High Performance Computing
[Due to the increasing size of the archives, each topic page now contains only the prior 365 days of content. Access to older stories is now solely through the Monthly Archive pages or the site search function.]
GE using Large Eddy Simulation on Sandia’s Red Mesa to lay groundwork for quieter wind turbine blades with better power yield
August 15, 2013
|Transition of flow to turbulence on a wind-turbine airfoil; isosurfaces of vorticity from a Large Eddy Simulation (LES). Credit: GE Global Research. Click to enlarge.|
GE Global Research, the technology development arm of the General Electric Company, recently completed a research project in partnership with Sandia National Laboratories that could significantly affect the design—and thus the noise and power output—of future wind turbine blades.
A 1 decibel quieter rotor design would result in a 2% increase in annual energy yield per turbine. With approximately 240 GW of new wind installations forecasted globally over the next five years, a 2% increase would create 5 GW of additional wind power capacity—enough to power every household in New York City, Boston, and Los Angeles, combined, GE Research noted.
Reaction Design introduces model fuel library resulting from work of Model Fuels Consortium
November 14, 2012
|Good fuel models are required for good predictions. Left: modeling using a reduced n-heptane model (34 chemical types) vs. data. Right: mofe accurate n-heptane model (174 chemical types) vs. data. Source: Reaction Design. Click to enlarge.|
Reaction Design is introducing the first volume of the industry’s most well-validated available Model Fuel Library, the result of seven years of research and validation under the Model Fuels Consortium (earlier post). MFC members included Toyota, GE Energy, VW, Suzuki, Petrobras and Conoco. The MFC is ending its work in December.
The Model Fuel Library is a subscription-based library which includes more than 40 fully validated, self-consistent components that can be used to simulate fuel effects in virtually all types of automotive and aircraft engines, as well as engines used for electric power generation. The components can be combined to model a large variety of new or existing fuel blends.
Cray unveils 100 petaflop XC30 supercomputer
November 08, 2012
|Cray XC30. Click to enlarge.|
Cray Inc. launched its next-generation high-end supercomputing system: the Cray XC30 supercomputer. Previously code-named “Cascade,” the Cray XC30 supercomputer combines the new Aries interconnect, Intel Xeon processors, Cray’s fully-integrated software environment, and innovative power and cooling technologies to create a production supercomputer that is designed to scale high performance computing (HPC) workloads of more than 100 petaflops.
The US Department of Energy’s (DOE) Oak Ridge National Laboratory recently launched its new 20 petaflop supercomputer, Titan—a hybrid-architecture Cray XK6 system. (Earlier post.)
High Performance Computing key enabler for accelerating development of high efficiency engines
November 05, 2012
|Increasing complexity of vehicle design is driving the need for better simulation and more powerful computers. Wagner and Pannala. Click to enlarge.|
The complexity of new and future vehicles—driven by the need for increasing fuel efficiency and decreasing emissions with ever-changing drive-cycle demands and environmental conditions—is adding unprecedented flexibility in design and driving the need for better simulation and more powerful computers, observed Dr. Robert M. Wagner, Director of the Fuels Engines and Emissions Research Center, and Dr. Sreekanth Pannala, Senior Research Staff Member in the Computing and Computational Sciences Directorate at Oak Ridge National Laboratory in a keynote talk at the recent Global Powertrain Conference.
Advances in high performance computing (HPC) resources are leading to a new frontier in engine and vehicle development, Wagner and Pannala suggested, including the ability to produce detailed simulations to generate benchmark data; engineering simulations to explore the design space (e.g., injector optimization at ORNL); and reduced models for design optimization and control strategies. In general, HPC can help solve problems which were once thought unsolvable, they noted.