Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (728)
  • 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

    Dynamic Hypergraph Modeling and Robustness Analysis for SIoT

    Yue Wan, Nan Jiang*, Ziyu Liu

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3017-3034, 2024, DOI:10.32604/cmes.2024.051101

    Abstract The Social Internet of Things (SIoT) integrates the Internet of Things (IoT) and social networks, taking into account the social attributes of objects and diversifying the relationship between humans and objects, which overcomes the limitations of the IoT’s focus on associations between objects. Artificial Intelligence (AI) technology is rapidly evolving. It is critical to build trustworthy and transparent systems, especially with system security issues coming to the surface. This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT, aiming to build an SIoT hypergraph generation… More >

  • Open Access

    ARTICLE

    Modeling of Leachate Propagation in a Municipal Solid Waste Landfill Foundation

    Nadezhda Zubova*, Andrey Ivantsov

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1407-1424, 2024, DOI:10.32604/fdmp.2024.051130

    Abstract The study deals with the numerical modeling of leachate distribution in the porous medium located under a municipal solid waste disposal landfill (MSWLF). The considered three-layer system is based on geological data obtained from field measurements. For simplicity, the problem is investigated by assuming a two-component approach. Nevertheless, the heat produced by landfills due to biological and chemical processes and the thermal diffusion mechanism contributing to pollution transport are taken into account. The numerical modeling of the propagation of leachate in the considered layered porous medium is implemented for parameters corresponding to natural soil and More >

  • Open Access

    ARTICLE

    Modeling and Analysis of OFDMA-NOMA-RA Protocol Considering Imperfect SIC in Multi-User Uplink WLANs

    Hailing Yang1, Suoping Li1,2,*, Duo Peng2

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5273-5294, 2024, DOI:10.32604/cmc.2024.050869

    Abstract To address the problems of network congestion and spectrum resources shortage in multi-user large-scale scenarios, this paper proposes a twice random access OFDMA-NOMA-RA protocol combining the advantages of orthogonal frequency division multiple access (OFDMA) and non-orthogonal multiple access (NOMA). The idea of this protocol is that OFMDA is used to divide the entire frequency field into multiple orthogonal resource units (RUs), and NOMA is used on each RU to enable more users to access the channel and improve spectrum efficiency. Based on the protocol designed in this paper, in the case of imperfect successive interference… More >

  • Open Access

    ARTICLE

    Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

    Weiming Huang1,2, Baisong Liu1,*, Zhaoliang Wang1

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4449-4469, 2024, DOI:10.32604/cmc.2024.050389

    Abstract In the tag recommendation task on academic platforms, existing methods disregard users’ customized preferences in favor of extracting tags based just on the content of the articles. Besides, it uses co-occurrence techniques and tries to combine nodes’ textual content for modelling. They still do not, however, directly simulate many interactions in network learning. In order to address these issues, we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations. Specifically, we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles… More >

  • Open Access

    REVIEW

    Progress in Mechanical Modeling of Implantable Flexible Neural Probes

    Xiaoli You1,2,3,, Ruiyu Bai1,2,3,4,, Kai Xue1,2,3, Zimo Zhang1,2,3, Minghao Wang5, Xuanqi Wang1,2,3, Jiahao Wang1,2,3, Jinku Guo1,2, Qiang Shen3, Honglong Chang3, Xu Long6,*, Bowen Ji1,2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1205-1231, 2024, DOI:10.32604/cmes.2024.049047

    Abstract Implanted neural probes can detect weak discharges of neurons in the brain by piercing soft brain tissue, thus as important tools for brain science research, as well as diagnosis and treatment of brain diseases. However, the rigid neural probes, such as Utah arrays, Michigan probes, and metal microfilament electrodes, are mechanically unmatched with brain tissue and are prone to rejection and glial scarring after implantation, which leads to a significant degradation in the signal quality with the implantation time. In recent years, flexible neural electrodes are rapidly developed with less damage to biological tissues, excellent… More >

