Pengfei Duan^1,*, Luling Li¹, Jianhui Liu¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012431

Abstract The supply of hydrogen-blended natural gas to civil and industrial users can assist downstream firm to achieve carbon emission reduction, and ensure energy security as an alternative gas source. This application mode has been widely concerned by urban gas enterprises. This paper focuses on the leakage problem of hydrogen-blended pipelines in utility tunnel due to corrosion and other reasons. Using dimensional analysis method, a model experiment is designed to verify that the three-dimensional compressible fluid model coupled with transport equations can effectively simulate the concentration change of hydrogen-blended natural gas after leakage in the utility… More >

Hossam S. El-Beltagi^1,2,*, Mohamed Fathi El-Nady³, Adel A. Rezk^1,4, Abdelaziz M. Tahoon⁵, Mohammed I. Al-Daej¹, Dina Abdulmajid⁶, Mohamed M. El-Mogy⁷, Elsayed Abd Elmaksoud Abomarzoka⁸, Sherif Mohamed El-Ganainy^7,9, Metwaly Mahfouz Salem Metwaly³

Phyton-International Journal of Experimental Botany, Vol.93, No.10, pp. 2535-2556, 2024, DOI:10.32604/phyton.2024.056734 - 30 October 2024

Abstract Rice (Oryza sativa L.) is one of the most important cereal crops in the world. Bakanae disease is a significant rice disease widely distributed in rice-growing regions worldwide. Therefore, the present investigation aimed to assess the optimal concentrations of paclobutrazol (PBZ) as a treatment for rice grains (cv. Sakha 108) to control bakanae disease, also evaluating its impact on grain germination, seedling growth parameters as well as disease index. Paclobutrazol concentrations had no significant impact on seed germination, regardless of whether the seeds were incubated with Fusarium fujikuroi or not. Application of PBZ, either alone or in… More >

Zhenjiang Zhao¹, Lei Jiang¹, Ling Bai^2,*, Bo Pan³, Ling Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1111-1136, 2024, DOI:10.32604/cmes.2024.055399 - 27 September 2024

Abstract The fluid’s viscosity significantly affects the performance of a centrifugal pump. The entropy production method and leakage are employed to analyze the performance changes under various viscosities by numerical simulation and validated by experiments. The results showed that increasing viscosity reduces both the pump head and efficiency. In addition, the optimal operating point shifts to the left. Leakage is influenced by vortex distribution in the front chamber and boundary layer thickness in wear-ring clearance, leading to an initial increase and subsequent decrease in leakage with increasing viscosity. The total entropy production inside the pump rises More >

Liqiong Chen¹, Kui Zhao¹, Kai Zhang^1,*, Duo Xv¹, Hongxvan Hu², Guoguang Ma¹, Wenwen Zhan³

Energy Engineering, Vol.121, No.8, pp. 2143-2165, 2024, DOI:10.32604/ee.2024.049362 - 19 July 2024

Abstract The leakage gas from a buried natural gas pipelines has the great potential to cause economic losses and environmental pollution owing to the complexity of the mountainous environment. In this study, computational fluid dynamics (CFD) method was applied to investigate the diffusion law and hazard range of buried natural gas pipeline leakage in mountainous environment. Based on cloud chart, concentration at the monitoring site and hazard range of lower explosion limit (LEL) and upper explosion limit (UEL), the influences of leakage hole direction and shape, soil property, burial depth, obstacle type on the diffusion law… More >

Yuyuan Li^1,2, Lang Li^1,2,*, Yu Ou^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1245-1262, 2024, DOI:10.32604/cmc.2024.049882 - 25 April 2024

Abstract The Inner Product Masking (IPM) scheme has been shown to provide higher theoretical security guarantees than the Boolean Masking (BM). This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of security. Some previous work unfolds when certain (adversarial and implementation) conditions are met, and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected behaviour. In this paper, we investigate the security characteristics of IPM under different conditions. In adversarial condition, the security properties of first-order IPMs obtained through parametric characterization More >

