Diego Ferreño

962 total citations
73 papers, 709 citations indexed

About

Diego Ferreño is a scholar working on Mechanical Engineering, Mechanics of Materials and Civil and Structural Engineering. According to data from OpenAlex, Diego Ferreño has authored 73 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Mechanical Engineering, 34 papers in Mechanics of Materials and 21 papers in Civil and Structural Engineering. Recurrent topics in Diego Ferreño's work include Railway Engineering and Dynamics (15 papers), Fatigue and fracture mechanics (12 papers) and Non-Destructive Testing Techniques (10 papers). Diego Ferreño is often cited by papers focused on Railway Engineering and Dynamics (15 papers), Fatigue and fracture mechanics (12 papers) and Non-Destructive Testing Techniques (10 papers). Diego Ferreño collaborates with scholars based in Spain, United Kingdom and Portugal. Diego Ferreño's co-authors include Isidro Carrascal, J.A. Casado, Soraya Diego, Estela Ruiz, José A. Sáinz-Aja, F. Gutiérrez‐Solana, R. Lacalle, Miguel Cuartas, J. Pombo and J.A. Polanco and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Molecular Sciences and Construction and Building Materials.

In The Last Decade

Diego Ferreño

69 papers receiving 688 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Diego Ferreño Spain 16 416 250 231 149 87 73 709
Soraya Diego Spain 14 384 0.9× 381 1.5× 118 0.5× 59 0.4× 49 0.6× 35 600
Francesco Penta Italy 14 276 0.7× 219 0.9× 253 1.1× 79 0.5× 21 0.2× 46 617
Vitalii Kovalchuk Ukraine 17 596 1.4× 388 1.6× 143 0.6× 122 0.8× 24 0.3× 93 730
Tao Zhu China 16 478 1.1× 153 0.6× 246 1.1× 168 1.1× 22 0.3× 94 711
Isidro Carrascal Spain 21 651 1.6× 620 2.5× 523 2.3× 212 1.4× 135 1.6× 81 1.3k
Weiwei Guo China 13 728 1.8× 538 2.2× 129 0.6× 39 0.3× 25 0.3× 31 970
Md. Rehan Sadique India 15 138 0.3× 454 1.8× 258 1.1× 179 1.2× 22 0.3× 47 684
Mingfa Ren China 17 424 1.0× 270 1.1× 513 2.2× 140 0.9× 16 0.2× 60 834
Ezequiel Alberto Gallardo-Hernández Mexico 21 1.0k 2.4× 85 0.3× 813 3.5× 288 1.9× 31 0.4× 61 1.3k
Kwang-Bok Shin South Korea 14 568 1.4× 305 1.2× 438 1.9× 133 0.9× 36 0.4× 79 830

Countries citing papers authored by Diego Ferreño

Since Specialization
Citations

This map shows the geographic impact of Diego Ferreño's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Diego Ferreño with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Ferreño more than expected).

Fields of papers citing papers by Diego Ferreño

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diego Ferreño. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Diego Ferreño. The network helps show where Diego Ferreño may publish in the future.

