Argitalpenak (56) ANA MARIA CAMACHO LOPEZ argitalpenak

2024

  1. Data-Analytics-Driven Selection of Die Material in Multi-Material Co-Extrusion of Ti-Mg Alloys

    Mathematics, Vol. 12, Núm. 6

2023

  1. Hybrid additive and subtractive manufacturing: Evolution of the concept and last trends in research and industry

    Procedia CIRP

2022

  1. Multicriteria Analytical Model for Mechanical Integrity Prognostics of Reactor Pressure Vessels Manufactured from Forged and Rolled Steels

    Mathematics, Vol. 10, Núm. 10

  2. Optimal Parameters Selection in Advanced Multi-Metallic Co-Extrusion Based on Independent MCDM Analytical Approaches and Numerical Simulation

    Mathematics, Vol. 10, Núm. 23

2021

  1. Analysis of the technological evolution of materials requirements included in reactor pressure vessel manufacturing codes

    Sustainability (Switzerland), Vol. 13, Núm. 10

  2. Evolution of standardized specifications on materials, manufacturing and in-service inspection of nuclear reactor vessels

    Sustainability (Switzerland), Vol. 13, Núm. 19

  3. Reliability prediction of acrylonitrile o-ring for nuclear power applications based on shore hardness measurements

    Polymers, Vol. 13, Núm. 6

  4. Selection of die material and its impact on the multi-material extrusion of bimetallic az31b–ti6al4v components for aeronautical applications

    Materials, Vol. 14, Núm. 24

  5. Special issue of the manufacturing engineering society 2020 (SIMES-2020)

    Applied Sciences (Switzerland)

  6. Special issue of the manufacturing engineering society 2020 (Simes-2020)

    Materials

  7. Topological optimization of artificial neural networks to estimate mechanical properties in metal forming using machine learning

    Metals, Vol. 11, Núm. 8

2020

  1. Analysis of General and Specific Standardization Developments in Additive Manufacturing from a Materials and Technological Approach

    IEEE Access, Vol. 8, pp. 125056-125075

  2. Considerations on the applicability of test methods for mechanical characterization of materials manufactured by FDM

    Materials, Vol. 13, Núm. 1

  3. Effect of process parameters and definition of favorable conditions in multi-material extrusion of bimetallic az31b–ti6al4v billets

    Applied Sciences (Switzerland), Vol. 10, Núm. 22, pp. 1-17

  4. Fitness for Service and Reliability of Materials for Manufacturing Components Intended for Demanding Service Conditions in the Petrochemical Industry

    IEEE Access, Vol. 8, pp. 92275-92286

  5. Prediction of Physical and Mechanical Properties for Metallic Materials Selection Using Big Data and Artificial Neural Networks

    IEEE Access, Vol. 8, pp. 13444-13456

  6. Prediction of mechanical properties by artificial neural networks to characterize the plastic behavior of aluminum alloys

    Materials, Vol. 13, Núm. 22, pp. 1-22

  7. Prediction of the bilinear stress-strain curve of aluminum alloys using artificial intelligence and big data

    Metals, Vol. 10, Núm. 7, pp. 1-29

  8. Reliability-based evaluation of the suitability of polymers for additive manufacturing intended for extreme operating conditions

    Polymers, Vol. 12, Núm. 10, pp. 1-21

  9. Special issue of the manufacturing engineering society 2019 (SIMES-2019)

    Applied Sciences (Switzerland)