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Institution

Beijing Institute of Petrochemical Technology

EducationBeijing, China
About: Beijing Institute of Petrochemical Technology is a education organization based out in Beijing, China. It is known for research contribution in the topics: Catalysis & Corrosion. The organization has 2468 authors who have published 1937 publications receiving 19270 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, a 3D geological model is presented to explore the groundwater flow conditions in the aquifers that feed springs, and a date integration technique is adopted to ensure the accuracy of the model.
Abstract: Withdrawal of groundwater can dry up springs. It is, however, often difficult to determine the exact causes for the depletion of spring flow by the traditional methods. A 3-D geological model is presented in this paper to explore the groundwater flow conditions in the aquifers that feed springs. Because of the various geological data in spring areas, a date integration technique is adopted to ensure the accuracy of the model. This model is implemented in the spring protection program in Jinan City, China, and the reasons for the drying up of the springs in the city are studied. The proposed model would be particularly helpful in the spring protection, and the appropriate application of the model would result in economic and social benefits of the city.

14 citations

Journal ArticleDOI
TL;DR: Results indicated that the proposed intelligent assessment model of the warehouse fire dynamic risk based on the ESDA and improved SVM (ESDA-NPSVM) had excellent performance for the dynamic risk assessment of fire accidents in Class A hazardous chemical warehouses, suggesting that it is useful for practical applications.

14 citations

Journal ArticleDOI
TL;DR: In this paper, the Gibbs free energies of 1-butyl-3-methylimidazolium perchlorate-based ionic liquids (ILs) were derived for three isomeric xylenes separation problems, and the Hildebrand's solubility parameters of the IL [BMIM][ClO4] were also determined by the regular solution theory combined with Flory "combinatorial" equation.

14 citations

Journal ArticleDOI
TL;DR: In this article, the authors focused on predicting the erosion of a tee junction (T) under various flow types during hydraulic fracturing operation, and the failure mode and failure mechanism were defined.
Abstract: Erosion wear in piping is an unavoidable degradation process in the oil and gas industry that causes pipe wall thinning and leads to economic losses and potentially produce personal injuries. The mechanism of pipe erosion remains poorly understood. This study focused on predicting the erosion of a tee junction (T) under various flow types during fracturing operation. The failure analysis of tee junction was determined from its macroscopic features and scanning electron microscope (SEM) images and allowed definition of the failure mode and failure mechanism were defined, which appeared to be significantly different from what has been considered to be traditional. The failure analysis and fluid mechanics theory were used to build a computational fluid dynamics (CFD) simulation method to predict the erosion of the tee junction. The model of two-phase flow in a tee junction indicated that the solid-phase flow is determined by combined effects of the main tube flow, the flow inertia, and the turbulent flow. The distribution of the erosion in the tee was significantly different for various flow types and the simulation results were consistent with the results of the failure analysis. This model of predicted local distribution of erosion wear can assist the monitoring of pipe walls to prevent accidents and reduce maintenance labor.

14 citations


Authors

Showing all 2499 results

NameH-indexPapersCitations
J. S. Lange1602083145919
Chao Zhang127311984711
S. J. Chen116155962804
Y. Ban104134649897
Min Zhang85154834853
Shan Jin8336537419
Y. J. Mao8182929089
Lei Zhang78148530058
Jialun Ping7367622314
Li Li6785522796
D. Y. Wang6463718612
M. Qi5846619175
J. G. Messchendorp5459312498
Xiangming He5248010801
Nasser Kalantar-Nayestanaki5169111500
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202310
202293
2021264
2020219
2019211
2018173