Jinxing Wang

ORCID: 0009-0003-0174-6277
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About
Contact & Profiles
Research Areas
  • Manufacturing Process and Optimization
  • Drilling and Well Engineering
  • Industrial Vision Systems and Defect Detection
  • Hydraulic Fracturing and Reservoir Analysis
  • Engineering Applied Research
  • Railway Engineering and Dynamics
  • Methane Hydrates and Related Phenomena
  • Geophysical Methods and Applications
  • Advanced Sensor and Control Systems
  • Image and Object Detection Techniques
  • Geotechnical and Geomechanical Engineering
  • Remote Sensing and Land Use
  • Underwater Acoustics Research
  • Biometric Identification and Security
  • Smart Agriculture and AI
  • Railway Systems and Energy Efficiency
  • Advanced Algorithms and Applications
  • Traffic Prediction and Management Techniques
  • Advanced SAR Imaging Techniques

Changzhou University
2023-2025

Beijing Jiaotong University
2023

Wuyi University
2019

Huazhong University of Science and Technology
2005-2011

Shandong Agricultural University
2008

During the drilling of natural gas hydrate reservoirs, invasion may occur, which has an adverse impact on upward return process cuttings and control bottom-hole pressure. A multiphase fluid CFD simulation method based Eulerian model was optimized. With help Fluent 23R1 software, simulations three-phase flow fluid–cuttings–invaded in vertical section, build-up horizontal section complex annulus wellbore particle dynamics were carried out. The characteristics after revealed, impacts deposition...

10.3390/pr13020455 article EN Processes 2025-02-07

An effective Max-Fire CNN model MF-SarNet for synthetic aperture radar (SAR) automatic target recognition (ATR) is presented, here. By selecting the convolution kernel of Fire module in network, parameters are reduced to obtain convolutional neural network less parameter. In view requirement deep learning large-scale data, an augmentation method proposed, which can learn features large database better. The results based on MSTAR show that and result encouraging. accuracy SAR image 98.53%.

10.1049/joe.2019.0218 article EN cc-by The Journal of Engineering 2019-07-25

Accurately predicting delays for high-speed railways (HSRs) is a challenging yet significant task. The historical operation data of the HSRs, implicating delay derivation rules under dispatchers' rescheduling strategies, have sparsity characteristics, resulting in heterogeneous prediction performances different scenarios. This article proposes Gaussian noise augmentation-based method to cope with sparsity. Specifically, added original based on train characteristics. Then, rather than...

10.1109/mits.2023.3274787 article EN IEEE Intelligent Transportation Systems Magazine 2023-05-31

Abstract Formation gravity displacement refers to the phenomenon of "overflow and leakage" in same crack due difference density between drilling fluid formation fluid. In order restrain leakage accident caused by displacement, this paper studies window, conditions puts forward corresponding solutions. summary, develops wellbore-formation experimental device, carries out gas-liquid critical point experiments, summarizes analyzes fits pressure curve window based on results constant...

10.2118/217522-ms article EN Day 4 Thu, November 18, 2021 2023-11-21
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