Optimization of the Induction Process on Light Gauge Steel Profiles Used in Metallic Framed Sustainable Eco-Constructions

Mihaiela Iliescu, Maria-Magdalena Roşu and Dragoș Căpăţină
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Mihaiela Iliescu: Robotics and Mechatronics Department, Institute of Solid Mechanics, Romanian Academy, 15 Constantin Mille, 10141 Bucharest, Romania
Maria-Magdalena Roşu: Manufacturing Engineering Department, POLITEHNICA University of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania
Dragoș Căpăţină: Robotics and Mechatronics Department, Institute of Solid Mechanics, Romanian Academy, 15 Constantin Mille, 10141 Bucharest, Romania

Sustainability, 2019, vol. 11, issue 23, 1-15

Abstract: Ecological steel framed sustainable and anti-seismic constructions have been highly developed in America, Asia and Europe. Following this trend, Romania has the opportunity to build houses, flats, offices and storage halls using the light gauge steel (LGS) framing system. For reasons of efficient and economic building, sustainable development and requirements from builders of steel framed constructions in Romania, it has been considered an issue to improve some of the steel mechanical characteristics. The metallic profile, which is the basic component of the steel framed system, is manufactured by cold roll forming from laminated low carbon steel strips, galvanized for good corrosion protection. Improving the material’s hardness and tensile strength stands as a challenge caused by the limitations that follow: Reduced material thickness, low carbon content of the material (required for the cold deformation process), estimated profile thermal deformation and customized profile section to harden. This research is focused on the optimization of the induction process (by high frequency current) applied to the LGS material. The advantages and benefits of improving the light gauge steel profile’s hardness are pointed out towards the end of this article.

Keywords: induction; light gauge steel; metallic framed; sustainable eco-construction; hardness; regression model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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