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Engineering Diagnostics and Reliability

Engineering Diagnostics and Reliability is a research topic within Mechanics of Materials. Science Explorer counts 27k research works in it since 1950. 8.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on materials engineering in industrial applications, particularly in the fields of corrosion, steel strength, pipeline durability, deformation processes, and industrial safety. It addresses issues such as fatigue, electrochemical parameters, friction welding, and heat resistance in various mechanical components and equipment used in oil and gas, power generation, and other industrial sectors.

  • Corrosion
  • Steel
  • Pipeline
  • Deformation
  • Industrial Safety
  • Fatigue
  • Electrochemical Parameters
  • Friction Welding
  • Heat Resistance
  • Machine Mechanics
Research works
27k
fractional, since 1950
In the world top 10%
2.2k
per year above
Top-10% rate
8.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+102%
the tick is no change

Which countries lead Engineering Diagnostics and Reliability research?

By volume, China and Russia publish the most (2.1k and 1.9k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.1k works
  2. 2 Russia 1.9k works
  3. 3 Ukraine 507 works
  4. 4 United States 311 works
  5. 5 India 206 works
  6. 6 Indonesia 108 works
  7. 7 Uzbekistan 106 works
  8. 8 Poland 98 works
  9. 9 Kazakhstan 90 works
  10. 10 United Kingdom 75 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: 38.3%Russia: 34.6%Ukraine: 9.2%United States: 5.6%6 others listed: 12.4%38%largest
China2,120 · 38.3%Russia1,913 · 34.6%Ukraine507 · 9.2%United States311 · 5.6%6 others listed683 · 12.4%

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

Which institutions lead Engineering Diagnostics and Reliability research?

By volume in 2022–2025, Ufa State Petroleum Technological University publishes the most Engineering Diagnostics and Reliability research, followed by Moscow Power Engineering Institute and Bauman Moscow State Technical University.

By volume, 2022–2025

  1. 1 Ufa State Petroleum Technological University Russia 64 works
  2. 2 Moscow Power Engineering Institute Russia 43 works
  3. 3 Bauman Moscow State Technical University Russia 41 works
  4. 4 Azerbaijan State Oil and Industry University Azerbaijan 39 works
  5. 5 Xi'an Jiaotong University China 39 works
  6. 6 Moscow Aviation Institute Russia 36 works
  7. 7 Weatherford College United States 35 works
  8. 8 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine 34 works
  9. 9 Moscow State University of Civil Engineering Russia 32 works
  10. 10 National Academy of Sciences of Ukraine Ukraine 32 works

Who are the leading researchers in Engineering Diagnostics and Reliability?

The most-cited researchers publishing on Engineering Diagnostics and Reliability include C. Guedes Soares.

  1. 1 C. Guedes Soares 2.7k citations

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

Where is Engineering Diagnostics and Reliability research done?

The largest centres of Engineering Diagnostics and Reliability research in 2022–2025 are Moscow (Russia), Beijing (China), Saint Petersburg (Russia) and Kyiv (Ukraine). Among places with at least 20 works in it, it is an unusually large share of all research in Komsomol'skiy, Astrakhan and Ufa.

Largest cities, 2022–2025

  1. 1 Moscow Russia 555 works
  2. 2 Beijing China 362 works
  3. 3 Saint Petersburg Russia 210 works
  4. 4 Kyiv Ukraine 151 works
  5. 5 Xi'an China 149 works
  6. 6 Shanghai China 145 works
  7. 7 Wuhan China 115 works
  8. 8 Nanjing China 99 works
  9. 9 Ufa Russia 90 works
  10. 10 Kharkiv Ukraine 88 works

Where it is the local speciality

  1. Komsomol'skiyRU · 23.6 works56×
  2. AstrakhanRU · 24.1 works45×
  3. UfaRU · 89.8 works36×
  4. OmskRU · 33.9 works29×
← less than its size predictsmore →

Location quotient: how much more of its research is in Engineering Diagnostics and Reliability than the world average.

See Engineering Diagnostics and Reliability on the map

Where is the best place to study Engineering Diagnostics and Reliability?

Among universities, judged by research, Yanshan University, Ufa State Petroleum Technological University and Azerbaijan State Oil and Industry University 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.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1Yanshan University China 63.359.7%6.8×15 +88.0%
2Ufa State Petroleum Technological University Russia 62.21.6%142.8×64 +2052.1%
3Azerbaijan State Oil and Industry University Azerbaijan 61.15.7%83.4×39 +384.4%
4Moscow Power Engineering Institute Russia 59.41.8%43.8×43 +303.1%
5Bauman Moscow State Technical University Russia 58.41.9%34.3×41 +207.3%
6Ural Federal University Russia 58.20.6%15.8×30 +262.6%
7Peter the Great St. Petersburg Polytechnic University Russia 57.91.6%22.7×31 +445.9%
8Moscow Aviation Institute Russia 56.81.6%35.1×36 +1023.9%
9Don State Technical University Russia 56.75.5%38.2×30 +344.7%
10National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine 56.53.8%22.4×34 +168.4%

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 Engineering Diagnostics and Reliability research growing?

Output in 2018–2022 was 102% higher than in 2013–2017, peaking in 2021. The fastest-growing topics are Engineering Diagnostics and Reliability.

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.