Jing Li¹, Bo Ning^1,*, Bo Li², Xuemei Jin¹, Dezhi Qiu¹, Fenlan Ou¹

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074335 - 06 February 2026

Abstract As a controllable power generation method requiring no energy storage, Ocean Thermal Energy Conversion (OTEC) technology demonstrates characteristics of abundant reserves, low pollution, and round-the-clock stable operation. The free-standing cold-water pipe (CWP) in the system withstands various complex loads during operation, posing potential failure risks. To reveal the deformation and stress mechanisms of OTEC CWPs, this study first analyzes wave particle velocity and acceleration to determine wave loads at different water depths. Based on the Euler-Bernoulli beam model, a quasi-static load calculation model for OTEC CWPs was established. The governing equations were discretized using the… More >

Divya Ramesh, Sriram Venkatachalam^*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.069854 - 29 January 2026

Abstract A hybrid model combining Fully Non-Linear Potential Flow Theory (FNPT) based on the Finite Element Method (FEM) and the Unified Navier-Stokes equation, using the 3D Improved Meshless Local Petrov Galerkin method with Rankine Source (IMLPG_R), is developed to study wave interactions with a porous layer. In previous studies, the above formulations are applied to wave interaction with fixed cylindrical structures. The present study extends this framework by integrating a unified governing equation within the hybrid modeling approach to capture the dynamics of wave interaction with porous media. The porous layers are employed to replicate the… More >

Dexiecia Anak Francis¹, Jalal Tavalaei¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070501 - 27 January 2026

Abstract Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions. Despite Malaysia’s extensive coastline, the exploration of wave energy in Sarawak remains limited due to economic, technical, and environmental challenges that hinder its implementation. Compared to other renewable energy sources, wave energy is underutilized largely because of cost uncertainties and the lack of local performance data. This research aims to identify the most suitable coastal zone in Sarawak that achieves an optimal balance between energy potential, cost-effectiveness, and environmental impact, particularly in relation to… More >

Lei Zhao¹, Lihui Ma², Junwen Chen³, Pan Zhang², Jiang Bian^4,*, Dong Sun²

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070290 - 27 January 2026

Abstract Shock waves in the nozzle during supersonic separation under different conditions can disrupt the flow field’s thermodynamic equilibrium. While it contributes to the recovery of pressure energy, it also leads to the dissipation of mechanical energy. This study aimed to investigate the effects of changes in back pressure on the shock wave position and its subsequent impact on the refrigeration performance of nozzles. A mathematical model for the supersonic gas in a nozzle was established and evaluated via experiments. The results show that when the back pressure is less than 0.2 MPa, no shock wave… More >

Sarina Sulaiman^*, Muhammad Faris

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0105 - 23 January 2026

Abstract In this study, Palm kernel shell (PKS) is utilized as a raw material to produce activated biochar as adsorbent for dye removal from wastewater, specifically methylene blue (MB) dye, by utilizing a simplified and cost-effective approach. Production of activated biochar was carried out using both a furnace and a domestic microwave oven without an inert atmosphere. Three samples of palm kernel shell (PKS) based activated biochar labeled as samples A, B and C were carbonized inside the furnace at 800°C for 1 h and then activated using the microwave-heating technique with varying heating times (0,… More >

Jie Li¹, Nan An^2,3, Youliang Ding^2,3,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072361 - 08 January 2026

Abstract Vehicle-induced response separation is a crucial issue in structural health monitoring (SHM). This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data. To extend the separation target from a fixed dataset to a continuously updating data stream, a block-wise sliding framework is first developed. This framework is further optimized considering the characteristics of real-time data streams, and its advantage in computational efficiency is theoretically demonstrated. During the decomposition and reconstruction processes, information from neighboring data blocks is fully utilized to reduce algorithmic complexity. In addition, a… More >

Longqi Liao¹, Jing Li², Yuhua Li³, Yuemin Wang³, Jinhua Li^1,*, Liyuan Cao^4,*, Chunxiang Li^4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072237 - 08 January 2026

Abstract Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing. This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis. It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters. First, this study made samples with gradient defects for two types of grouting sleeves, G18 and G20. These included four cases: 2D, 4D, 6D defects (where D is the diameter of the grouting sleeve), and no-defect. Then, an ultrasonic input/output data acquisition system was established. Three-dimensional sound field distribution data were obtained through an orthogonal… More >

Mo Hou^1,2,3,#,*, Bin Xu^4,#, Wen Shang^1,2,3

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.071282 - 09 December 2025

Abstract Image captioning, a pivotal research area at the intersection of image understanding, artificial intelligence, and linguistics, aims to generate natural language descriptions for images. This paper proposes an efficient image captioning model named Mob-IMWTC, which integrates improved wavelet convolution (IMWTC) with an enhanced MobileNet V3 architecture. The enhanced MobileNet V3 integrates a transformer encoder as its encoding module and a transformer decoder as its decoding module. This innovative neural network significantly reduces the memory space required and model training time, while maintaining a high level of accuracy in generating image descriptions. IMWTC facilitates large receptive… More >

Hongji Chen, Jianxun Zhang^*, Tianze Yu, Yingzhu Zeng, Huan Zeng

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.067041 - 09 December 2025

Abstract Low-light image enhancement aims to improve the visibility of severely degraded images captured under insufficient illumination, alleviating the adverse effects of illumination degradation on image quality. Traditional Retinex-based approaches, inspired by human visual perception of brightness and color, decompose an image into illumination and reflectance components to restore fine details. However, their limited capacity for handling noise and complex lighting conditions often leads to distortions and artifacts in the enhanced results, particularly under extreme low-light scenarios. Although deep learning methods built upon Retinex theory have recently advanced the field, most still suffer from insufficient interpretability… More >

Jia Liu¹, Hao Chen¹, Hang Gu¹, Yushan Pan^2,3, Haoran Chen¹, Erlin Tian⁴, Min Huang⁴, Zuhe Li^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-24, 2026, DOI:10.32604/cmc.2025.068162 - 10 November 2025

Abstract Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning, disaster emergency response, and resource management. However, existing methods face challenges such as spectral similarity between buildings and backgrounds, sensor variations, and insufficient computational efficiency. To address these challenges, this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network (MewCDNet), which integrates the advantages of Convolutional Neural Networks and Transformers, balances computational costs, and achieves high-performance building change detection. The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction, integrates multi-level feature maps through a multi-scale fusion… More >