Risk, Safety and Large-Scale Systems Analysis

Basic research includes:

• the development of deterministic models and the acquisition of experimental data for understanding severe accidents in nuclear power reactors
• probabilistic methods and models for assessing nuclear power plant risk
• optimization methods that integrate mechanistic and probabilistic considerations.

Historically, these methods and models focused on complicated systems or machines composed of pumps, valves, invertors, switches, piping, electronic control systems, instrumentation, etc. These systems are amenable to reductionism because second-order effects are small (can be treated in a linear fashion) and the boundaries are well defined. Safety considerations involved standard mechanistic models for heat transfer, fluid  dynamics and material behavior, as well as accepted reliability methods such as fault and event trees. These complicated systems have now given way to very large-scale complex systems, in which second order or nonlinear effects become important, and the boundaries are less well defined. By large-scale, we mean systems with large dimensionality (or very  many variables), and not necessarily large spatially. Such complex systems may exhibit
chaotic behavior, may be tightly coupled and exhibit emergent properties, and may exhibit properties that can only be described subjectively.

An initial focus for this new avenue of research is Generation IV nuclear energy systems,  which integrates the nuclear fuel cycle in terms of high-level radioactive waste disposal, nuclear reactor safety, overall fuel cycle analysis and economics, safeguards and security.
Other complex large-scale systems considered in this program include biological systems,  environmental and ecological systems, information systems and electric power distribution systems.  Participating in this work is Professor Kammen.

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• Faculty whose research and teaching involves Risk
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