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  • Open Access

    REVIEW

    Exploring the Applications of Digital Twin Technology in Enhancing Sustainability in Civil Engineering: A Review

    Jiamin Huang1,2, Ping Wu2,*, Wangxin Li3, Jun Zhang2, Yidong Xu2

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 577-598, 2024, DOI:10.32604/sdhm.2024.050338

    Abstract With the advent of the big data era and the rise of Industrial Revolution 4.0, digital twins (DTs) have gained significant attention in various industries. DTs offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering industry. In this paper, 605 documents obtained from the search were first analysed using CiteSpace for literature visualisation, and an author co-occurrence network, a keyword co-occurrence network, and a keyword clustering set were obtained. Next, through a literature review of 86 papers, this paper summarises the current status of DT More >

  • Open Access

    ARTICLE

    Track Defects Recognition Based on Axle-Box Vibration Acceleration and Deep-Learning Techniques

    Xianxian Yin1, Shimin Yin1, Yiming Bu2, Xiukun Wei3,*

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 623-640, 2024, DOI:10.32604/sdhm.2024.050195

    Abstract As an important component of load transfer, various fatigue damages occur in the track as the rail service life and train traffic increase gradually, such as rail corrugation, rail joint damage, uneven thermite welds, rail squats fastener defects, etc. Real-time recognition of track defects plays a vital role in ensuring the safe and stable operation of rail transit. In this paper, an intelligent and innovative method is proposed to detect the track defects by using axle-box vibration acceleration and deep learning network, and the coexistence of the above-mentioned typical track defects in the track system… More >

  • Open Access

    REVIEW

    Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

    S. F. Ismael1,2,*, A. H. Alias1, N. A. Haron1, B. B. Zaidan3, Abdulrahman M. Abdulghani4

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 525-551, 2024, DOI:10.32604/sdhm.2024.050088

    Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

  • Open Access

    ARTICLE

    Impact Damage Testing Study of Shanxi-Beijing Natural Gas Pipeline Based on Decision Tree Rotary Tiller Operation

    Liqiong Chen1, Kai Zhang1,*, Song Yang1, Duo Xu1, Weihe Huang1, Hongxuan Hu2, Haonan Liu2

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 683-706, 2024, DOI:10.32604/sdhm.2024.049536

    Abstract The North China Plain and the agricultural region are crossed by the Shanxi-Beijing natural gas pipeline. Residents in the area use rototillers for planting and harvesting; however, the depth of the rototillers into the ground is greater than the depth of the pipeline, posing a significant threat to the safe operation of the pipeline. Therefore, it is of great significance to study the dynamic response of rotary tillers impacting pipelines to ensure the safe operation of pipelines. This article focuses on the Shanxi-Beijing natural gas pipeline, utilizing finite element simulation software to establish a finite More >

  • Open Access

    ARTICLE

    Numerical Simulation of Thermocapillary Convection with Evaporation Induced by Boundary Heating

    O. N. Goncharova1, V. B. Bekezhanova2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1667-1686, 2024, DOI:10.32604/fdmp.2024.047959

    Abstract The dynamics of a bilayer system filling a rectangular cuvette subjected to external heating is studied. The influence of two types of thermal exposure on the flow pattern and on the dynamic contact angle is analyzed. In particular, the cases of local heating from below and distributed thermal load from the lateral walls are considered. The simulation is carried out within the frame of a two-sided evaporative convection model based on the Boussinesq approximation. A benzine–air system is considered as reference system. The variation in time of the contact angle is described for both heating More > Graphic Abstract

    Numerical Simulation of Thermocapillary Convection with Evaporation Induced by Boundary Heating

  • Open Access

    ARTICLE

    Numerical Analysis of Permeability of Functionally Graded Scaffolds

    Dmitry Bratsun*, Natalia Elenskaya, Ramil Siraev, Mikhail Tashkinov

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1463-1479, 2024, DOI:10.32604/fdmp.2024.047928

    Abstract In this work, we numerically study the hydrodynamic permeability of new-generation artificial porous materials used as scaffolds for cell growth in a perfusion bioreactor. We consider two popular solid matrix designs based on triply periodic minimal surfaces, the Schwarz P (primitive) and D (diamond) surfaces, which enable the creation of materials with controlled porosity gradients. The latter property is crucial for regulating the shear stress field in the pores of the scaffold, which makes it possible to control the intensity of cell growth. The permeability of functionally graded materials is studied within the framework of… More > Graphic Abstract

    Numerical Analysis of Permeability of Functionally Graded Scaffolds

  • Open Access

    REVIEW

    A Comprehensive Survey on Deep Learning Multi-Modal Fusion: Methods, Technologies and Applications

    Tianzhe Jiao, Chaopeng Guo, Xiaoyue Feng, Yuming Chen, Jie Song*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1-35, 2024, DOI:10.32604/cmc.2024.053204

    Abstract Multi-modal fusion technology gradually become a fundamental task in many fields, such as autonomous driving, smart healthcare, sentiment analysis, and human-computer interaction. It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities. Under complex scenes, multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions. However, achieving outstanding performance is challenging because of equipment performance limitations, missing information, and data noise. This paper comprehensively reviews existing methods based on multi-modal fusion techniques and completes a detailed and in-depth analysis.… More >

  • Open Access

    ARTICLE

    CRBFT: A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

    Xiangyu Wu1, Xuehui Du1,*, Qiantao Yang1,2, Aodi Liu1, Na Wang1, Wenjuan Wang1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1491-1519, 2024, DOI:10.32604/cmc.2024.052708

    Abstract Blockchain has been widely used in finance, the Internet of Things (IoT), supply chains, and other scenarios as a revolutionary technology. Consensus protocol plays a vital role in blockchain, which helps all participants to maintain the storage state consistently. However, with the improvement of network environment complexity and system scale, blockchain development is limited by the performance, security, and scalability of the consensus protocol. To address this problem, this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance (PBFT) and proposes a Byzantine fault-tolerant (BFT) consensus… More >

  • Open Access

    ARTICLE

    Sentiment Analysis Using E-Commerce Review Keyword-Generated Image with a Hybrid Machine Learning-Based Model

    Jiawen Li1,2, Yuesheng Huang1, Yayi Lu1, Leijun Wang1,*, Yongqi Ren1, Rongjun Chen1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1581-1599, 2024, DOI:10.32604/cmc.2024.052666

    Abstract In the context of the accelerated pace of daily life and the development of e-commerce, online shopping is a mainstream way for consumers to access products and services. To understand their emotional expressions in facing different shopping experience scenarios, this paper presents a sentiment analysis method that combines the e-commerce review keyword-generated image with a hybrid machine learning-based model, in which the Word2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence (AI). Subsequently, a hybrid Convolutional Neural Network and Support Vector Machine (CNN-SVM) model… More >

  • Open Access

    ARTICLE

    Floating Waste Discovery by Request via Object-Centric Learning

    Bingfei Fu*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1407-1424, 2024, DOI:10.32604/cmc.2024.052656

    Abstract Discovering floating wastes, especially bottles on water, is a crucial research problem in environmental hygiene. Nevertheless, real-world applications often face challenges such as interference from irrelevant objects and the high cost associated with data collection. Consequently, devising algorithms capable of accurately localizing specific objects within a scene in scenarios where annotated data is limited remains a formidable challenge. To solve this problem, this paper proposes an object discovery by request problem setting and a corresponding algorithmic framework. The proposed problem setting aims to identify specified objects in scenes, and the associated algorithmic framework comprises pseudo… More >

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