Ionut Moldovan

520 total citations
40 papers, 366 citations indexed

About

Ionut Moldovan is a scholar working on Civil and Structural Engineering, Mechanics of Materials and Computational Mechanics. According to data from OpenAlex, Ionut Moldovan has authored 40 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Civil and Structural Engineering, 22 papers in Mechanics of Materials and 9 papers in Computational Mechanics. Recurrent topics in Ionut Moldovan's work include Numerical methods in engineering (18 papers), Structural Health Monitoring Techniques (15 papers) and Geotechnical Engineering and Underground Structures (11 papers). Ionut Moldovan is often cited by papers focused on Numerical methods in engineering (18 papers), Structural Health Monitoring Techniques (15 papers) and Geotechnical Engineering and Underground Structures (11 papers). Ionut Moldovan collaborates with scholars based in Portugal, Brazil and Romania. Ionut Moldovan's co-authors include Elói Figueiredo, J. A. Teixeira de Freitas, Samuel da Silva, Adam Santos, João C. W. A. Costa, Pedro Campos, Toan Duc Cao, A. Gomes Correia, Lucian Radu and Corneliu Cismaşiu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and International Journal for Numerical Methods in Engineering.

In The Last Decade

Ionut Moldovan

40 papers receiving 360 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ionut Moldovan Portugal 11 256 164 61 50 40 40 366
G. W. Singapore 7 295 1.2× 391 2.4× 92 1.5× 52 1.0× 28 0.7× 10 516
Johan Clausen Denmark 13 371 1.4× 263 1.6× 57 0.9× 84 1.7× 14 0.3× 32 559
V. Murti Australia 10 153 0.6× 238 1.5× 54 0.9× 62 1.2× 31 0.8× 19 333
Cédric Giry France 10 188 0.7× 263 1.6× 43 0.7× 26 0.5× 11 0.3× 33 417
Andrzej Truty Poland 11 227 0.9× 88 0.5× 76 1.2× 30 0.6× 7 0.2× 24 323
Ali Khojasteh Iran 12 375 1.5× 408 2.5× 50 0.8× 113 2.3× 39 1.0× 40 580
Wenan Wu China 18 375 1.5× 459 2.8× 185 3.0× 66 1.3× 16 0.4× 37 739
Chengzhi Qi China 10 305 1.2× 158 1.0× 18 0.3× 53 1.1× 8 0.2× 51 455
A. Peano United States 11 220 0.9× 347 2.1× 172 2.8× 34 0.7× 53 1.3× 22 499
Nikos Pnevmatikos Greece 14 513 2.0× 52 0.3× 25 0.4× 68 1.4× 19 0.5× 44 569

Countries citing papers authored by Ionut Moldovan

Since Specialization
Citations

This map shows the geographic impact of Ionut Moldovan'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 Ionut Moldovan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ionut Moldovan more than expected).

Fields of papers citing papers by Ionut Moldovan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ionut Moldovan. 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 Ionut Moldovan. The network helps show where Ionut Moldovan may publish in the future.

