William Arrighi

445 total citations
7 papers, 330 citations indexed

About

William Arrighi is a scholar working on Civil and Structural Engineering, Mechanics of Materials and Computational Theory and Mathematics. According to data from OpenAlex, William Arrighi has authored 7 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Civil and Structural Engineering, 2 papers in Mechanics of Materials and 2 papers in Computational Theory and Mathematics. Recurrent topics in William Arrighi's work include Topology Optimization in Engineering (3 papers), Composite Material Mechanics (2 papers) and Manufacturing Process and Optimization (1 paper). William Arrighi is often cited by papers focused on Topology Optimization in Engineering (3 papers), Composite Material Mechanics (2 papers) and Manufacturing Process and Optimization (1 paper). William Arrighi collaborates with scholars based in United States. William Arrighi's co-authors include D. White, Jun Kudo, Seth Watts, Daniel A. Tortorelli, Ghaleb Abdulla, Terence Critchlow, R. L. Berger, T. Chapman, S. Brunner and Jeffrey W. Banks and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, International Journal for Numerical Methods in Engineering and SIAM Journal on Scientific Computing.

In The Last Decade

William Arrighi

7 papers receiving 321 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William Arrighi United States	5	192	133	68	59	51	7	330
Amélie Fau France	12	133 0.7×	121 0.9×	100 1.5×	75 1.3×	89 1.7×	33	446
James E. Warner United States	10	151 0.8×	112 0.8×	49 0.7×	108 1.8×	26 0.5×	33	388
Liangxian Gu China	13	109 0.6×	112 0.8×	87 1.3×	96 1.6×	22 0.4×	51	466
Jilei Zhou China	10	256 1.3×	99 0.7×	28 0.4×	84 1.4×	59 1.2×	28	503
Yonggyun Yu South Korea	10	250 1.3×	83 0.6×	91 1.3×	71 1.2×	12 0.2×	25	412
Yuanxian Gu China	12	212 1.1×	187 1.4×	158 2.3×	89 1.5×	16 0.3×	37	475
Geoffrey Bomarito United States	11	63 0.3×	103 0.8×	24 0.4×	155 2.6×	39 0.8×	28	398
Diego Hayashi Alonso Brazil	11	128 0.7×	51 0.4×	98 1.4×	95 1.6×	121 2.4×	24	334
François Louf France	12	181 0.9×	71 0.5×	18 0.3×	110 1.9×	56 1.1×	48	389
Lei Gu China	9	213 1.1×	257 1.9×	157 2.3×	94 1.6×	11 0.2×	30	581

Countries citing papers authored by William Arrighi

Since Specialization

Citations

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

Fields of papers citing papers by William Arrighi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Arrighi

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

All Works

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7 of 7 papers shown

1.

Watts, Seth, William Arrighi, Jun Kudo, Daniel A. Tortorelli, & D. White. (2020). Correction to: Simple, accurate surrogate models of the elasticresponse of three-dimensional open truss micro-architectures with applications tomultiscale topology design. Structural and Multidisciplinary Optimization. 61(4). 1759–1762. 4 indexed citations

2.

Watts, Seth, William Arrighi, Jun Kudo, Daniel A. Tortorelli, & D. White. (2019). Simple, accurate surrogate models of the elastic response of three-dimensional open truss micro-architectures with applications to multiscale topology design. Structural and Multidisciplinary Optimization. 60(5). 1887–1920. 80 indexed citations

3.

Choi, Youngsoo, et al.. (2019). libROM. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations

4.

Banks, Jeffrey W., et al.. (2019). High-Order Accurate Conservative Finite Difference Methods for Vlasov Equations in 2D+2V. SIAM Journal on Scientific Computing. 41(5). B953–B982. 11 indexed citations

5.

White, D., William Arrighi, Jun Kudo, & Seth Watts. (2018). Multiscale topology optimization using neural network surrogate models. Computer Methods in Applied Mechanics and Engineering. 346. 1118–1135. 191 indexed citations

6.

Arrighi, William, et al.. (2016). Limited‐memory adaptive snapshot selection for proper orthogonal decomposition. International Journal for Numerical Methods in Engineering. 109(2). 198–217. 34 indexed citations

7.

Abdulla, Ghaleb, Terence Critchlow, & William Arrighi. (2004). Simulation data as data streams. ACM SIGMOD Record. 33(1). 89–94. 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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