Co-authorship network of co-authors of Diego Ferreño

This figure shows the co-authorship network connecting the top 25 collaborators of Diego Ferreño. A scholar is included among the top collaborators of Diego Ferreño based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Diego Ferreño. Diego Ferreño is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ferreño, Diego, et al.. (2025). Machine learning assessment of the importance of unirradiated yield strength as a variable in embrittlement trend forecasting. International Journal of Pressure Vessels and Piping. 214. 105444–105444. 1 indexed citations
2.
Iglesias, L. Lloret, et al.. (2024). Classification of Cast Iron Alloys through Convolutional Neural Networks Applied on Optical Microscopy Images. steel research international. 95(12). 1 indexed citations
3.
Rosa, Ángel De La, et al.. (2024). Comparative analysis of flexural strength prediction in SFRC using frequentist, Bayesian, and Machine Learning approaches. Case Studies in Construction Materials. 21. e03822–e03822. 3 indexed citations
4.
Sáinz-Aja, José A., Isidro Carrascal, Diego Ferreño, et al.. (2024). Impact of hydrocarbon exposure on the mechanical properties of rail pads. Construction and Building Materials. 419. 135561–135561. 3 indexed citations
5.
Usategui‐Martín, Ricardo, Salvador Pastor‐Idoate, Álvaro del Real, et al.. (2024). A Missense Variant in TP53 Could Be a Genetic Biomarker Associated with Bone Tissue Alterations. International Journal of Molecular Sciences. 25(3). 1395–1395.
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Casanueva, Rosario, Christian Brañas, F. Javier Díaz, et al.. (2023). Characterization of an energy efficient pulsed current TIG welding process on AISI 316 and 304 stainless steels. Heliyon. 9(9). e19819–e19819. 4 indexed citations
9.
Ortiz, A., et al.. (2023). The Impact of Thermal Ageing on the Compression Strength of Radial Spacers in Power Transformers. UCrea (University of Cantabria). 143–147.
10.
Pérez‐Núñez, María Isabel, Álvaro del Real, Guillermo Menéndez, et al.. (2022). Effects of Systemic or Local Administration of Mesenchymal Stem Cells from Patients with Osteoporosis or Osteoarthritis on Femoral Fracture Healing in a Mouse Model. Biomolecules. 12(5). 722–722. 7 indexed citations
11.
Ferreño, Diego, Mark Kirk, Marta Serrano, & José A. Sáinz-Aja. (2022). Assessment of the Generalization Ability of the ASTM E900-15 Embrittlement Trend Curve by Means of Monte Carlo Cross-Validation. Metals. 12(3). 481–481. 3 indexed citations
12.
Carrascal, Isidro, A. Ortiz, I. Fernández, et al.. (2021). Fracture toughness as an alternative approach to quantify the ageing of insulation paper in oil. Cellulose. 28(18). 11533–11550. 4 indexed citations
13.
Ferreño, Diego, et al.. (2019). Structural Integrity Assessment of a Nuclear Vessel through ASME and Master Curve Approaches Using Irradiation Embrittlement Predictions. Journal of Testing and Evaluation. 48(6). 4748–4766. 1 indexed citations
14.
Blanco‐Fernández, Elena, et al.. (2018). Use of explicit FEM models for the structural and parametrical analysis of rockfall protection barriers. Engineering Structures. 166. 212–226. 20 indexed citations
15.
Ortiz, A., et al.. (2018). Mechanical Behaviour of the Cellulosic Dielectric Materials of Windings in Power Transformers in Operation. UCrea (University of Cantabria). 32. 2400–2406. 1 indexed citations
16.
Ferreño, Diego, José A. Sáinz-Aja, Isidro Carrascal, et al.. (2016). Orientation of whole bone samples of small rodents matters during bending tests. Journal of the mechanical behavior of biomedical materials. 65. 200–212. 2 indexed citations
17.
Ferreño, Diego, et al.. (2015). Comparative study of the effect of PTH (1–84) and strontium ranelate in an experimental model of atrophic nonunion. Injury. 46(12). 2359–2367. 8 indexed citations
18.
Ferreño, Diego, et al.. (2010). Failure analysis of a Pelton turbine manufactured in soft martensitic stainless steel casting. Engineering Failure Analysis. 18(1). 256–270. 28 indexed citations
19.
Ferreño, Diego, et al.. (2009). Structural integrity of an X-750 jet pump beam of a BWR by means of FITNET FFS procedure. Engineering Failure Analysis. 16(7). 2130–2139. 1 indexed citations
20.
Ferreño, Diego, et al.. (2004). Optimisation of heat treatment for improvement of IGSCC properties of an X-750 alloy. Engineering Failure Analysis. 11(5). 799–810. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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