Anastasia Bushueva, Olga Vlasova, Denis Polezhaev^*

FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2024.048271

Abstract The steady flow in a Hele-Shaw cell filled with fluids with a high viscosity contrast in the presence of fluid oscillations is experimentally studied. The control of oscillatory dynamics of multiphase systems with interfaces is a challenging technological problem. We consider miscible (water and glycerol) and immiscible (water and high-viscosity silicone oil PMS-1000) fluids under subsonic oscillations perpendicular to the interface. Observations show that the interface shape depends on the amplitude and frequency of oscillations. The interface is undisturbed only in the absence of oscillations. Under small amplitudes, the interface between water and glycerol widens due to mixing. When the… More >

Mengdong An¹, Weiyuan Zhong¹, Wei Xu², Xiuli Wang^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.046604

Abstract The reactor coolant pump (RCP) rotor seizure accident is defined as a short-time seizure of the RCP rotor. This event typically leads to an abrupt flow decrease in the corresponding loop and an ensuing reactor and turbine trip. The significant reduction of core coolant flow while the reactor is being operated at full load can have very negative consequences. This potentially dangerous event is typically characterized by a complex transient behavior in terms of flow conditions and energy transformation, which need to be analyzed and understood. This study constructed transient flow and rotational speed mathematical models under various degrees of… More >

Shuilian Li¹, Fan Zeng¹, Xinli Wei^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.043614

Abstract In order to increase the efficiency of solar air collectors, a new variant with a protrusion is proposed in this study, and its performances are analyzed from two points of view, namely, in terms of optics and thermodynamics aspects. By comparing and analyzing the light paths of the protrusion and the dimple, it can be concluded that when sunlight shines on the dimple, it is reflected and absorbed multiple times, whereas for the sunlight shining on the protrusion, there is no secondary reflection or absorption of light. When the lighting area and the properties of the surfaces are the same,… More >

Haosong Gou¹, Gaoyi Zhang¹, Renê Ripardo Calixto², Senthil Kumar Jagatheesaperumal³, Victor Hugo C. de Albuquerque^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047806

Abstract Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs. The primary goal is to enhance the reliability of data collection and transmission services, ensuring a comprehensive and practical approach. Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability. Additionally,… More >

Chengkan Xu^1,2,4, Xiaofei Wang³, Yixuan Li², Guannan Wang^2,*, He Zhang^2,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047327

Abstract Structural damage in heterogeneous materials typically originates from microstructures where stress concentration occurs. Therefore, evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial. Repeating unit cells (RUCs) are commonly used to represent microstructural details and homogenize the effective response of composites. This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs. The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters, including volume fraction, fiber/matrix property ratio, fiber shapes, and loading direction. Subsequently, the conditional generative adversarial network… More > Graphic Abstract

Muhammad Shoaib Arif^1,2,*, Kamaleldin Abodayeh¹, Yasir Nawaz²

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.046944

Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part description of its membership level.… More >

Dongsheng Jia, Yingjie Xu^*, Liangdi Wang, Jihong Zhu, Weihong Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.046703

Abstract The abalone shell, a composite material whose cross-section is composed of inorganic and organic layers, has high strength and toughness. Inspired by the abalone shell, several multi-layer composite plates with different layer sequences and thicknesses are studied as bullet-proof material in this paper. To investigate the ballistic performance of this multi-layer structure, the complete characterization model and related material parameters of large deformation, failure and fracture of Al₂O₃ ceramics and Carbon Fiber Reinforced Polymer (CFRP) are studied. Then, 3D finite element models of the proposed composite plates with different layer sequences and thicknesses impacted by a 12.7 mm armor-piercing incendiary… More >

S. Dickson¹, S. Padmasekaran¹, Pushpendra Kumar^2,*, Kottakkaran Sooppy Nisar³, Hamidreza Marasi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.030286

Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQI_cRVW and SQIRV models, considering the delay in converting susceptible individuals into infected ones. The significant delays eventually resulted in the pandemic’s containment. To ensure the safety of the host population, this concept integrates quarantine and the COVID-19 vaccine. We investigate the stability of the proposed models. The fundamental reproduction number influences stability conditions. According to our findings, asymptomatic cases considerably impact the prevalence of Omicron infection in the community. The real data of the Omicron variant from Chennai, Tamil Nadu, India, is used to validate the… More >

Jiadong Wu, Yinan Wang^*, Zhiwei Li^*, Lun Lu, Qingjiang Li

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047240

Abstract Artificial neural networks (ANNs) have led to landmark changes in many fields, but they still differ significantly from the mechanisms of real biological neural networks and face problems such as high computing costs, excessive computing power, and so on. Spiking neural networks (SNNs) provide a new approach combined with brain-like science to improve the computational energy efficiency, computational architecture, and biological credibility of current deep learning applications. In the early stage of development, its poor performance hindered the application of SNNs in real-world scenarios. In recent years, SNNs have made great progress in computational performance and practicability compared with the… More >

Zihao Song, Yan Zhou^*, Wei Cheng, Futai Liang, Chenhao Zhang

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047034

Abstract The frequent missing values in radar-derived time-series tracks of aerial targets (RTT-AT) lead to significant challenges in subsequent data-driven tasks. However, the majority of imputation research focuses on random missing (RM) that differs significantly from common missing patterns of RTT-AT. The method for solving the RM may experience performance degradation or failure when applied to RTT-AT imputation. Conventional autoregressive deep learning methods are prone to error accumulation and long-term dependency loss. In this paper, a non-autoregressive imputation model that addresses the issue of missing value imputation for two common missing patterns in RTT-AT is proposed. Our model consists of two… More >