Correlation analysis of penetration based on keyhole and plasma plume in laser welding

Despite the industrial relevance of LASER welding, determination of sustainable parameterization is still a challenge. Trial and error, or even not totally justified methodologies, are frequently applied on LASER welding parametrization. This approach potentially leads to a decrease of the process tolerance and, consequently, increasing the likelihood of imperfections, which means extra operational time and raising of the final cost. The present paper addresses a comparative discussion about five factors experimentally determined and frequently used to predict depth of penetration in LASER welding. The experiments were performed with a 10-kW fiber LASER. In a first batch, power was varied while welding speed was fixed at 1 m/min. In a second batch, welding speed was varied and power was kept at 10 kW. The first demonstrated concern on using these popular factors is the definition and quantification of LASER energy. For evidencing this aspect, two samples were processed with the same welding energy of 120 kJ/m, yet resulting in completely different penetrations. Eventually, an empirical model based on power as a factor allowed a more reliable prediction of the depth of penetration.

Comparison of methods to correlate input parameters with depth of penetration in LASER welding

Laser welding process is used in many industrial sectors. One of the most important aspects of the laser welding quality refers to the geometrical and mechanical properties of welding joints. In order to develop optimal conditions for the laser welding process it is desirable to know in advance which machining parameters to select. Though there are manuals which recommend specific parameters combinations for the desired laser welding quality it is difficult to cover all possible combinations because of the process nonlinearity. Therefore, in this study the main aim is to establish an algorithm for optimal parameters forecasting of the laser welding process. The algorithm is based on an artificial intelligence approach. The main goal is to forecast the geometrical parameters of the welding joints like front width, front heights, back width and back heights of the welding joints. Experimental process was performed in order to acquire training and testing data of the laser welding process. The obtained results could be of practical importance for engineers in industry.

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Parameters forecasting of laser welding by the artificial intelligence techniques

Incomplete fusion, pore and melt sagging are common defects for multi-layer narrow-gap laser welding with filler wire in vertical positions for large and heavy structures. This investigation showed that vertical-up laser welding had a lower sensitivity to pores than vertical-down welding, whereas increasing welding speed could improve welding stability and reduce the formation possibility of pores. For laser vertical welding with hot wire, surface tension transfer mode could effectively guarantee pre-heating of filler wire and achieve a stable welding process. The keyhole stability and melt flow varied with welding directions. The melt sagging defect was usually observed and mainly caused by the concentrated laser energy, which easily led to discontinuous weld bead. Laser beam oscillation technology increased laser melting area and promoted wetting behavior of filler wire with base metal. The weld width increased and concave weld metal surface was obtained with suitable process parameters. Narrow-gap welding process could be carried out at a small defocusing position with a lower laser power, further decreasing tendency of melt slagging. The 20-mm defect-free joint was obtained by vertical-up and vertical-down narrow-gap laser oscillation welding with hot wire.

Process stability and parameters optimization of narrow-gap laser vertical welding with hot wire for thick stainless steel in nuclear power plant

Texture evolution and properties analysis of R60702 pure zirconium joint by fiber laser welding

Plasma behavior and control with small diameter assisting gas nozzle during CO2 laser welding

Carbon nanotube/continuous carbon fiber–reinforced poly(etherketoneketone) (CNT/CCF/PEKK) prepreg tapes were prepared by the wet powder impregnation method, and then the prepreg tapes were molded into laminates. The effects of carbon nanotubes on the mechanical properties, conductivity, thermal conductivity and crystallinity of the composites were studied by universal testing machine, thermal conductivity and resistivity tester, dynamic mechanical analyzer (DMA) and differential scanning calorimeter (DSC). The results show that when the content of carbon nanotubes is 0.5 wt% (relative to the mass of PEKK resin, the same below), the flexural strength and interlaminar shear strength of the laminates reach the maximum, which are increased by 15.99% and 18.16%, respectively, compared with the laminates without carbon nanotubes. The results of conductivity and thermal conductivity show that the higher the content of carbon nanotubes, the better the conductivity and thermal conductivity of the material. DSC results show that the addition of CNT promoted the crystallization of PEKK in the material and decreased the cold crystallization of PEKK. DMA results show that the deformation resistance of the material can be improved by adding an appropriate amount of CNT and the bonding between CF and PEKK can be enhanced, while excessive CNT destroys this phenomenon.

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Effect of Carbon Nanotubes on the Mechanical, Crystallization, Electrical and Thermal Conductivity Properties of CNT/CCF/PEKK Composites

Lysozyme regulates the extracellular polymer of activated sludge and promotes the formation of electroactive biofilm

In this paper, metallocene polypropylene (mPP) composites filled with carbon nanotubes (CNTs) were prepared using twin-screw extruder. The crystallization behavior, mechanical properties and rheological behavior were characterized by a differential scanning calorimetry (DSC), universal material testing machine and rotational rheometer. The results of DSC indicated that the effect of CNTs on heterogeneous nucleation of mPP was very obvious and the crystallizability of the resin matrix was improved after adding CNTs, especially the initial crystallization temperature (T 0), crystallization temperature (T c) increased by 9.63 °C and 8.28 °C when the CNTs content was 1.25 wt%. The yield stress and elastic modulus increased to 33.98 MPa and 1605.6 MPa as the CNTs concentration increased to 1.0 wt% in contrast to that of the neat mPP. The results of SEM images showed that the better dispersion and adhesion of CNTs into polymer matrix. The results of rotational rheometer proved that interactions increased between CNTs and mPP as the content of CNTs increasing.

https://iopscience.iop.org/article/10.1088/2053-1591/acb41b/pdf

Kaili Zhu

Papers

Plasma behavior and control with small diameter assisting gas nozzle during CO2 laser welding

Effect of Carbon Nanotubes on the Mechanical, Crystallization, Electrical and Thermal Conductivity Properties of CNT/CCF/PEKK Composites

Lysozyme regulates the extracellular polymer of activated sludge and promotes the formation of electroactive biofilm

Crystallization, rheological behavior and mechanical properties of carbon nanotube/metallocene polypropylene composites