Engineering

The objective of this course is for students to learn to appropriately apply discrete event simulation modeling for decision support in Industrial Engineering problems through developing skills in model building, simulation output analysis, and communication of technical information and conclusions drawn from data analysis. Topics include Introduction to Discrete, Event System Simulation, Simulating a Queueing System, General Principles, Discrete Distributions & Continuous Distributions, Poisson Process and Characteristics of Queueing Systems, Long-Run Measures of Performance of Queueing Systems, Steady-State Behavior, Networks of Queues, Techniques for Generating Random Numbers, Tests for Random Numbers: Tests for Autocorrelation, Inverse-Transform & Acceptance-Rejection Techniques, Parameter Estimation, Data Collection & Identifying the Distribution with Data, Multivariate and Time-Series Input Models, and Stochastic Nature of Output Data.

This course covers elasticity, structural analysis, energy and matrix methods, fatigue, vibration, airworthiness and aeroelasticity. It provides general information of aircraft structures and materials, and transfer of external aerodynamic loads into structural internal forces. The focus is to deliver the fundamental knowledge for stresses, deflection, and buckling analysis of these structural components under various static loading conditions including torsion, bending and shear. Lectures emphasize the fundamentals of structural mechanics and analytical approaches for analysis of aircraft structures. Students learn to derive the theory of linear elasticity and apply it to analyze the components subjected to typical aircraft loading conditions and design requirements. Tutorials provide a set of lessons and exercises teaching the concepts and methodology in analysis of aircraft structures. The students learn and understand the procedure of aircraft structural analysis from following tutorial problem solving exercises with group discussions.

This course is designed to acquire knowledge of fundamental and advanced concepts in optics, and a general understanding of when and how these concepts are possible and appropriate to use. The course deals with optical devices and their operation and aims to provide students with practical knowledge in optical design using a ray-tracing program. The course has the following content. Every topic is coupled to a chapter or parts of a chapter in the course book: Ray optics, matrix formulation; Wave optics, interference; Fourier optics, diffraction; Electromagnetic optics; Anisotropic media; Polarization, Jones matrix formalism; and Optics of layered media and photonic crystals.
 

This course covers an in-depth understanding of the physics and principles behind lasers. The course covers the theoretical foundations of beam optics, cavity optics, light–matter interaction, laser amplifiers, and laser systems. Furthermore, the course aims for the student to gain both fundamental knowledge and practical skills necessary to study and apply lasers in scientific and technical contexts.
 

This course is part of the Laurea Magistrale degree program and is intended for advanced level students. Enrollment is by permission of the instructor. This course consists of two modules: Marine Renewable Energy and Bioenergy, Hydrogen, and Heat Recovery Systems. 

For Marine Renewable Energy, students acquire the ability to assess marine renewable energy potential and to conceptually design energy devices. They are able to assess marine energy potential (wind, waves, tides, currents, etc.) and have knowledge about devices for marine energy harvesting and technological challenges, and assessment of environmental, social, and economic impacts. The module covers the following topics: Marine renewable energy: sources (wind, wave, tide) and variability; Type of marine renewable energy converters; Environmental impact and cost of MRE devices; Optimal mixing of MRE; Multi-use marine areas and integration of different economic activities: MRE, aquaculture, tourism, maritime hubs; and Re-purposing of O&G platforms.

Bioenergy, Hydrogen and Heat Recovery Systems module provides the student with knowledge and understanding about: Biomass and alternative fuels for energy application: production, treatment and storage, thermochemical conversion, environmental and economic aspects; Hydrogen for energy and transport applications: characteristics, production, gas-to-power (G2P) and power-to-gas (P2G) systems, technologies for upgrading fuels (synthetic methane), fields of application, integration into the existing infrastructure; Heat recovery systems: cycles and working principle of the main heat-to-power (H2P) technologies (Organic Rankine Cycle and Stirling engine). After completion of the course the students should (i) gain general competence related to bioenergy and hydrogen-based systems and their potential in future energy supply; (ii) working with cross-cutting problems related to bioenergy and hydrogen; (iii) analyzing potential and characteristics of Organic Rankine Cycle systems heat recovery from medium and low-temperature heat sources. 

Originated from Stanford University’s Life Design Lab (Bill Burnett and Dave Evans), this course employs a method called “design thinking” to help students from any program develop a constructive and effective approach to finding and designing their vocation after university. Through small group discussions, in-class activities, personal reflections and individual coaching, this course teaches students to use design thinking to explore many of life’s major challenges, such as pursuing careers they love and finding personal fulfillment. Topics include the integration of work and worldviews, ideation techniques, a portfolio approach to thriving, designing to increase balance and energy, and how to prototype all aspects of life. The course touches on the realities of engaging the workplace, and practices that support vocation formation throughout the career of students. The capstone assignment is the creation of an “Odyssey Plan” focusing on taking actions in the 3-5 years following their graduation. For Engineering students only. Graded P or F.

Production technology covers major part of manufacturing processes applied for creating form and shape of the product. The manufacturing processes covered in this course include: casting processes, such as sand casting, shell mold casting, die casting and investment casting; forming processes, such as hot and cold forging, rolling, extrusion, bending, deep drawing, wire drawing and spinning; shearing operations such as blanking and fine blanking; metal cutting methods such as turning, milling grinding, threading and drilling; non-traditional machining processes, such as chemical, electrochemical, erosive, laser and ultrasound machining; joining processes including metallurgy, weldability of the materials and different welding methods, such as fusion welding and solid state welding processes. 

The course introduces the principles of probability and statistics and their applications in engineering. Topics include the relationship between probability and statistics; random variables; probability distributions; mathematical expectation; random sampling; estimation; tests of hypotheses, and regression analysis. 

This course covers the fundamental concepts of databases—an essential component in implementing e-business information systems—including the entity-relationship model, relational databases, and the use of structured query language (SQL). Through individual projects, students also explore how to integrate databases with business information systems. Topics include Introduction to Database Industrial Information Management, Introduction to Structured Query Language (SQL), Relational model and normalization, Database design using normalization, Data modelling with the entity-relationship model, Transforming data models into a database design, SQL for database construction and application processing, Database redesign, Managing multi-user databases, Web Server Environment, and Data warehouses, business intelligent systems, and big data. 

Systems do not in general naturally behave in a manner which accords with the user’s wishes. Systems must in general be extended by the addition of a controller in order to force them to behave in an acceptable fashion. The controller may be a human (as in the case of the driver of a car for example), but the controller may also be a human-designed engineering system in its own right. In the latter case the controller is called an automatic controller. This course addresses the need for, the value of and the design of automatic controllers for some of the most common classes of engineering systems. Automatic controllers appear in more or less every engineering environment, from automotive/aerospace to biomedical equipment and including almost everything in between.