Deze vraagstukkenbundel is bedoeld als oefenmateriaal bij het bestuderen van de basiscolleges Fysische Transportverschijnselen, zoals die aan de TU Delft worden gegeven. De vraagstukken zijn afkomstig uit oude vraagstukkenbundels en uit recente tentamens. Wij hebben de formulering van veel van deze vraagstukken herzien.
Vooral door de vraagstukken in meerdere onderdelen te splitsen, hopen we aan te geven dat een stapsgewijze aanpak, veelal gebaseerd op één of meer balansen, een bruikbaar recept voor het oplossen van de opgaven is. Overigens is deze splitsing bij lang niet alle opgaven doorgevoerd om aan studenten de gelegenheid te geven juist dit moeilijke facet zelf te oefenen.

This guide takes the reader through the 3D Printing for Repair (3DP4R) process. It consists of guidelines and tools to create a 3D printable version of spare parts needed for a product repair. 3D printing a spare part is more than just printing the original part. Instead, it is an iterative process in which the part is analysed, redesigned, manufactured, and tested, in order to come to a final part. This guide will describe these four phases in detail. The guide is meant for anybody who is interested in trying to manufacture spare parts with 3D printing technologies, remakers, tinkerers, volunteer repairers, professional repairers, and everyone who is interested in repair initiatives.

Students and professionals in science, design and technology have to develop and communicate concepts that are often difficult to comprehend for the public, their peers and even themselves.

IMAGE | ABILITY – Visualizing the Unimaginable, will help you enhance your communication and interpersonal skills and provide insight, tips and tricks to make such complex and seemingly unimaginable concepts and ideas imaginable.

After finishing this course you will be more skilled in finding the right visual language to convey your ideas, thoughts and vision. You will be able to illustrate units and quantities, concepts and themes and you will know how to unravel complexity by using diagrams and schemes.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning how to integrate AI into their own organization.

To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases.

As part of our two-course program ‘AI in Practice’, this course will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications.

The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN.

‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

This course, AI in Practice: Preparing for AI, is the 1st course of the online education program AI in Practice. The course gives you a kaleidoscope of examples of applications of AI in various organizations, outlines the state of the art in modern AI research, and provides practical tools for integrating AI into your own organization. The program AI in Practice is built from two initial courses, AI in Practice: Preparing for AI and AI in Practice: Applying AI.

The AI in Practice: Preparing for AI course is designed for people who want to apply AI in their own practical situation.

For the experienced manager who wants to know what AI can do for her own organization.
For the data analyst or business consultant who wants to understand how AI can be applied in the business processes of the company for which they work.
For the student who wants to understand how the results of AI research can be translated into practical applications.

Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems.

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems.

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

The course treats the following topics: - Relevant physical oceanography - Elements of marine geology (seafloor topography, acoustical properties of sediments and rocks) - Underwater sound propagation (ray acoustics, ocean noise) - Interaction of sound with the seafloor (reflection, scattering) - Principles of sonar (beamforming) - Underwater acoustic mapping systems (single beam echo sounding, multi-beam echo sounding, sidescan sonar) - Data analysis (refraction corrections, digital terrain modelling) - Applications (hydrographic survey planning and navigation, coastal engineering) - Current and future developments.

Adjustment theory can be regarded as the part of mathematical geodesy that deals with the optimal combination of redundant measurements together with the estimation of unknown parameters. It is essential for a geodesist, its meaning comparable to what mechanics means to a civil engineer or a mechanical engineer. Historically, the first methods of combining redundant measurements originate from the study of three problems in geodesy and astronomy, namely to determine the size and shape of the Earth, to explain the long-term inequality in the motions of Jupiter and Saturn, and to find a mathematical representation of the motions of the Moon. Nowadays, the methods of adjustment are used for a much greater variety of geodetic applications, ranging from, for instance, surveying and navigation to remote sensing and global positioning.

The two main reasons for performing redundant measurements are the wish to increase the accuracy of the results computed and the requirement to be able to check for errors. Due to the intrinsic uncertainty in measurements, measurement redundancy generally leads to an inconsistent system of equations. Without additional criteria, such a system of equations is not uniquely solvable. In this introductory course on adjustment theory, methods are developed and presented for solving inconsistent systems of equations. The leading principle is that of least-squares adjustment together with its statistical properties.

The inconsistent systems of equations can come in many different guises. They could be given in parametric form, in implicit form, or as a combination of these two forms. In each case the same principle of least-squares applies. The algorithmic realizations of the solution will differ however. Depending on the application at hand, one could also wish to choose between obtaining the solution in one single step or in a step-wise manner. This leads to the need of formulating the system of equations in partitioned form. Different partitions exist, measurement partitioning, parameter partitioning, or a partitioning of both measurements and parameters. The choice of partitioning also affects the algorithmic realization of the solution. In this introductory text the methodology of adjustment is emphasized, although various samples are given to illustrate the theory. The methods discussed form the basis for solving different adjustment problems in geodesy.

This course introduces the basic components of an airframe structure and discusses their use and limitations. The realities of composite design such as the effect of material scatter, environmental knockdowns, and damage knockdowns are discussed and guidelines accounting for these effects and leading to robust designs are presented.