Co-authorship network of co-authors of Ionut Moldovan

This figure shows the co-authorship network connecting the top 25 collaborators of Ionut Moldovan. A scholar is included among the top collaborators of Ionut Moldovan 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 Ionut Moldovan. Ionut Moldovan 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.
Moldovan, Ionut, et al.. (2025). Transfer learning and Bayesian calibration addressing data scarcity and uncertainty for structural health monitoring of twin concrete bridges. Mechanical Systems and Signal Processing. 235. 112845–112845. 2 indexed citations
2.
Moldovan, Ionut, Mohammad Jawed Roshan, Miguel Azenha, & A. Gomes Correia. (2025). Dissipation boundaries for bender element experiments on geomaterials based on experimental and computational models. Transportation Engineering. 20. 100331–100331. 1 indexed citations
3.
Moldovan, Ionut, et al.. (2024). A Computational Platform for Automatic Signal Processing for Bender Element Sensors. Algorithms. 17(4). 131–131. 1 indexed citations
4.
Moldovan, Ionut, et al.. (2024). Hybrid Approach for Supervised Machine Learning Algorithms to Identify Damage in Bridges. Journal of Bridge Engineering. 29(8). 3 indexed citations
5.
Correia, A. Gomes, et al.. (2024). A Modified Rowe Cell with Bender Elements for Small Strain Shear Modulus Measurements. Geotechnical Testing Journal. 47(5). 985–1005. 1 indexed citations
6.
Figueiredo, Elói, et al.. (2024). Impact of climate change on long-term damage detection for structural health monitoring of bridges. Structural Health Monitoring. 24(4). 2252–2270. 8 indexed citations
7.
Figueiredo, Elói, et al.. (2023). Transfer Learning for Structural Health Monitoring in Bridges That Underwent Retrofitting. Buildings. 13(9). 2323–2323. 8 indexed citations
8.
Figueiredo, Elói, et al.. (2023). A Roadmap for an Integrated Assessment Approach to the Adaptation of Concrete Bridges to Climate Change. Journal of Bridge Engineering. 28(6). 7 indexed citations
9.
Silva, Samuel da, et al.. (2023). Bayesian calibration for Lamb wave propagation on a composite plate using a machine learning surrogate model. Mechanical Systems and Signal Processing. 208. 111011–111011. 9 indexed citations
10.
Moldovan, Ionut, et al.. (2022). Reliability of probabilistic numerical data for training machine learning algorithms to detect damage in bridges. Structural Control and Health Monitoring. 29(7). 23 indexed citations
11.
Moldovan, Ionut, et al.. (2022). Hybrid-Trefftz displacement elements for three-dimensional elastodynamics. Computational Mechanics. 70(6). 1083–1105. 1 indexed citations
12.
Moldovan, Ionut, et al.. (2020). A hybrid-Trefftz finite element platform for solid and porous elastodynamics. Engineering Analysis with Boundary Elements. 124. 155–173. 10 indexed citations
13.
14.
Figueiredo, Elói, Ionut Moldovan, Adam Santos, Pedro Campos, & João C. W. A. Costa. (2019). Finite Element–Based Machine-Learning Approach to Detect Damage in Bridges under Operational and Environmental Variations. Journal of Bridge Engineering. 24(7). 60 indexed citations
15.
Moldovan, Ionut, et al.. (2019). On rank-deficiency in direct Trefftz method for 2D Laplace problems. Engineering Analysis with Boundary Elements. 106. 102–115. 3 indexed citations
16.
Moldovan, Ionut. (2016). A new approach to non-homogeneous hyperbolic boundary value problems using hybrid-Trefftz stress finite elements. Engineering Analysis with Boundary Elements. 69. 57–71. 3 indexed citations
17.
Moldovan, Ionut. (2015). A new particular solution strategy for hyperbolic boundary value problems using hybrid-Trefftz displacement elements. International Journal for Numerical Methods in Engineering. 102(6). 1293–1315. 9 indexed citations
18.
Moldovan, Ionut, Toan Duc Cao, & J. A. Teixeira de Freitas. (2013). Elastic wave propagation in unsaturated porous media using hybrid‐Trefftz stress elements. International Journal for Numerical Methods in Engineering. 97(1). 32–67. 9 indexed citations
19.
Freitas, J. A. Teixeira de, Ionut Moldovan, & Milan Toma. (2009). Mixed and hybrid stress elements for biphasic media. Computers & Structures. 88(23-24). 1286–1299. 10 indexed citations
20.
Moldovan, Ionut & J. A. Teixeira de Freitas. (2008). Hybrid-Trefftz stress and displacement elements for dynamic analysis of bounded and unbounded saturated porous media. SHILAP Revista de lepidopterología. 289–303. 6 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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