LEADER 01962nam 2200481 450 001 9910703860303321 005 20150715153515.0 035 $a(CKB)5470000002435127 035 $a(OCoLC)913834877 035 $a(EXLCZ)995470000002435127 100 $a20150715j198501 ua 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSpace shuttle orbiter trimmed center-of-gravity extension study$hVolume ix$iEffects of configuration modifications on the aerodynamic characteristics of the 140 A/B orbiter at mach numbers of 1.5, 2.0, and 2.5 /$fW. Pelham Phillips and Roger H. Fournier 210 1$aHampton, Virginia :$cNational Aeronautics and Space Administration, Langley Research Center,$dJanuary1985. 215 $a1 online resource (97 pages) $cillustrations 225 1 $aNASA technical memorandum ;$v72661. vol. IX 300 $aTitle from title screen (viewed July 15, 2015). 300 $a"January1985." 320 $aIncludes bibliographical references (pages 10-11). 517 3 $aEffects of configuration modifications on the aerodynamic characteristics of the 140 A/B orbiter at mach numbers of 1.5, 2.0, and 2.5 606 $aAerodynamic characteristics$2nasat 606 $aCenter of gravity$2nasat 606 $aSpace Shuttle orbiters$2nasat 606 $aWind tunnel tests$2nasat 606 $aCanard configurations$2nasat 615 7$aAerodynamic characteristics. 615 7$aCenter of gravity. 615 7$aSpace Shuttle orbiters. 615 7$aWind tunnel tests. 615 7$aCanard configurations. 700 $aPhillips$b W. Pelham$01416408 702 $aFournier$b Roger H. 712 02$aLangley Research Center, 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910703860303321 996 $aSpace shuttle orbiter trimmed center-of-gravity extension study$93521649 997 $aUNINA LEADER 01812nam 2200421z- 450 001 9910634082603321 005 20221206 010 $a1000144792 035 $a(CKB)5840000000218142 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/94466 035 $a(oapen)doab94466 035 $a(EXLCZ)995840000000218142 100 $a20202212d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDistributed Optimization with Application to Power Systems and Control 210 $aKarlsruhe$cKIT Scientific Publishing$d2022 215 $a1 online resource (226 p.) 311 08$a3-7315-1180-0 330 $aMathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized-all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization. 606 $aMaths for computer scientists$2bicssc 610 $aADMM 610 $aALADIN 610 $adecentralized optimization 610 $aDezentrale Optimierung 610 $adistributed optimization 610 $aoptimal power flow 610 $aOptimal Power Flow 610 $aVerteilte Optimierung 615 7$aMaths for computer scientists 700 $aEngelmann$b Alexander$4auth$01285816 906 $aBOOK 912 $a9910634082603321 996 $aDistributed Optimization with Application to Power Systems and Control$93019660 997 $aUNINA