Pei Wei
- Automotive Engineering top 1%
- Additive Manufacturing and 3D Printing Technologies 20
- Mechanical Engineering top 2%
- Additive Manufacturing Materials and Processes 24
- High Entropy Alloys Studies 15
- Welding Techniques and Residual Stresses 4
- Aerospace Engineering top 5%
- High-Temperature Coating Behaviors 7
- Computational Mechanics top 10%
- Fluid Dynamics and Heat Transfer 6
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- Metallurgy and Material Forming 6
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- Particle Dynamics in Fluid Flows 4
In The Last Decade
Pei Wei
52 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 78
- Automotive Engineering 714
- Mechanical Engineering 1.2k
- Aerospace Engineering 230
- Computational Mechanics 121
- Industrial and Manufacturing Engineering 58
Countries citing papers authored by Pei Wei
This map shows the geographic impact of Pei Wei'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 Pei Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei Wei more than expected).
Fields of papers citing papers by Pei Wei
This network shows the impact of papers produced by Pei Wei. 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 Pei Wei. The network helps show where Pei Wei may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Pei Wei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 6 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 11 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 4 | |
| 7 | Constitutive model of low carbon alloy steel (LCAS) expandable tubular | 2022 | 1 |
| 8 | Hot forging for producing railway wagon bogie adapter | 2022 | 1 |
| 9 | Johnson-Cook model for TC4 titanium alloy based on compression experiment | 2022 | 3 |
| 10 | 2022 | 2 | |
| 11 | High temperature constitutive model of q345B steel | 2022 | 0 |
| 12 | 2022 | 17 | |
| 13 | 2022 | 0 | |
| 14 | 2022 | 7 | |
| 15 | Constitutive model of AISI 1035 at high temperature | 2021 | 0 |
| 16 | Constitutive relationship of 7075 aluminum alloy based on modified Zerilli-Armstrong (M - ZA) model | 2021 | 1 |
| 17 | 2021 | 29 | |
| 18 | Study on crack propagation of 42CrMo | 2019 | 1 |
| 19 | Constitutive model of 3Cr23Ni8Mn3N heat-resistant steel based on back propagation (BP) neural network (NN) | 2019 | 6 |
| 20 | 2015 | 29 |
About Pei Wei
Pei Wei is a scholar working on Automotive Engineering, Mechanical Engineering and Mechanics of Materials, having authored 60 papers that have together received 1.4k indexed citations. Recurring topics across this work include Additive Manufacturing Materials and Processes (24 papers), Additive Manufacturing and 3D Printing Technologies (20 papers), High Entropy Alloys Studies (15 papers), High-Temperature Coating Behaviors (7 papers), Metallurgy and Material Forming (6 papers), Fluid Dynamics and Heat Transfer (6 papers), Welding Techniques and Residual Stresses (4 papers) and Particle Dynamics in Fluid Flows (4 papers). The work is most often cited by research in Automotive Engineering (714 citations), Mechanical Engineering (1.2k citations) and Aerospace Engineering (230 citations). Pei Wei has collaborated with scholars based in China, Australia and Japan. Frequent co-authors include Zhengying Wei, Jun Du, Zhen Chen, Shuzhe Zhang, Junfeng Li, Yuyang He, Bingheng Lu, Zhen Chen, Yatong Zhou and Lijuan Zhang. Their work appears in journals such as Materials Science and Engineering A, Applied Physics A, Materials, Applied Surface Science and Materials Letters.
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.