PPT-Gyrokinetic simulation of electron turbulence spectrum

Chika Kawai 12 Shinya Maeyama 2 Yasuhiro Idomura 2 Yuichi Ogawa 1 1 GSFSUniv Tokyo 2JAEA This work was carried out using the HELIOS supercomputer system at Computational Simulation Centre of International Fusion Energy Research Centre IFERCCSC Aomori Japan under the Broader Approach collaboration between . Superfluid. . 4. He in the . T . = 0 Limit. Andrei . Golov. Paul . Walmsley. , Sasha . Levchenko. , Joe . Vinen. , Henry Hall, . Peter . Tompsett. , Dmitry . Zmeev. , . Fatemeh. . Pakpour. , Matt Fear. Katherine McCaffrey. PhD Candidate, Fox-Kemper Research Group. Department of Atmospheric and Oceanic Sciences. Cooperative Institute for Research in Environmental Sciences. 1. Thank you to my advisor and collaborators:. A. Najmi – University of Maryland. B. . Eliasson. – University of . StrathClyde. X. Shao, G. . Milikh. , S. Sharma, K. Papadopoulos – University of Maryland. Introduction. Observation of DAILs (Descending Artificial Ionized Layers) (Pedersen et al 2009, 2011). local winds. Scales of Atmospheric Motion vs. Lifespan. We’ve already started to investigate some of the synoptic-scale features…. Topics for today’s discussion. Basically here’s our roadmap for the rest of the course.. CSDMS Annual Meeting 2016: Capturing Climate Change (May 17-19, 2016). Zhen Cheng. 1. (Charlie. ), . Tian-Jian. . Hsu. 1. . (Tom. ), . Julien. Chauchat. 2. ,. . Thibaud. Revil-. Baudard. 3. 1. University of Delaware, Newark, DE, 19716, USA. in a Developing Turbulence. . Shuichi M. ATSUKIYO. . ESST Kyushu Univ.. Collaborator : T. . Hada. Outline . Background. -- motivation. -- acceleration processes in turbulent plasmas. -- parametric instability (PI). Pawel. . Artymowicz. U of Toronto. MRI turbulence. Some non-MRI turbulence. Roles and the dangers of turbulence. UCSC Santa Cruz 2010. I borrowed some . figures & slides from. X. Wu (2004). R. Nelson (2008). Bas van de . Wiel. , . Ivo. van . Hooijdonk. & Judith . Donda. in collaboration with:. Fred . Bosveld. , Peter Baas, . Arnold . Moene. , Harm . Jonker. , . Jielun. Sun, Herman Clercx, . e.a. .. Rick Curtis. Southwest Airlines Meteorology. ADF – 10/9/18. Turbulence Issues. Many Causes. CAT. Mountain Wave. Convection. Wake. Thermal. Difficult to Forecast. Difficult to Verify. Quiz. Question 1:. in Arbitrary Domains. Lasse Gilling and Søren R. K. Nielsen. Department of Civil Engineering, Aalborg University, Denmark. Niels N. Sørensen. National Laboratory for Sustainable Energy, Risø-DTU, Denmark. Siming. Liu. University of Glasgow. Collaborators. Vahe. ’ . Petrosian. , . Yanwei. Jiang: Stanford University. Zhonghui. Fan: Yunnan University. Oct. 2008 Krakow, Poland . Outline. I: Observations: Distribution. S. Ku et al.. A fast edge turbulence bifurcation achieved in XGC1 when heat accumulation ~P. L-H. in the edge layer. in an L-mode diverted C-Mod edge geometry. with neutral particle recycling (R=0.99). Katya Vashchankova, Head, IATA MET Program. Turbulence Impact Mitigation Workshop, 2018. Flight Operations Efficiency. . Flight Operations Efficiency. . Flight Operations Efficiency. . All 3 aircraft will hit the same turbulence because the data is too often not shared by ATC, nor between airlines or different solution providers. Yang . Ren. Walter Guttenfelder. Gregory W. Hammett. for the NSTX-U Research Team. NSTX-U PAC-33 Meeting. PPPL – B318. February 19-21, 2013. NSTX-U. Supported by . Culham Sci Ctr. York U. Chubu U.