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Ryan T. Armstrong

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 55 3079 2946 161 157 271 8922

Ryan T. Armstrong publications per year

The chart shows the history of publications by Ryan T. Armstrong between 1987 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Ryan T. Armstrong published across 40 years, from 1987 to 2026, averaging 8 papers a year. Output peaked at 41 publications in 2023. 33 of the 318 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 1987 to 2026. Vertical axis: number of publications, 0 to 41. Peak 41 publications in 2023. 1987: 1 publication 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 0 publications 1998: 0 publications 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 0 publications 2007: 1 publication 2008: 1 publication 2009: 3 publications 2010: 2 publications 2011: 8 publications 2012: 9 publications 2013: 6 publications 2014: 16 publications 2015: 16 publications 2016: 22 publications 2017: 20 publications 2018: 12 publications 2019: 26 publications 2020: 26 publications 2021: 27 publications 2022: 29 publications 2023: 41 publications 2024: 19 publications 2025: 26 publications 2026: 7 publications
1987 2026

318 publications in total across all disciplines

View publications per year as a table
Ryan T. Armstrong: publications per year, 1987 to 2026
Year Publications
1987 1
1988 0
1989 0
1990 0
1991 0
1992 0
1993 0
1994 0
1995 0
1996 0
1997 0
1998 0
1999 0
2000 0
2001 0
2002 0
2003 0
2004 0
2005 0
2006 0
2007 1
2008 1
2009 3
2010 2
2011 8
2012 9
2013 6
2014 16
2015 16
2016 22
2017 20
2018 12
2019 26
2020 26
2021 27
2022 29
2023 41
2024 19
2025 26
2026 7
Total 318
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Ryan T. Armstrong publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ryan T. Armstrong sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 268–277 publications, is where this scientist sits. 38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38–47 publications 804+

This scientist: 271 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214 271
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Ryan T. Armstrong D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ryan T. Armstrong sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 55 D-Index, is where this scientist sits. 30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 55 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186 55
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
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Overview

Ryan T. Armstrong is affiliated with the University of New South Wales in Australia and focuses their research primarily within the field of Engineering. Their work covers several subfields including Ocean Engineering, Mechanics of Materials, Mechanical Engineering, Environmental Engineering, and Geophysics.

Their research topics encompass a variety of areas relevant to energy and environmental sciences. Notable topics include Enhanced Oil Recovery Techniques, Hydrocarbon Exploration and Reservoir Analysis, Hydraulic Fracturing and Reservoir Analysis, Groundwater Flow and Contamination Studies, Seismic Imaging and Inversion Techniques, Coal Properties and Utilization, and CO2 Sequestration and Geologic Interactions.

Among recent publications authored or co-authored by Ryan T. Armstrong are:

  • Deep learning in pore scale imaging and modeling, 2021, Earth-Science Reviews
  • In-situ hydrogen wettability characterisation for underground hydrogen storage, 2022, International Journal of Hydrogen Energy
  • Automated lithology classification from drill core images using convolutional neural networks, 2020, Journal of Petroleum Science and Engineering
  • Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning, 2023, Nature Communications
  • Deep neural networks for improving physical accuracy of 2D and 3D multi-mineral segmentation of rock micro-CT images, 2021, Applied Soft Computing

Ryan T. Armstrong regularly collaborates with several researchers, including:

  • Peyman Mostaghimi
  • Ying Da Wang
  • James E. McClure
  • Kunning Tang
  • Chenhao Sun

Common venues for publishing their work include:

  • arXiv (Cornell University)
  • Water Resources Research
  • Transport in Porous Media
  • Zenodo (CERN European Organization for Nuclear Research)
  • Fuel

Best Publications

  • From connected pathway flow to ganglion dynamics

    M. Rücker;M. Rücker;S. Berg;R. T. Armstrong;A. Georgiadis

  • Porosity and permeability characterization of coal: A micro-computed tomography study

    Hamed Lamei Ramandi;Peyman Mostaghimi;Ryan T. Armstrong;Mohammad Saadatfar

  • Beyond Darcy's law: The role of phase topology and ganglion dynamics for two-fluid flow

    Ryan T. Armstrong;James E. McClure;Mark A. Berrill;Maja Rücker

  • Interfacial velocities and capillary pressure gradients during Haines jumps.

