Todd Chapman

981 total citations
8 papers, 688 citations indexed

About

Todd Chapman is a scholar working on Statistical and Nonlinear Physics, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Todd Chapman has authored 8 papers receiving a total of 688 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistical and Nonlinear Physics, 4 papers in Mechanical Engineering and 3 papers in Mechanics of Materials. Recurrent topics in Todd Chapman's work include Model Reduction and Neural Networks (4 papers), Probabilistic and Robust Engineering Design (3 papers) and Epoxy Resin Curing Processes (3 papers). Todd Chapman is often cited by papers focused on Model Reduction and Neural Networks (4 papers), Probabilistic and Robust Engineering Design (3 papers) and Epoxy Resin Curing Processes (3 papers). Todd Chapman collaborates with scholars based in United States, United Kingdom and China. Todd Chapman's co-authors include Charbel Farhat, Philip Avery, Julien Cortial, Regina M. Black, James C. Seferis, R. Byron Pipes, John W. Gillespie, J. W. Gillespie, I. M. Ward and G. Capaccio and has published in prestigious journals such as Polymer, AIAA Journal and International Journal for Numerical Methods in Engineering.

In The Last Decade

Todd Chapman

8 papers receiving 665 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Todd Chapman United States	7	393	228	214	195	173	8	688
Chady Ghnatios France	14	240 0.6×	85 0.4×	278 1.3×	254 1.3×	129 0.7×	84	698
F. Chinesta France	11	163 0.4×	77 0.3×	127 0.6×	254 1.3×	122 0.7×	19	532
A. Poitou France	13	81 0.2×	51 0.2×	264 1.2×	370 1.9×	145 0.8×	30	688
F. A. Brogan United States	15	106 0.3×	89 0.4×	201 0.9×	566 2.9×	178 1.0×	38	957
G. Cederbaum Israel	16	46 0.1×	97 0.4×	161 0.8×	550 2.8×	34 0.2×	53	752
K. Subbaraj Canada	7	55 0.1×	27 0.1×	125 0.6×	204 1.0×	167 1.0×	10	694
Qun Huang China	19	107 0.3×	36 0.2×	239 1.1×	522 2.7×	78 0.5×	49	875
Zhiyong Zhang China	13	81 0.2×	59 0.3×	625 2.9×	221 1.1×	143 0.8×	46	885
K. Dems Poland	17	24 0.1×	189 0.8×	136 0.6×	643 3.3×	244 1.4×	49	962
Javad Alamatian Iran	13	22 0.1×	33 0.1×	140 0.7×	296 1.5×	71 0.4×	36	550

Countries citing papers authored by Todd Chapman

Since Specialization

Citations

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

Fields of papers citing papers by Todd Chapman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Todd Chapman

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

All Works

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8 of 8 papers shown

Farhat, Charbel, Radek Tezaur, Todd Chapman, Philip Avery, & Christian Soize. (2019). Feasible Probabilistic Learning Method for Model-Form Uncertainty Quantification in Vibration Analysis. AIAA Journal. 57(11). 4978–4991. 30 indexed citations

Chapman, Todd, et al.. (2016). Accelerated mesh sampling for the hyper reduction of nonlinear computational models. International Journal for Numerical Methods in Engineering. 109(12). 1623–1654. 48 indexed citations

Farhat, Charbel, Todd Chapman, & Philip Avery. (2015). Structure‐preserving, stability, and accuracy properties of the energy‐conserving sampling and weighting method for the hyper reduction of nonlinear finite element dynamic models. International Journal for Numerical Methods in Engineering. 102(5). 1077–1110. 189 indexed citations

Farhat, Charbel, Philip Avery, Todd Chapman, & Julien Cortial. (2014). Dimensional reduction of nonlinear finite element dynamic models with finite rotations and energy‐based mesh sampling and weighting for computational efficiency. International Journal for Numerical Methods in Engineering. 98(9). 625–662. 231 indexed citations

Gillespie, J. W. & Todd Chapman. (1993). The Influence of Residual Stresses on Mode I Interlaminar Fracture of Thermoplastic Composites. Journal of Thermoplastic Composite Materials. 6(2). 160–174. 12 indexed citations

Chapman, Todd, John W. Gillespie, R. Byron Pipes, Regina M. Black, & James C. Seferis. (1990). Prediction of Process-Induced Residual Stresses in Thermoplastic Composites. Journal of Composite Materials. 24(6). 616–643. 152 indexed citations

Chapman, Todd, et al.. (1988). Thermal skin/core residual stresses induced during cooling of thermoplastic matrix composites. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 74. 449–458. 6 indexed citations

Capaccio, G., Todd Chapman, & I. M. Ward. (1975). Preparation of ultra-high modulus linear poly-ethylenes: effect of initial crystallization conditions. Polymer. 16(6). 469–469. 20 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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