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  • Open Access

    ARTICLE

    Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A Numerical Modeling Study

    Farman Saifi1,*, Mohd Javaid1, Abid Haleem1, S. M. Anas2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2747-2777, 2024, DOI:10.32604/cmes.2024.051490

    Abstract Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infrastructure systems and networks capable of withstanding blast loading. Initially centered on high-profile facilities such as embassies and petrochemical plants, this concern now extends to a wider array of infrastructures and facilities. Engineers and scholars increasingly prioritize structural safety against explosions, particularly to prevent disproportionate collapse and damage to nearby structures. Urbanization has further amplified the reliance on oil and gas pipelines, making them vital for urban life and prime targets for terrorist activities. Consequently, there is a growing imperative for computational… More >

  • Open Access

    ARTICLE

    Optimization of a Pipeline-Type Savonius Hydraulic Turbine

    Xiaohui Wang1,2,3,*, Kai Zhang1, Xiaobang Bai4, Senchun Miao1, Zanxiu Wu1, Jicheng Li1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1123-1146, 2024, DOI:10.32604/fdmp.2023.043272

    Abstract This study focuses on a DN50 pipeline-type Savonius hydraulic turbine. The torque variation of the turbine in a rotation cycle is analyzed theoretically in the framework of the plane potential flow theory. Related numerical simulations show that the change in turbine torque is consistent with the theoretical analysis, with the main power zone and the secondary power zone exhibiting a positive torque. In contrast, the primary resistance zone and the secondary resistance zone are characterized by a negative torque. Analytical relationships between the turbine’s internal flow angle θ, the deflector’s inclination angle α, and the… More >

  • Open Access

    ARTICLE

    Experimental and Finite Element Analysis of Corroded High-Pressure Pipeline Repaired by Laminated Composite

    Seyed Mohammad Reza Abtahi1, Saeid Ansari Sadrabadi2,*, Gholam Hosein Rahimi1, Gaurav Singh2, Hamid Abyar3, Daniele Amato4, Luigi Federico5

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1783-1806, 2024, DOI:10.32604/cmes.2024.047575

    Abstract Repairs of corroded high-pressure pipelines are essential for fluids transportation under high pressure. One of the methods used in their repairs is the use of layered composites. The composite used must have the necessary strength. Therefore, the experiments and analytical solutions presented in this paper are performed according to the relevant standards and codes, including ASME PCC-2, ASME B31.8S, ASME B31.4, ISO 24817 and ASME B31.G. In addition, the experimental tests are replicated numerically using the finite element method. Setting the strain gauges at different distances from the defect location, can reduce the nonlinear effects, More >

  • Open Access

    ARTICLE

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

    Zhuo Chen1,*, Ningning Wang2, Wenbo Jin3, Dui Li1

    Energy Engineering, Vol.121, No.4, pp. 1007-1026, 2024, DOI:10.32604/ee.2023.045270

    Abstract A hard problem that hinders the movement of waxy crude oil is wax deposition in oil pipelines. To ensure the safe operation of crude oil pipelines, an accurate model must be developed to predict the rate of wax deposition in crude oil pipelines. Aiming at the shortcomings of the ENN prediction model, which easily falls into the local minimum value and weak generalization ability in the implementation process, an optimized ENN prediction model based on the IRSA is proposed. The validity of the new model was confirmed by the accurate prediction of two sets of… More > Graphic Abstract

    Prediction Model of Wax Deposition Rate in Waxy Crude Oil Pipelines by Elman Neural Network Based on Improved Reptile Search Algorithm

  • Open Access

    ARTICLE

    Prediction on Failure Pressure of Pipeline Containing Corrosion Defects Based on ISSA-BPNN Model

    Qi Zhuang1,*, Dong Liu2, Zhuo Chen3

    Energy Engineering, Vol.121, No.3, pp. 821-834, 2024, DOI:10.32604/ee.2023.044054

    Abstract Oil and gas pipelines are affected by many factors, such as pipe wall thinning and pipeline rupture. Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management. Aiming at the shortcomings of the BP Neural Network (BPNN) model, such as low learning efficiency, sensitivity to initial weights, and easy falling into a local optimal state, an Improved Sparrow Search Algorithm (ISSA) is adopted to optimize the initial weights and thresholds of BPNN, and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established. Taking 61 sets More >

