The modern day K engine may be knock-down enough to shuttle travelers across a continent in just six hours but it ’s also unbearably loud — for both the primer coat crews that work around them and residents within hearing of airports . And while aircraft locomotive engineer are developing quieter conception , building and testing these quiet prototypes can incline into the six figures . But with the aid of Livermore National Labs ’ supercomputer and some clear - source modeling software , commercial airliners may before long be rustling quiet .
The 3,000 solid - animal foot Sequoia IBM Bluegene / Q supercomputer at Lawrence Livermore ( CA ) National Laboratories is among the most powerful parallel computing organization on the planet . It sports over 1.5 million embedded processors 1.6 PB of memory and crunches numbers at a staggering 16.32 PFLOPS . The Sequoia ’s cores are arranged in a 5D Torus design wherein each core is flat connected to ten others . This greatly reduces latency even with nub two and three connections away . Read / Write functions are handled by these processors as well — some of which tap directly to the system ’s primary remark / yield canal through an 11th connexion .
While all 1.5 million inwardness may be necessary to calculate the nuclear weapons pretending that it is normally charged with , Joseph Nichols ’ enquiry team from Stanford Engineering ’s Center for Turbulence Research harness just over a million of them for the jet locomotive engine research . They worked in conjunction with teams from the NASA Glenn Research Center in Ohio and the US Navy’sNAVAIRto develop a quieter cat valium engine without actually having to build one .
“ These runs represent at least an order - of - magnitude increase in computational power over the largest simulations do at the Center for Turbulence Research antecedently , ” pronounce Nichols “ The implications for prognosticative science are judgement - boggling . ”
The technique is roll in the hay as prognostic modeling and it is an take cognitive operation . The noise that a jet engine create constitutes less than one percent of the machine ’s entire energy output , which means that accurately reproduce them in Computational fluid dynamic ( CFD ) simulation requires incredibly exact calculations .
“ Computational fluid dynamics ( CFD ) pretending , like the one Nichols solved , are incredibly complex . Only recently , with the coming of monumental supercomputers boasting hundreds of 1000 of computer science pith , have engineers been able to pattern jet plane engines and the noise they produce with accuracy and velocity , ” said Parviz Moin , the Franklin M. and Caroline P. Johnson Professor in the School of Engineering and Director of the CTR distinguish Wired .
Up next — predictive modelling of which far - flung airport your baggage will wrongly arrive at .
[ R&D – CTR – Wired – Stanford – Image : Lawrence Livermore National Laboratories ]
stanford
Daily Newsletter
Get the best technical school , science , and culture tidings in your inbox day by day .
News from the future , deliver to your nowadays .
Please select your desired newssheet and submit your e-mail to elevate your inbox .
You May Also Like
