Jisun Kim, Jung Jin Kim^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079665 - 27 May 2026

Abstract Synthetic proximal femur models avoid the ethical and technical limitations of human specimens and thus serve as an effective alternative for studying the proximal femur. This structure is directly connected to the hip joint, endures complex multi-directional loads, and exhibits region-specific structural adaptations due to its unique triangular geometry. However, most previous studies have examined only global load distributions or restricted regions, limiting the understanding of regional structural optimality. Therefore, this study aims to quantitatively evaluate the load adaptability and structural optimality of the proximal femur across individual regions of interest (ROIs). Three types of… More >

Meng Zhao¹, Shuai Li¹, Yuanyuan Zhang^2,3, Yunduan Qin^2,3, Yu Xu^2,3, Chunyang Feng^2,3, Kekang Su^2,3, Xinlei Guo^2,3, Changwei Shen^1,*, Jingping Yuan^2,3,*

Phyton-International Journal of Experimental Botany, Vol.95, No.5, 2026, DOI:10.32604/phyton.2026.077668 - 27 May 2026

Abstract Chinese cabbage (Brassica rapa ssp. pekinensis) is a typical potassium (K)-demanding crop that is highly sensitive to soil K availability. Severe soil potassium deficiency in production fields frequently impairs both yield and quality. Therefore, screening for potassium-efficient varieties is essential for identifying germplasm resources and breeding materials tolerant to low-K conditions. To evaluate genetic variation in potassium utilization efficiency, 12 Chinese cabbage germplasms were assessed under two field conditions: with adequate potassium supply (K₂O 165 kg/ha) and without potassium application (K₂O 0 kg/ha). Fourteen parameters, including yield, plant growth, potassium content, and potassium accumulation, were measured and compared.… More >

Emmanuel E. Anyanwu¹, Obinna I. Anyanwu², Princewill Ikpeka^3,*

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.077231 - 27 May 2026

Abstract Increasing demand for freshwater and the need to reduce the carbon intensity of conventional desalination have accelerated interest in solar-driven distillation technologies. This study performs a cradle-to-grave Life-Cycle Assessment (LCA) of a nano-enhanced, double-effect single-slope Solar Still fabricated in Nigeria to quantify its embodied environmental impacts and identify material-level hotspots. Modeling was conducted in openLCA v2.4.1 using the Australian Life-Cycle Inventory (2019) database as a proxy. The functional unit was defined as the production of 1 m³ of freshwater distillate over a ten-year operational lifetime. From the analysis, the total Global Warming Potential (GWP₁₀₀) of the… More > Graphic Abstract

Ziliang Yang¹, Mykola Sysyn², Jin Li¹, Jizhe Zhang¹, Jian Liu¹, Lei Kou^1,3,*

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.078140 - 18 May 2026

Abstract Accurate assessment of the failure stage of rail rolling contact fatigue (RCF) is critical for guiding timely maintenance by track personnel, ensuring safe rail operations, and reducing maintenance costs. Although various methods have been developed to detect rail damage and classify surface defects, the rolling contact fatigue failure state of rails has not yet been comprehensively and objectively evaluated. This paper introduces the application of image processing and improved deep-learning network algorithms in rail failure evaluation and judgment. Based on Swin Transformer, a deep learning network is developed. By dividing the rail rolling contact fatigue More >

Pengcheng Kang¹, Yuanyuan Tian¹, Ying Liu¹, Qian Xu¹, Yuting Chen¹, Lixin Jia², Shuge Guo², Heng Rong², Taolong Xu^2,*

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077643 - 18 May 2026

Abstract Accurate assessment of gas explosion risks in urban underground culverts is often hindered by the decoupling of leakage diffusion and explosion mechanics. This study develops a high-fidelity numerical framework by implementing a one-way coupling strategy, where the steady-state methane concentration field simulated in FLUENT is mapped into ANSYS/LS-DYNA as the initial material status. Unlike traditional models assuming uniform gas distribution, this approach captures the realistic impact of complex culvert geometries on explosion precursors. A multi-material coupled model involving the confined space, road surface, and surrounding air was established to investigate shock-wave propagation and structural response. The More >

Gaeul Kim¹, Dohoon Kim^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078931 - 08 May 2026

Abstract Manned-Unmanned Teaming (MUM-T) is an operational system where manned and unmanned systems perform missions through a collaboration interface, expanding beyond defense into civilian domains. The core of MUM-T lies in the organic interaction between manned and unmanned systems. The Collaboration Interface enabling this interaction becomes a primary target for cyber attacks due to its reliance on wireless networks. Compromising the reliability of the collaboration interface goes beyond simple communication failures; it directly leads to mission failure and aircraft safety issues. Therefore, systematic threat analysis and assessment tailored to this specific domain are essential. This study… More >

Ali S. Alghamdi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079763 - 27 April 2026

Abstract The integration of wind-based DG introduces significant variability and uncertainty into the operation of distribution networks, which complicates the planning and decision-making process. This paper presents a dual-objective stochastic optimization framework for the optimal allocation of wind DG, considering dynamic network reconfiguration across multiple loading conditions. Probabilistic modeling of wind speed is integrated using the Weibull distribution and the associated wind power uncertainty is discretized through a scenario-based point estimation method. Variability in load is accounted for by considering multiple loading levels, and the integrated uncertainty space is constructed as the Cartesian product of wind… More >

Nai-Wei Lo¹, Cheng-I Lin², Chih-Chieh Chang^3,*, Chi-Yang Chang⁴, Tran Thi Luu Ly¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077316 - 27 April 2026

Abstract The growing frequency of malicious attacks on Internet of Things (IoT) devices has rendered conventional approaches with static label-dependent risk assessment models obsolete, especially when coping with unknown and continuously evolving threats. To mitigate these challenges, a novel dynamic trust evaluation framework approach is proposed in this work. The proposed framework utilized unsupervised learning and zero-knowledge proofs to assess device risks in complex environments adaptively, with an accuracy rate of 98.96% for normal clustering and 95.39% for anomalies. K-means clustering algorithm is leveraged to distinguish risk patterns with an additional Decision Tree classification algorithm to More >

Safaa M. Ali¹, Ranj S. Abdullah², Hussain H. Al-Kayiem³, Ali M. Tukkee^4,5,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.076252 - 27 April 2026

Abstract Energy supply and ventilation for isolated offices in rural areas are strongly recommended to be powered by renewable or standalone energy systems under the concept of net-zero-energy building (netZEB). A rooftop solar chimney is one of the adopted methods for space ventilation to improve thermal comfort. This approach has not been investigated under forced convection to support the netZEB. The objective of the current work is to experimentally assess the effectiveness of natural and forced ventilation methods for a prototype net-zero-energy office with a rooftop solar chimney. The prototype is a low-cost office constructed in… More > Graphic Abstract

Junwei Zhang¹, Pei Liu¹, Huihang Li¹, Guokang Huang¹, Bozheng Yuan¹, Wenjing Wei¹, Xiaoshun Zhang^2,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.072462 - 27 April 2026

Abstract Addressing global climate challenges necessitates urgent low carbon transitions in high energy consuming enterprises (HECEs). This study proposes a comprehensive framework to assess their carbon reduction potential (CRP) by integrating electricity usage behavior analysis and dynamic carbon emission factor (DCEF) prediction. HECEs are classified into “electricity reduction” and “electricity transfer” categories based on load characteristics, enabling tailored optimization strategies. The framework employs machine learning to predict DCEFs, capturing real time variations in grid carbon intensity. A low carbon optimization model is then formulated to minimize emissions while adhering to production requirements and grid constraints, solved… More > Graphic Abstract