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MOOC
Humanity faces an immense challenge: providing abundant energy to everyone without wrecking the planet. If we want a high-energy future while protecting the natural world for our children, we must consider the environmental consequences of energy production and use. But money matters too: energy solutions that ignore economic costs are not realistic, particularly in a world where billions of people currently can’t afford access to basic energy services. How can we proceed? Energy Within Environmental Constraints won’t give you the answer. Instead, we will teach you how to ask the right questions and estimate the consequences of different choices. This course is rich in details of real devices and light on theory. You won’t find any electrodynamics here, but you will find enough about modern commercial solar panels to estimate if they would be profitable to install in a given location. We emphasizes costs: the cascade of capital and operating costs from energy extraction all the way through end uses. We also emphasize quantitative comparisons and tradeoffs: how much more expensive is electricity from solar panels than from coal plants, and how much pollution does it prevent? Is solar power as cost-effective an environmental investment as nuclear power or energy efficiency? And how do we include considerations other than cost? This course is intended for a diverse audience. Whether you are a student, an activist, a policymaker, a business owner, or a concerned citizen, this course will help you start to think carefully about our current energy system and how we can improve its environmental performance.
- Subjects:
- Environmental Engineering, Building Services Engineering, and Building and Real Estate
- Keywords:
- Environmental protection Environmental management Renewable energy sources Power resources
- Resource Type:
- MOOC
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Others
Create interactive maps, and discover patterns in geospatial data.
- Subjects:
- Land Surveying and Geo-Informatics and Computing
- Keywords:
- Geospatial data Python (Computer program language)
- Resource Type:
- Others
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Others
Discover the most effective way to improve your models.
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Python (Computer program language)
- Resource Type:
- Others
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Others
Solve short hands-on challenges to perfect your data manipulation skills.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Electronic data processing Information visualization
- Resource Type:
- Others
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Courseware
The course “Fluid Flow, Heat and Mass Transfer,” course number ta3220, is third-year BSc course in the program of Applied Earth Sciences at Delft University of Technology. Students in this class have already taken a course in “Transport Phenomena” in the second year, and “Fluid Flow Heat and Mass Transfer” is designed as a follow-up to that class, with an emphasis on topics of importance in applied earth sciences, and in particular to Petroleum Engineering, groundwater flow and mining. In practice, however I start over again with first principles with this class, because the initial concepts of the shell balance are difficult for students to grasp and can always use a second time through. The course covers simple fluid mechanics problems (rectilinear flow) using shell balances, for Newtonian and power-law fluids and Bingham plastics. Turbulence for Newtonian fluids is covered in the context of friction factors for flow in pipes, flow around spheres and flow in packed beds. In heat transfer we start again with shell balances for solving simple steady-state conduction problems. Thereafter, special attention is given to unsteady and multidimensional heat conduction, since the equations are similar for unsteady flow in aquifers and petroleum reservoirs. The concepts of orthogonal conduction and superposition are emphasized, as well as ways to treat perfectly insulated boundaries. The final topic in heat transfer is estimation of heat-transfer coefficients in flow in tubes. Although no other geometries are treated explicitly, I hope students recognize certain principles they can apply to other situations. We cover mass transfer only lightly, and only as by analogy to heat conduction: unsteady diffusion (by analogy to unsteady head conduction) and mass transfer in tubes (by analogy to heat transfer in tubes).
- Subjects:
- Land Surveying and Geo-Informatics
- Keywords:
- Heat -- Transmission Mass transfer Fluid mechanics
- Resource Type:
- Courseware
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Courseware
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).
- Subjects:
- Land Surveying and Geo-Informatics and Disaster Control and Management
- Keywords:
- Seismic prospecting Seismometry Earthquakes Seismic reflection method
- Resource Type:
- Courseware
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Courseware
Basic principles: Hydrostatics, constant flow phenomena and waves The treated theory includes: - Archimedes’ Law, hydrostatic pressure - Stability computations for floating structures – including the effect of shifting loads, and partially filled fluid tanks - Potential flow basics, 2D potential flow elements, superposition principle - Real (viscous) flows, scaling laws, flow regimes - Fluid forces on structures, drag and lift, resistance and propulsion, wind and current loads - Linear wave theory in regular and irregular waves and wave statistics
- Subjects:
- Hydraulic Engineering
- Keywords:
- Offshore structures -- Hydrodynamics Hydrodynamics Hydrostatics Fluid mechanics Waves
- Resource Type:
- Courseware
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MOOC
The building industry is exploding with data sources that impact the energy performance of the built environment and health and well-being of occupants. Spreadsheets just don’t cut it anymore as the sole analytics tool for professionals in this field. Participating in mainstream data science courses might provide skills such as programming and statistics, however the applied context to buildings is missing, which is the most important part for beginners. This course focuses on the development of data science skills for professionals specifically in the built environment sector. It targets architects, engineers, construction and facilities managers with little or no previous programming experience. An introduction to data science skills is given in the context of the building life cycle phases. Participants will use large, open data sets from the design, construction, and operations of buildings to learn and practice data science techniques. Essentially this course is designed to add new tools and skills to supplement spreadsheets. Major technical topics include data loading, processing, visualization, and basic machine learning using the Python programming language, the Pandas data analytics and sci-kit learn machine learning libraries, and the web-based Colaboratory environment. In addition, the course will provide numerous learning paths for various built environment-related tasks to facilitate further growth.
- Keywords:
- City planning -- Statistical methods Python (Computer program language) Information visualization
- Resource Type:
- MOOC
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MOOC
In this course, we will introduce you to the fundamentals of sensor fusion for automotive systems. Key concepts involve Bayesian statistics and how to recursively estimate parameters of interest using a range of different sensors. The course is designed for students who seek to gain a solid understanding of Bayesian statistics and how to use it to fuse information from different sensors. We emphasize object positioning problems, but the studied techniques are applicable much more generally. The course contains a series of videos, quizzes and hand-on assignments where you get to implement many of the key techniques and build your own sensor fusion toolbox. The course is self-contained, but we highly recommend that you also take the course ChM015x: Multi-target Tracking for Automotive Systems. Together, these courses give you an excellent foundation to tackle advanced problems related to perceiving the traffic situation around an autonomous vehicle using observations from a variety of different sensors, such as, radar, lidar and camera.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Automobiles -- Electronic equipment Automotive sensors
- Resource Type:
- MOOC
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MOOC
Why are hybrid vehicles still more common than battery electric ones? Why are electric vehicles still more expensive than conventional or hybrid ones? In this course, you will get the answers to this and much more. While electric motors can improve vehicles regarding performance, energy consumption and emissions, they suffer from high cost and weight of batteries. Smart combinations of electric motors and combustion engines in a hybrid powertrain can combine these strengths with the advantages of combustion engines. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge about hybridpowertrains. Inthis course, we willexamine different mechanical layouts of hybrid powertrains and how they influence the performance and complexity of the powertrain. Different sizing of powertrains in micro, mild, full hybrids, as well as plug-in hybrids, is also discussed and you'll learn how they can be modelled and analyzed for example by simulation of driving cycles. You will also learn about the Energy Management system and how this controls the hybrid powertrain modes and when to charge and discharge the battery. As a result of support from MathWorks, students will be granted access to MATLAB/Simulink for the duration of the course.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Electric vehicles Hybrid electric vehicles
- Resource Type:
- MOOC