Abidhan Bardhan^1,*, Raushan Kumar Singh², Mohammed Alatiyyah³, Sulaiman Abdullah Alateyah^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1521-1555, 2024, DOI:10.32604/cmes.2023.044467 - 29 January 2024

Abstract This research proposes a highly effective soft computing paradigm for estimating the compressive strength (CS) of metakaolin-contained cemented materials. The proposed approach is a combination of an enhanced grey wolf optimizer (EGWO) and an extreme learning machine (ELM). EGWO is an augmented form of the classic grey wolf optimizer (GWO). Compared to standard GWO, EGWO has a better hunting mechanism and produces an optimal performance. The EGWO was used to optimize the ELM structure and a hybrid model, ELM-EGWO, was built. To train and validate the proposed ELM-EGWO model, a sum of 361 experimental results… More >

Jie Li^1,3,*, Rongwen Wang², Yongtao Hu^1,3, Jinjun Li¹

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 73-90, 2024, DOI:10.32604/sdhm.2023.044023 - 11 January 2024

Abstract The aging prediction of railway catenary is of profound significance for ensuring the regular operation of electrified trains. However, in real-world scenarios, accurate predictions are challenging due to various interferences. This paper addresses this challenge by proposing a novel method for predicting the aging of railway catenary based on an improved Kalman filter (KF). The proposed method focuses on modifying the priori state estimate covariance and measurement error covariance of the KF to enhance accuracy in complex environments. By comparing the optimal displacement value with the theoretically calculated value based on the thermal expansion effect… More > Graphic Abstract

RABIRANJAN MURMU^a,b, DEBASHIS ROY^a, HAREKRUSHNA SUTAR^b

Journal of Polymer Materials, Vol.40, No.3-4, pp. 125-139, 2023, DOI:10.32381/JPM.2023.40.3-4.1

Abstract A one dimensional isothermal model is proposed by modelling the kinetics of methanol transport at anode flow channel (AFC), membrane and cathode catalyst layer of direct methanol fuel cell (DMFC). Analytical model is proposed to predict methanol cross-over rate through the electrolyte membrane and cell performance. The model presented in this paper considered methanol diffusion and electrochemical oxidation at the anode and cathode channels. The analytical solution of the proposed model was simulated in a MATLAB environment to obtain the polarization curve and leakage current. The effect of methanol concentration on cell voltage and leakage More >

A. C. Filankembo Kava^*, B. C. Ndjengue Bengono, P. L. Nzamba Bissielou, C. Nziengui Tirogo, A. Kabena, T. Mpami, E. Belembaogo

Psycho-Oncologie, Vol.17, No.4, pp. 267-273, 2023, DOI:10.32604/po.2023.044512 - 28 December 2023

Abstract Objectif. Le syndrome d’épuisement professionnel est fréquent chez les travailleurs de la santé en oncologie. Non diagnostiqué et incorrectement pris en charge, le burnout peut avoir un impact négatif sur le rendement professionnel. L’Institut de Cancérologie d’Akanda (ICA) est un centre hospitalier ultra-moderne qui se veut une référence en matière de prise en charge du cancer en Afrique centrale. L’objectif de l’étude est de mesurer la fréquence du burnout au sein du personnel soignant de l’Institut de Cancérologie d’Akanda et d’évaluer les principaux facteurs de risque. Patients et méthodes. Nous avons mené une étude transversale à l’Institut… More >

Jiansheng Peng^1,2,*, Jinsong Guo¹, Fengbo Bao¹, Chengjun Yang², Yong Xu², Yong Qin²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2971-2994, 2023, DOI:10.32604/cmc.2023.041897 - 26 December 2023

Abstract The robotics industry has seen rapid development in recent years due to the Corona Virus Disease 2019. With the development of sensors and smart devices, factories and enterprises have accumulated a large amount of data in their daily production, which creates extremely favorable conditions for robots to perform machine learning. However, in recent years, people’s awareness of data privacy has been increasing, leading to the inability to circulate data between different enterprises, resulting in the emergence of data silos. The emergence of federated learning provides a feasible solution to this problem, and the combination of… More >