Yanzhao Yang¹, Kai Yang², Junwei Zhang³, Fengsuo Jiang¹, Sheng Xu¹, Lei Chen⁴, Jun Bai⁵, Luyi Lu⁵, Hua Ji⁵, Zhihao Jing⁵, Senhao Wang¹, Jingjing Zheng¹, Haifeng Zhai^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075227 - 06 February 2026

Abstract The low-pressure and low-density conditions encountered at high altitudes significantly reduce the operating Reynolds number of micro radial-flow turbines, frequently bringing it below the self-similarity critical threshold of 3.5 × 10⁴. This departure undermines the applicability of conventional similarity-based design approaches. In this study, micro radial-flow turbines with rotor diameters below 50 mm are investigated through a combined approach integrating high-fidelity numerical simulations with experimental validation, aiming to elucidate the mechanisms by which low Reynolds numbers influence aerodynamic and thermodynamic performance. The results demonstrate that decreasing Reynolds number leads to boundary-layer thickening on blade surfaces, enhanced More >

Hussain H. Al-Kayiem^1,*, Safaa M. Ali², Sundus S. Al-Azawiey³, Raed A. Jessam³

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073303 - 27 January 2026

Abstract Gas Turbines are among the most important energy systems for aviation and thermal-based power generation. The performance of gas turbine intakes with S-shaped diffusers is vulnerable to flow separation, reversal flow, and pressure distortion, mainly in aggressive S-shaped diffusers. Several methods, including vortex generators and energy promoters, have been proposed and investigated both experimentally and numerically. This paper compiles a review of experimental investigations that have been performed and reported to mitigate flow separation and restore system performance. The operational principles, classifications, design geometries, and performance parameters of S-shaped diffusers are presented to facilitate the… More > Graphic Abstract

Cheng Yang^*, Hanjie Qi, Qing Yin

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070957 - 27 January 2026

Abstract In order to enhance the off-peak performance of gas turbine combined cycle (GTCC) units, a novel collaborative power generation system (CPG) was proposed. During off-peak operation periods, the remaining power of the GTCC was used to drive the adiabatic compressed air energy storage (ACAES), while the intake air of the GTCC was heated by the compression heat of the ACAES. Based on a 67.3 MW GTCC, under specific demand load distribution, a CPG system and a benchmark system (BS) were designed, both of which used 9.388% of the GTCC output power to drive the ACAES.… More >

Hongsheng Su, Zhensheng Teng^*, Zihan Zhou

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.069495 - 27 January 2026

Abstract Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy, replacement-based maintenance practices that deviate from actual operational conditions, and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization, this study proposes a Time-Based Incomplete Maintenance (TBIM) strategy incorporating reliability constraints through stochastic differential equations (SDE). By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions, a high-precision SDE degradation model is constructed, achieving 16% residual reduction compared to… More >

Lifu He¹, Zhongchu Huang¹, Haidong Shao^2,*, Zhangbo Hu¹, Yuting Wang¹, Jie Mei¹, Xiaofei Zhang³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073227 - 12 January 2026

Abstract Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction. However, several challenges remain. First, signal noise collected during blade operation masks fault features, severely impairing the fault diagnosis performance of deep learning models. Second, current blade fault diagnosis often relies on single-sensor data, resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states. To address these issues, a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed. Specifically, a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to More >

Tao Zhang^1,*, Hailun Wang¹, Tianyue Wang¹, Tian Tian²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072696 - 12 January 2026

Abstract The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation, mechanical wear, and airflow disturbances during prolonged operation. These conditions can lead to a series of issues, including mechanical faults, air path malfunctions, and combustion irregularities. Traditional model-based approaches face inherent limitations due to their inability to handle nonlinear problems, natural factors, measurement uncertainties, fault coupling, and implementation challenges. The development of artificial intelligence algorithms has provided an effective solution to these issues, sparking extensive research into data-driven fault diagnosis methodologies. The review mechanism involved searching IEEE Xplore, ScienceDirect,… More >

Ramazan Özkan^1,2, Mustafa Serdar Genç^1,3,*, İlker Kayali^1,4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3349-3380, 2025, DOI:10.32604/cmes.2025.072519 - 23 December 2025

Abstract The optimization of turbine blades is crucial in improving the efficiency of wind energy systems and developing clean energy production models. This paper presented a novel approach to the structural design of small-scale turbine blades using the Artificial Bee Colony (ABC) Algorithm based on the stochastic method to optimize both mass and cost (objective functions). The study used computational fluid dynamics (CFD) and structural analysis to consider the fluid-structure interaction. The optimization algorithm defined several variables: structural constraints, the type of composite material, and the number of composite layers to form a mathematical model. The More >

Yan Wang^1,2,*, Fuqiang Zhang¹, Long An¹, Bo Wang¹, Xueya Yang¹, Jie Jin^3,4

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2651-2671, 2025, DOI:10.32604/fdmp.2025.070122 - 01 December 2025

Abstract A downburst is a strong downdraft generated by intense thunderstorm clouds, producing radially divergent and highly destructive winds near the ground. Its characteristic scales are expressed through random variations in jet height, velocity, and diameter during an event. In this study, a reduced-scale parked wind turbine is exposed to downburst wind fields to investigate the resulting extreme wind loads. The analysis emphasizes both the flow structure of downbursts and the variations of surface wind pressure on turbine blades under different jet parameters. Results show that increasing jet velocity markedly enhances the maximum horizontal wind speed,… More > Graphic Abstract

Erping Song^1,*, Zipin Yao²

Energy Engineering, Vol.122, No.12, pp. 5129-5147, 2025, DOI:10.32604/ee.2025.063827 - 27 November 2025

Abstract Wind farm layout optimization is a critical challenge in renewable energy development, especially in regions with complex terrain. Micro-siting of wind turbines has a significant impact on the overall efficiency and economic viability of wind farm, where the wake effect, wind speed, types of wind turbines, etc., have an impact on the output power of the wind farm. To solve the optimization problem of wind farm layout under complex terrain conditions, this paper proposes wind turbine layout optimization using different types of wind turbines, the aim is to reduce the influence of the wake effect… More >

Feng Zhou^1,2, Qifei Li^1,*, Lu Xin¹, Shiang Zhang³, Yang Liu¹, Ming Guo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 411-429, 2025, DOI:10.32604/cmes.2025.069639 - 30 October 2025

Abstract Bulb-type hydro turbines are commonly used in small- to medium-scale hydropower stations due to their compact design and adaptability to low-head conditions. However, long-term operation often results in wear at the runner rim, increasing tip clearance and triggering leakage flow and cavitation. These effects reduce hydraulic efficiency and accelerate blade surface erosion, posing serious risks to unit safety and operational stability. This study investigates the influence of tip clearance on cavitation performance in a 24 MW prototype bulb turbine. A three-dimensional numerical model is developed to simulate various operating conditions with different tip clearance values… More >