F. Mascari

563 total citations
52 papers, 266 citations indexed

About

F. Mascari is a scholar working on Aerospace Engineering, Materials Chemistry and Statistics, Probability and Uncertainty. According to data from OpenAlex, F. Mascari has authored 52 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Aerospace Engineering, 30 papers in Materials Chemistry and 10 papers in Statistics, Probability and Uncertainty. Recurrent topics in F. Mascari's work include Nuclear reactor physics and engineering (40 papers), Nuclear Engineering Thermal-Hydraulics (39 papers) and Nuclear Materials and Properties (29 papers). F. Mascari is often cited by papers focused on Nuclear reactor physics and engineering (40 papers), Nuclear Engineering Thermal-Hydraulics (39 papers) and Nuclear Materials and Properties (29 papers). F. Mascari collaborates with scholars based in Italy, United States and France. F. Mascari's co-authors include Brian Woods, Andrea Bersano, L.E. Herranz, Francesco Saverio D'Auria, Sandro Paci, Francesco Di Maio, Víctor Hugo Sánchez-Espinoza, Enrico Zio, Olivia Coindreau and Luke Lebel and has published in prestigious journals such as Energies, Nuclear Engineering and Design and Progress in Nuclear Energy.

In The Last Decade

F. Mascari

44 papers receiving 255 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
F. Mascari Italy 9 235 147 67 19 16 52 266
Yifeng Che United States 6 199 0.8× 240 1.6× 38 0.6× 14 0.7× 33 2.1× 13 296
Jordi Freixa Spain 10 269 1.1× 162 1.1× 65 1.0× 20 1.1× 31 1.9× 41 290
Pavlin Groudev Bulgaria 10 274 1.2× 222 1.5× 62 0.9× 67 3.5× 17 1.1× 63 325
F. Reventós Spain 14 406 1.7× 226 1.5× 116 1.7× 38 2.0× 43 2.7× 49 458
Egidijus Urbonavičius Lithuania 7 133 0.6× 111 0.8× 24 0.4× 65 3.4× 5 0.3× 37 170
M. Sonnenkalb Germany 9 207 0.9× 233 1.6× 44 0.7× 77 4.1× 19 1.2× 21 312
T. Skorek Germany 6 177 0.8× 53 0.4× 121 1.8× 5 0.3× 16 1.0× 15 193
P. Méloni Italy 9 223 0.9× 143 1.0× 16 0.2× 11 0.6× 41 2.6× 46 249
J. Birchley Switzerland 11 227 1.0× 256 1.7× 27 0.4× 43 2.3× 22 1.4× 26 309
Russell Gardner United States 8 260 1.1× 284 1.9× 14 0.2× 43 2.3× 31 1.9× 8 324

Countries citing papers authored by F. Mascari

Since Specialization
Citations

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

Fields of papers citing papers by F. Mascari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Mascari

This figure shows the co-authorship network connecting the top 25 collaborators of F. Mascari. A scholar is included among the top collaborators of F. Mascari 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 F. Mascari. F. Mascari 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.
Giannetti, Fabio, et al.. (2025). Analyses of the MELCOR capability to simulate integral PWR using passive systems in a DBA scenario. Nuclear Engineering and Design. 437. 114004–114004.
2.
3.
Zhang, Jinzhao, Michel Havet, Junlin Zheng, et al.. (2024). Analyses of design extension conditions without significant fuel degradation for operating nuclear power plants: An OECD/NEA review. Nuclear Engineering and Design. 425. 113320–113320. 1 indexed citations
4.
Mascari, F., et al.. (2024). Scaling-up assessment of natural circulation phenomena in integral Small Modular Reactor by TRACE code. Nuclear Engineering and Design. 420. 113018–113018. 2 indexed citations
5.
Ahn, Kwang-Il, Shawkat Ali, Xuewu Cao, et al.. (2024). Uncertainty and Sensitivity Analyses for Postulated Severe Accidents of Reference PWRs and SMRs in the Frame of the IAEA CRP and Relevant Insights. Nuclear Technology. 1–27. 1 indexed citations
6.
Mascari, F., Francesco Saverio D'Auria, D. Bestion, et al.. (2023). OECD/NEA/CSNI state-of-the-art report on scaling in system thermal-hydraulics applications to nuclear reactor safety and design (The S-SOAR). Nuclear Engineering and Design. 416. 112750–112750. 6 indexed citations
7.
Mascari, F., et al.. (2022). Analysis of BDBA sequences in a generic IRIS reactor using ASTEC code. Annals of Nuclear Energy. 182. 109611–109611. 3 indexed citations
8.
Maio, P.A. Di, et al.. (2022). Cold Leg LBLOCA uncertainty analysis using TRACE/DAKOTA coupling. Journal of Physics Conference Series. 2177(1). 12023–12023. 3 indexed citations
9.
Mascari, F., et al.. (2022). Analysis of an unmitigated 2-inch cold leg LOCA transient with ASTEC and MELCOR codes. Journal of Physics Conference Series. 2177(1). 12024–12024. 1 indexed citations
10.
Bersano, Andrea, et al.. (2021). Qualification of RELAP5-3D code condensation model against full-scale PERSEO Test 9. Progress in Nuclear Energy. 139. 103891–103891. 2 indexed citations
11.
Maio, Francesco Di, et al.. (2021). A Bayesian framework of inverse uncertainty quantification with principal component analysis and Kriging for the reliability analysis of passive safety systems. Nuclear Engineering and Design. 379. 111230–111230. 25 indexed citations
12.
Herranz, L.E., et al.. (2021). The EC MUSA Project on Management and Uncertainty of Severe Accidents: Main Pillars and Status. Energies. 14(15). 4473–4473. 30 indexed citations
13.
Bersano, Andrea, et al.. (2020). Qualification of RELAP5-3D Code Against the In-pool Passive Energy Removal System PERSEO Data. Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference. 1150–1157. 5 indexed citations
14.
Bersano, Andrea, et al.. (2020). Ingress of Coolant Event simulation with TRACE code with accuracy evaluation and coupled DAKOTA Uncertainty Analysis. Fusion Engineering and Design. 159. 111944–111944. 13 indexed citations
15.
Bersano, Andrea, et al.. (2019). Validation of RELAP5-3D thermal-hydraulic code against full-scale PERSEO Test 9. 2 indexed citations
16.
Mascari, F., et al.. (2018). ASTEC–MAAP Comparison of a 2 Inch Cold Leg LOCA until RPV Failure. Science and Technology of Nuclear Installations. 2018. 1–24. 5 indexed citations
17.
Mascari, F., et al.. (2017). Analysis of unmitigated large break loss of coolant accidents using MELCOR code. Journal of Physics Conference Series. 923. 12009–12009. 5 indexed citations
18.
Mascari, F., et al.. (2015). Scaling issues for the experimental characterization of reactor coolant system in integral test facilities and role of system code as extrapolation tool. CINECA IRIS Institutial research information system (University of Pisa). 4921–4934. 17 indexed citations
19.
Mascari, F., et al.. (2012). ANALYSES OF TRACE-PARCS COUPLING CAPABILITY. 1 indexed citations
20.
Mascari, F., et al.. (2009). TRACE, RELAP5 Mod 3.3, and RELAP5-3D Code Comparison of OSU-MASLWR-001 Test. Nova Science Publishers (Nova Science Publishers, Inc.). 101. 892–893. 4 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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