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Advanced Numerical Analysis Techniques

Advanced Numerical Analysis Techniques is a research topic within Computational Mechanics. Science Explorer counts 42k research works in it since 1950. 14.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of isogeometric analysis in computational engineering, particularly in the areas of structural analysis, fluid-structure interaction, shape optimization, and boundary element methods. The use of NURBS, finite elements, CAD, mesh refinement, T-splines, and their implementation in CNC machining are central to the research.

  • NURBS
  • Finite Elements
  • CAD
  • Mesh Refinement
  • T-splines
  • Structural Analysis
  • Fluid-structure Interaction
  • Shape Optimization
  • Boundary Element Method
  • CNC Machining
Research works
42k
fractional, since 1950
In the world top 10%
5.9k
per year above
Top-10% rate
14.0%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-7%
the tick is no change

Which countries lead Advanced Numerical Analysis Techniques research?

By volume, China and the United States publish the most (1.5k and 599 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.5k works
  2. 2 United States 599 works
  3. 3 Germany 361 works
  4. 4 France 222 works
  5. 5 India 215 works
  6. 6 Italy 172 works
  7. 7 Japan 167 works
  8. 8 Türkiye 161 works
  9. 9 Russia 159 works
  10. 10 United Kingdom 115 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 40.6%United States: 16.4%Germany: 9.9%France: 6.1%6 others listed: 27.1%41%largest
China1,483 · 40.6%United States599 · 16.4%Germany361 · 9.9%France222 · 6.1%6 others listed990 · 27.1%

Shares of the rows listed above, not of the whole node.

Which institutions lead Advanced Numerical Analysis Techniques research?

By volume in 2022–2025, Dalian University of Technology publishes the most Advanced Numerical Analysis Techniques research, followed by Shanghai Jiao Tong University and Zhejiang University.

By volume, 2022–2025

  1. 1 Dalian University of Technology China 52 works
  2. 2 Shanghai Jiao Tong University China 38 works
  3. 3 Zhejiang University China 37 works
  4. 4 Tsinghua University China 32 works
  5. 5 Huazhong University of Science and Technology China 30 works
  6. 6 Beihang University China 28 works
  7. 7 University of Science and Technology of China China 28 works
  8. 8 Technical University of Munich Germany 27 works
  9. 9 Harbin Institute of Technology China 26 works
  10. 10 Centre National de la Recherche Scientifique France 25 works

Who are the leading researchers in Advanced Numerical Analysis Techniques?

The most-cited researchers publishing on Advanced Numerical Analysis Techniques include Xiaogang Wang, Stanley Osher and Leonidas Guibas.

  1. 1 Xiaogang Wang 13k citations
  2. 2 Stanley Osher 8k citations
  3. 3 Leonidas Guibas 6.3k citations
  4. 4 Lei Zhang 5.3k citations
  5. 5 Takeo Kanade 4.8k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Advanced Numerical Analysis Techniques research done?

The largest centres of Advanced Numerical Analysis Techniques research in 2022–2025 are Beijing (China), Shanghai (China), Xi'an (China) and Wuhan (China).

Largest cities, 2022–2025

  1. 1 Beijing China 253 works
  2. 2 Shanghai China 105 works
  3. 3 Xi'an China 88 works
  4. 4 Wuhan China 79 works
  5. 5 Hangzhou China 76 works
  6. 6 Nanjing China 71 works
  7. 7 Moscow Russia 71 works
  8. 8 Dalian China 69 works
  9. 9 Tokyo Japan 64 works
  10. 10 Paris France 54 works
See Advanced Numerical Analysis Techniques on the map

Where is the best place to study Advanced Numerical Analysis Techniques?

Among universities, judged by research, Dalian University of Technology, École Polytechnique Fédérale de Lausanne and Huazhong University of Science and Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 24.32%fractional works in this node (log) →share in the world top 10% →Dalian University of Technology: 52, 17.8%École Polytechnique Fédérale de Lausanne: 15, 32.5%Huazhong University of Science and Technology: 30, 34.8%Carnegie Mellon University: 13, 29.0%Graz University of Technology: 9, 14.2%Technical University of Munich: 27, 11.8%Tsinghua University: 32, 27.4%Indian Institute of Technology Madras: 12, 32.3%Waseda University: 8, 33.7%Technische Universität Berlin: 16, 9.7%Huazhong University …École Polytechnique …Carnegie Mellon Univ…Dalian University of…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1Dalian University of Technology China 63.017.8%11.1×52 -0.6%
2École Polytechnique Fédérale de Lausanne Switzerland 60.432.5%7.1×15 +7.0%
3Huazhong University of Science and Technology China 51.934.8%3.8×30 -21.8%
4Carnegie Mellon University United States 50.429.0%6.2×13 +33.2%
5Graz University of Technology Austria 47.814.2%9.0×9 +78.3%
6Technical University of Munich Germany 47.011.8%6.9×27 +0.3%
7Tsinghua University China 46.827.4%3.2×32 -10.6%
8Indian Institute of Technology Madras India 46.332.3%5.6×12 -15.6%
9Waseda University Japan 45.333.7%4.8×8 +46.9%
10Technische Universität Berlin Germany 44.59.7%9.3×16 -12.9%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Advanced Numerical Analysis Techniques research growing?

Output in 2018–2022 was 7% lower than in 2013–2017, peaking in 2011.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.