Masaya Muto

517 total citations
25 papers, 435 citations indexed

About

Masaya Muto is a scholar working on Computational Mechanics, Ocean Engineering and Biomedical Engineering. According to data from OpenAlex, Masaya Muto has authored 25 papers receiving a total of 435 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Mechanics, 7 papers in Ocean Engineering and 7 papers in Biomedical Engineering. Recurrent topics in Masaya Muto's work include Combustion and flame dynamics (13 papers), Particle Dynamics in Fluid Flows (6 papers) and Advanced Combustion Engine Technologies (5 papers). Masaya Muto is often cited by papers focused on Combustion and flame dynamics (13 papers), Particle Dynamics in Fluid Flows (6 papers) and Advanced Combustion Engine Technologies (5 papers). Masaya Muto collaborates with scholars based in Japan, United Kingdom and China. Masaya Muto's co-authors include Ryoichi Kurose, Satoru Komori, Hiroaki Watanabe, Tomoaki Kitano, Nobuyuki Oshima, Makoto Tsubokura, Saravanan Balusamy, Simone Hochgreb, Kenji Tanno and Nilanjan Chakraborty and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Hydrogen Energy and Fuel.

In The Last Decade

Masaya Muto

21 papers receiving 427 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masaya Muto Japan 10 376 232 138 118 68 25 435
Nijso Beishuizen Netherlands 5 373 1.0× 97 0.4× 163 1.2× 123 1.0× 55 0.8× 10 416
David Honoré France 11 311 0.8× 147 0.6× 162 1.2× 96 0.8× 65 1.0× 32 382
Bertrand Naud Spain 13 487 1.3× 92 0.4× 327 2.4× 137 1.2× 70 1.0× 34 510
Stefano Orsino United States 9 534 1.4× 184 0.8× 332 2.4× 151 1.3× 93 1.4× 42 583
Tomoaki Kitano Japan 9 535 1.4× 117 0.5× 281 2.0× 180 1.5× 110 1.6× 14 571
Hendrik Nicolai Germany 13 327 0.9× 220 0.9× 151 1.1× 76 0.6× 88 1.3× 52 401
Jean-Charles Sautet France 14 405 1.1× 46 0.2× 244 1.8× 133 1.1× 155 2.3× 32 483
Shih-Yang Hsieh United States 7 651 1.7× 80 0.3× 270 2.0× 89 0.8× 199 2.9× 16 676
Franziska Hunger Germany 13 414 1.1× 85 0.4× 326 2.4× 122 1.0× 74 1.1× 24 460
Martin Rieth Germany 15 765 2.0× 339 1.5× 487 3.5× 196 1.7× 196 2.9× 31 848

Countries citing papers authored by Masaya Muto

Since Specialization
Citations

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

Fields of papers citing papers by Masaya Muto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masaya Muto

This figure shows the co-authorship network connecting the top 25 collaborators of Masaya Muto. A scholar is included among the top collaborators of Masaya Muto 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 Masaya Muto. Masaya Muto 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.
Muto, Masaya. (2025). Tabulated Chemistry Models for Numerical Simulation of Combustion Flow Field. Fluids. 10(4). 83–83. 1 indexed citations
2.
Muto, Masaya, et al.. (2025). DEM-CFD modeling of limestone flowing-down in a combustion field in a rotary kiln. Journal of Thermal Science and Technology. 20(2). 25–147.
3.
Hayashi, Jun, et al.. (2020). Soot formation characteristics in a pulverized coal flame formed in a swirling flow. Advanced Powder Technology. 31(9). 3921–3927. 5 indexed citations
4.
Muto, Masaya, Hiroaki Watanabe, & Ryoichi Kurose. (2019). Large eddy simulation of pulverized coal combustion in multi-burner system–effect of in-furnace blending method on NO emission. Advanced Powder Technology. 30(12). 3153–3162. 23 indexed citations
5.
Taniguchi, Atsushi, Y. Kuriyama, T. Uesugi, et al.. (2019). Experimental study of multiplex energy recovery internal target ring. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 953. 162988–162988.
6.
Muto, Masaya, et al.. (2018). Numerical simulation of soot formation in pulverized coal combustion with detailed chemical reaction mechanism. Advanced Powder Technology. 29(5). 1119–1127. 34 indexed citations
7.
Ahmed, Umair, et al.. (2018). Statistics of reaction progress variable and mixture fraction gradients of a pulverised coal jet flame using Direct Numerical Simulation data. Proceedings of the Combustion Institute. 37(3). 2821–2830. 16 indexed citations
8.
Muto, Masaya, et al.. (2017). Direct numerical simulation of ignition of syngas (H2/CO) mixtures with temperature and composition stratifications relevant to HCCI conditions. International Journal of Hydrogen Energy. 42(41). 26152–26161. 12 indexed citations
9.
Muto, Masaya, et al.. (2016). Numerical simulation of ignition in pulverized coal combustion with detailed chemical reaction mechanism. Fuel. 190. 136–144. 56 indexed citations
10.
Muto, Masaya. (2015). Prediction of NO<sub>x</sub> Formation in Pulverized Coal Combustion Fields Using Large-eddy Simulation. Journal of the Society of Powder Technology Japan. 52(11). 658–662. 2 indexed citations
11.
Muto, Masaya, et al.. (2015). Direct numerical simulation of a pulverized coal jet flame employing a global volatile matter reaction scheme based on detailed reaction mechanism. Combustion and Flame. 162(12). 4391–4407. 112 indexed citations
12.
Zhang, Wei, Masaya Muto, Kotaro Hori, Hiroaki Watanabe, & Toshiaki KITAGAWA. (2015). Numerical investigation of motion of a non-spherical particle (Effects of gas blowing-out on motion of a particle in a uniform flow). SHILAP Revista de lepidopterología. 81(827). 15–68. 3 indexed citations
13.
14.
Watanabe, Hiroaki, et al.. (2014). Effects of Parcel Model on the Particle Motion in a Turbulent Mixing Layer. Journal of the Society of Powder Technology Japan. 51(12). 846–855. 2 indexed citations
15.
Muto, Masaya, et al.. (2013). Effect of Parcel Models on Turbulent Property and Scalar Diffusion Yield from Dispersed Liquid Particles in a Particle-laden Turbulent Mixing Layer. Journal of the Society of Powder Technology Japan. 50(9). 646–655. 2 indexed citations
16.
Muto, Masaya, Makoto Tsubokura, & Nobuyuki Oshima. (2012). Negative Magnus lift on a rotating sphere at around the critical Reynolds number. Physics of Fluids. 24(1). 50 indexed citations
17.
Muto, Masaya, Makoto Tsubokura, & Nobuyuki Oshima. (2011). Numerical Simulation of Negative Magnus Force on a Rotating Sphere. TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series B. 77(775). 781–792.
18.
Muto, Masaya, Hiroaki Watanabe, Makoto Tsubokura, & Nobuyuki Oshima. (2011). Negative Magnus Effect on a Rotating Sphere at around the Critical Reynolds Number. Journal of Physics Conference Series. 318(3). 32021–32021. 7 indexed citations
19.
Muto, Masaya, et al.. (2009). Drag Force on Particles at High Volume Fraction(Fluids Engineering). TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series B. 75(749). 61–67.
20.
Sakai, I., Y Arakaki, Kebin Fan, et al.. (2004). OPPOSITE FIELD SEPTUM MAGNET SYSTEM FOR THE J-PARC 50- GEV RING INJECTION *. 3 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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