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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 37 2396 2239 290 290 225 5455

Xueguan Song publications per year

The chart shows the history of publications by Xueguan Song between 1999 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Xueguan Song published across 27 years, from 1999 to 2025, averaging 10.4 papers a year. Output peaked at 47 publications in 2023. 67 of the 282 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 1999 to 2025. Vertical axis: number of publications, 0 to 47. Peak 47 publications in 2023. 1999: 1 publication 2000: 0 publications 2001: 1 publication 2002: 0 publications 2003: 0 publications 2004: 0 publications 2005: 0 publications 2006: 0 publications 2007: 0 publications 2008: 3 publications 2009: 1 publication 2010: 3 publications 2011: 1 publication 2012: 3 publications 2013: 7 publications 2014: 11 publications 2015: 11 publications 2016: 6 publications 2017: 5 publications 2018: 17 publications 2019: 13 publications 2020: 15 publications 2021: 27 publications 2022: 43 publications 2023: 47 publications 2024: 30 publications 2025: 37 publications
1999 2025

282 publications in total across all disciplines

View publications per year as a table
Xueguan Song: publications per year, 1999 to 2025
Year Publications
1999 1
2000 0
2001 1
2002 0
2003 0
2004 0
2005 0
2006 0
2007 0
2008 3
2009 1
2010 3
2011 1
2012 3
2013 7
2014 11
2015 11
2016 6
2017 5
2018 17
2019 13
2020 15
2021 27
2022 43
2023 47
2024 30
2025 37
Total 282
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Xueguan Song publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Xueguan Song sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 63 bars. Horizontal axis: publications, 47–56 to 659+. Vertical axis: number of scientists, 0 to 155. Most scientists, 155, have 147–156 publications. The last bar groups every scientist with 659 publications or more. The highlighted bar, 217–226 publications, is where this scientist sits. 47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47–56 publications 659+

This scientist: 225 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

View publications distribution as a table
Number of Mechanical and Aerospace Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
Publications Scientists This scientist
47–56 10
57–66 23
67–76 32
77–86 62
87–96 67
97–106 91
107–116 113
117–126 115
127–136 130
137–146 140
147–156 155
157–166 132
167–176 133
177–186 130
187–196 140
197–206 115
207–216 125
217–226 117 225
227–236 99
237–246 92
247–256 100
257–266 95
267–276 88
277–286 77
287–296 74
297–306 74
307–316 62
317–326 70
327–336 59
337–346 58
347–356 45
357–366 44
367–376 36
377–386 41
387–396 32
397–406 23
407–416 28
417–426 27
427–436 25
437–446 23
447–456 23
457–466 20
467–476 12
477–486 24
487–496 18
497–506 12
507–516 13
517–526 21
527–536 12
537–546 8
547–556 16
557–566 3
567–576 11
577–586 6
587–596 5
597–606 6
607–616 7
617–626 7
627–636 10
637–646 4
647–656 3
657–658 2
659+ 100
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Xueguan Song D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Xueguan Song sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 64 bars. Horizontal axis: D-Index, 30 to 93+. Vertical axis: number of scientists, 0 to 189. Most scientists, 189, have 34 D-Index. The last bar groups every scientist with 93 D-Index or more. The highlighted bar, 37 D-Index, is where this scientist sits. 30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 37 D-Index — 32nd percentile

32% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

View D-Index distribution as a table
Number of Mechanical and Aerospace Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
D-Index Scientists This scientist
30 83
31 113
32 144
33 153
34 189
35 158
36 139
37 127 37
38 130
39 126
40 104
41 100
42 107
43 101
44 103
45 79
46 88
47 70
48 83
49 44
50 64
51 56
52 50
53 48
54 58
55 52
56 48
57 42
58 34
59 42
60 37
61 42
62 44
63 22
64 33
65 29
66 23
67 29
68 24
69 19
70 34
71 26
72 19
73 18
74 19
75 14
76 19
77 8
78 18
79 16
80 12
81 17
82 11
83 16
84 7
85 9
86 8
87 6
88 6
89 7
90 10
91 4
92 4
93+ 100
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Overview

Xueguan Song is affiliated with Dalian University of Technology in China. Their research primarily spans the fields of engineering and computer science, with a strong focus on mechanical engineering and civil and structural engineering. They also contribute to computational theory and mathematics, control and systems engineering, and areas related to statistics, probability, and uncertainty.

