"Estimation theory provides a broad and natural mathematical foundation for data assimilation science. Stochastic-dynamic modeling and stochastic observation modeling are described first. Optimality criteria for linear and nonlinear state estimation problems are then explored, leading to conditional-mean estimation procedures such as the Kalman filter and some of its generalizations, and to conditional-mode estimation procedures such as variational methods. A detailed derivation of the Kalman filter is given to illustrate the role of key probabilistic concepts and assumptions. Extensions of the Kalman filter to nonlinear observation operators and to non-Gaussian errors are then described. In a simple illustrative example, rigorous treatment of representativeness error and model error is highlighted in finite-dimensional estimation procedures for continuum dynamics and observations of the continuum state." -- Stephen E. Cohn, NASA Goddard Space Flight Center

Focus on scientific understanding and development of power generation that is the basis of modern society. Concentration on power generation methods that are sustainable, in particular, discussion of the most recent innovations.

Overview of mechatronics system and control system design concepts, control software architecture, control hardware architecture, microcontroller and interface technology for mechatronics control, sensor for mechatronics systems, actuator drives.

 Experiments illustrating principles of thermal-fluid systems and related measurement devices. Statistical design of experiments and uncertainty analysis of data; thermodynamic cycles, combustion, compressible and incompressible flows.

Principles of mechanics applied to design. Deformation and stress analysis. Structural integrity under static and fluctuating loads. Projects demonstrate progression from concept to engineering analysis, with emphasis on strength and durability.

Conduction, convection, and radiation heat transfer. Computational modeling of heat transfer in engineering. Applications to engineering equipment with the use of digital computers.

Experiments to illustrate principles of mechanical systems. Signal analysis; Demonstration of basic sensors for mechanical systems; Experimental project design; Experiments involving voltage measurement; strain gauges, dynamic systems of 1st order.

Modern manufacturing methods, safety, manufacturing instructions, computer-aided manufacturing and their role in the engineering design and development process.

Inviscid incompressible flow, compressible flow, ideal gas mixtures, psychrometrics, reacting mixtures and combustion.

Methodology for solving engineering problems. Engineering computing and visualization based on MATLAB. Engineering examples and applications. 

Number representation, Taylor expansions, error and stability analysis, roots of nonlinear equations, sets of linear equations, numerical integration, ordinary differential equations.

Introduction to general principles and analytical methods used in physics for physical science and engineering majors. Classical mechanics. Fluid mechanics, thermodynamics, wave phenomena, optics. Electricity and magnetism including circuits and Maxwell's equations.