  • Open Access

    ARTICLE

    Modeling the Interaction between Vacancies and Grain Boundaries during Ductile Fracture

    Mingjian Li, Ping Yang*, Pengyang Zhao

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2019-2034, 2024, DOI:10.32604/cmes.2024.048334

    Abstract The experimental results in previous studies have indicated that during the ductile fracture of pure metals, vacancies aggregate and form voids at grain boundaries. However, the physical mechanism underlying this phenomenon remains not fully understood. This study derives the equilibrium distribution of vacancies analytically by following thermodynamics and the micromechanics of crystal defects. This derivation suggests that vacancies cluster in regions under hydrostatic compression to minimize the elastic strain energy. Subsequently, a finite element model is developed for examining more general scenarios of interaction between vacancies and grain boundaries. This model is first verified and More >

  • Open Access

    ARTICLE

    Analyzing COVID-19 Discourse on Twitter: Text Clustering and Classification Models for Public Health Surveillance

    Pakorn Santakij1, Samai Srisuay2,*, Pongporn Punpeng1

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 665-689, 2024, DOI:10.32604/csse.2024.045066

    Abstract Social media has revolutionized the dissemination of real-life information, serving as a robust platform for sharing life events. Twitter, characterized by its brevity and continuous flow of posts, has emerged as a crucial source for public health surveillance, offering valuable insights into public reactions during the COVID-19 pandemic. This study aims to leverage a range of machine learning techniques to extract pivotal themes and facilitate text classification on a dataset of COVID-19 outbreak-related tweets. Diverse topic modeling approaches have been employed to extract pertinent themes and subsequently form a dataset for training text classification models.… More >

  • Open Access

    ARTICLE

    Optimizing Two-Phase Flow Heat Transfer: DCS Hybrid Modeling and Automation in Coal-Fired Power Plant Boilers

    Ming Yan1, Caijiang Lu2,*, Pan Shi1,*, Meiling Zhang3, Jiawei Zhang1, Liang Wang1

    Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 615-631, 2024, DOI:10.32604/fhmt.2024.048333

    Abstract In response to escalating challenges in energy conservation and emission reduction, this study delves into the complexities of heat transfer in two-phase flows and adjustments to combustion processes within coal-fired boilers. Utilizing a fusion of hybrid modeling and automation technologies, we develop soft measurement models for key combustion parameters, such as the net calorific value of coal, flue gas oxygen content, and fly ash carbon content, within the Distributed Control System (DCS). Validated with performance test data, these models exhibit controlled root mean square error (RMSE) and maximum absolute error (MAXE) values, both within the… More > Graphic Abstract

    Optimizing Two-Phase Flow Heat Transfer: DCS Hybrid Modeling and Automation in Coal-Fired Power Plant Boilers

  • Open Access

    ARTICLE

    Artificial Neural Network Modeling for Predicting Thermal Conductivity of EG/Water-Based CNC Nanofluid for Engine Cooling Using Different Activation Functions

    Md. Munirul Hasan1, Md Mustafizur Rahman2,*, Mohammad Saiful Islam3, Wong Hung Chan4, Yasser M. Alginahi5, Muhammad Nomani Kabir6, Suraya Abu Bakar1, Devarajan Ramasamy2

    Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 537-556, 2024, DOI:10.32604/fhmt.2024.047428

    Abstract A vehicle engine cooling system is of utmost importance to ensure that the engine operates in a safe temperature range. In most radiators that are used to cool an engine, water serves as a cooling fluid. The performance of a radiator in terms of heat transmission is significantly influenced by the incorporation of nanoparticles into the cooling water. Concentration and uniformity of nanoparticle distribution are the two major factors for the practical use of nanofluids. The shape and size of nanoparticles also have a great impact on the performance of heat transfer. Many researchers are… More > Graphic Abstract

    Artificial Neural Network Modeling for Predicting Thermal Conductivity of EG/Water-Based CNC Nanofluid for Engine Cooling Using Different Activation Functions

Displaying 1-10 on page 1 of 728. Per Page