Electric power transmission systems are a key infrastructure, and blackouts of these systems have major consequences for the economy and national security. Analyses of blackout data suggest that blackout size distributions have a power law form over much of their range. This result is an indication that blackouts behave as a complex dynamical system. We use a simulation of an upgrading power transmission system to investigate how these complex system dynamics impact the assessment and mitigation of blackout risk. The mitigation of failures in complex systems needs to be approached with care. The mitigation efforts can move the system to a new dynamic equilibrium while remaining near criticality and preserving the power law region. Thus, while the absolute frequency of blackouts of all sizes may be reduced, the underlying forces can still cause the relative frequency of large blackouts to small blackouts to remain the same. Moreover, in some cases, efforts to mitigate small blackouts can even increase the frequency of large blackouts. This result occurs because the large and small blackouts are not mutually independent, but are strongly coupled by the complex dynamics.

Full cross section calculations of ion-temperature-gradient-driven turbulence with Landau closure are being carried out as part of the Numerical Tokamak Turbulence Project, one of the U. S. Department of Energy's Phase II Grand Challenges. To include the full cross section of a magnetic fusion device like the tokamak requires more memory and CPU time than is available on the National Energy Research Scientific Computing Center's (NERSC's) shared-memory vector machines such as the CRAY C90 and J90. Calculations of cylindrical multihelicity ion-temperature-gradient-driven turbulence were completed on NERSC's 160-processor distributed-memory CRAY T3E parallel computer with 256 Mbytes of memory per processor. This augurs well for yet more memory and CPU intensive calculations on the next-generation T3E at NERSC. This paper presents results on benchmarks with the current T3E at NERSC. Physics results pertaining to plasma confinement at the core of tokamaks subject to ion-temperature-gradient-driven-turbulence are also highlighted. Results at this resolution covering this extent of physical time were previously unattainable. Work is in progress to increase the resolution, improve the performance of the parallel code, and include toroidal geometry in these calculations in anticipation of the imminent arrival of a fully configured, 512-processor, T3E-900 model.

Significant improvements in real-time eficiency have been obtained for plasntajluid turbulence calculatwns by m"crotasking the nonlinear jlu"d co& KITE in which they are implemented on the CRAY Y-MP C90 at the National Energy Research Supercomputer Center (NERSC).The number of processors accessed concurrently scales linearly with problem size.Close to six concurrent processors have so far been obtained with a three-dimensional nonlinear production calculation at the currently allowed memory size of 80 Mword.With a calculation size corresponding to the maximum allowed memory of 200 Mword in the next system configuration, we expect to be able to access close to ten processors of the C90 concurrently with a commensurate improvement in realtime eficiency.These improvements in pe~ormance are comparable to those expected from a massively parallel implementation of the same calculations on the Intel Paragon.

One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchstone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchstone Delta machine, the corresponding improvement factor is 13. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel sigma machine gives an improvement factor close to 64 over the single-processor CRAY-2.>