Corrosion behaviour of micro-plasma arc welded stainless steels in H3PO4 under flowing conditions at different temperatures

[EN] This paper studies the general corrosion behaviour of the micro-plasma arc welded AISI 316L stainless steel in phosphoric acid at different temperatures (25-60°C) and at a Reynolds number of 1456. Galvanic corrosion has been studied using zero-resistance ammeter (ZRA) measurements and polarization curves (by the mixed potential theory). Results show that the microstructure of the stainless steel is modified due to the micro-plasma arc welding procedure. Coupled current density values obtained from polarization curves increase with temperature. ZRA tests present the highest iG values at 60°C; however, the values are very close to zero for all the temperatures studied. This is in agreement with the low value of the compatibility limit and of the parameter which evaluates the importance of the galvanic phenomenon. Both techniques present the most positive potentials at the highest temperature. This study reveals that micro-plasma arc welded AISI 316L stainless steels are appropriated working in the studied H3PO4 media from a corrosion point of view for all the temperatures analysedThe authors would like to express their gratitude to the Spanish MAEC (PCI Mediterráneo C/8196/07, C/018046/08, D/023608/09) and to Asuncion Jaime for her translation assistance.Sánchez Tovar, R.; Montañés Sanjuan, MT.; García Antón, J.; Guenbour, A.; Ben Bachir, A. (2011). Corrosion behaviour of micro-plasma arc welded stainless steels in H3PO4 under flowing conditions at different temperatures. Corrosion Science. 53(4):1237-1246. https://doi.org/10.1016/j.corsci.2010.12.017S1237124653

The development of a finite element for delamination growth in composites.

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Review of state-of-the-art research on the design and manufacturing of support structures for powder-bed fusion additive manufacturing

The use of support structures is an essential requirement for powder-bed fusion additive manufacturing (AM) processes. Supports are responsible for fixing the component on the build plate, carrying the weight of the structure, providing heat dissipation from the component to the build plate and preventing distortion during the process. Support efficiency and performance can be evaluated through the ease of removability, strength, thermal management, cost-effectiveness, and material consumption. As the support structures are the waste material during manufacturing of metal AM components, their design has a significant impact on the productivity and cost of the manufacturing process. Due to lack of concentrated information on the effect of each mentioned support function, this paper aims to gather studies and innovations in support design and production, specifically for the powder-bed fusion methods. At first, the effect of support type and contributing geometrical parameters on the overall performance of support structures is discussed. Then, an in-detail approach is taken to categorize each key characteristics of metallic support structures and reinforce the discussion with related published papers. Finally, the role of topology optimization (TO) in designing optimum support geometry is presented. The overall conclusion is that unless there are several studies on design and manufacturing of support structures, achieving the best setup has not been guaranteed by the existing tools. The research trend is toward developing more cost-effective optimization methods based on genetic algorithms (GA) and multi-objective functions to generate automated and high-performance supports, especially for complex geometries. Furthermore, integrating AM constraints with GA and TO can be achieved through defining self-supporting index or coupling with multi-objective optimization methods, which leads to a more efficient solution

The development of a finite element for delamination growth in composites

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DEVELOPMENT OF A REVERSE ENGINEERING PROCEDURE FOR UPGRADING AND MANUFACTURING OF LEGACY MECHANICAL AND STRUCTURAL COMPONENTS

In this article, a reverse engineering procedure has been presented to achieve an upgraded design applicable to legacy mechanical and structural components of aeronautical systems. In this way, a methodology comprising re-engineering and rapid prototyping methods has been proposed. Assuming no available useful original design data, this procedure focuses on re-producing engineering design data to develop an engineering platform for innovative design. In this procedure, first cloud point data are extracted by laser scanning to create 3D solid parametric modeling. Then, reasonable changes are applied to the original design to achieve a new design compatible with requirements and available rapid prototyping techniques and material resources. A special attention has been paid to stress and fracture analysis to ensure reliability and damage tolerance capability of the new design. The method is benchmarked using an actual aircraft component

Fatigue performance of metal additive manufacturing: a comprehensive overview

Fatigue life assessment of metal additive manufacturing (AM) products has remained challenging due to the uncertainty of as–built defects, heterogeneity of the microstructure, and residual stress. In the past few years, many works have been conducted to develop models in order to predict fatigue life of metal AM samples by considering the existence of AM inherent defects. This review paper addresses the main issues regarding fatigue assessment of metal AM parts by considering the effect of defects and post processing strategies. Mechanisms that are contributing to the failure of metal AM samples are categorized and discussed in detail. Several modelling approaches exist in the case of fatigue life prediction. The common fatigue models that are compatible with AM properties are thoroughly explained by discussing the previous works and highlighting their major conclusions. In addition, the use of machine learning is identified as the future of metal AM fatigue life assessment due to their high performance. The main challenge of today's fatigue and fracture community was identified as the fatigue life estimation of complex geometries with the presence of different types of defects, anisotropic microstructure, and complex state of residual stress. This work proposes the available approaches to tackle this challenge

Process parameter optimization for laser powder directed energy deposition of Inconel 738LC

Processing nickel-based superalloys is one of the major challenges in the additive manufacturing (AM) field. Nickel-based superalloys consist of several alloying elements, which make them prone to the formation of undesired phases and cracking due to the complex thermodynamics during the metal AM processes. In order to produce defect-free parts from nickel-based superalloys via metal AM processes, optimization of process parameters is required. In this study, the effect of laser powder directed energy deposition (LP-DED) process parameters on the geometrical properties and porosity ratio of Inconel 738 LC (low carbon) is investigated. Geometrical specifications, including the track height, width, and wetting angle are the major factors that indicate the quality of the final product. The analysis of variance (ANOVA) and response surface methodology (RSM) were developed in order to predict the geometrical specifications of single tracks from the key process parameters, namely laser power, scan speed, and powder feed rate. An optimum set of process parameters was obtained through multi-objective optimization by minimizing the porosity ratio, crack formation and maximizing the deposition rate. The results were verified and a good agreement with the experimental measurements was achieved. The produced bulk sample showed less than one percent porosity content, which indicates the effectiveness of single-track optimization prior to bulk sample production. The overall microstructure of the bulk sample showed a high content of MC carbides resulting from the abundance of alloying elements