Jingxiang Zhou¹, Qiaoling Zhou^1,*, Chunlian Liang¹, Yulu Guo¹, Zhao Xiao², Yingfeng Xu¹

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 953-983, 2025, DOI:10.32604/sdhm.2024.058501 - 30 June 2025

Abstract Streamlined box girders serve as a prevalent choice for the primary structural elements in large-span suspension bridge designs. With the increase in traffic demands, the design of such girders is evolving towards wider bridge decks and larger aspect ratios (B/D). To obtain more effective and aerodynamic design shapes for streamlined box girders, it is essential to investigate the impact of B/D on their aerodynamic performance. Accordingly, in this study we investigate the buffeting responses of large-span suspension bridges using girders of varying aspect ratios (B/D of 7.5, 9.3, and 12.7). First, the aerodynamic coefficients… More >

Sergio Cassese¹, Riccardo Guida^2,3,*, Daniele Trincone¹, Stefano Mungiguerra¹, Raffaele Savino¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1299-1337, 2025, DOI:10.32604/fdmp.2025.065605 - 30 June 2025

Abstract Robust numerical tools are essential for enabling the use of hybrid rocket engines (HREs) in future space applications. In this context, Computational Fluid Dynamics (CFD) transient simulations can be employed to analyse and predict relevant fluid dynamics phenomena within the thrust chamber of small-scale HREs. This work applies such techniques to investigate two unexpected behaviours observed in a 10 N-class hydrogen peroxide-based hybrid thruster: an uneven regression rate during High-Density Polyethylene (HDPE) and Acrylonitrile Butadiene Styrene (ABS) fuel tests, and non-negligible axial consumption in the ABS test case. The present study seeks to identify their… More >

Dumitru Baleanu^1,2, Carla M. A. Pinto³, Sunil Kumar^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1297-1299, 2025, DOI:10.32604/cmes.2025.067010 - 30 May 2025

Abstract This article has no abstract. More >

Mohamad Firdaus Omar¹, Fathilah Ali^1,*, Mohammed Saedi Jami¹, Azlin Suhaida Azmi¹, Farah Ahmad¹, Mohd Zahid Marzuki², Shantha Kumari Muniyandi³, Zuraidah Zainudin⁴, Minsoo P. Kim⁵

Journal of Renewable Materials, Vol.13, No.3, pp. 497-538, 2025, DOI:10.32604/jrm.2024.057248 - 20 March 2025

Abstract This review provides a comprehensive overview of natural rubber (NR) composites, focusing on their properties, compounding aspects, and renewable practices involving natural fibre reinforcement. The properties of NR are influenced by the compounding process, which incorporates ingredients such as elastomers, vulcanizing agents, accelerators, activators, and fillers like carbon black and silica. While effective in enhancing properties, these fillers lack biodegradability, prompting the exploration of sustainable alternatives. The potential of natural fibres as renewable reinforcements in NR composites is thoroughly covered in this review, highlighting both their advantages, such as improved sustainability, and the challenges they More > Graphic Abstract

Nahed Alsaleh^1,2, Reem Alnanih^1,*, Nahed Alowidi¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 949-976, 2025, DOI:10.32604/cmc.2024.059351 - 03 January 2025

Abstract App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products. Automating the analysis of these reviews is vital for efficient review management. While traditional machine learning (ML) models rely on basic word-based feature extraction, deep learning (DL) methods, enhanced with advanced word embeddings, have shown superior performance. This research introduces a novel aspect-based sentiment analysis (ABSA) framework to classify app reviews based on key non-functional requirements, focusing on usability factors: effectiveness, efficiency, and satisfaction. We propose a hybrid DL model, combining BERT (Bidirectional Encoder Representations from Transformers) More >

Tianzhi Zhang¹, Gang Zhou^1,*, Shuang Zhang², Shunhang Li¹, Yepeng Sun¹, Qiankun Pi¹, Shuo Liu³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 279-305, 2025, DOI:10.32604/cmc.2024.055943 - 03 January 2025

Abstract Joint Multimodal Aspect-based Sentiment Analysis (JMASA) is a significant task in the research of multimodal fine-grained sentiment analysis, which combines two subtasks: Multimodal Aspect Term Extraction (MATE) and Multimodal Aspect-oriented Sentiment Classification (MASC). Currently, most existing models for JMASA only perform text and image feature encoding from a basic level, but often neglect the in-depth analysis of unimodal intrinsic features, which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features. Given this problem, we propose a Text-Image Feature Fine-grained… More >

Wei Lu^1,3, Yujie Chen^2,*, Bo Yu², Dongliang Sun², Wei Zhang², Yanru Yang^1,3, Xiaodong Wang^1,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012265

Abstract Flow boiling offers superior heat transfer performance compared to single-phase flow, therefore holding significant potential for application in thermal management. In mini-channel applications, due to their narrow dimensions, the size characteristics of the channel have a particularly notable impact on bubble dynamics and flow boiling heat transfer performance. This study employs the VOSET method to explore the impact of different aspect ratios (1:3, 1:2, 1:1, 2:1, 3:1) on the heat transfer performance of mini-channels. By maintaining a consistent equivalent diameter across the channels, the study aims to unveil the mechanism by which aspect ratios affect… More >

Maan Habib^1,*, Ahed Habib², Mohammad Abboud³

Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >

Yuanjun Dai^1,2,3,*, Zetao Deng¹, Baohua Li², Lei Zhong¹, Jianping Wang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1517-1537, 2024, DOI:10.32604/fdmp.2024.046828 - 23 July 2024

Abstract A combined experimental and numerical research study is conducted to investigate the complex relationship between the structure and the aerodynamic performances of an Archimedes spiral wind turbine (ASWT). Two ASWTs are considered, a prototypical version and an improved version. It is shown that the latter achieves the best aerodynamic performance when the spread angles at the three sets of blades are α = 30°, α = 55°, α = 60°, respectively and the blade thickness is 4 mm. For a velocity V = 10 m/s, a tip speed ratio (TSR) = 1.58 and 2, the maximum C values More > Graphic Abstract

Mengqi Zhang¹, Jiazhao Chai², Jianxiang Cao³, Jialing Ji³, Tong Yi^4,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3743-3762, 2024, DOI:10.32604/cmc.2024.048486 - 26 March 2024

Abstract In recent years, deep learning methods have developed rapidly and found application in many fields, including natural language processing. In the field of aspect-level sentiment analysis, deep learning methods can also greatly improve the performance of models. However, previous studies did not take into account the relationship between user feature extraction and contextual terms. To address this issue, we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method. To be specific, we design user comment feature extraction (UCFE) to distill salient features from users’ historical comments and transform them More >