This map shows the geographic impact of Davide Elmo'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 Davide Elmo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Davide Elmo more than expected).
This network shows the impact of papers produced by Davide Elmo. 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 Davide Elmo. The network helps show where Davide Elmo may publish in the future.
Co-authorship network of co-authors of Davide Elmo
This figure shows the co-authorship network connecting the top 25 collaborators of Davide Elmo.
A scholar is included among the top collaborators of Davide Elmo 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 Davide Elmo. Davide Elmo is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Elmo, Davide, et al.. (2018). A Proposed Probabilistic Analysis Methodology for Tunnel Support Cost Estimation Depending on the Construction Method. 52nd U.S. Rock Mechanics/Geomechanics Symposium.8 indexed citations
8.
Gao, Fuqiang, Peter Kaiser, D. Stead, Erik Eberhardt, & Davide Elmo. (2018). A Numerical Study on the Effect of Loading System Stiffness on Strainbursts. 52nd U.S. Rock Mechanics/Geomechanics Symposium.1 indexed citations
9.
Stead, Doug, et al.. (2017). A Review of the Application of Numerical Modelling in the Prediction of Depth of Spalling Damage around Underground Openings. RWTH Publications (RWTH Aachen).5 indexed citations
10.
Liu, Y., S. Nadolski, Davide Elmo, Bern Klein, & Malcolm J. Scoble. (2015). Use of Digital Imaging Processing Techniques to Characterise Block Caving Secondary Fragmentation and Implications for a Proposed Cave-to-Mill Approach.3 indexed citations
11.
Elmo, Davide, et al.. (2015). Numerical Simulation of Rock Cone Pullout and the Influence of Discrete Fracture Network Statistics on Foundation Anchor Capacity.1 indexed citations
12.
Eberhardt, Erik, et al.. (2015). Influence of Block Strength and Veining on Secondary Fragmentation Related to Block Caving.1 indexed citations
13.
Eberhardt, Erik, et al.. (2015). Transitioning from Open Pit to Underground Mass Mining: Meeting the Rock Engineering Challenges of Going Deeper.3 indexed citations
14.
Hunt, Christopher H., et al.. (2015). Characterising Groundwater in Rock Slopes using a Combined Remote Sensing - Numerical Modelling Approach.2 indexed citations
15.
Hutchinson, D. Jean, et al.. (2013). Impacts of Limited Data Collection Windows on Accurate Rock Simulation Using Discrete Fracture Networks.1 indexed citations
16.
Stead, D., et al.. (2013). Numerical Simulation of Damage During Laboratory Testing on Rock Using a 3D-FEMM/DEM Approach.4 indexed citations
17.
Elmo, Davide, et al.. (2011). Numerical Simulations of Scale Effects Under Varying Loading Conditions For Naturally Fractured Rock Masses And Implications For Rock For Rock Mass Strength Characterization And the Design of Overhanging Rock Slopes.2 indexed citations
18.
Elmo, Davide, et al.. (2011). Numerical Analysis of Caving Mechanism Using a Hybrid FEM/DEM Approach: Experience Gained And Lessons Learned.5 indexed citations
19.
Stead, D., et al.. (2010). A Photogrammetric Approach to Brittle Fracture Characterization In Mine Pillars.5 indexed citations
20.
Yan, Ming, Davide Elmo, & Doug Stead. (2007). Characterization of Step-path Failure Mechanisms: A Combined Field Based- Numerical Modeling Study.2 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.