Bengt Sundén^*, Jinliang Yuan

Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-20, 2010, DOI:10.5098/hmt.v1.1.3008

Abstract Depending on specific configuration and design, a variety of physical phenomena is present in fuel cells, e.g., multi-component gas flow, energy and mass transfer of chemical species in composite domains and sites. These physical phenomena are strongly affected by chemical/electrochemical reactions in nano-/micro-scale structured electrodes and electrolytes. Due to the electrochemical reactions, generation and consumption of chemical species together with electric current production take place at the active surfaces for all kinds of fuel cells. Furthermore, water management and twophase flow in proton exchange membrane fuel cells (PEMFCs) and internal reforming reactions of hydrocarbon fuels More >

Po Ting Lin, Hae Chang Gea, Yogesh Jaluria^*

Frontiers in Heat and Mass Transfer, Vol.1, No.1, pp. 1-20, 2010, DOI:10.5098/hmt.v1.1.3003

Abstract Thermal systems play significant roles in the engineering practice and our lives. To improve those thermal systems, it is necessary to model and optimize the design and the operating conditions. More importantly, the design uncertainties should be considered because the failures of the thermal systems may be very dangerous and produce large loss. This review paper focuses on a systematic strategy of modeling and optimizing of the thermal systems with the considerations of the design uncertainties. To demonstrate the proposed strategy, one of the complicated thermal systems, Chemical Vapor Deposition (CVD), is simulated, parametrically modeled,… More >

Kamaldeep Singh Oberoi¹, Géraldine Del Mondo²

Revue Internationale de Géomatique, Vol.31, No.2, pp. 377-399, 2022, DOI:10.3166/RIG.31.377-399c2022

Abstract Spatio-temporal (ST) graphs have been used in many application domains to model evolving ST phenomenon. Such models represent the underlying structure of the phenomenon in terms of its entities and different types of spatial interactions between them. The reason behind using graph-based models to represent ST phenomenon is due to the existing well-established graph analysis tools and algorithms which can be directly applied to analyze the phenomenon under consideration. In this paper, considering the use case of two distinct, highly dynamic phenomena - invasive team sports, with a focus on handball and urban road traffic,… More >

Mohammad Izadifar^a,b,* , Jane Alcorn^c

Frontiers in Heat and Mass Transfer, Vol.3, No.3, pp. 1-7, 2012, DOI:10.5098/hmt.v3.3.3005

Abstract Applying local volume averaging method a mathematical model including liver porosity, tortuosity, permeability, unbound drug fraction, drugplasma diffusivity, axial/radial dispersion and hepatocellular metabolism parameters was developed for hepatic drug elimination. The model was numerically solved using implicit finite difference method to describe drug concentration gradient with time across the liver. Statistically validated by observations and other models, the model suggested axial dispersion as a significant variable in drug distribution across the liver. Sensitivity analyses revealed that lower liver porosity resulted in faster drug distribution across the liver, and bioavailability was sensitive to the interaction between More >

Muhammad Akbar¹, Huali Pan^1,*, Jiangcheng Huang², Bilal Ahmed³, Guoqiang Ou¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2835-2863, 2024, DOI:10.32604/cmes.2024.046993

Abstract The present work aims to assess earthquake-induced earth-retaining (ER) wall displacement. This study is on the dynamics analysis of various earth-retaining wall designs in hollow precast concrete panels, reinforcement concrete facing panels, and gravity-type earth-retaining walls. The finite element (FE) simulations utilized a 3D plane strain condition to model full-scale ER walls and numerous nonlinear dynamics analyses. The seismic performance of different models, which includes reinforcement concrete panels and gravity-type and hollow precast concrete ER walls, was simulated and examined using the FE approach. It also displays comparative studies such as stress distribution, deflection of… More >

Peng Liao¹, Chaoge Liu², Jie Yin^1,3,*, Zhi Wang², Xiang Cui²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3255-3285, 2024, DOI:10.32604/cmes.2024.043855

Abstract Digital assets have boomed over the past few years with the emergence of Non-fungible Tokens (NFTs). To be specific, the total trading volume of digital assets reached an astounding $55.5 billion in 2022. Nevertheless, numerous security concerns have been raised by the rapid expansion of the NFT ecosystem. NFT holders are exposed to a plethora of scams and traps, putting their digital assets at risk of being lost. However, academic research on NFT security is scarce, and the security issues have aroused rare attention. In this study, the NFT ecological process is comprehensively explored. This… More >

Xianfeng Cao¹, Meihua Yao², Yahui Zhang^3,*, Xiaofeng Hu⁴, Chuanxun Wu³

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3233-3253, 2024, DOI:10.32604/cmes.2023.030773

Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control More > Graphic Abstract

Jian Pang^1,3, Tingting Mao², Wenyu Jia³, Xiaoli Jia^3,*, Peisong Dai², Haibo Huang^1,2,*

Sound & Vibration, Vol.58, pp. 59-80, 2024, DOI:10.32604/sv.2024.046247

Abstract Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both… More >

Elias Hossain¹, Abdullah Alshahrani², Wahidur Rahman^3,*

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511

Abstract This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling. The Methodology of this study is categorized into three phases: the Text Classification Approach (TCA), the Proposed Algorithms Interpretation (PAI), and finally, Information Retrieval Approach (IRA). The TCA reflects the text preprocessing pipeline called a clean corpus. The Global Vectors for Word Representation (Glove) pre-trained model, FastText, Term Frequency-Inverse Document Frequency (TF-IDF), and Bag-of-Words (BOW) for extracting the features have been interpreted in this research. The PAI manifests the Bidirectional Long Short-Term Memory (Bi-LSTM)… More >

Yanmei Li^1,*, Jinghong Tang¹, Weiwu Ding¹, Jian Luo², Naveed Ahmad³, Rajesh Kumar⁴

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 713-733, 2024, DOI:10.32604/cmc.2023.046872

Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder. The subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical practice. In this study, we introduce an advanced diagnostic methodology rooted in the Med-3D transfer model and enhanced with an attention mechanism. We aim to improve the precision of AD diagnosis and facilitate its early identification. Initially, we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation, which are commonly observed in imaging datasets. Subsequently, an attention mechanism is incorporated to More >