    Ryan T. Armstrong;Steffen Berg

  • Deep learning in pore scale imaging and modeling

    Ying Da Wang;Martin J. Blunt;Ryan T. Armstrong;Peyman Mostaghimi

  • Linking pore-scale interfacial curvature to column-scale capillary pressure

    Ryan T. Armstrong;Mark L. Porter;Dorthe Wildenschild

  • Pore-scale displacement mechanisms as a source of hysteresis for two-phase flow in porous media

    S. Schlüter;S. Schlüter;S. Berg;M. Rücker;M. Rücker;R. T. Armstrong

  • Critical capillary number: Desaturation studied with fast X‐ray computed microtomography

    Ryan T. Armstrong;Apostolos Georgiadis;Holger Ott;Denis Klemin

  • Porous Media Characterization Using Minkowski Functionals: Theories, Applications and Future Directions

    Ryan T. Armstrong;James E. McClure;Vanessa Robins;Zhishang Liu

  • In-situ hydrogen wettability characterisation for underground hydrogen storage

    Unknown

  • Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning

    Unknown

  • Cleat-scale characterisation of coal: An overview

    Peyman Mostaghimi;Ryan T. Armstrong;Alireza Gerami;Yibing Hu

  • Connected pathway relative permeability from pore-scale imaging of imbibition

    S. Berg;M. Rücker;M. Rücker;H. Ott;H. Ott;A. Georgiadis

  • Fast X-ray Micro-Tomography of Multiphase Flow in Berea Sandstone: A Sensitivity Study on Image Processing

    L. Leu;L. Leu;S. Berg;F. Enzmann;R. T. Armstrong;R. T. Armstrong

  • Modeling the velocity field during Haines jumps in porous media

    Ryan T. Armstrong;Nikolay Evseev;Dmitry Koroteev;Steffen Berg

  • Automated lithology classification from drill core images using convolutional neural networks

    Fatimah Alzubaidi;Peyman Mostaghimi;Pawel Swietojanski;Stuart R. Clark

  • Machine learning for predicting properties of porous media from 2d X-ray images

    Naif Alqahtani;Fatimah Alzubaidi;Ryan T. Armstrong;Pawel Swietojanski

  • Coal cleat reconstruction using micro-computed tomography imaging

    Yu Jing;Ryan T. Armstrong;Hamed Lamei Ramandi;Peyman Mostaghimi

  • Enhancing Resolution of Digital Rock Images with Super Resolution Convolutional Neural Networks

    Ying Da Wang;Ryan T. Armstrong;Peyman Mostaghimi

  • Deep neural networks for improving physical accuracy of 2D and 3D multi-mineral segmentation of rock micro-CT images

    Ying Da Wang;Mehdi Shabaninejad;Ryan T. Armstrong;Peyman Mostaghimi

  • Rough-walled discrete fracture network modelling for coal characterisation

    Yu Jing;Ryan T. Armstrong;Peyman Mostaghimi

  • Geometric state function for two-fluid flow in porous media

    James E. McClure;Ryan T. Armstrong;Mark A. Berrill;Steffen Schlüter

  • Trapping and hysteresis in two‐phase flow in porous media: A pore‐network study

    V Joekar-Niasar;Florian Doster;R. T. Armstrong;D. Wildenschild

Frequent Co-Authors

Peyman Mostaghimi
Peyman Mostaghimi University of New South Wales
Steffen Berg
Steffen Berg Shell (Netherlands)
Dorthe Wildenschild
Dorthe Wildenschild Oregon State University
Michael Kersten
Michael Kersten Johannes Gutenberg University of Mainz
Steffen Schlüter
Steffen Schlüter Helmholtz Centre for Environmental Research
Christoph H. Arns
Christoph H. Arns University of New South Wales
William G. Gray
William G. Gray University of North Carolina at Chapel Hill
Majid Ebrahimi Warkiani
Majid Ebrahimi Warkiani University of Technology Sydney
Klaus Regenauer-Lieb
Klaus Regenauer-Lieb University of New South Wales
Alexander G. Schwing
Alexander G. Schwing University of Illinois at Urbana-Champaign

External Links

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