Carlo Graziani

507 total citations
11 papers, 138 citations indexed

About

Carlo Graziani is a scholar working on Computational Mechanics, Aerospace Engineering and Astronomy and Astrophysics. According to data from OpenAlex, Carlo Graziani has authored 11 papers receiving a total of 138 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Mechanics, 4 papers in Aerospace Engineering and 3 papers in Astronomy and Astrophysics. Recurrent topics in Carlo Graziani's work include Computational Fluid Dynamics and Aerodynamics (5 papers), Fluid Dynamics and Turbulent Flows (3 papers) and Laser-Plasma Interactions and Diagnostics (3 papers). Carlo Graziani is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (5 papers), Fluid Dynamics and Turbulent Flows (3 papers) and Laser-Plasma Interactions and Diagnostics (3 papers). Carlo Graziani collaborates with scholars based in United States, United Kingdom and Australia. Carlo Graziani's co-authors include Petros Tzeferacos, D. Q. Lamb, Milad Fatenejad, Klaus Weide, G. Gregori, N. Flocke, J. Meinecke, Anthony Scopatz, R. Sina and A. K. Harding and has published in prestigious journals such as Journal of Computational Physics, Journal of Scientific Computing and The International Journal of High Performance Computing Applications.

In The Last Decade

Carlo Graziani

10 papers receiving 135 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carlo Graziani United States	7	73	42	34	29	25	11	138
Thibaut Lery Ireland	7	117 1.6×	162 3.9×	24 0.7×	26 0.9×	41 1.6×	16	229
T. Olson United States	8	114 1.6×	155 3.7×	45 1.3×	11 0.4×	30 1.2×	14	212
Edward J. Mannery United States	7	29 0.4×	146 3.5×	19 0.6×	5 0.2×	26 1.0×	23	198
Piotr A. Ra̧czka Poland	9	195 2.7×	13 0.3×	10 0.3×	65 2.2×	63 2.5×	31	208
Roberto Viotti Italy	11	44 0.6×	353 8.4×	41 1.2×	4 0.1×	23 0.9×	33	382
V. M. Balebanov Russia	7	19 0.3×	118 2.8×	9 0.3×	8 0.3×	22 0.9×	25	172
Fumie Akimoto Japan	8	53 0.7×	162 3.9×	9 0.3×	9 0.3×	20 0.8×	15	207
F. Palmonari Italy	8	83 1.1×	55 1.3×	3 0.1×	5 0.2×	35 1.4×	19	162
P. D. Usher United States	9	70 1.0×	196 4.7×	41 1.2×	3 0.1×	12 0.5×	62	244
Stephen M. Doe United States	6	131 1.8×	314 7.5×	34 1.0×	2 0.1×	19 0.8×	16	339

Countries citing papers authored by Carlo Graziani

Since Specialization

Citations

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

Fields of papers citing papers by Carlo Graziani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlo Graziani

This figure shows the co-authorship network connecting the top 25 collaborators of Carlo Graziani. A scholar is included among the top collaborators of Carlo Graziani 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 Carlo Graziani. Carlo Graziani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

Lee, Dongwook, et al.. (2019). A variable high-order shock-capturing finite difference method with GP-WENO. Journal of Computational Physics. 381. 189–217. 8 indexed citations

Ceccarelli, Claudio, et al.. (2017). Quality Improvements In Variance Estimation For The Labour Force Survey. IRIS Research product catalog (Sapienza University of Rome). 71(4). 11–20. 1 indexed citations

Lee, Dongwook, et al.. (2017). A New Class of High-Order Methods for Fluid Dynamics Simulations Using Gaussian Process Modeling: One-Dimensional Case. Journal of Scientific Computing. 76(1). 443–480. 7 indexed citations

Lee, Dongwook, et al.. (2017). New High-order Methods using Gaussian Processes for Computational Fluid Dynamics Simulations. Journal of Physics Conference Series. 837. 12018–12018. 1 indexed citations

Tzeferacos, Petros, Milad Fatenejad, N. Flocke, et al.. (2014). FLASH MHD simulations of experiments that study shock-generated magnetic fields. High Energy Density Physics. 17. 24–31. 60 indexed citations

Fatenejad, Milad, B. Fryxell, J.G. Wohlbier, et al.. (2012). Collaborative comparison of simulation codes for high-energy-density physics applications. High Energy Density Physics. 9(1). 63–66. 21 indexed citations

Dubey, Anshu, A. C. Calder, Christopher Daley, et al.. (2012). Pragmatic optimizations for better scientific utilization of large supercomputers. The International Journal of High Performance Computing Applications. 27(3). 360–373. 12 indexed citations

Dubey, Anshu, Robert Fisher, Carlo Graziani, et al.. (2008). Challenges of Extreme Computing using the FLASH code. ASPC. 385. 145. 12 indexed citations

Graziani, Carlo, Donald Q. Lamb, & Jean M. Quashnock. (1998). Are the four gamma-ray bursts of 1996 October 27–29 due to repetition of a single source?. ArXiv.org. 161–165. 2 indexed citations

10.

Graziani, Carlo & Donald Q. Lamb. (1996). Likelihood methods and classical burster repetition. AIP conference proceedings. 366. 196–200.

11.

Graziani, Carlo, A. K. Harding, & R. Sina. (1995). Elimination of resonant divergences from QED in superstrong magnetic fields. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 51(12). 7097–7110. 14 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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