Courses tagged with "Information Theory" (113)

The course begins with the basics of compressible fluid dynamics, including governing equations, thermodynamic context and characteristic parameters. The next large block of lectures covers quasi-one-dimensional flow, followed by a discussion of disturbances and unsteady flows. The second half of the course comprises gas dynamic discontinuities, including shock waves and detonations, and concludes with another large block dealing with two-dimensional flows, both linear and non-linear.

16.225 is a graduate level course on Computational Mechanics of Materials. The primary focus of this course is on the teaching of state-of-the-art numerical methods for the analysis of the nonlinear continuum response of materials. The range of material behavior considered in this course includes: linear and finite deformation elasticity, inelasticity and dynamics. Numerical formulation and algorithms include: variational formulation and variational constitutive updates, finite element discretization, error estimation, constrained problems, time integration algorithms and convergence analysis. There is a strong emphasis on the (parallel) computer implementation of algorithms in programming assignments. The application to real engineering applications and problems in engineering science is stressed throughout the course.

This course serves as an introduction to computational techniques arising in aerospace engineering. Applications are drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques include: numerical integration of systems of ordinary differential equations; finite-difference, finite-volume, and finite-element discretization of partial differential equations; numerical linear algebra; eigenvalue problems; and optimization with constraints.

This course covers the fundamentals of Newtonian mechanics, including kinematics, motion relative to accelerated reference frames, work and energy, impulse and momentum, 2D and 3D rigid body dynamics. The course pays special attention to applications in aerospace engineering including introductory topics in orbital mechanics, flight dynamics, inertial navigation and attitude dynamics. By the end of the semester, students should be able to construct idealized (particle and rigid body) dynamical models and predict model response to applied forces using Newtonian mechanics.

This course provides students with an opportunity to conceive, design and implement a product, using rapid prototyping methods and computer-aid tools. The first of two phases challenges each student team to meet a set of design requirements and constraints for a structural component. A course of iteration, fabrication, and validation completes this manual design cycle. During the second phase, each team conducts design optimization using structural analysis software, with their phase one prototype as a baseline.

Acknowledgements

This course is made possible thanks to a grant by the alumni sponsored Teaching and Education Enhancement Program (Class of '51 Fund for Excellence in Education, Class of '55 Fund for Excellence in Teaching, Class of '72 Fund for Educational Innovation). The instructors gratefully acknowledge the financial support. The course was approved by the Undergraduate Committee of the MIT Department of Aeronautics and Astronautics in 2003. The instructors thank Prof. Manuel Martinez-Sanchez and the committee members for their support and suggestions.

The Experimental Project Lab in the Department of Aeronautics and Astronautics is a two-semester course sequence: 16.621 Experimental Projects I (this course) and 16.622 Experimental Projects II. This site offers material on 16.621. In the course, two-person teams initiate a project of their own conception and design in 16.621 and then complete it in 16.622. For many students, this is a first encounter with research standards and techniques. It is a complicated course that requires a lot of interaction and support and also access to facilities and materials, but it is rewarding for students to explore an hypothesis under the guidance of a faculty advisor.

This OCW site presents the building block materials of the course, which can provide only a profile of the course because the most important learning elements are the interactions between student team, faculty, project advisor, and shop staff and also between student team members. However, this site offers some of the preparation and guidance materials for students embarking on an experimental project. To emphasize the focus on communication skills, a set of study materials and examples of student work are provided.

The Experimental Project Lab in the Department of Aeronautics and Astronautics is a two-semester course sequence: 16.621 Experimental Projects I and 16.622 Experimental Projects II (this course). Students in 16.622 gain practical insight and improved understanding of engineering experimentation through design and execution of "project" experiments. Building upon work in course 16.621, students construct and test equipment, make systematic experimental measurements of phenomena, analyze data, and compare theoretical predictions with results. Deliverables comprise a written final project report and formal oral presentations. Instructions on oral presentations and multi-section reporting are given. Experimental Projects I and II provide a valuable link between theory (16.621) and practice (16.622).

