Louis F. Marie^*, Karina Sałek, Tadhg S. O’Donovan

Energy Engineering, Vol.120, No.10, pp. 2193-2209, 2023, DOI:10.32604/ee.2023.043075

Abstract Composite thermochemical energy storage (TCES) represents an exciting field of thermal energy storage which could address the issue of seasonal variance in renewable energy supply. However, there are open questions about their performance and the root cause of some observed phenomena. Some researchers have observed the breakdown of particles in their production phase, and in their use. This study seeks to investigate the underlying cause of this breakdown. SEM and EDX analysis have been conducted on MgCl₂ impregnated 13X zeolite composites of differing diameters, as well as LiX zeolite. This was done in order to study… More > Graphic Abstract

Zhengmao Yang^1,*, Junjie Yang², Yang Chen³, Fulei Jing⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09229

Abstract Woven ceramic matrix composites (CMCs), exhibiting excellent thermomechanical properties at high temperatures, are promising as alternative materials to the conventional nickel-based superalloys in the hot section components of aero-engines. Therefore, understanding and predicting the lifetime of CMCs is critical. Fatigue prediction of woven CMCs currently involves long-term and costly testing. A feasible alternative is to use predictive modelling based on a deep understanding of the damage mechanisms. Therefore, this study develops a multiscale analysis modelling method for predicting the fatigue life of CMC materials at high temperature by investigating the thermomechanical fatigue damage evolution. To… More >

Haiming Zhang^1,2,*, Shilin Zhao^1,2, Zhenshan Cui^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.08884

Abstract Particle-reinforced aluminum matrix composites (PRAMCs) have great potential for application in aerospace, automobile, defense, and electronics due to their high specific strength and stiffness and good resistance to wear and corrosion. Achieving a superior trade-off between the strength and ductility of PRAMCs necessitates an elaborative control of the microstructures, like the size and distribution of particles, as well as grain size, morphology, and texture of the matrix. The multiscale interaction between the particles and the matrix’s microstructure is insufficiently understood due to the lagging of high-resolved in-situ characterization. This work proposes a nonlocal physically based… More >

Fei Li¹, Haci Mehmet Baskonus^2,*, S. Kumbinarasaiah³, G. Manohara³, Wei Gao⁴, Esin Ilhan⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2381-2408, 2023, DOI:10.32604/cmes.2023.028069

Abstract This article considers three types of biological systems: the dengue fever disease model, the COVID-19 virus model, and the transmission of Tuberculosis model. The new technique of creating the integration matrix for the Bernoulli wavelets is applied. Also, the novel method proposed in this paper is called the Bernoulli wavelet collocation scheme (BWCM). All three models are in the form system of coupled ordinary differential equations without an exact solution. These systems are converted into a system of algebraic equations using the Bernoulli wavelet collocation scheme. The numerical wave distributions of these governing models are More >

Loc Vu-Quoc^1,*, Alexander Humer²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130

Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting… More >

Ming Cheng¹, Shiming Li^1,3,*, Yuhe Wang¹, Guohui Zhou¹, Peng Han¹, Yan Zhao²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427

Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the… More >

Ali Arshad^1,*, Muhammad Nadeem², Saman Riaz¹, Syeda Wajiha Zahra², Ashit Kumar Dutta³, Zaid Alzaid⁴, Rana Alabdan⁵, Badr Almutairi⁶, Sultan Almotairi^4,7

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3065-3089, 2023, DOI:10.32604/cmc.2023.035695

Abstract There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker… More >

Fawad Nasim^1,2,*, Muhammad Adnan Yousaf¹, Sohail Masood^1,2, Arfan Jaffar^1,2, Muhammad Rashid³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2865-2877, 2023, DOI:10.32604/iasc.2023.034258

Abstract Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We… More >

AAYUSHI RANDHAWA^1,2, SAYAN DEB DUTTA¹, KEYA GANGULY¹, TEJAL V. PATIL^1,2, RACHMI LUTHFIKASARI¹, KI-TAEK LIM^1,2,*

BIOCELL, Vol.47, No.4, pp. 789-808, 2023, DOI:10.32604/biocell.2023.026217

Abstract Tissues are made up of cells and the extracellular matrix (ECM) which surrounds them. These cells and tissues are actively adaptable to enduring significant stress that occurs in daily life. This astonishing mechanical stress develops due to the interaction between the live cells and the non-living ECM. Cells in the matrix microenvironment can sense the signals and forces produced and initiate a signaling cascade that plays a crucial role in the body’s normal functioning and influences various properties of the native cells, including growth, proliferation, and differentiation. However, the matrix’s characteristic features also impact the More >

Mohamed Maher Ata¹, Reem N. Yousef², Faten Khalid Karim^3,*, Doaa Sami Khafaga³

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1597-1616, 2023, DOI:10.32604/csse.2023.034375

Abstract Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the… More >