Periodica Polytechnica (Budapest University of Technology and Economics)
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Validation of a Small UAV Dynamic Model Using CFD and Flight Test Data
Full text linkFixed-wing Unmanned Aerial Vehicles (UAV) are increasingly utilized in various missions requiring stable and responsive performance. Accurate dynamic models are essential to ensure effective UAV control. This study presents the development and validation of a 6-DOF UAV dynamic model, constructed using aerodynamic data derived from Computational Fluid Dynamics (CFD) simulations. The model integrates aerodynamics, weight, and thrust. To validate the model, three sets of flight test data were collected. The dataset showed the most consistent trends. The longitudinal, phugoid and short-period modes were successfully executed. However, residual oscillations in pitch angle and forward speed responses suggest the need to re-evaluate pitch-related aerodynamic coefficients and include CDu to the model. Despite these oscillations, pitch angle and pitch rate exhibited the lowest Mean Absolute Error (MAE) values when compared to flight data, indicating strong agreement in trend and amplitude. In contrast, forward speed showed the highest MAE due to discrepancies in initial conditions. For lateral/directional modes, characteristic responses such as roll subsidence, spiral, and Dutch roll were accurately reproduced. Yaw rate achieved the best fit, while yaw angle had the largest MAE due to range differences between simulation and flight test data. The differences between simulation results and flight test data are mainly due to the inaccuracy of aerodynamic coefficients in some parameters, simplifying assumptions in CFD simulations, as well as differences in initial conditions. Overall, the results demonstrate that the CFD-derived aerodynamic model, when validated against flight test data, can reliably represent the actual dynamic behaviour of a UAV
Kinetic Investigation on Thermal Degradation of Empty Oil Palm Bunches Pyrolysis
Full text linkEmpty oil palm bunches, a byproduct of the palm oil industry, are typically returned to plantations as mulch but represent a valuable renewable energy source. Through pyrolysis, these biomass residues can be converted into useful chemicals and energy. Before pyrolysis, the raw materials were characterized using thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX). Pyrolysis experiments were conducted on samples of 30, 60, and 80 mesh at temperatures of 350 °C, 450 °C, and 550 °C. TGA revealed a significant degradation peak at 301 °C, with kinetic analysis indicating a first-order reaction. Mineral analysis identified potassium as dominant, and SEM-EDX revealed a porous, fibrous structure in the bunches and the mineral with the highest content is potassium. The highest liquid yield of 38.76%, was achieved from the 80-mesh sample at 350 °C. Gas chromatography-mass spectrometry of the liquid fraction identified Vinyl methyl ether as the predominant compound, accounting for 96.81% of the composition
Assessment of the Energy Intensity of Ammonia Production by Microbubbles
Full text linkThe present paper investigates the energy intensity of ammonia production by a freely oscillating microbubble placed in an infinite liquid domain. The spherical bubble initially contains a mixture of nitrogen and hydrogen. The bubble is expanded from its equilibrium size to a specific maximum radius via an isothermal expansion. The work needed to expand the bubble is its potential energy calculated by the sum of the work done by the internal gas, the work needed to displace the mass of the surrounding liquid, and the work needed to increase the area of the bubble against the surface tension. During the radial pulsation of the freely oscillating bubble, the internal temperature can reach several thousands of kelvin inducing chemical reactions. The chemical yield is computed by solving a set of ordinary differential equations describing the radial dynamics of the bubble (Keller—Miksis equation), the temporal evolution of the internal temperature (first law of thermodynamics), and the concentrations of the chemical species (reaction mechanism). The control parameters during the simulations were the equilibrium bubble size, the initial expansion ratio, the ambient pressure, and the initial concentration ratio of nitrogen and hydrogen. In the best-case scenario, the energy requirement in terms of GJ/t is 18.4 times higher than the best available facility of the Haber—Bosch process (assuming that the hydrogen is produced via the electrolysis of water)
Predictive Modeling of Li-Air Batteries Using Artificial Neural Network: A Comparative Study of Cathode Morphology
Full text linkThe artificial neural network (ANN) modeling is used to analyze the impact of two different cathode morphologies urchins (α-MnO2 ) and flower (δ-MnO2 ), on the charge/discharge voltage in lithium air batteries (LABs). Previous research has focused on ANN models for traditional lithium-ion batteries (LIBs) without accounting for varied cathode morphologies in LABs. This research presents an ANN modeling technique to predict the charge/discharge voltage LAB using manganese oxide as cathode materials with two distinct morphologies. For modeling Specific capacity use as the input variable, to perform a comprehensive analysis to validate charge/discharge voltages. This study explores multiple ANN configurations with varying neuron counts, identifying the optimal architecture (10 neurons in hidden layers) that balances prediction accuracy and efficiency. This systematic exploration provides insights into ANN tuning for LABs, which is a topic with limited coverage in existing literature. The ANN predicted results closely matched with the reported experimental work with the coefficient of determination R2 = 0.9998 for almost all models. The models performance was assessed by various error metrics mean absolute deviation (MAD), root mean square error (RMSE) and average absolute relative error (AARE). This study provides empirical validation of the model's robustness. The study highlights the applicability of ANN in capturing complex LAB performance metrics, such as the non-linear behaviors due to morphological differences
Investigation of Turbojet Engine Performance in Subsonic Flight Conditions with Turbofan Power Ratio as Thrust Parameter
Full text linkTurbojet engines have been used for many decades in aviation. Although their share in civil aviation is minimal, with the advent of Unmanned Aerial Vehicles (UAV's) there are new applications. Their operation depends on complex aero-thermodynamic laws, and optimum performance is strongly affected by the control system. The authors have previously investigated how the Turbofan Power Ratio (TPR), originally introduced on Rolls-Royce commercial turbofans, can be used in control of single stream turbojet engines. Based on those results, in the present paper the assessment of flight characteristics is introduced, based on mathematical models, which are available of the particular gas turbine type under investigation. Like the corrected rotor speed, the ratio of TPR and actual thrust depends on Mach number, therefore, this function is determined in this paper. The investigations also included a deteriorated model under control of both corrected rotor speed and TPR, which has shown that TPR can partially recover thrust loss thus improving the safety of the power plant. As a conclusion, TPR is worth of utilizing in control systems as it results in more straightforward thrust correlation and reduced performance loss over time. Furthermore, measuring simultaneously with other common engine parameters, the extent of deterioration can be signalized to the crew before it evolves into a catastrophic failure
Determination of Plastic Limit by Fall Cone Test for Soils with Different Grain Size Distribution
Full text linkCompaction parameters and consistency limits are fundamental engineering properties considered in the design of geotechnical applications. It is important to compare these parameters derived from experimental studies with the equations proposed in the literature or alternative methods. This study determined the plastic limit values of soils with different grain size distributions and different consistency limits using the relationship between penetration depth and water content from the fall cone test, employing a cone with 30° and 80 g characteristics. The method for determining the plastic limits has been developed based on a wide range of data. It defines the water content corresponding to a 3 mm penetration of the cone into the soil as the plastic limit. The plastic limit values determined by the proposed method were tested with a comprehensive dataset compiled from literature studies. The results indicated a satisfactory correlation between the plastic limits determined by the tread rolling method and those determined by the proposed method (R2 = 0.76). Furthermore, the compaction parameters obtained from the standard compaction tests were investigated using univariate and multivariate regression analyses, with consideration given to the liquid and plastic limits determined from the fall cone tests. The findings indicate that the compaction parameters can be predicted with high coefficients of determination (R2 = 0.89) using the plastic and liquid limits determined from the relationship between water content and penetration depth in the fall cone tests