Introduction to seismic theory, measurements and processing of seismic data to final focussed image for geological and/or physical interpretation.This course deals with the most important aspects of reflection seismics. Theory of seismic waves, aspects of data acquisition (seismic sources, receivers and recorders), and of data processing (CMP processing, velocity analysis, stacking, migration) will be dealt with. The course will be supplemented by a practical of 6 afternoons where the students will see the most important data-processing steps via exercises (in Matlab).
Groningen, a province in the northeast of the Netherlands, is experiencing earthquakes due to the extraction of gas. This phenomenon is called induced seismicity. But what is induced seismicity? And how can the risk to life safety and the consequences for the built environment be reduced? The Groningen situation is unique and for this reason, solutions for the built environment cannot simply be copied from abroad. To contribute to a basic understanding of the various topics in this field, knowledge lectures have been developed as Open Course Ware by a large number of scientists and practitioners.
This Open Course Ware is initiated by TU Delft in cooperation with Arup, TU Eindhoven and TNO. This public and private initiative combines engineering, architecture and management perspectives. The 30 video lectures provide conceptual knowledge of seismicity and basic seismic concepts. This knowledge is then related to the different structures and their behaviour under seismic loading. Finally, in the last theme more procedural knowledge will be outlined, related to the multidisciplinary challenges in Groningen.
Water is essential for life on earth and of crucial importance for society. Also within our climate water plays a major role. The natural cycle of ocean to atmosphere, by precipitation back to earth and by rivers and aquifers to the oceans has a decisive impact on regional and global climate patterns.
This course will cover six main topics:
Global water cycle. In this module you will learn to explain the different processes of the global water cycle.
Water systems. In this module you will learn to describe the flows of water and sand in different riverine, coastal and ocean systems.
Water and climate change. In this module you will learn to identify mechanisms of climate change and you will learn to explain the interplay of climate change, sea level, clouds, rainfall and future weather.
Interventions. In this module you will learn to explain why, when and which engineering interventions are needed in rivers, coast and urban environment.
Water resource management. In this module you will learn to explain why water for food and water for cities are the main challenges in water management and what the possibilities and limitations of reservoirs and groundwater are to improve water availability.
Challenges. In this module you will learn to explain the challenges in better understanding and adapting to the impact of climate change on water for the coming 50 years.
- Applied Science
- Environmental Science
- Material Type:
- Full Course
- Delft University of Technology
- Provider Set:
- Delft University OpenCourseWare
- Prof.dr. Nick van de Giesen
- Prof.dr.ir. Herman Russchenberg
- Prof.dr.ir. Hubert Savenije
- Prof.dr.ir. Marcel Stive
- Date Added:
The course will discuss the objectives and functions of water management systems for irrigation and drainage purposes. Analysing system requirements in terms of technical engineering constraints, management possibilities and water users (wishes and options) is central. This includes the design and operation of regulation structures, dams, reservoirs, weirs and conveyance systems; balancing water supply and water requirements in time and space is a main focus of analysis too.
Many of today’s global challenges require tech-driven solutions — climate change, the growth of the world population, cyber security, the increasing demand for scarce resources, digitalization, the transition from fossil fuels to renewable energy. With this in mind, it is no surprise that one fourth of the CEOs of the world’s 100 largest corporations have an engineering degree.
Solving these global problems requires leaders who, in the first place, are comfortable with technology, models and quantitative analyses — Leaders who see systems instead of isolated problems. However, simply understanding technology is not enough. Successful leaders today must have both the ideas and the know-how to put these ideas into action by working collaboratively with others, winning their hearts and minds.
We need leaders who know how to seize opportunities in a networked world, and can mobilize people and other stakeholders for large-scale change. Leaders who lead fulfilling lives and who are able to move themselves and others from the ‘me’ to the ‘we’. Leaders who are long-term oriented and who deliver economic profit, while also making positive contributions to society and the environment. We call these leaders ‘sustainable leaders’.
Runway extension, construction of works in protected areas, subsidizing sustainable projects... they all happen within a design space, limited amongst others by legal rules and requirements. To make optimal use of the design space, you have to know about these rules and requirements. When does a contract have to be tendered out, what rules are then applicable, what can be subsidized and what are the restrictions, how to comply with air quality requirements and can a frog really block a project? What alternative designs can be given in order to avoid legal problems? These and other problems will be addressed in this course.
