prerequisite: APMA 6410 and CE 6710 or 6720 or MAE 6020.Ĭoncepts of stress, strain, equilibrium, compatibility Hooke's law (isotropic materials) displacement and stress formulations of elasticity problems plane stress and strain problems in rectangular coordinates (Airy's stress function approach) plane stress and strain problems in polar coordinates, axisymmetric problems thermal stress and energy methods.Īnalyzes basic concepts, postulates, and relationships of classical thermodynamics thermodynamics potentials and derivatives energy minimum and entropy maximum principle generalized Maxwell relations stability considerations phase transitions application to perfect and imperfect systems and extension to chemically reacting and solid systems. Cross listed as AM 6040 and taught concurrently w/ CE 6740.
Includes the classical analysis of plates and shells of various shapes closed-form numerical and approximate methods of solution of governing partial differential equations and advanced topics (large deflection theory, thermal stresses, orthotropic plates). Prerequisites: MAE 2320 Dynamics and CS 1110 or CS 1111 or CS 1112 Introduction to Programming, or instructor's permission.Īnalyzes variational and computational mechanics of solids potential energy complementary energy virtual work Reissner's principle Ritz and Galerkin methods displacement force and mixed methods of analysis finite element analysis including shape functions, convergence, and integration.
Basic probability theory, numerical techniques for recursive Bayesian estimation and multi-sensor data fusion, Simultaneous Localization and Mapping, quantification of belief, and autonomous control. Principles of robotic autonomy for navigating unstructured environments using mathematical principles. Introduces rocket-engine design and optimization problems materials, temperature-exposure, and stress-strain issues rocket flight mechanics and trajectories rocket staging issues liquid propellants liquid-propellant engine designs rocket thrust-chamber flow behaviors and modeling rocket exhaust behaviors modeling methods maneuver, orbit-adjustment, and attitude-adjustment engines Prerequisite: MAE 2320, 3010, 3210 corequisite: MAE 3220
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