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  • 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 experimental data on wax deposition… 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

    Heat Recovery from Automotive Exhaust Using Heat Pipes with Limited Fluid Charge

    Bin Xiao*

    Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 35-48, 2024, DOI:10.32604/fhmt.2024.048039

    Abstract Experiments were conducted in this study to examine the thermal performance of a thermosyphon, made from Inconel alloy 625, could recover waste heat from automobile exhaust using a limited amount of fluid. The thermosyphon has an outer diameter of 27 mm, a thickness of 2.6 mm, and an overall length of 483 mm. The study involved directing exhaust gas onto the evaporator. This length includes a 180-mm evaporator, a 70-mm adiabatic section, a 223-mm condenser, and a 97-mm finned exchanger. The study examined the thermal performance of the thermosyphon under exhaust flow rates ranging from 0–10 g/sec and temperatures varying… More >

  • Open Access

    ARTICLE

    Flow Patterns and Heat Transfer Characteristics of a Polymer Pulsating Heat Pipe Filled with Hydrofluoroether

    Nobuhito Nagasato1, Zhengyuan Pei1, Yasushi Koito2,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 49-63, 2024, DOI:10.32604/fhmt.2024.047502

    Abstract Visualization experiments were conducted to clarify the operational characteristics of a polymer pulsating heat pipe (PHP). Hydrofluoroether (HFE)-7100 was used as a working fluid, and its filling ratio was 50% of the entire PHP channel. A semi-transparent PHP was fabricated using a transparent polycarbonate sheet and a plastic 3D printer, and the movements of liquid slugs and vapor plugs of the working fluid were captured with a high-speed camera. The video images were then analyzed to obtain the flow patterns in the PHP. The heat transfer characteristics of the PHP were discussed based on the flow patterns and temperature distributions… More >

  • Open Access

    ARTICLE

    Virtual Keyboard: A Real-Time Hand Gesture Recognition-Based Character Input System Using LSTM and Mediapipe Holistic

    Bijon Mallik1, Md Abdur Rahim1, Abu Saleh Musa Miah2, Keun Soo Yun3,*, Jungpil Shin2

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 555-570, 2024, DOI:10.32604/csse.2023.045981

    Abstract In the digital age, non-touch communication technologies are reshaping human-device interactions and raising security concerns. A major challenge in current technology is the misinterpretation of gestures by sensors and cameras, often caused by environmental factors. This issue has spurred the need for advanced data processing methods to achieve more accurate gesture recognition and predictions. Our study presents a novel virtual keyboard allowing character input via distinct hand gestures, focusing on two key aspects: hand gesture recognition and character input mechanisms. We developed a novel model with LSTM and fully connected layers for enhanced sequential data processing and hand gesture recognition.… More >

  • 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 of pipelines blasting test data… More >

  • Open Access

    ARTICLE

    A Composite Transformer-Based Multi-Stage Defect Detection Architecture for Sewer Pipes

    Zifeng Yu1, Xianfeng Li1,*, Lianpeng Sun2, Jinjun Zhu2, Jianxin Lin3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 435-451, 2024, DOI:10.32604/cmc.2023.046685

    Abstract Urban sewer pipes are a vital infrastructure in modern cities, and their defects must be detected in time to prevent potential malfunctioning. In recent years, to relieve the manual efforts by human experts, models based on deep learning have been introduced to automatically identify potential defects. However, these models are insufficient in terms of dataset complexity, model versatility and performance. Our work addresses these issues with a multi-stage defect detection architecture using a composite backbone Swin Transformer. The model based on this architecture is trained using a more comprehensive dataset containing more classes of defects. By ablation studies on the… 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 output feature layer of the… More >

  • Open Access

    ARTICLE

    Large-Scale 3D Thermal Transfer Analysis with 1D Model of Piped Cooling Water

    Shigeki Kaneko1, Naoto Mitsume2, Shinobu Yoshimura1,*

    Digital Engineering and Digital Twin, Vol.2, pp. 33-48, 2024, DOI:10.32604/dedt.2023.044279

    Abstract In an integrated coal gasification combined cycle plant, cooling pipes are installed in the gasifier reactor and water cooling is executed to avoid reaching an excessively high temperature. To accelerate the design, it is necessary to develop an analysis system that can simulate the cooling operation within the practical computational time. In the present study, we assumed the temperature fields of the cooled object and the cooling water to be governed by the three-dimensional (3D) heat equation and the one-dimensional (1D) convection-diffusion equation, respectively. Although some existing studies have employed similar modeling, the applications have been limited to simple-shaped structures.… More >

  • Open Access

    PROCEEDINGS

    Numerical Study on the Thermal Management of Lithium-Ion Battery Pack Based on Heat Pipes and Phase Change Material

    Chen Gao1, Kai Sun1, QingZhi Hou2,3, KeWei Song1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.08905

    Abstract As the fossil energy is increasingly exhausted and air pollution becomes more and more serious, blade electric vehicles equipped with rechargeable lithium-ion battery turns into the major developing direction of new energy automobile [1-3]. Lithium-ion batteries have the advantages of high energy density, light weight, and no pollution, and thereby are widely used in electric vehicles [4,5]. However, the working performance and service life of lithium-ion batteries are greatly affected by temperature [6]. Excessive high and low temperature will reduce the charge and discharge capacity of lithium-ion batteries, shorten their service life, and even lead to safety accidents [7]. Therefore,… More >

  • Open Access

    PROCEEDINGS

    Experimental and Numerical Simulation Study on Axial Drop Hammer Impact of Rubber Modified Non-Autoclaved Concrete Pipe Pile

    Sheng Lan1, Fei Yang1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09077

    Abstract Non-autoclaved concrete pipe piles are gaining attention as an environmentally friendly alternative to autoclaved concrete pipe piles. The purpose of this study was to investigate the changes in the impact resistance of a non-autoclaved concrete pipe pile with the addition of rubber. To this end, various volume fractions of rubber particles were used to replace the fine sand in the non-autoclaved pipe pile concrete (0%, 5%, 10% and 15%). Additionally, the axial impact resistance of rubber modified non-autoclaved concrete pipe pile was studied from the concrete materials and pipe pile components through quasi-static, dynamic compression and splitting tensile tests and… More >

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