Online courses directory (273)
This course is a survey of principal concepts and methods of fluid dynamics. Topics include mass conservation, momentum, and energy equations for continua; Navier-Stokes equation for viscous flows; similarity and dimensional analysis; lubrication theory; boundary layers and separation; circulation and vorticity theorems; potential flow; introduction to turbulence; lift and drag; surface tension and surface tension driven flows.
This subject introduces the key concepts and formalism of quantum mechanics and their relevance to topics in current research and to practical applications. Starting from the foundation of quantum mechanics and its applications in simple discrete systems, it develops the basic principles of interaction of electromagnetic radiation with matter.
Topics covered are composite systems and entanglement, open system dynamics and decoherence, quantum theory of radiation, time-dependent perturbation theory, scattering and cross sections. Examples are drawn from active research topics and applications, such as quantum information processing, coherent control of radiation-matter interactions, neutron interferometry and magnetic resonance.
The purpose of this course is to discuss modern techniques of generation of x-ray photons and neutrons and then follow with selected applications of newly developed photon and neutron scattering spectroscopic techniques to investigations of properties of condensed matter which are of interest to nuclear engineers.
This course provides an introduction to the transportation industry's major technical challenges and considerations. For upper level undergraduates interested in learning about the transportation field in a broad but quantitative manner. Topics include road vehicle engineering, internal combustion engines, batteries and motors, electric and hybrid powertrains, urban and high speed rail transportation, water vessels, aircraft types and aerodynamics, radar, navigation, GPS, GIS. Students will complete a project on a subject of their choosing.
This course surveys a variety of reasoning, optimization and decision making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their application, taken from the disciplines of artificial intelligence and operations research.
Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, and machine learning. Optimization paradigms include linear programming, integer programming, and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes.
This class is an introduction to classical mechanics for students who are comfortable with calculus. The main topics are: Vectors, Kinematics, Forces, Motion, Momentum, Energy, Angular Motion, Angular Momentum, Gravity, Planetary Motion, Moving Frames, and the Motion of Rigid Bodies.
This course was created for the "product development" track of MIT's System Design and Management Program (SDM) in conjunction with the Center for Innovation in Product Development. After taking this course, a student should be able to:
- Formulate measures of performance of a system or quality characteristics. These quality characteristics are to be made robust to noise affecting the system.
- Sythesize and select design concepts for robustness.
- Identify noise factors whose variation may affect the quality characteristics.
- Estimate the robustness of any given design (experimentally and analytically).
- Formulate and implement methods to reduce the effects of noise (parameter design, active control, adjustment).
- Select rational tolerances for a design.
- Explain the role of robust design techniques within the wider context of the product development process.
- Lead product development activities that include robust design techniques.