The Petawatt Aquitaine Laser (PETAL) facility was designed and constructed by the French Commissariat à l'énergie atomique et aux énergies alternatives (CEA) as an additional PW beamline to the Laser MegaJoule (LMJ) facility. PETAL energy is limited to 1 kJ at the beginning due to the damage threshold of the final optics. In this paper, we present the commissioning of the PW PETAL beamline. The first kJ shots in the amplifier section with a large spectrum front end, the alignment of the synthetic aperture compression stage and the initial demonstration of the 1.15 PW @ 850 J operations in the compression stage are detailed. Issues encountered relating to damage to optics are also addressed.
An experimental approach is presented in order to study the evolution of the spreading of a macro-drop of liquid metal. The objective of this work is to supply qualitative and quantitative information during the deposit of liquid metal in static pulsed Gas Metal Arc Welding (P-GMAW). The experimental results are analyzed in the light of dimensionless numbers in order to identify the involved physical mecanisms and appreciate the heat and mass effects on the behavior of such a macro-drop.
This paper presents a new mechanism, observed directly for the first time, to explain low carbide fractions in Ni-WC overlays produced with GMAW. In this loss mechanism, a significant amount of powder loss is a consequence of the non-wetting behaviour of tungsten carbide. High speed videography and quantitative metallography of weld deposits are used to identify this mechanism. The non-wetting mechanism found acts simultaneously with the carbide dissolution mechanism, which until now was the only suggested cause of low carbide fraction in GMAW Ni-WC overlays. The non-wetting behaviour is observed in both short circuit and free flight metal transfer, accounting for carbide losses between 20 and 70% in the experiments performed. Low carbide fraction has prevented the mainstream use of GMAW for Ni-WC overlays, despite the advantages of simplicity, capability of in situ repair, and low capital costs. The findings presented here have a potential large impact for further consumable and process development.
This article describes an image analysis algorithm used to detect profiles during arc welding processes. The new algorithm is an aggregation of image processing (segmentation, filtering), computational geometry (alpha shape) and graph theory (cycle detection). It allows to extract precise geometrical profile entities, whether open or closed contours, that could be used for the monitoring of the welding process. The algorithm is shown to be really efficient and could be used for real-time monitoring of gas metal arc welding process.
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