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

Sk. A. Shezan^*

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.073418 - 27 December 2025

Abstract Modern power systems increasingly depend on interconnected microgrids to enhance reliability and renewable energy utilization. However, the high penetration of intermittent renewable sources often causes frequency deviations, voltage fluctuations, and poor reactive power coordination, posing serious challenges to grid stability. Conventional Interconnection Flow Controllers (IFCs) primarily regulate active power flow and fail to effectively handle dynamic frequency variations or reactive power sharing in multi-microgrid networks. To overcome these limitations, this study proposes an enhanced Interconnection Flow Controller (e-IFC) that integrates frequency response balancing and an Interconnection Reactive Power Flow Controller (IRFC) within a unified adaptive… More >

Yinyu Tang^1,2,3,*, Mingzhi Yang^1,2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011292

Abstract Energy efficiency and environmental sustainability in rail transit are key engineering goals. In urban trains, pressure drag plays a more significant role than in high-speed EMUs, primarily due to the blunt shape of the train’s head. The constraints imposed by underground construction and engineering protocols prevent the optimization strategies used in high-speed EMUs from being applied to urban trains. Therefore, aerodynamic drag reduction in blunt-tail urban trains, through active wake flow control, holds promise for improving train aerodynamics.
This study investigates drag reduction on the tail car of blunt urban trains using a hybrid numerical and… More >

Shuxun Li^1,2, Yuhao Tian^1,2,*, Guolong Deng^1,2, Wei Li^1,2, Yinggang Hu^1,2, Xiaoya Wen^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.8, pp. 1809-1837, 2025, DOI:10.32604/fdmp.2025.065877 - 12 September 2025

Abstract The conventional Shear Stress Transport (SST) k–ω turbulence model often exhibits substantial inaccuracies when applied to the prediction of flow behavior in complex regions within axial flow control valves. To enhance its predictive fidelity for internal flow fields, this study introduces a novel calibration framework that integrates an artificial neural network (ANN) surrogate model with a particle swarm optimization (PSO) algorithm. In particular, an optimal Latin hypercube sampling strategy was employed to generate representative sample points across the empirical parameter space. For each sample, numerical simulations using ANSYS Fluent were conducted to evaluate the flow characteristics,… More >

Shuo Zhang^1,2, Guibin Zou^1,*

Energy Engineering, Vol.122, No.1, pp. 85-99, 2025, DOI:10.32604/ee.2024.057452 - 27 December 2024

Abstract The multi-terminal direct current (DC) grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy. Both the DC circuit breaker (DCCB) and the current flow controller (CFC) are demanded to ensure the multiterminal DC grid to operates reliably and flexibly. However, since the CFC and the DCCB are all based on fully controlled semiconductor switches (e.g., insulated gate bipolar transistor, integrated gate commutated thyristor, etc.), their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses. To solve these problems, integrated equipment with… More >

Jiaxin Wu^1,2, Yi Zhan¹, Min Luo^1,*, Boo Cheong Khoo²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.011058

Abstract Research on the mechanism of fluid flows (particularly nonlinear) on solid structures is of great scientific and engineering significance, as well as to implement effective control by using intelligent solid structures (i.e., agents). These dynamical systems involve complex interactions of fluid dynamics and solid mechanics and, thus are typically defined as fluid-structure interaction (FSI) problems. For effective analysis of FSI systems and implementing active control, numerical modeling that couples fluid and solid solvers proves to be an effective approach. However, the efficiency and accuracy of conventional numerical methods for solving such problems are limited due… More >

He Wang¹, Xiangsheng Xu¹, Guanye Shen², Bian Jing^1,*

Energy Engineering, Vol.120, No.10, pp. 2251-2272, 2023, DOI:10.32604/ee.2023.028965 - 28 September 2023

Abstract There are issues with flexible DC transmission system such as a lack of control freedom over power flow. In order to tackle these issues, a DC power flow controller (DCPFC) is incorporated into a multi-terminal, flexible DC power grid. In recent years, a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust scalability. This work proposes a model predictive control (MPC) strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic performance. Initially, the… More >

P. Venkatesh^1,*, N. Visali²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1001-1012, 2023, DOI:10.32604/iasc.2023.036268 - 29 April 2023

Abstract In the conventional technique, in the evaluation of the severity index, clustering and loading suffer from more iteration leading to more computational delay. Hence this research article identifies, a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects. The polynomial load modelling or ZIP (constant impedances (Z), Constant Current (I) and Constant active power (P)) is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security. The process of finding the severity of the line using a Hybrid Line Stability Ranking… More >

Qun Li, Ningyu Zhang^*, Jianhua Zhou, Xinyao Zhu, Peng Li

Energy Engineering, Vol.120, No.6, pp. 1485-1502, 2023, DOI:10.32604/ee.2023.022856 - 03 April 2023

Abstract The access of unified power flow controllers (UPFC) has changed the structure and operation mode of power grids all across the world, and it has brought severe challenges to the traditional real-time calculation of security correction based on traditional models. Considering the limitation of computational efficiency regarding complex, physical models, a data-driven power system security correction method with UPFC is, in this paper, proposed. Based on the complex mapping relationship between the operation state data and the security correction strategy, a two-stage deep neural network (DNN) learning framework is proposed, which divides the offline training… More >

R. B. Sarooraj^*, S. Prayla Shyry

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2071-2084, 2023, DOI:10.32604/iasc.2023.034716 - 05 January 2023

Abstract In Intelligent Transportation Systems (ITS), controlling the traffic flow of a region in a city is the major challenge. Particularly, allocation of the traffic-free route to the taxi drivers during peak hours is one of the challenges to control the traffic flow. So, in this paper, the route between the taxi driver and pickup location or hotspot with the spatial-temporal dependencies is optimized. Initially, the hotspots in a region are clustered using the density-based spatial clustering of applications with noise (DBSCAN) algorithm to find the hot spots at the peak hours in an urban area.… More >