Henning Wessels

801 total citations · 1 hit paper
21 papers, 539 citations indexed

About

Henning Wessels is a scholar working on Statistical and Nonlinear Physics, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Henning Wessels has authored 21 papers receiving a total of 539 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistical and Nonlinear Physics, 6 papers in Mechanical Engineering and 5 papers in Mechanics of Materials. Recurrent topics in Henning Wessels's work include Model Reduction and Neural Networks (8 papers), Probabilistic and Robust Engineering Design (5 papers) and Structural Health Monitoring Techniques (4 papers). Henning Wessels is often cited by papers focused on Model Reduction and Neural Networks (8 papers), Probabilistic and Robust Engineering Design (5 papers) and Structural Health Monitoring Techniques (4 papers). Henning Wessels collaborates with scholars based in Germany, Switzerland and United States. Henning Wessels's co-authors include Christian Weißenfels, Peter Wriggers, Rolf Mahnken, Michele Marino, Fadi Aldakheel, Blaž Hudobivnik, Jason K. Eshraghian, Tarek I. Zohdi, Ulrich Römer and Laura De Lorenzis and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computer Methods in Applied Mechanics and Engineering and Mechanical Systems and Signal Processing.

In The Last Decade

Henning Wessels

16 papers receiving 512 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Physics informed neural networks for continuum micromechanics

2022 139 citations Henning Wessels, Rolf Mahnken et al. Computer Methods in Applied Mechanics and Engineering profile →

Peers

Henning Wessels

SNP

ME

CM

MM

AE

Christian Weißenfels Germany

Houpu Yao United States

Mingwu Li China

Erman Guleryuz United States

Nikolaos N. Vlassis United States

C. Kane India

C. Steve Suh United States

Olivier Goury France

Yu-Ching Yang Taiwan

Qiaofeng Li China

Christian Weißenfels Germany

Henning Wessels

136 ×0.7

SNP

207 ×1.2

ME

242 ×1.5

CM

274 ×1.8

MM

73 ×1.2

AE

Citations per year, relative to Henning Wessels Henning Wessels (= 1×) peers Christian Weißenfels

Countries citing papers authored by Henning Wessels

Since Specialization

Citations

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

Fields of papers citing papers by Henning Wessels

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Henning Wessels

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

All Works

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20 of 20 papers shown

1.

Cirak, Fehmi, et al.. (2026). Unsupervised Constitutive Model Discovery from Sparse and Noisy Data. Computer Methods in Applied Mechanics and Engineering. 452. 118722–118722.

2.

Lorenzis, Laura De, et al.. (2025). Automated constitutive model discovery by pairing sparse regression algorithms with model selection criteria. Computer Methods in Applied Mechanics and Engineering. 449. 118551–118551. 1 indexed citations

3.

Römer, Ulrich, et al.. (2025). Gaussian processes enabled model calibration in the context of deep geological disposal. SHILAP Revista de lepidopterología. 6.

4.

Wessels, Henning, et al.. (2025). Mechanical state estimation with a Polynomial-Chaos-Based Statistical Finite Element Method. Computer Methods in Applied Mechanics and Engineering. 441. 117970–117970. 1 indexed citations

5.

Eshraghian, Jason K., et al.. (2024). Spiking neural networks for nonlinear regression. Royal Society Open Science. 11(5). 231606–231606. 15 indexed citations

6.

Römer, Ulrich, et al.. (2024). Reduced and All-At-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics. Applied Mechanics Reviews. 77(4). 13 indexed citations

7.

Wessels, Henning, et al.. (2024). Towards model‐guided feedback control of hydrogels bioprinting. PAMM. 24(3).

8.

Wessels, Henning, et al.. (2024). Parameter identification and uncertainty propagation of hydrogel coupled diffusion-deformation using POD-based reduced-order modeling. Computational Mechanics. 75(2). 515–545. 3 indexed citations

9.

Wessels, Henning, et al.. (2023). Generative adversarial networks for three‐dimensional microstructure generation. PAMM. 22(1). 2 indexed citations

10.

Wessels, Henning, et al.. (2023). Inferring displacement fields from sparse measurements using the statistical finite element method. Mechanical Systems and Signal Processing. 200. 110574–110574. 9 indexed citations

11.

Eshraghian, Jason K., et al.. (2023). Spiking Neural Networks for Nonlinear Regression. 13 indexed citations

12.

Aldakheel, Fadi, et al.. (2022). Current Trends and Open Problems in Computational Mechanics. Cineca Institutional Research Information System (Tor Vergata University). 63 indexed citations

13.

Wessels, Henning, et al.. (2022). Three-dimensional microstructure generation using generative adversarial neural networks in the context of continuum micromechanics. Computer Methods in Applied Mechanics and Engineering. 400. 115497–115497. 38 indexed citations

14.

Wessels, Henning, et al.. (2022). Physics informed neural networks for continuum micromechanics. Computer Methods in Applied Mechanics and Engineering. 393. 114790–114790. 139 indexed citations breakdown →

15.

Wessels, Henning, et al.. (2022). Identification of Material Parameters from Full-Field Displacement Data Using Physics-Informed Neural Networks. 813–820. 3 indexed citations

16.

Wessels, Henning, et al.. (2021). Physics informed neural networks for continuum micromechanics. PAMM. 21(1). 2 indexed citations

17.

Wessels, Henning, Christian Weißenfels, & Peter Wriggers. (2020). The neural particle method – An updated Lagrangian physics informed neural network for computational fluid dynamics. Computer Methods in Applied Mechanics and Engineering. 368. 113127–113127. 99 indexed citations

18.

Wessels, Henning, et al.. (2019). Generating virtual process maps of SLM using powder-scale SPH simulations. Computational Particle Mechanics. 7(4). 655–677. 56 indexed citations

19.

Wessels, Henning, et al.. (2018). Investigation of heat source modeling for selective laser melting. Computational Mechanics. 63(5). 949–970. 43 indexed citations

20.

Wessels, Henning, Christian Weißenfels, & Peter Wriggers. (2018). Metal particle fusion analysis for additive manufacturing using the stabilized optimal transportation meshfree method. Computer Methods in Applied Mechanics and Engineering. 339. 91–114. 35 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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