The major topics covered in their work include advanced multi-objective optimization algorithms, probabilistic and robust engineering design, hydraulic and pneumatic systems, optimal experimental design methods, tunneling and rock mechanics, structural health monitoring techniques, and advanced machining processes and optimization.

Song has published extensively in a variety of venues. Frequent publication outlets include:

  • Journal of Mechanical Design
  • Structural and Multidisciplinary Optimization
  • SSRN Electronic Journal
  • Automation in Construction
  • Advanced Engineering Informatics

Co-authorship is a significant aspect of Song's career. Collaborators frequently working with Song are:

  • Yong Pang
  • Xiwang He
  • Xiaonan Lai
  • Wei Sun
  • Qingye Li

Recent published papers by Song include:

  • "The Digital Twin in Medicine: A Key to the Future of Healthcare?" (2022), published in Frontiers in Medicine
  • "Ensemble regression based on polynomial regression-based decision tree and its application in the in-situ data of tunnel boring machine" (2022), published in Mechanical Systems and Signal Processing
  • "Designing a Shape-Performance Integrated Digital Twin Based on Multiple Models and Dynamic Data: A Boom Crane Example" (2021), published in Journal of Mechanical Design
  • "A multi-fidelity surrogate model based on support vector regression" (2020), published in Structural and Multidisciplinary Optimization
  • "Digital twin-based structural health monitoring by combining measurement and computational data: An aircraft wing example" (2023), published in Journal of Manufacturing Systems

Best Publications

  • Recurrent neural networks for real-time prediction of TBM operating parameters

    Xianjie Gao;Maolin Shi;Xueguan Song;Chao Zhang

  • Crashworthiness optimization of foam-filled tapered thin-walled structure using multiple surrogate models

    Xueguan Song;Guangyong Sun;Guangyao Li;Weizhao Gao

  • In Situ Diagnostics and Prognostics of Solder Fatigue in IGBT Modules for Electric Vehicle Drives

    Bing Ji;Xueguan Song;Wenping Cao;Volker Pickert

  • New SR Drive With Integrated Charging Capacity for Plug-In Hybrid Electric Vehicles (PHEVs)

    Yihua Hu;Xueguan Song;Wenping Cao;Bing Ji

  • A CFD analysis of the dynamics of a direct-operated safety relief valve mounted on a pressure vessel

    Xueguan Song;Lei Cui;Maosen Cao;Wenping Cao

  • Dynamic load prediction of tunnel boring machine (TBM) based on heterogeneous in-situ data

    Wei Sun;Maolin Shi;Chao Zhang;Junhong Zhao

  • A radial basis function-based multi-fidelity surrogate model: exploring correlation between high-fidelity and low-fidelity models

    Xueguan Song;Liye Lv;Wei Sun;Jie Zhang

  • Multiobjective Design Optimization of IGBT Power Modules Considering Power Cycling and Thermal Cycling

    Bing Ji;Bing Ji;Xueguan Song;Edward Sciberras;Wenping Cao

  • Numerical analysis of the optimum membrane/ionomer water content of PEMFCs: The interaction of Nafion® ionomer content and cathode relative humidity

    Lei Xing;Lei Xing;Prodip K. Das;Xueguan Song;Mohamed Mamlouk

  • Comparison of 12/8 and 6/4 Switched Reluctance Motor: Noise and Vibration Aspects

    Jian Li;Xueguan Song;Yunhyun Cho

  • Robust optimization of foam-filled thin-walled structure based on sequential Kriging metamodel

    Guangyong Sun;Xueguan Song;Seokheum Baek;Qing Li

  • Photovoltaic fault detection using a parameter based model

    Yihua Hu;Bin Gao;Xueguan Song;Gui Yun Tian

  • Multidisciplinary optimization of a butterfly valve.

