CNPC Tubular Goods Research Institute at IgMin Research
Our commitment is to promote shared insights across disciplines for rapid scientific growth.
| Name | CNPC Tubular Goods Research Institute |
| Location | Xi An, China |
| URL | https://www.prci.org |
About University
PRCI is happy to welcome CNPC Tubular Goods Research Institute (TGRI) as a full Associate Member. Representing TGRI is Chen Hongyuan.
Founded in 1981, TGRI is a division of China National Petroleum Corporation. A poly-technical center, TGRI integrates scientific research, quality and technical supervision, and engineering technical services in the oil tubular goods engineering field. With the tenet of "Innovation, Long-term, Rigorousness, Impartiality," TGRI is dedicated to the development of technology innovation, research and development, quality technical supervision and engineering technical service. Since its foundation over 40 years ago, TGRI has many successful accomplishments and completed more than 200 national and provincial projects.
Welcome to PRCI! We look forward to working together in our mission to enhance global pipeline safety and integrity.
Articles
Stay tuned for early online updates. If you want to join us
Why Publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
現在トレンドになっている記事はどれですか？
研究論文
- Examining the Causal Connection between Lipid-lowering Medications and Malignant Meningiomas through Drug-target Mendelian Randomization Analysis
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
- Kinetic Study of the Removal of Reafix Yellow B8G Dye by Boiler Ash
- Preparing for SpaceX Mission to Mars
- A Machine Learning-based Method for COVID-19 and Pneumonia Detection
- Knowledge Discovery on Artificial Intelligence and Physical Therapy: Document Mining Analysis
