Engineering

This course examines the principles of fluid mechanics. Topics discussed include fluid properties; hydrostatics; buoyancy; pressures in fluid systems; principles of mass conservation; steady flow energy equations; flow measurement; forces and momentum in flowing fluids; dimensional analysis, similarity and physical modelling; pipe flow; incompressible laminar and turbulent flow in pipes; friction factor; elementary boundary layer flow; skin friction and drag; pumps and turbines; and pump and pipeline system characteristics.

This course examines the analysis of the equilibrium and dynamic behavior of mechanical systems. It covers equilibrium of particles and of rigid bodies; distributed forces; analysis of structures, including, trusses, frames, cables and beams; kinematics of particles; kinetics of particles, Newton's second law, energy, momenta, impact dynamics; systems of particles; kinematics of rigid bodies; and kinetics of rigid bodies in two and three dimensions.

This course critically examines the technology of energy systems that will be acceptable in a world faced with global warming, local pollution, and declining supplies of oil. It covers conventional fossil fuel energy systems, renewable energy systems (wind, solar, ocean), and non-carbon emitting energy systems.

This course examines irrotational flow, circulation, 2D airfoils, thin airfoil theory, 3D wings, lifting line theory, boundary layers, turbulence, supersonic flow, shock waves, expansion fans, transonic flow, and swept wings.

This course offers a study of the fundamentals of Python3 programming language for scientific computation (computational fluid dynamics). Topics include: basic commands for running python routines in a jupyter environment-- manipulation of files, directories, and processes, parameters of a command in POSIX format, interactive environments, and git; numerical methods for wave field models-- finite differences, finite volume method, and finite element method.

This course examines flight dynamics, with emphasis on aircraft performance and stability. It covers the fundamentals of flight dynamics, focusing more especially on the key concepts pertaining to flight performance and stability; the methodological tools (fundamental theories and mathematical models) that are commonly used for analyzing the performance and stability characteristics of aircraft; and how these theoretical and methodological knowledge are used across aerospace industries for the safety and efficiency of aircraft can be maximized.

This course explores and identifies why engineering is essential to the modern world. Students learn how engineers draw on scientific knowledge, research techniques, technical know-how, skills and collective experiences as well as societal facts and values to solve problems of any size or complexity. Within the interplay of these factors, many life-changing decisions and engineering solutions cannot be made using only calculations but require sound thinking and justifications based on often incomplete information.   

This course provides research training for exchange students. Students work on a research project under the guidance of assigned faculty members. Through a full-time commitment, students improve their research skills by participating in the different phases of research, including development of research plans, proposals, data analysis, and presentation of research results. A pass/no pass grade is assigned based a progress report, self-evaluation, midterm report, presentation, and final report.

This course provides individual research training for students in the Junior Year Engineering Program through the experience of belonging to a specific laboratory at Tohoku University. Students are assigned to a laboratory with the consent of the faculty member in charge. They participate in various group activities, including seminars, for the purposes of training in research methods and developing teamwork skills. The specific topic studied depends on the instructor in charge of the laboratory to which each student is assigned. The methods of assessment vary with the student's project and laboratory instructor. Students submit an abstract concerning the results of their individual research each semester and present the results near the end of the program.

This course is part of the Laurea Magistrale program. The course is intended for advanced level students only. Enrollment is by permission of the instructor. The objective of the course is to present the most effective techniques for the solution of complex decisional problems arising in the optimal planning and management of large-scale systems concerning both the public and the private sectors. Mathematical models and heuristic algorithms for the practical solution of the corresponding optimization problems are described. Particular attention is given to the algorithmic and implementation aspects. Applications of the proposed techniques to real-world problems are presented and analyzed. The course discusses topics including: basic integer programming optimization: integer programming models, formulations, relaxations; basic heuristic approaches: constructive algorithms and local search procedures, examples for KP01 and TSP; worst-case performance analysis; metaheuristics: Multistart, Tabu Search, Simulated Annealing, Genetic Algorithms, Iterated Local Search, Variable Neighborhood Search, Large Neighborhood Search, Ruin and Recreate, and Ant Systems; optimization on graphs: shortest path, minimum spanning tree, and maximum flow; heuristic and metaheuristic algorithms for difficult combinatorial optimization problems; and real-world applications. Prerequisites for this course are: basic knowledge of Operations Research, as well as the implementation of computer codes and complexity theory.