  • Open Access

    ARTICLE

    SDH-FCOS: An Efficient Neural Network for Defect Detection in Urban Underground Pipelines

    Bin Zhou, Bo Li*, Wenfei Lan, Congwen Tian, Wei Yao

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 633-652, 2024, DOI:10.32604/cmc.2023.046667

    Abstract Urban underground pipelines are an important infrastructure in cities, and timely investigation of problems in underground pipelines can help ensure the normal operation of cities. Owing to the growing demand for defect detection in urban underground pipelines, this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector (FCOS), called spatial pyramid pooling-fast (SPPF) feature fusion and dual detection heads based on FCOS (SDH-FCOS) model. This study improved the feature fusion component of the model network based on FCOS, introduced an SPPF network structure behind the last… More >

  • Open Access

    ARTICLE

    THE STUDY OF TEMPERATURE PROFILE INSIDE WAX DEPOSITION LAYER OF WAXY CRUDE OIL IN PIPELINE

    Zhen Tiana,*, Wenbo Jina, Lei Wangb, Zhi Jinc

    Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-8, 2014, DOI:10.5098/hmt.5.5

    Abstract Taking the axial heat conduction of wax deposition layer into account, a two-dimensional heat transfer model of calculating the temperature profile inside wax deposition layer was deduced and established based on the energy balance equation, the finite difference method was used to solve this model, and the influence of axial heat conduction on the distribution law of temperature profile inside the wax deposition layer under different boundary conditions and thickness were discussed. The results showed that: Temperature profile inside wax deposition layer in middle region of testing pipe section was mainly influenced by axial heat More >

  • Open Access

    PROCEEDINGS

    Linearization Solution and Component Tracking of Natural Gas Pipeline Transient Simulation

    Yuming He1,*, Jie Chen1, Yubo Jiao1, Wei Wang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09061

    Abstract In present study, a fast simulation algorithm based on linearization is used to simulate the flow parameters of the natural gas pipeline under transient operating conditions, analyze the impact of natural gas components on the transient operation, and conduct the tracking calculation of natural gas components [1- 3]. Under the condition that the simulation calculation accuracy is not affected, the first-order Taylor linearization expansion method is used to linearize the transient simulation model of natural gas pipeline, while the second-order implicit difference dispersion method is used to obtain the linearized discrete equations without initial value… More >

  • Open Access

    PROCEEDINGS

    Efficient and Robust Temperature Field Simulation of Long-Distance Crude Oil Pipeline Based on Bayesian Neural Network and PDE

    Weixin Jiang1,*, Qing Yuan2, Zongze Li3, Junhua Gong3, Bo Yu4

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.08861

    Abstract The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe transportation and accurate regulation of pipelines. With reasonable basic parameters, the solution of the traditional partial differential equation (PDE) for the axial soil temperature field on the pipeline can obtain accurate simulation results, yet it brings about a low calculation efficiency problem. In order to overcome the low-efficiency problem, an efficient and robust hybrid solution model for soil temperature field coupling with Bayesian neural network and PDE is proposed, which considers the dynamic changes of boundary conditions. Four models,… More >

  • Open Access

    ARTICLE

    3D Model Occlusion Culling Optimization Method Based on WebGPU Computing Pipeline

    Liming Ye1,2, Gang Liu1,2,3,4,*, Genshen Chen1,2, Kang Li1,2, Qiyu Chen1,2,3, Wenyao Fan1,2, Junjie Zhang1,2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2529-2545, 2023, DOI:10.32604/csse.2023.041488

    Abstract Nowadays, Web browsers have become an important carrier of 3D model visualization because of their convenience and portability. During the process of large-scale 3D model visualization based on Web scenes with the problems of slow rendering speed and low FPS (Frames Per Second), occlusion culling, as an important method for rendering optimization, can remove most of the occluded objects and improve rendering efficiency. The traditional occlusion culling algorithm (TOCA) is calculated by traversing all objects in the scene, which involves a large amount of repeated calculation and time consumption. To advance the rendering process and… More >

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