Zijian Liu¹, Yong Shi², Chuanqi Li¹, Xiliang Zhang^3,*, Jian Zhou¹, Manoj Khandelwal^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 153-183, 2025, DOI:10.32604/cmes.2025.062426 - 11 April 2025

Abstract Given the growing concern over global warming and the critical role of carbon dioxide (CO₂) in this phenomenon, the study of CO₂-induced alterations in coal strength has garnered significant attention due to its implications for carbon sequestration. A large number of experiments have proved that CO₂ interaction time (T), saturation pressure (P) and other parameters have significant effects on coal strength. However, accurate evaluation of CO₂-induced alterations in coal strength is still a difficult problem, so it is particularly important to establish accurate and efficient prediction models. This study explored the application of advanced machine learning (ML)… More >

Nour Elhouda Chalabi¹, Abdelouahab Attia², Abdulaziz S. Almazyad³, Ali Wagdy Mohamed^4,5, Frank Werner⁶, Pradeep Jangir⁷, Mohammad Shokouhifar^8,9,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 967-1008, 2025, DOI:10.32604/cmes.2025.062332 - 11 April 2025

Abstract Multi-objective optimization is critical for problem-solving in engineering, economics, and AI. This study introduces the Multi-Objective Chef-Based Optimization Algorithm (MOCBOA), an upgraded version of the Chef-Based Optimization Algorithm (CBOA) that addresses distinct objectives. Our approach is unique in systematically examining four dominance relations—Pareto, Epsilon, Cone-epsilon, and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto front. Our comparison investigation, which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering, mechanical design, and power systems, reveals that the dominance approach More >

Yaojin Fan, Huaqing Dong^*, Zixuan Zong, Tingting Long, Qianglin Huang, Guoqiang Huang

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 731-769, 2025, DOI:10.32604/sdhm.2025.061056 - 03 April 2025

Abstract This study presents a comprehensive investigation of residual strength in corroded pipelines within the Yichang-Qianjiang section of the Sichuan-East Gas Pipeline, integrating advanced numerical simulation with experimental validation. The research methodology incorporates three distinct parameter grouping approaches: a random group based on statistical analysis of 389 actual corrosion defects detected during 2023 MFL inspection, a deviation group representing historically documented failure scenarios, and a structural group examining systematic parameter variations. Using ABAQUS finite element software, we developed a dynamic implicit analysis model incorporating geometric nonlinearity and validated it through 1:12.7 scaled model testing, achieving prediction… More >

Yuanyin Song¹, Wenwei Wang^2,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 549-574, 2025, DOI:10.32604/sdhm.2024.055382 - 03 April 2025

Abstract To meticulously dissect the cracking issue in the transverse diaphragm concrete, situated at the anchor point of a colossal large-span, single cable plane cable-stayed bridge, this research paper adopts an innovative layered modeling analysis methodology for numerical simulations. The approach is structured into three distinct layers, each tailored to address specific aspects of the cracking phenomenon. The foundational first layer model operates under the assumption of linear elasticity, adhering to the Saint Venant principle. It narrows its focus to the crucial zone between the Bp20 transverse diaphragm and the central axis of pier 4’s support,… More >

Ulla Milbreta^1,2, Laura Andze¹, Juris Zoldners¹, Ilze Irbe¹, Marite Skute¹, Inese Filipova^1,*

Journal of Renewable Materials, Vol.13, No.3, pp. 583-597, 2025, DOI:10.32604/jrm.2024.057663 - 20 March 2025

Abstract This study investigated the potential of locally sourced mushrooms as a sustainable alternative to marine-derived chitosan in papermaking. Chitosan was extracted from four local (Boletus edulis, Suillus luteus, Leccinum aurantiacum, Suillus variegatus), one commercially available (Agaricus bisporus) and one laboratory-grown (Phanerochaete chrysosporium) fungal species. Paper handsheets were prepared using either 100% regenerated paper or a 50/50 blend of regenerated paper and hemp fibres. 2.5% chitosan (based on dry mass) was incorporated into the paper mass, using chitosan sourced from B. edulis, A. bisporus, P. chrysosporium, and crustacean chitosan. Fungal chitosan sources were selected based on multiple factors. B. edulis exhibited the highest chitosan yield… More >

