This paper presents a study of the hydrodynamics of several rowing blade designs. The study was done using Computational Fluid Dynamics (CFD) which enabled the investigation to be done similar to the experimental stud...
This paper presents a study of the hydrodynamics of several rowing blade designs. The study was done using Computational Fluid Dynamics (CFD) which enabled the investigation to be done similar to the experimental study, but with additional hydrodynamic visualization for further analysis and understanding. The CFD method was validated using quasi-static experimental data from Caplan (2007). Besides that, the proposed CFD analyses have improved the precious CFD results with the percentage of error of 6.58 percent of lift and 0.69 percent of drag force compared to 33.65 and 18.75 percent obtained by Coppel (2010). Consequent to the successful validation, the study then proceeded with the real size of Macon, Big balde and Fat blade. It was found that the hydrodynamic performance of the Fat blade was the highest due to the area, aspect ratio and the shape of the blade. Besides that, distribution of pressure for all models were also investigated which deepened the understanding of the blade fluid mechanics of rowing.
ALICE is one of the four experiments installed at the CERN Large Hadron Collider (LHC), especially designed for the study of heavy-ion collisions. The online data Quality Monitoring (DQM) is an important part of the d...
ALICE is one of the four experiments installed at the CERN Large Hadron Collider (LHC), especially designed for the study of heavy-ion collisions. The online data Quality Monitoring (DQM) is an important part of the data acquisition (DAQ) software. It involves the online gathering, the analysis by user-defined algorithms and the visualization of monitored data. This paper presents the final design, as well as the latest and coming features, of the ALICE's specific DQM software called AMORE (Automatic MonitoRing Environment). It describes the challenges we faced during its implementation, including the performances issues, and how we tested and handled them, in particular by using a scalable and robust publish-subscribe *** also review the on-going and increasing adoption of this tool amongst the ALICE collaboration and the measures taken to develop, in synergy with their respective teams, efficient monitoring modules for the sub-detectors. The related packaging and release procedure needed by such a distributed framework is also described. We finally overview the wide range of usages people make of this framework, and we review our own experience, before and during the LHC start-up, when monitoring the data quality on both the sub-detectors and the DAQ side in a real-world and challenging environment.
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