    Xue Guan Song;Lin Wang;Seok Heum Baek;Young Chul Park

  • Performance comparison and erosion prediction of jet pumps by using a numerical method

    Xue Guan Song;Joon Hong Park;Seung Gyu Kim;Young Chul Park

  • Sensitivity analysis and reliability based design optimization for high-strength steel tailor welded thin-walled structures under crashworthiness

    Xueguan Song;Guangyong Sun;Qing Li

  • A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data

    Junhong Zhao;Maolin Shi;Gang Hu;Xueguan Song

  • Multi-variable optimisation of PEMFC cathodes based on surrogate modelling

    Lei Xing;Lei Xing;Xueguan Song;Keith Scott;Volker Pickert

  • An Advanced and Robust Ensemble Surrogate Model: Extended Adaptive Hybrid Functions

    Xueguan Song;Liye Lv;Jieling Li;Wei Sun

  • Transient Analysis of a Spring-Loaded Pressure Safety Valve Using Computational Fluid Dynamics (CFD)

    Xue Guan Song;Lin Wang;Young Chul Park

  • A multi-fidelity surrogate model based on support vector regression

    Maolin Shi;Liye Lv;Wei Sun;Xueguan Song

  • Digital twin-based structural health monitoring by combining measurement and computational data: An aircraft wing example

    Unknown

  • Blowdown prediction of a conventional pressure relief valve with a simplified dynamic model

    Xue-Guan Song;Young Chul Park;Joon Hong Park

  • NUMERICAL ANALYSIS OF BUTTERFLY VALVE-PREDICTION OF FLOW COEFFICIENT AND HYDRODYNAMIC TORQUE COEFFICIENT

    Xue guan Song

  • Surrogate based multidisciplinary design optimization of lithium-ion battery thermal management system in electric vehicles

    Xiaobang Wang;Xiaobang Wang;Mao Li;Yuanzhi Liu;Wei Sun

  • Sliding cable modeling: A nonlinear complementarity function based framework

    Ziyun Kan;Fei Li;Haijun Peng;Biaosong Chen

  • Energy-minimum optimization of the intelligent excavating process for large cable shovel through trajectory planning

    Xiaobang Wang;Wei Sun;Eryang Li;Xueguan Song

  • A data-driven framework to predict the morphology of interfacial Cu6Sn5 IMC in SAC/Cu system during laser soldering

    Anil Kunwar;Anil Kunwar;Lili An;Jiahui Liu;Shengyan Shang

  • Metamodel-based optimization of a control arm considering strength and durability performance

    Xue Guan Song;Ji Hoon Jung;Hwan Jung Son;Joon Hong Park

  • Heat and mass transfer effects of laser soldering on growth behavior of interfacial intermetallic compounds in Sn/Cu and Sn-3.5Ag0.5/Cu joints

    Anil Kunwar;Shengyan Shang;Peter Råback;Yunpeng Wang

  • Multidisciplinary design optimization of tunnel boring machine considering both structure and control parameters under complex geological conditions

    Wei Sun;Xiaobang Wang;Lintao Wang;Jie Zhang

Frequent Co-Authors

Wenping Cao
Wenping Cao Anhui University
Volker Pickert
Volker Pickert Newcastle University
Jie Zhang
Jie Zhang The University of Texas at Dallas
Yihua Hu
Yihua Hu University of York
Jian Li
Jian Li Huazhong University of Science and Technology
Lei Xing
Lei Xing Stanford University
Qing Li
Qing Li University of Sydney
Maosen Cao
Maosen Cao Hohai University
Guangyong Sun
Guangyong Sun Hunan University
Gui Yun Tian
Gui Yun Tian Chongqing University of Posts and Telecommunications

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