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Problem solving
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Courseware
This course focuses on national environmental and energy policy-making; environmental ethics; the techniques of environmental analysis; and strategies for collaborative environmental decision-making. The primary objective of the course is to help students formulate a personal theory of environmental planning practice. The course is taught comparatively, with constant references to examples from around the world. It is required of all graduate students pursuing an environmental policy and planning specialization in the Department of Urban Studies and Planning at MIT. This course is the first subject in the Environmental Policy and Planning sequence. It reviews philosophical debates including growth vs. deep ecology, "command-and-control" vs. market-oriented approaches to regulation, and the importance of expertise vs. indigenous knowledge. Emphasis is placed on environmental planning techniques and strategies. Related topics include the management of sustainability, the politics of ecosystem management, environmental governance and the changing role of civil society, ecological economics, integrated assessment (combining environmental impact assessment (EIA) and risk assessment), joint fact finding in science-intensive policy disputes, environmental justice in poor communities of color, and environmental dispute resolution. Environmental Problem-Solving (Susskind et. al, 2017, Anthem Press), a video-enhanced eBook, provides students with full access to all the assigned readings, faculty commentary on the readings, and examples of the best student performance on course assignments in previous years.
- Subjects:
- Environmental Policy and Planning
- Keywords:
- Environmental protection Environmental policy
- Resource Type:
- Courseware
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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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MOOC
In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles. This course will teach you the fundamental mathematical model for many of these real-world problems. Key topics include Markov decision process, reinforcement learning and event-based methods as well as the modelling and solving of decision-making for autonomous systems. This course is aimed at learners with a bachelor's degree or engineers in the automotive industry who need to develop their knowledge in decision-making models for autonomous systems. Enhance your decision-making skills in automotive engineering by learning from Chalmers, one of the top engineering schools that distinguished through its close collaboration with industry.
- Subjects:
- Electrical Engineering, Mechanical Engineering, and Transportation
- Keywords:
- Decision making Automobiles -- Design construction Automated vehicles
- Resource Type:
- MOOC