D. Wilhelm

1.3k total citations · 1 hit paper
36 papers, 900 citations indexed

About

D. Wilhelm is a scholar working on Computational Mechanics, Aerospace Engineering and Materials Chemistry. According to data from OpenAlex, D. Wilhelm has authored 36 papers receiving a total of 900 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computational Mechanics, 12 papers in Aerospace Engineering and 7 papers in Materials Chemistry. Recurrent topics in D. Wilhelm's work include Nuclear reactor physics and engineering (8 papers), Nuclear Materials and Properties (6 papers) and Fluid Dynamics and Turbulent Flows (5 papers). D. Wilhelm is often cited by papers focused on Nuclear reactor physics and engineering (8 papers), Nuclear Materials and Properties (6 papers) and Fluid Dynamics and Turbulent Flows (5 papers). D. Wilhelm collaborates with scholars based in Switzerland, Germany and United States. D. Wilhelm's co-authors include D.R. Simbeck, R.L. Dickenson, Leonhard Kleiser, Bettina Jenny, Blas L. Valero‐Garcés, Eckart Meiburg, Frank Engelke, Armin Purea, C.H.M. Broeders and Günter Kessler and has published in prestigious journals such as Journal of Fluid Mechanics, Journal of Computational Physics and Annals of the New York Academy of Sciences.

In The Last Decade

D. Wilhelm

31 papers receiving 848 citations

Hit Papers

Syngas production for gas-to-liquids applications: techno... 2001 2026 2009 2017 2001 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Wilhelm Switzerland 10 401 340 209 144 138 36 900
Jia Luo China 17 390 1.0× 224 0.7× 126 0.6× 203 1.4× 31 0.2× 99 1.3k
Kwong Yung Germany 4 291 0.7× 177 0.5× 671 3.2× 498 3.5× 30 0.2× 4 1.4k
J.T.R. Watson United Kingdom 15 153 0.4× 67 0.2× 784 3.8× 391 2.7× 176 1.3× 22 1.4k
Mark J. McCready United States 20 190 0.5× 144 0.4× 371 1.8× 238 1.7× 500 3.6× 54 1.1k
Lars Christiansen Denmark 15 396 1.0× 466 1.4× 291 1.4× 190 1.3× 44 0.3× 37 973
Zoltán Kis Hungary 23 294 0.7× 34 0.1× 85 0.4× 60 0.4× 43 0.3× 103 1.6k
Roger Angel United States 14 57 0.1× 138 0.4× 165 0.8× 157 1.1× 82 0.6× 84 1.1k
J.F. Pauwels France 25 419 1.0× 121 0.4× 156 0.7× 79 0.5× 905 6.6× 71 1.6k
H. D. Australia 13 241 0.6× 48 0.1× 280 1.3× 246 1.7× 48 0.3× 20 826
А. В. Мохов Russia 16 284 0.7× 42 0.1× 116 0.6× 86 0.6× 112 0.8× 109 955

Countries citing papers authored by D. Wilhelm

Since Specialization
Citations

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

Fields of papers citing papers by D. Wilhelm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Wilhelm

This figure shows the co-authorship network connecting the top 25 collaborators of D. Wilhelm. A scholar is included among the top collaborators of D. Wilhelm 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 D. Wilhelm. D. Wilhelm 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.
Scarso, Alessandro, et al.. (2025). A deep learning framework for multiplet splitting classification in 1H NMR. Journal of Magnetic Resonance. 373. 107851–107851. 1 indexed citations
2.
Lorenzi, Flavio De, et al.. (2023). Modelling of Peristaltic Pumps with Respect to Viscoelastic Tube Material Properties and Fatigue Effects. Fluids. 8(9). 254–254. 2 indexed citations
3.
Caldarelli, Guido, et al.. (2023). Automatic classification of signal regions in 1H Nuclear Magnetic Resonance spectra. Frontiers in Artificial Intelligence. 5. 1116416–1116416. 8 indexed citations
4.
Paruzzo, Federico M., et al.. (2022). Deconvolution of 1D NMR spectra: A deep learning-based approach. Journal of Magnetic Resonance. 347. 107357–107357. 46 indexed citations
5.
Purea, Armin, et al.. (2022). Ultra Low Temperature Microturbine for Magic Angle Spinning System. Journal of Fluids Engineering. 144(8). 5 indexed citations
6.
Deb, Rajdeep, Andreas Hunkeler, D. Wilhelm, Patrick Jenny, & Beat H. Meier. (2022). Numerical modeling and design decisions for aerostatic bearings with relatively large nozzle sizes in Magic-Angle Spinning (MAS) systems. Tribology International. 175. 107855–107855. 4 indexed citations
7.
Cousin, Samuel F., Cyril Charlier, Pavel Kadeřávek, et al.. (2016). High-resolution two-field nuclear magnetic resonance spectroscopy. Physical Chemistry Chemical Physics. 18(48). 33187–33194. 25 indexed citations
8.
Wilhelm, D., Armin Purea, & Frank Engelke. (2015). Fluid flow dynamics in MAS systems. Journal of Magnetic Resonance. 257. 51–63. 14 indexed citations
9.
Wilhelm, D.. (2015). Rotating Flow Simulations with OpenFOAM. Zenodo (CERN European Organization for Nuclear Research). 1–7. 7 indexed citations
10.
Meiburg, Eckart, et al.. (2004). Density‐Driven Instabilities of Variable‐Viscosity Miscible Fluids in a Capillary Tube. Annals of the New York Academy of Sciences. 1027(1). 383–402. 4 indexed citations
11.
Jenny, Bettina, D. Wilhelm, & Blas L. Valero‐Garcés. (2003). The Southern Westerlies in Central Chile: Holocene precipitation estimates based on a water balance model for Laguna Aculeo (33°50′S). Climate Dynamics. 20(2). 269–280. 61 indexed citations
12.
Meiburg, Eckart, et al.. (2003). Density-driven instabilities of miscible fluids in a capillary tube: linear stability analysis. Journal of Fluid Mechanics. 497. 99–121. 12 indexed citations
13.
Wilhelm, D. & Leonhard Kleiser. (2000). Stable and unstable formulations of the convection operator in spectral element simulations. Applied Numerical Mathematics. 33(1-4). 275–280. 9 indexed citations
14.
Blanchat, Thomas K., et al.. (1999). Experiments on Corium Dispersion after Lower Head Failure at Moderate Pressure. University of North Texas Digital Library (University of North Texas). 29(4). 235–8. 2 indexed citations
15.
Kaiser, Antonio Sánchez, et al.. (1998). Experiments on the behaviour of a hot melt injected into sodium. Experimental Thermal and Fluid Science. 18(1). 48–69. 14 indexed citations
16.
Wilhelm, D., Carlos Härtel, & Helmut Eckelmann. (1998). On the Relation between Fronts and High-Shear Layers in Wall Turbulence. Flow Turbulence and Combustion. 60(1). 87–103. 1 indexed citations
17.
Tobita, Yoshiharu, et al.. (1997). Status and achievement of assessment program for SIMMER-III, a multiphase, multicomponent code for LMFR safety analysis. 18 indexed citations
18.
Wilhelm, D.. (1994). Darstellung und Analyse der Wandturbulenz anhand von Simulationsdaten. elib (German Aerospace Center). 1 indexed citations
19.
Simbeck, D.R., et al.. (1994). The fluid bed market: Status, trends, & outlook. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 3 indexed citations
20.
Bohl, W.R. & D. Wilhelm. (1992). The Advanced Fluid Dynamics Model Program: Scope and Accomplishment. Nuclear Technology. 99(3). 366–373. 8 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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