Chi Zhong¹, Bo Ye¹, Xiao Wang², Yang Liu^1,*, Linmin Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082583 - 30 June 2026

Abstract With the sharp increase in the heat flux of high-power electronic devices, efficient thermal management has become critically important. Boiling heat transfer in parallel small channels, which utilizes latent heat efficiently, has emerged as a key enabling technology for next-generation cooling solutions. However, parallel channel systems are extremely susceptible to flow instabilities, resulting in severely uneven distributions of flow rate and heat transfer among the channels. This unevenness often leads to local overheating, which in turn restricts the system’s reliability and limits its practical application. In this paper, a three-dimensional transient numerical simulation method was… More >

Shuai Wang^1,*, Ke Han¹, Min Yi^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082535 - 30 June 2026

Abstract Ferroelectric materials, integral to modern sensors, actuators, and transducers, exhibit complex fracture behavior under coupled electromechanical loading due to the intrinsic interplay between cracks, domain structures, and microstructural features. Linear piezoelectric fracture mechanics provides a foundational framework but fails to capture nonlinearities induced by domain switching and microstructure. This review synthesizes advances in computational modeling of ferroelectric fracture, with a focus on the unifying capabilities of the phase-field method (PFM). We first establish the fundamentals, including fracture toughness anisotropy and the crack-tip flexoelectric effect. We then critically assess traditional approaches like cohesive zone models and… More >

Menghua Li^1,2,3, Bin Ou^1,2,3,4, Jiahao Li^1,2,3, Sitong Jin^1,2,3, Yanming Zhang^1,2,3, Shuyan Fu^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082514 - 30 June 2026

Abstract Accurate prediction of seepage discharge in earth-rock dams remains challenging due to the strong non-stationary and nonlinear characteristics, limited robustness of individual models, and poor interpretability of black-box approaches. To address these issues, this paper proposes an interpretable hybrid model that integrates Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM) networks, and Support Vector Machine (SVM). The model first decomposes the seepage discharge sequence and relevant lagged features using VMD. The LSTM network then captures temporal dependencies of the decomposed components, while the SVM performs regression on the original sequences and features. An adaptive fusion… More >

Hyunjun Park¹, Hee-Gook Jun², Seongyong Kim³, Dong-Hyuk Im^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082506 - 30 June 2026

Abstract Time-series forecasting can significantly aid decision-making in fields in which immediate action is required, such as power demand forecasting, financial market analysis, and traffic flow management. Transformer-based models achieve high forecasting accuracy by learning complex temporal patterns; however, their extensive parameters and substantial computational costs make practical deployment difficult in latency-sensitive environments. Therefore, lightweight models based on linear layers have recently been studied for improved efficiency. However, existing linear-based models have difficulty capturing local patterns and fail to reflect sudden volatility or fine-grained local trends, limiting their overall representational capacity. In this paper, SegTSF is… More >

Jinha Kim¹, Hwankuk Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082504 - 30 June 2026

Abstract The advent of 5th Generation (5G) mobile networks has introduced Network Slicing as a core mechanism for supporting heterogeneous vertical services—such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC) over a shared physical infrastructure, thereby significantly expanding the attack surface at the User Plane Function (UPF). Securing this multi-slice environment requires intrusion detection systems that can simultaneously accommodate the statistical heterogeneity of per-slice traffic and the stringent Quality of Service (QoS) constraints of real-time slices, yet the practical cost of obtaining high-quality labeled traffic in operational 5G cores remains… More >

Weiguo Chen¹, Xiaobin Hong^1,*, Kai Chen¹, Yunyun Deng¹, Bin Zhang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082376 - 30 June 2026

Abstract Structural health monitoring (SHM) of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems. During the detection of ship T-shaped pipes using ultrasonic guided waves, signal overlap arises from the diffusion of guided wave branches. To address this issue, an intelligent wave-guidance mechanism based on acoustic metamaterials is proposed for dynamic propagation control of ultrasonic guided waves. First, a metamaterial unit composed of a stainless steel substrate and a copper column is designed. The control of bandgap characteristics by lattice constant, column diameter, and column height is systematically… More > Graphic Abstract

Riad Mollik Babu¹, Md Shafiul Alam^2,*, Md. Hasibur Rahman³, Mohammad Ali², Md. Alamgir Hossain⁴, Md. Arifuzzaman⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082366 - 30 June 2026

Abstract The increasing penetration of solar photovoltaic (PV) systems into power grids poses challenges due to their inherent intermittency and variability, which can compromise grid stability and reliability. Hybridizing solar PV with wind energy and battery energy storage system (BESS) offers a promising solution by leveraging resource complementarity and providing fast frequency response. This study presents a techno-economic and environmental assessment of a hybrid renewable energy system. Wind turbines and a BESS are integrated with the existing 7.5 MW Sirajganj Solar PV Power Plant in Bangladesh. The proposed hybrid configuration is evaluated using real-world operational data… More >

Botambu Collins, Jin-Taek Seong^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082245 - 30 June 2026

Abstract Classical image denoising methods remain relevant in practical scenarios where training data or noise models are unavailable, yet their performance is highly sensitive to parameter selection. Non-Local Means (NLM) is a representative example whose effectiveness depends critically on smoothing strength, patch size, and search window configuration. This paper formulates NLM parameter selection as a black-box optimization problem under unknown noise conditions and employs adaptive metaheuristic optimization strategies for this task. We propose an adaptive optimization framework that integrates rank-based perturbation, opposition-based learning, Lévy-flight exploration, and noise-aware parameter constraints to improve robustness and convergence. The proposed More >

Cristina Roxana Popa¹, Maria Tănase^2,*, Gheorghe Brănoiu³, Elena-Emilia Sirbu^4,5, Cătălina Călin⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082244 - 30 June 2026

Abstract Glass-fiber-reinforced polymer (GFRP) pipes are increasingly used in aggressive environments due to their high corrosion resistance and favorable mechanical properties. However, long-term exposure to saline environments and elevated temperatures can lead to degradation of their structural performance. This study investigates the influence of accelerated saltwater aging on the tensile behavior and structural characteristics of GFRP pipes and proposes machine-learning-based predictive models for the ultimate tensile strength (UTS). Experimental specimens were immersed in a 3.5% NaCl solution under controlled temperature and exposure time conditions. Tensile testing revealed that the unexposed samples exhibited a maximum UTS of… More >

Arvind Prasad^1,*, Ibrahim Aljubayri², Mohammad Zubair Khan^3,*, Abdulfattah Noorwali⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.3, 2026, DOI:10.32604/cmes.2026.082021 - 30 June 2026

Abstract Intrusion detection in large-scale IoT deployments becomes particularly challenging during ongoing attack scenarios, where malicious traffic may temporarily dominate benign traffic. In such conditions, streaming network data exhibits severe class imbalance in favor of attack traffic, while device behavior remains heterogeneous, non-identically distributed (non-IID), and temporally evolving. Within federated learning environments, this imbalance can destabilize early aggregation rounds, dominant attack gradients bias the global model, distort decision boundaries, and degrade reliable discrimination of residual benign behavior. Since the server has no access to raw data, these effects can persist across communication rounds if not addressed… More >