Field-data-based validation of an aero-servo-elastic solver for high-fidelity large-eddy simulations of industrial wind turbines

Autor: E. Muller, S. Gremmo, F. Houtin-Mongrolle, B. Duboc, P. Bénard

Publikováno v: Wind Energy Science, Vol 9, Pp 25-48 (2024)

To design the next generations of wind turbines, engineers from the wind energy industry must now have access to new numerical tools, allowing the high-fidelity simulation of complex physical phenomena and thus a further calibration of lower-order mo

Externí odkaz: https://doaj.org/article/a2d46d56bbe1455fafb36194413ce685

The hidden role of dissolved organic carbon in the biogeochemical cycle of carbon in modern redox-stratified lakes

Autor: R. Havas, C. Thomazo, M. Iniesto, D. Jézéquel, D. Moreira, R. Tavera, J. Caumartin, E. Muller, P. López-García, K. Benzerara

Publikováno v: Biogeosciences, Vol 20, Pp 2405-2424 (2023)

The dissolved organic carbon (DOC) reservoir plays a critical role in the C cycle of marine and freshwater environments because of its size and implication in many biogeochemical reactions. Although it is poorly constrained, its importance in ancient

Externí odkaz: https://doaj.org/article/d96a8af4380545aa95ee35cc3dbc568b

Gastrointestinal symptoms in HIV-positive kidney transplant candidates and recipients from an HIV-positive donor

Autor: C. J. Martin, F. J. Veldman, D. Labadarios, Z. Ebrahim, E. Muller, S. M. Kassier

Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)

Abstract Gastrointestinal symptoms (GIS) are common in kidney transplant candidates and recipients and may be worsened by HIV. Objective: To determine the frequency and severity of GIS in HIV-positive kidney transplant recipients from HIV-positive do

Externí odkaz: https://doaj.org/article/6b1ac5ecc1c346aa856f600dd4bd2457

Codeposition of ultrasmooth and high quantum efficiency cesium telluride photocathodes

Autor: M. Gaowei, J. Sinsheimer, D. Strom, J. Xie, J. Cen, J. Walsh, E. Muller, J. Smedley

Publikováno v: Physical Review Accelerators and Beams, Vol 22, Iss 7, p 073401 (2019)

Cesium telluride (CsTe) photocathodes have been the primary choice for electron sources by worldwide accelerators, due to their high quantum yield, stable performance in complex operation environments and long lifetime. In this paper we compared the

Externí odkaz: https://doaj.org/article/3fc677ffc6af492da06bd94fbd774d95

Applications and Techniques for Fast Machine Learning in Science

Autor: Deiana, Allison McCarn, Tran, Nhan, Agar, Joshua, Blott, Michaela, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Hauck, Scott, Liu, Mia, Neubauer, Mark S., Ngadiuba, Jennifer, Ogrenci-Memik, Seda, Pierini, Maurizio, Aarrestad, Thea, Bahr, Steffen, Becker, Jurgen, Berthold, Anne-Sophie, Bonventre, Richard J., Bravo, Tomas E. Muller, Diefenthaler, Markus, Dong, Zhen, Fritzsche, Nick, Gholami, Amir, Govorkova, Ekaterina, Hazelwood, Kyle J, Herwig, Christian, Khan, Babar, Kim, Sehoon, Klijnsma, Thomas, Liu, Yaling, Lo, Kin Ho, Nguyen, Tri, Pezzullo, Gianantonio, Rasoulinezhad, Seyedramin, Rivera, Ryan A., Scholberg, Kate, Selig, Justin, Sen, Sougata, Strukov, Dmitri, Tang, William, Thais, Savannah, Unger, Kai Lukas, Vilalta, Ricardo, Krosigk, Belinavon, Warburton, Thomas K., Flechas, Maria Acosta, Aportela, Anthony, Calvet, Thomas, Cristella, Leonardo, Diaz, Daniel, Doglioni, Caterina, Galati, Maria Domenica, Khoda, Elham E, Fahim, Farah, Giri, Davide, Hawks, Benjamin, Hoang, Duc, Holzman, Burt, Hsu, Shih-Chieh, Jindariani, Sergo, Johnson, Iris, Kansal, Raghav, Kastner, Ryan, Katsavounidis, Erik, Krupa, Jeffrey, Li, Pan, Madireddy, Sandeep, Marx, Ethan, McCormack, Patrick, Meza, Andres, Mitrevski, Jovan, Mohammed, Mohammed Attia, Mokhtar, Farouk, Moreno, Eric, Nagu, Srishti, Narayan, Rohin, Palladino, Noah, Que, Zhiqiang, Park, Sang Eon, Ramamoorthy, Subramanian, Rankin, Dylan, Rothman, Simon, Sharma, Ashish, Summers, Sioni, Vischia, Pietro, Vlimant, Jean-Roch, Weng, Olivia

Publikováno v: Front. Big Data 5, 787421 (2022)

In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery.

Externí odkaz: http://arxiv.org/abs/2110.13041