1,720,965 research outputs found
Optimal battery selection for hybrid rocket engine
No full textIn the present paper, the optimal selection of batteries for an electric pump -fed hybrid rocket engine is analyzed. A two -stage Mars Ascent Vehicle, suitable for the Mars Sample Return Mission, is considered as test case. A single engine is employed in the second stage, whereas the first stage uses a cluster of two engines. The initial mass of the launcher is equal to 500 kg and the same hybrid rocket engine is considered for both stages. Ragone plot -based correlations are embedded in the optimization process in order to chose the optimal values of specific energy and specific power, which minimize the battery mass ad hoc for the optimized engine design and ascent trajectory. Results show that a payload close to 100 kg is achievable considering the current commercial battery technology
Hybrid rocket engine design optimization at politecnico di torino: A review
Full text linkOptimization of Hybrid Rocket Engines at Politecnico di Torino began in the 1990s. A comprehensive review of the related research activities carried out in the last three decades is here presented. After a brief introduction that retraces driving motivations and the most significant steps of the research path, the more relevant aspects of analysis, modeling and achieved results are illustrated. First, criteria for the propulsion system preliminary design choices (namely the propellant combination, the feed system and the grain design) are summarized and the engine modeling is presented. Then, the authors describe the in-house tools that have been developed and used for coupled trajectory and propulsion system design optimization. Both deterministic and robust-based approaches are presented. The applications that the authors analyzed over the years, starting from simpler hybrid powered sounding rocket to more complex multi-stage launchers, are then presented. Finally, authors’ conclusive remarks on the work done and their future perspective in the context of the optimization of hybrid rocket propulsion systems are reported
Robust Design Approaches for Hybrid Rocket Upper Stage
Full text linkComputational costs of robust-based design optimization methods may be very high. Evaluation of new procedures for the management of uncertainty with applications to hybrid rocket engines is here carried out. Two newly developed procedures are presented (hybrid algorithm and iterated local search), and their performances are compared with those of two previously developed procedures (genetic algorithm and particle swarm optimization). A liquid oxygen/paraffin-based fuel hybrid rocket engine that powers the third stage of a Vega-like launcher is considered. The conditions at third-stage ignition are assigned, and a proper set of parameters are used to define the engine design and compute the payload mass. Uncertainties in the regression rate are taken into account. An indirect trajectory optimization approach is used to determine a mission-specific objective function, which takes into account both the payload mass and ability of the rocket to reach the required final orbit despite uncertainties. Results show that for this kind of problem, particle swarm optimization and iterated local search
outperform the genetic algorithm, but the use of a local search operator may slightly improve its performance
Optimal Design Comparison of Hybrid Rocket for Small Satellite Launchers
No full textIn the present paper, a three stage hybrid rocket is considered as a small satellite launcher. The same engine is used in different numbers in each stage: 6,3 and 1 in the first, second and third stage, respectively. This design choice aims at an overall reduction of the launcher cost. Liquid oxygen and a paraffin-based fuel are employed as propellants. The feasibility of a ground launch from 45° North latitude is evaluated and compared to a similar three-stage launcher with airborne launch. In the present work, an electric turbo pump feed system is used. The optimization procedure exploits of a direct method for engine design parameters, whereas an indirect method optimizes the ascent trajectory once the engine design is given. Constant power operation is assumed for the electrical feed system. The initial mass of the launcher is given (5000 kg) and the payload mass is maximized for a given insertion orbit. The initial thrust is fixed in order to have an initial acceleration equal to 1.4 g. The results show that the proposed small satellite launcher concept is able to deliver payload mass in the range 50-100 kg into the desired orbit
Swirl Injection Modeling for Paraffin-Based Hybrid Rocket Engines Combustion Instabilities
