The Vector Analyzing Power in Elastic Deuteron-Deuteron Scattering between 20 and 40 MeV

1976 ◽  
pp. 516-517 ◽  
Author(s):  
H. E. Conzett ◽  
W. Dahme ◽  
R. M. Larimer ◽  
Ch. Leemann ◽  
J. S. C. Mckee
Keyword(s):  
Deuteron Scattering ◽  
Analyzing Power

Measurement of tensor analyzing power in elastic electron-deuteron scattering at momentum transfer range 2.8 – 4.6fm−1

2003 ◽  
Vol 721 ◽  
pp. C409-C412 ◽  
Author(s):  
D.M. Nikolenko ◽  
H. Arenhövel ◽  
L.M. Barkov ◽  
S.L. Belostotsky ◽  
V.F. Dmitriev ◽  
...  
Keyword(s):  
Momentum Transfer ◽  
Elastic Electron ◽  
Deuteron Scattering ◽  
Momentum Transfer Range ◽  
Analyzing Power

scholarly journals Analyzing power in nucleon-deuteron scattering and three-nucleon forces

1999 ◽  
Vol 59 (3) ◽  
pp. R1247-R1251 ◽  
Author(s):  
S. Ishikawa
Keyword(s):  
Deuteron Scattering ◽  
Analyzing Power

ANALYZING POWER MEASUREMENTS FOR p-p ELASTIC SCATTERING AT HIGH-P⊥2

1985 ◽  
Vol 46 (C2) ◽  
pp. C2-303-C2-305
Author(s):  
R. S. Raymond ◽  
K. A. Brown ◽  
R. J. Bruni ◽  
P. R. Cameron ◽  
D. G. Crabb ◽  
...  
Keyword(s):  
Elastic Scattering ◽  
Power Measurements ◽  
Analyzing Power

Neutron-deuteron scattering at 152 MeV

1972 ◽  
Vol 188 (1) ◽  
pp. 72-76 ◽  
Author(s):  
J.N. Palmieri
Keyword(s):  
Deuteron Scattering

scholarly journals Goals and measures for analyzing power consumption data in manufacturing enterprises

2021 ◽  
Vol 3 (1) ◽  
pp. 65-82
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring ◽  
Heinz Burmester ◽  
Armin Möbius ◽  
Maik Wojcieszak
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Manufacturing Industry ◽  
Fog Computing ◽  
Electrical Power ◽  
Time Data ◽  
Manufacturing Enterprises ◽  
Computing Paradigm ◽  
Consumption Data ◽  
Analyzing Power

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

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