Xinrong Zhang¹, Bo Chang^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5079-5095, 2025, DOI:10.32604/cmc.2025.059469 - 06 March 2025

Abstract In the RSSI-based positioning algorithm, regarding the problem of a great conflict between precision and cost, a low-power and low-cost synergic localization algorithm is proposed, where effective methods are adopted in each phase of the localization process and fully use the detective information in the network to improve the positioning precision and robustness. In the ranging period, the power attenuation factor is obtained through the wireless channel modeling, and the RSSI value is transformed into distance. In the positioning period, the preferred reference nodes are used to calculate coordinates. In the position optimization period, Taylor… More >

Jinxing Li¹, Mustafa Zor², Xiaojian Zhou³, Guanben Du³, Denis Rodrigue⁴, Xiaodong (Alice) Wang^1,*

Journal of Renewable Materials, Vol.13, No.2, pp. 329-347, 2025, DOI:10.32604/jrm.2024.056795 - 20 February 2025

Abstract In this study, two series of foams based on tannic acid (TA), furfuryl alcohol (FA), soybean protein isolate (SPI), and casein (CA), namely TA–FA–SPI (TS series) and TA–FA–CA (TC series) were developed, and their properties were enhanced by adding poplar fibers (WF). From the samples produced, a complete set of characterization was performed including possible crosslinking reactions, morphology, mechanical properties, flame retardancy, thermal insulation and thermal stability. Fourier-transform infrared spectroscopy (FTIR) revealed possible covalent crosslinking among the components and hydrogen bonding between WF and the matrix. Viscosity results indicated that lower prepolymer viscosity led to… More >

Chenglong Zhong¹, Xianfeng Hou^1,*, Shuai Peng¹, Zhenzhong Gao¹, Qiaofang Zhou¹, Shijing Yan²

Journal of Renewable Materials, Vol.13, No.2, pp. 297-310, 2025, DOI:10.32604/jrm.2024.049534 - 20 February 2025

Abstract The main raw material utilized in wood adhesives comes from petrochemical extractives. However, due to the excessive dependence on petrochemical resources and the adverse impact on the ecosystem and human well-being, there is an increasing trend to develop byproduct protein-based adhesives in the current global food safety context. In this research, flaxseed meal was subjected to pretreatment, and trimethylolpropane triglycidyl ether (TTE) and ethylenediamine (EN) were utilized as crosslinkers to establish a more compact adhesive layer and to prevent water intrusion. The pretreatment decreased the FM/UB viscosity by 60% compared to FM. The combination… More > Graphic Abstract

Quynh-Anh Thi Bui^1,*, Dam Duc Nguyen¹, Hiep Van Le¹, Indra Prakash², Binh Thai Pham^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 691-712, 2025, DOI:10.32604/cmes.2024.054766 - 17 December 2024

Abstract Determination of Shear Bond strength (SBS) at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures. The study used three Machine Learning (ML) models, including K-Nearest Neighbors (KNN), Extra Trees (ET), and Light Gradient Boosting Machine (LGBM), to predict SBS based on easily determinable input parameters. Also, the Grid Search technique was employed for hyper-parameter tuning of the ML models, and cross-validation and learning curve analysis were used for training the models. The models were built on a database of 240 experimental results and three input variables: temperature, normal pressure, and tack coat… More >

Weiwei Hu¹, Kiran Sree Pokkuluri², Rajesh Arunachalam^3,*, Bander A. Jabr⁴, Yasser A. Ali⁴, Preethi Palanisamy⁵

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4833-4851, 2024, DOI:10.32604/cmc.2024.055561 - 19 December 2024

Abstract Wireless Sensor Network (WSNs) consists of a group of nodes that analyze the information from surrounding regions. The sensor nodes are responsible for accumulating and exchanging information. Generally, node localization is the process of identifying the target node’s location. In this research work, a Received Signal Strength Indicator (RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization models. Initially, the RSSI value is identified using the Deep Neural Network (DNN). The RSSI is conceded as the range-based method and it does not require special hardware for the node… More >