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A maximum entropy supervised learning algorithm for the identification of skin/core debonding in honeycomb aluminium panels

  • April 11, 2020
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The Twelfth International Conference on Computational Structures Technology (CST2014) 2 – 5 September 2014, Naples, Italy Proceedings of CST2014 Civil-Comp Press, Stirlingshire, UK, Paper 120, 2014 V. Meruane, V. del Fierro and A. Ortiz-Bernardin Abstract Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these

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Accepted Paper: Modal Strain Energy-Based Debonding Assessment of Sandwich Panels Using a Linear Approximation with Maximum Entropy

  • November 21, 2017
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Paper Accepted for Publication in Entropy V. Meruane, Matias Lasen, E. López Droguett, A. Ortiz-Bernardin, “Modal strain energy-based debonding assessment of sandwich panels using a linear approximation with maximum entropy.” ABSTRACT Sandwich structures are very attractive due to their high strength at a minimum weight, and, therefore, there has been a rapid increase in their

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Modal strain energy-based debonding assessment of sandwich panels using a linear approximation with maximum entropy

  • November 21, 2017
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Entropy Vol. 19, No. 11, pp. 619, 2017 V. Meruane, M. Lasen, E. López Droguett, A. Ortiz-Bernardin Abstract Sandwich structures are very attractive due to their high strength at a minimum weight, and, therefore, there has been a rapid increase in their applications. Nevertheless, these structures may present imperfect bonding or debonding between the skins and

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Accepted Paper: A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
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Paper Accepted for Publication in Smart Materials and Structures N. Sanchez, V. Meruane, A. Ortiz-Bernardin, “A novel impact identification algorithm based on a linear approximation with maximum entropy.” ABSTRACT This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear

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A novel impact identification algorithm based on a linear approximation with maximum entropy

  • August 8, 2016
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Smart Materials and Structures Vol. 25, No. 9, pp. 095050, 2016 N. Sanchez, V. Meruane, A. Ortiz-Bernardin Abstract This article presents a novel impact identification algorithm that uses a linear approximation handled by a statistical inference model based on the maximum-entropy principle, termed linear approximation with maximum entropy (LME). Unlike other regression algorithms as Artificial

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A maximum entropy approach to assess debonding in honeycomb aluminum plates

  • May 23, 2014
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Entropy Vol. 16, No. 5, pp. 2869-2889, 2014 V. Meruane, V. del Fierro, A. Ortiz-Bernardin Abstract Honeycomb sandwich structures are used in a wide variety of applications. Nevertheless, due to manufacturing defects or impact loads, these structures can be subject to imperfect bonding or debonding between the skin and the honeycomb core. The presence of

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