The resulting design constraints and predictive tools are applied to real-life design problems in composite structures. A brief revision of lamination theory and failure criteria leads into the development of analytical solutions for typical failure modes for monolithic skins (layup strength, buckling under combined loads and for a variety of boundary conditions) and stiffeners (strength, column buckling under a variety of loads and boundary conditions, local buckling or crippling for one-edge and no-edge-free conditions). These are then combined into stiffened composite structures where additional failure modes such as skin-stiffener separation are considered. Analogous treatment of sandwich skins examines buckling, wrinkling, crimping, intra-cellular buckling failure modes. Once the basic analysis and design techniques have been presented, typical designs (e.g. flange layup, stiffness, taper requirements) are presented and a series of design guidelines (stiffness mismatch minimization, symmetric and balanced layups, 10% rule, etc.) addressing layup and geometry are discussed. On the metal side, the corresponding design practices and analysis methods are presented for the more important failure modes (buckling, crippling) and comparisons to composite designs are made. A design problem is given in the end as an application of the material in this Part of the course.

This course will focus for a large part on MOSFET and CMOS, but also on heterojunction BJT, and photonic devices.First non-ideal characteristics of MOSFETs will be discussed, like channel-length modulation and short-channel effects. We will also pay attention to threshold voltage modification by varying the dopant concentration. Further, MOS scaling will be discussed. A combination of an n-channel and p-channel MOSFET is used for CMOS devices that form the basis for current digital technology. The operation of a CMOS inverter will be explained. We will explain in more detail how the transfer characteristics relate to the CMOS design.

This course is about the electronic properties of materials and contains lectures about scattering, transport in metals, phonons and superconductivity.

This course is designed to introduce students who wish to specialize in stress analysis of thin-walled structures to more advanced topics such as the analysis of statically indeterminate structures, warping, constraint stresses, shear diffusion, and elements of plate bending.

How can you reduce the energy loss of your home? What is the underlying science of energy loss in pipes? Which heat and mass transfer problems do we have to tackle to make consumer products?

In this engineering course, you will learn about the engineering principles that play an important role in all of these and more phenomena. You will learn about microbalances, radiation, convection, diffusion and more and their applications in everyday life.

This advanced course is for engineers who want to refresh their knowledge, engineering students who are eager to learn more about heat/mass transport and for all who have fun in explaining the science of phenomena in nature.

Building on Complex Adaptive Systems theory and basic Agent Based Modeling knowledge presented in SPM4530, the Advanced course will focus on the model development process. The students are expected to conceptualize, develop and verify a model during the course, individually or in a group. The modeling tasks will be, as much as possible, based on real life research problems, formulated by various research groups from within and outside the faculty.
Study Goals The main goal of the course is to learn how to form a modeling question, perform a system decomposition, conceptualize and formalize the system elements, implement and verify the simulation and validate an Agent Based Model of a socio-technical system.

Our human society consists of many intertwined Large Scale Socio-Technical Systems (LSSTS), such as infrastructures, industrial networks, the financial systems etc. Environmental pressures created by these systems on Earth‰ŰŞs carrying capacity are leading to exhaustion of natural resources, loss of habitats and biodiversity, and are causing a resource and climate crisis. To avoid this sustainability crisis, we urgently need to transform our production and consumption patterns. Given that we, as inhabitants of this planet, are part of a complex and integrated global system, where and how should we begin this transformation? And how can we also ensure that our transformation efforts will lead to a sustainable world? LSSTS and the ecosystems that they are embedded in are known to be Complex Adaptive Systems (CAS). According to John Holland CAS are "...a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it will have to to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment" by many individual agents. Understanding Complex Adaptive Systems requires tools that themselves are complex to create and understand. Shalizi defines Agent Based Modeling as "An agent is a persistent thing which has some state we find worth representing, and which interacts with other agents, mutually modifying each other‰ŰŞs states. The components of an agent-based model are a collection of agents and their states, the rules governing the interactions of the agents and the environment within which they live." This course will explore the theory of CAS and their main properties. It will also teach you how to work with Agent Based Models in order to model and understand CAS.

"Air Safety Investigation – The Journey" is an introductory book that explores the world of air safety investigation. Unlike a how-to manual for investigating aviation accidents, this book focuses on the essential knowledge and mindset required to conduct a safety investigation. It covers the various phases of an investigation, from gathering facts to formulating safety recommendations, with each chapter addressing a different relevant aspect. With the increasing complexity of investigations, critical thinking, logic, and speculation are essential skills for investigators to possess. This book delves into these topics, offering thought-provoking examples and questions to address the challenges of drawing conclusions and obtaining positive investigative outcomes. Its aim is to help students and readers interested in air safety develop the necessary mindset and knowledge to conduct an investigation. By the end of the book, readers will gain a deeper understanding of the complexities involved in an air safety investigation.

This course treats various methods to design and analyze datastructures and algorithms for a wide range of problems. The most important new datastructure treated is the graph, and the general methods introduced are: greedy algorithms, divide and conquer, dynamic programming and network flow algorithms. These general methods are explained by a number of concrete examples, such as simple scheduling algorithms, Dijkstra, Ford-Fulkerson, minimum spanning tree, closest-pair-of-points, knapsack, and Bellman-Ford. Throughout this course there is significant attention to proving the correctness of the discussed algorithms. All material for this course is in English. The recorded lectures, however, are in Dutch.

An introductory course in analog circuit synthesis for microelectronic designers. Topics include: Review of analog design basics; linear and non-linear analog building blocks: harmonic oscillators, (static and dynamic) translinear circuits, wideband amplifiers, filters; physical layout for robust analog circuits; design of voltage sources ranging from simple voltage dividers to high-performance bandgaps, and current source implementations from a single resistor to high-quality references based on negative-feedback structures.