The course linear modeling delivers the skillset in linear or structural modeling that is required to solve structural problems from which you can develop finite element (FE) models for practical applications. It also teaches how results can be correctly interpreted. The course uses an open source FE package in a series of weekly practical sessions where models are constructed for sample problems and results are validated against simplified analytical models or open literature.
Mathematics explained: Here you find videos on various math topics:
Pre-university Calculus (functions, equations, differentiation and integration)
Vector calculus (preparation for mechanics and dynamics courses)
Differential equations, Calculus
Functions of several variables, Calculus
Probability and Statistics
How do populations grow? How do viruses spread? What is the trajectory of a glider?
Many real-life problems can be described and solved by mathematical models. In this course, you will form a team with another student and work in a project to solve a real-life problem.
You will learn to analyze your chosen problem, formulate it as a mathematical model (containing ordinary differential equations), solve the equations in the model, and validate your results. You will learn how to implement Euler’s method in a Python program.
If needed, you can refine or improve your model, based on your first results. Finally, you will learn how to report your findings in a scientific way.
This course is mainly aimed at Bachelor students from Mathematics, Engineering and Science disciplines. However it will suit anyone who would like to learn how mathematical modeling can solve real-world problems.
This course is an introduction to measurement technology and describes the theoretical foundations and practical examples of measurement systems. The analyzing of measurements problems and specifying of measurements systems are the main subjects that are treated in this course, where the main focus will be on the different kind of measurement errors and the concept of uncertainty in measurement results. Electronic measurement instrumentation will be introduced; a number of conventional sensors for the measurement of non-electronic variables will be described, as well as electronic circuits for the reading of the sensors.-Analyzing of measurement problems-Describing of measurement problems -Analyzing the measurement quantity-Analyzing the measurement boundaries for a quantity to be measured in different circumstances-Professional use of the measurement system-Describing the operating principle of conventional instruments for electronic measurements.-Comparing the available measurement instruments on the basis of quality and accuracy.-Realization of simple measurement setups.-Using the electronic sensor for the measurement of non-electronic variables.-Using a simple signal processing circuits for the reading of the sensors.-Analyzing, presenting and interpreting of measurement results;-Recognizing and describing of error sources.
Mechatronic system design deals with the design of controlled motion systems by the integration of functional elements from a multitude of disciplines. It starts with thinking how the required function can be realised by the combination of different subsystems according to a Systems Engineering approach (V-model).
Some supporting disciplines, like power-electronics and electromechanics, are not part of the BSc program of mechanical engineers. For this reason this course introduces these disciplines in connection with PID-motion control principles to realise an optimally designed motion system.
The target application for the lectures are motion systems that combine high speed movements with extreme precision.
The course covers the following four main subjects:
Dynamics of motion systems in the time and frequency domain, including analytical frequency transfer functions that are represented in Bode and Nyquist plots.
Motion control with PID-feedback and model-based feed forward control-principles that effectively deal with the mechanical dynamic anomalies of the plant.
Electromechanical actuators, mainly based on the electromagnetic Lorentz principle. Reluctance force and piezoelectric actuators will be shortly presented to complete the overview.
Power electronics that are used for driving electromagnetic actuators.
The fifth relevant discipline, position measurement systems is dealt with in another course: WB2303, Electronics and measurement.
The most important educational element that will be addressed is the necessary knowledge of the physical phenomena that act on motion systems, to be able to critically judge results obtained with simulation software.
The lectures challenge the capability of students to match simulation models with reality, to translate a real system into a sufficiently simplified dynamic model and use the derived dynamic properties to design a suitable, practically realiseable controller.
This course increases the understanding what a position control system does in reality in terms of virtual mechanical properties like stiffness and damping that are added to the mechanical plant by a closed loop feedback controller.
It is shown how a motion system can be analysed and modelled top-down with approximating (scalar) calculations by hand, giving a sufficient feel of the problem to make valuable concept design decisions in an early stage.
With this method students learn to work more efficiently by starting their design with a quick and dirty global analysis to prove feasibility or direct further detailed modelling in specific problem areas.
