Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
Airfoil aerodynamic design represents an essential domain in aircraft development, where the pursuit of advanced and intelligent optimization strategies is important for achieving significant advancements. In this paper, we demonstrate the effectiveness and versatility of reinforcement learning (RL)-based optimization methods in enhancing aerodynamic performance for both transonic and supersonic airfoils. We introduced a novel methodology using RL to optimize airfoil designs, leveraging ADflow as the aerodynamic solver and constructing an RL environment where Class-Shape Transformation (CST) parameters describe the airfoil geometry, transforming it into a finite state variable. Key flow field features, especially shock waves, were incorporated to guide the optimization process, enabling the RL model to iteratively improve designs based on real-time feedback from simulations. Applied to transonic airfoils, this method yielded remarkable results, including a 70.20% increase in the lift-to-drag ratio for one airfoil, with consistent improvements across various initial geometries and flight conditions. Extending to the NASA SC(2)-0404 supersonic airfoil, the optimized design achieved significant geometric changes that resulted in a 6.25% increase in the lift-to-drag ratio, with improvements ranging from 4.90% to 25.46% across different lift coefficients. These findings highlight the robustness and adaptability of RL techniques in addressing the unique challenges of both transonic and supersonic aerodynamics while maintaining structural integrity....
Aerodynamic characteristics of a pitching NACA 0012 airfoil, including the load performance and flow field features, are studied using numerical simulations in this paper. Large Eddy Simulations (LESs) have been performed, and the chord-based Reynolds number is set to 6.6 × 104. Pitching frequency varies from 3 to 20 Hz, corresponding to a reduced frequency of 0.094–0.628 (k = π fpc/U∞, where fp is the pitching frequency, c is the chord length, and U∞ refers to the incident flow speed). As the pitching frequency increases, the maximum lift coefficient achieved in one pitching cycle decreases, and the direction of the lift hysteresis loop changes as the pitching frequency exceeds a certain value, leading to a change in the lift of the sign at the zero-incidence moment, which is a result of the instantaneous flow patterns on the airfoil surface. As the pitching frequency increases, flow unsteadiness develops less in one pitching cycle, and the time duration in which the turbulence boundary layer can be detected in one pitching cycle shrinks. Additionally, for the pitching airfoil, combinations of the flow patterns on the upper and lower sides, such as laminar separation and the turbulent boundary layer, or laminar separation and the laminar separation bubble, were observed on the airfoil surface, and these were not detected on a static airfoil at the corresponding Reynolds number. This is considered an effect of the pitching motion that is in addition to the phase-lag effect....
Pure hydrogen combustion is a critical pathway to achieving zero-carbon emissions for the gas turbine industry. Micro-mixing combustion is one of the most widely aractive hydrogen combustion methods in gas turbines. This study investigates pure hydrogen flame in a 3 × 3 matrix micro-mix combustor. The setup includes nine micro-mix injectors, each equipped with a bluff body and a hydrogen injection tube. The OH* chemiluminescence imaging and PIV (Particle Image Velocimetry) techniques were employed to visualize the single- and triple-flame morphology and flow field under various operating conditions. The results show that equivalence ratio, flow rate, and air injector exit angle can influence the flame structure and combustion characteristics, providing an insightful understanding of micro-mix pure hydrogen combustion....
The thermal decomposition of hydrogen peroxide (H2O2) as a promising green propellant was performed over free-noble metallic-based catalysts deposited on abundant supports. A 30% (w/w) H2O2 liquid was decomposed over 1 wt.% of copper-based catalysts deposited on three different supports: γ-alumina, graphite and monocrystal clay. In this research work, the catalytic performance of the thermal decomposition of H2O2 was carried out by measuring the differential pressure (ΔP) versus time at initial constant temperatures and, for the first time, by the DTA-TG technique and by the DIP-MS technique at atmospheric pressure. The obtained preliminary results showed that copper deposited on alumina and on graphite are promising catalysts for the decomposition of the H2O2 liquid propellant. Moreover, the natural clay can be valorized on the thermal decomposition of H2O2 due to its high resistivity and high surface area. The N2-physisorption technique and scanning electron microscopy technique were used to characterize the effect of the texture properties on the decomposition and to understand the morphological characteristics of the catalyst....
Accurate quantification of metallic contaminants in rocket exhaust plumes serves as a critical diagnostic indicator for engine wear monitoring. This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the metallic element concentrations in liquid-propellant rocket exhaust plumes. The proposed method establishes linearized intensity–concentration mapping through the introduction of a photon transmission factor, which is derived from radiative transfer theory and experimentally calibrated via AES measurement. This critical innovation decouples the inherent nonlinearities arising from self-absorption artifacts. Through the use of the transmission factor, the training dataset for the BP network is systematically constructed by performing spectral simulations of atomic emissions. Finally, the trained network is employed to predict the concentration of metallic elements from the measured atomic emission spectra. These spectra are generated by introducing a solution containing metallic elements into a CH4-air premixed jet flame. The predictive accuracy of the method is rigorously evaluated through 32 independent experimental trials. Results show that the quantification error of metallic elements remains within 6%, and the method exhibits robust performance under conditions of spectral selfabsorption, demonstrating its reliability for rocket engine health monitoring applications....
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