Area de Ingenieria

Durango Bizkaia, Spain

Area de Ingenieria

Durango Bizkaia, Spain
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Arenas M.A.,CSIC - National Center for Metallurgical Research | Niklas A.,Area de Ingenieria | Conde A.,CSIC - National Center for Metallurgical Research | Mendez S.,Area de Ingenieria | And 2 more authors.
Revista de Metalurgia | Year: 2014

The increasing demand of ductile cast irons with extensive technological applications leads to enlarge the corrosion resistance of this group of metallic materials. In this sense, the use of different chemical compositions on such cast irons becomes one of the most interesting aspects among the different ways to improve their behaviour against corrosion due to the extra opportunity for increasing the mechanical properties. Additionally such improvements have to be made without any increase of processing costs to keep the interesting competitiveness of developed cast irons. In the present work the preliminary results obtained from corrosion tests made on a group of cast irons with different chemical compositions are presented. Among ductile cast irons, silicon content has been varied in order to investigate the effect of this element on corrosion resistance of the alloys. The obtained results show a slight improvement of this property for the alloys with high silicon content with respect to the conventional ones though such effect was found in the first time period of the corrosion tests. Interestingly this improvement was found for alloys that exhibit better tensile properties than the conventional ductile irons. Thus an important way for developing new ductile cast irons with improved corrosion properties by alloying has been opened. © 2014 CSIC.

Nieves J.,University of Deusto | Santos I.,University of Deusto | Bringas P.G.,University of Deusto | Zabala A.,Area de Ingenieria | Sertucha J.,Area de Ingenieria
Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications, ICIEA 2014 | Year: 2014

A Model Predictive Control (MPC) is a system designed to control a production plant. These systems are composed by several phases, being one of the most important ones the phase for the prediction of the plant situation in a given time. In a previous work, we presented a machine-learning approach for this prediction phase that replaced the need of developing a single mathematical function with a more generic classification approach. However, standalone classifiers had some drawbacks like to select the most adequate classification models for the learning data and task. In this paper we extend our previous work with a general method to foresee Dross defects building a meta-classification system through the combination of different methods and removing the need of selecting the best algorithm for each objective or dataset. © 2014 IEEE.

Lacaze J.,ENSIACET | Sertucha J.,Area de Ingenieria
International Journal of Cast Metals Research | Year: 2016

In a previously published work, pearlite growth in cast irons was investigated and it was claimed that growth kinetics of pearlite in nodular cast iron does not depend on alloying elements and that only the start temperature for the transformation is modified. Since then, the authors have investigated the effect of copper at low level of manganese and the combined effect of copper and tin at intermediate manganese contents. In the first case, thermal records confirmed that copper decreases the formation temperature for both ferrite and pearlite. In the second work, an optimised content for tin, manganese and copper was found so as to improve mechanical properties while keeping fully pearlitic structures. The thermal records obtained during this latter study are here used to estimate the pearlite growth kinetics and the effect of copper and tin on it. Tin has been shown to reduce pearlite undercooling (increase of start transformation temperature) and thus to favour the formation of this constituent. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

Santos I.,University of Deusto | Nieves J.,University of Deusto | Bringas P.G.,University of Deusto | Zabala A.,Area de Ingenieria | Sertucha J.,Area de Ingenieria
Proceedings of the 2013 IEEE 8th Conference on Industrial Electronics and Applications, ICIEA 2013 | Year: 2013

Foundry is one of the key axes in society because it provides with important pieces to other industries. However, several defects may appear in castings. In particular, Dross is defect that is a type of non-metallic, elongated and filamentary inclusion. Unfortunately, the methods to detect Dross have to be performed once the production has already finished using quality controls that incur in a subsequent cost increment. Given this context, we propose the first machine-learning-based method able to foresee Dross in iron castings, modelling the foundry production parameters as input. Our results have shown that this method obtains good accuracy results when tested with real data from a heavy-section casting foundry. © 2013 IEEE.

De La Torre U.,Area de Ingenieria | Loizaga A.,Area de Ingenieria | Lacaze J.,Inter - University Research and Engineering Center on Materials | Sertucha J.,Area de Ingenieria
Materials Science and Technology (United Kingdom) | Year: 2014

The present work shows a comparative study regarding the mechanical properties of 25 as cast ferritic ductile iron alloys, nine of them with silicon contents higher than 3·00% and carbon contents lower than 3·60%. In a first step, different carbon equivalent values have been used in order to analyse the effect of this parameter on the mechanical properties. After this comparative analysis, the composition ranges C=3·30-3·40 wt-% and Si53·75-3·80 wt-% have been selected as the most proper ones to optimise the tensile and impact properties among the high silicon ductile iron alloys. Finally, a second study was carried out to compare the tensile and fatigue properties of the optimised high silicon alloy with the corresponding ones obtained from an EN GJS 400-18-LT grade alloy with low silicon content. Although the room temperature impact values obtained from the high silicon ductile iron are lower than 6 J cm-2, the measured fatigue limit of this alloy (358 MPa) is clearly higher than the one obtained from the low silicon cast iron (170 MPa). A discussion about the benefits and advantages of the high silicon alloy is included. © 2014 Institute of Materials, Minerals and Mining.

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