Mesoscopic physics is the area of Solid State physics that covers the transition regime between macroscopic objects and the microscopic, atomic world. The main goal of the course is to introduce the physical concepts underlying the phenomena in this field.
System design is the central topic of this course. We move beyond the methods developed in circuit design (although we shall have interest in those) and consider situations in which the functional behavior of a system is the first object under consideration.
Modelling is about understanding the nature: our world, ourselves and our work. Everything that we observe has a cause (typically several) and has the effect thereof. The heart of modelling lies in identifying, understanding and quantifying these cause-and-effect relationships.
A model can be treated as a (selective) representation of a system. We create the model by defining a mapping from the system space to the model space, thus we can map system state and behaviour to model state and behaviour. By defining the inverse mapping, we may map results from the study of the model back to the system. In this course, using an overarching modelling paradigm, students will become familiar with several instances of modelling, e.g., mechanics, thermal dynamics, fluid mechanics, etc.
Infrastructures for energy, water, transport, information and communications services create the conditions for livability and economic development. They are the backbone of our society. Similar to our arteries and neural systems that sustain our human bodies, most people however take infrastructures for granted. That is, until they break down or service levels go down.
In many countries around the globe infrastructures are ageing. They require substantial investments to meet the challenges of increasing population, urbanization, resource scarcity, congestion, pollution, and so on. Infrastructures are vulnerable to extreme weather events, and therewith to climate change.
Technological innovations, such as new technologies to harvest renewable energy, are one part of the solution. The other part comes from infrastructure restructuring. Market design and regulation, for example, have a high impact on the functioning and performance of infrastructures.
The course describes in a simple and practical way what non-equilibrium thermodynamics is and how it can contribute to engineering fields. It explains how to derive proper equations of transport from the second law of thermodynamics or the entropy production. The obtained equations are frequently more precise than used so far, and can be used to understand the waste of energy resources in central process units in the industry. The entropy balance is used to define the energy efficiency in energy conversion and create consistent thermodynamic models. It also provides a systematic method for minimizing energy losses that are connected with transport of heat, mass, charge and momentum. The entropy balance examines operation at the state of minimum entropy production and is used to propose some rules of design for energy efficient operation. For this course some knowledge of engineering thermodynamics is a prerequisite. The first and second law of thermodynamics and terms as entropy should be known before starting this course.
Non-Linear Structural Modeling covers the basics of non-linearities in the Finite Element Method (FEM), considering static and stability (buckling) analyses, and practical application thereof applied to both aerospace and non-aerospace examples. Special emphasis is put on the implementation of these non-linearities in a FEM model and any issues that might arise from incorporating these
Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.
TU Delft’s approach to observation theory is world leading and based on decades of experience in research and teaching in geodesy and the wider geosciences. The theory, however, can be applied to all the engineering sciences where measurements are used to estimate unknown parameters.
The course introduces a standardized approach for parameter estimation, using a functional model (relating the observations to the unknown parameters) and a stochastic model (describing the quality of the observations). Using the concepts of least squares and best linear unbiased estimation (BLUE), parameters are estimated and analyzed in terms of precision and significance.
The course ends with the concept of overall model test, to check the validity of the parameter estimation results using hypothesis testing. Emphasis is given to develop a standardized way to deal with estimation problems. Most of the course effort will be on examples and exercises from different engineering disciplines, especially in the domain of Earth Sciences.
This course is aimed towards Engineering and Earth Sciences students at Bachelor’s, Master’s and postgraduate level.
Part 2 of offshore hydromechanics (OE4630) involves the linear theory of calculating 1st order motions of floating structures in waves and all relevant subjects such as the concept of RAOs, response spectra and downtime/workability analysis.
Offshore Hydromechanics includes the following modules:1. Hydrostatics, static floating stability, constant 2-D potential flow of ideal fluids, and flows in real fluids. Introduction to resistance and propulsion of ships. Review of linear regular and irregular wave theory. 2. Analytical and numerical means to determine the flow around, forces on, and motions of floating bodies in waves. 3. Higher order potential theory and inclusion of non-linear effects in ship motions. Applications to motion of moored ships and to the determination of workability. 4. Interaction between the sea and sea bottom as well as the hydrodynamic forces and especially survival loads on slender structures.