General introduction to systems engineering using both the classical V-model and the new Meta approach. Topics include stakeholder analysis, requirements definition, system architecture and concept generation, trade-space exploration and concept selection, design definition and optimization, system integration and interface management, system safety, verification and validation, and commissioning and operations. Discusses the trade-offs between performance, lifecycle cost and system operability. Readings based on systems engineering standards and papers. Students apply the concepts of systems engineering to a cyber-electro-mechanical system, which is subsequently entered into a design competition.

Students will prepare a PDR (Preliminary Design Review)-level design intended for the Cansat Competition.This year's class will be taught in the form of a Small-Private-Online-Course (SPOC) and offered simultaneously to students at MIT under number 16.842 and Ecole Polytechnique Fédérale de Lausanne (EPFL) as ENG-421.

Human Supervisory Control of Automated Systems discusses elements of the interactions between humans and machines.  These elements include: assignment of roles and authority; tradeoffs between human control and human monitoring; and human intervention in automatic processes.  Further topics comprise: performance, optimization and social implications of the system; enhanced human interfaces; decision aiding; and automated alterting systems.  Topics refer to applications in aerospace, industrial and transportation systems.

This course will teach fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, you should be able to design controllers using state-space methods and evaluate whether these controllers are robust to some types of modeling errors and nonlinearities. You will learn to:

• Design controllers using state-space methods and analyze using classical tools.
• Understand impact of implementation issues (nonlinearity, delay).
• Indicate the robustness of your control design.
• Linearize a nonlinear system, and analyze stability.

This class addresses some of the important issues involved with the planning, development, and implementation of lean enterprises. People, technology, process, and management dimensions of an effective lean manufacturing company are considered in a unified framework. Particular emphasis is placed on the integration of these dimensions across the entire enterprise, including product development, production, and the extended supply chain. Analysis tools as well as future trends and directions are explored. A team project is a key component of this subject.

In 16.540 we address fluid dynamic phenomena of interest in internal flow situations. The emphasis tends to be on problems that arise in air breathing propulsion, but the application of the concepts covered is more general, and the course is wider in scope, than turbomachines (in spite of the title). Stated more directly, the focus is on the fluid mechanic principles that determine the behavior of a broad class of industrial devices. The material can therefore be characterized, only partly tongue in cheek, as "industrial strength fluid mechanics done in a rigorous manner".

The fundamental concepts, and approaches of aerospace engineering, are highlighted through lectures on aeronautics, astronautics, and design. Active learning aerospace modules make use of information technology. Student teams are immersed in a hands-on, lighter-than-air (LTA) vehicle design project, where they design, build, and fly radio-controlled LTA vehicles. The connections between theory and practice are realized in the design exercises. Required design reviews precede the LTA race competition. The performance, weight, and principal characteristics of the LTA vehicles are estimated and illustrated using physics, mathematics, and chemistry known to freshmen, the emphasis being on the application of this knowledge to aerospace engineering and design rather than on exposure to new science and mathematics.

This course introduces the fundamental Lean Six Sigma principles that underlay modern continuous improvement approaches for industry, government and other organizations. Lean emerged from the Japanese automotive industry, particularly Toyota, and is focused on the creation of value through the relentless elimination of waste. Six Sigma is a quality system developed at Motorola which focuses on elimination of variation from all processes. The basic principles have been applied to a wide range of organizations and sectors to improve quality, productivity, customer satisfaction, employee satisfaction, time-to-market and financial performance.

This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

A presentation of the fundamentals of modern numerical techniques for a wide range of linear and nonlinear elliptic, parabolic and hyperbolic partial differential equations and integral equations central to a wide variety of applications in science, engineering, and other fields. Topics include: Mathematical Formulations; Finite Difference and Finite Volume Discretizations; Finite Element Discretizations; Boundary Element Discretizations; Direct and Iterative Solution Methods.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5212 (Numerical Methods for Partial Differential Equations).

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 course studies basic optimization and the principles of optimal control. It considers deterministic and stochastic problems for both discrete and continuous systems. The course covers solution methods including numerical search algorithms, model predictive control, dynamic programming, variational calculus, and approaches based on Pontryagin's maximum principle, and it includes many examples and applications of the theory.

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 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.