No full textHybrid Rocket Engines have gained more and more attention in recent years due to their appealing safety and cost-effectiveness features, but they present some disadvantages, most notably a low regression rate. Swirl injection offers a promising solution, enhancing regression rate and stabilizing combustion by means of increased wall heat flux. This paper introduces a novel swirl model for regression rate evaluation consisting in two integrated sub-models: the first one involves a corrective factor linked to the geometric swirl number of the injector, while the other accounts for the naturally occurring swirl decay. The validity of the model was assessed across a range of different test cases, varying geometric parameters, engine scales, injection, and feeding conditions, and the results shows that the accuracy of local and mean regression rate prediction is improved. Corrections for the wall friction coefficient and the entrainment factor were introduced in an in-house code for paraffin-based fuels. A parametric analysis, carried out considering different swirl levels, revealed combustion chamber thermodynamics consistent with the expected trends observed in firing tests. Finally, an effective reduction in the delay time characteristic of the boundary layer was observed; moreover, the Rayleigh index results showed a marked decrease, indicating a decoupling of pressure fluctuations and heat release which tends to stabilize combustion as the swirl increases
Optimal Design of Hybrid Rocket Small Satellite Launchers: Ground Versus Airborne Launch
No full textA three-stage hybrid rocket is considered as a small satellite launcher. The same engine is used in different numbers in each stage: six, three, and one in the first, second, and third stages, respectively. This design choice aims at an overall reduction of the launcher cost. The propellants are liquid oxygen and a paraffin-based fuel. The performance of different feed systems and launch options are evaluated: the feasibility of a ground launch is analyzed and compared to similar three-stage launchers with airborne launch using both a gas pressurized feed system and an electric turbopump feed system. The optimization procedure exploits a direct method to evaluate the best values of engine design parameters, whereas an indirect method optimizes the ascent trajectory once the engine design is given. Constant power and blowdown operation are, respectively, assumed for the electrical feed system and the gas pressurized feed system. The initial mass of the launcher is given (5000 kg), and the payload mass is maximized for a given insertion orbit. The initial thrust is fixed in order to have an initial acceleration equal to 1.4g. The nozzle expansion ratio in the first-stage engines is reduced to avoid separation at liftoff in the ground case, and the third-stage engines are used at a lower vacuum thrust level to satisfy maximum acceleration constraints. The results show that the proposed small satellite launcher concepts are able to deliver payload masses in the range of 40-100 kg into the desired orbit
A Chemical Reactor Network methodology for estimating NOx emissions under non-premixed lean hydrogen combustion with water injection
Full text linkThis study investigates the ability of Chemical Reactor Network (CRN) methodologies in predicting NOx reduction through water injection in a lean non-premixed hydrogen combustor for a given outlet flame temperature. A new methodology for creating a chemical reactor network to analyze emissions is proposed and validated. The novelty lies in the definition of the connections between the different reactors composing the network using an optimization algorithm. This approach allows the prediction of emissions without the need for complete knowledge of the flow field of the combustor through PIV or high-fidelity CFD simulations. The proposed method proves to be a reliable and computationally efficient framework for predicting hydrogen combustion emissions, achieving thousand-fold computational savings over CFD while maintaining prediction accuracy on the NOx emissions within experimental uncertainty. The results are validated through comparisons with CFD simulations, which are first assessed against experimental data without water injection, demonstrating CFD’s effectiveness in this scenario. The CRN, trained without water injection, successfully applies to the water injection cases, demonstrating its predictive capability beyond the training conditions
Multi-Fidelity Modeling of a Lean Premixed Swirl-Stabilized Hydrogen Burner with Axial Air Injection
Full text linkPremixed hydrogen burners offer promising results in reducing pollutant emissions but are susceptible to flashback, posing significant safety risks and requiring high experimental costs. This study introduces a multi-fidelity modeling approach to address the challenges posed by the scarcity of high-fidelity data, leveraging the assumption of a linear correlation between high-fidelity and low-fidelity data. The model is tested on predicting the axial flame distance from the mixing tube, an indicator of flashback susceptibility, in a lean premixed swirl-stabilized hydrogen burner. Experimental results serve as high-fidelity data, while 2D steady axisymmetric RANS simulations provide low-fidelity data. The results demonstrate the potential of 2D RANS to approximate burner behavior accurately and the capability of the multi-fidelity model to enhance low-fidelity predictions with a severely limited set of training points
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