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The most efficient technique that is used for aircraft engine tuning is through mounting the engine on the engine test bench (ETB) to analyze, tune and monitor its variables through the ETB run. It is practically very difficult to unmount the engine from the aircraft and mount it on the ETB for analyzing and estimating a single variable such as fuel consumption or oil temperature as the unmounting process requires huge manpower and machinery. This problem can be resolved if the fuel consumption of an air vehicle is estimated without unmounting the engine from the aircraft through applying data analytics and machine learning models. Therefore, in this paper, the fuel consumption of an aircraft is analyzed and estimated through advanced data science techniques. The dataset went through data analyzing and preprocessing techniques before applying multiple machine learning models such as multiple linear regression (MLR), support vector regression, decision tree regression and deep learning algorithm RNN/LSTM. The performance of algorithms has been evaluated using model evaluation methods such as mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination. The models are evaluated in taxi, cruise and approach flight phases where the LSTM performs excellent among all other algorithms with RMSE 15.1%, 10.5% and 0.9%, respectively.

The stratosphere is the atmospheric layer with the strongest impact on long-range infrasound propagation. Natural and anthropogenic infrasound signals are efficiently ducted between refraction altitudes of 30 to 60 km and reflections on the ground and are thus propagated to infrasound receivers over long distances. The direction of favorable stratospheric ducting depends on the state of the atmosphere, primarily driven by the seasonal variation of stratospheric winds. This study uses a dataset of ground-truth infrasound events over two decades and all seasons to assess the station detectability and atmospheric model performance to correctly estimate according station observations and propagation conditions. From 2000 to 2019, the German Aerospace Center facility in Lampoldshausen has conducted ignition tests of the Ariane 5 main rocket engine. Out of the 159 engine tests considered in this study, 71 were observed at the infrasound array IS26 in the Bavarian forest, located eastward at 320 km distance. Observations were mostly made during wintertime, whereas reversed stratospheric wind patterns during summertime inhibited signal detections. A significant portion of wintertime non-detections however corresponded to stratospheric profiles that should enable signal observations. Using European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric model analyses and infrasound ray tracing only two-thirds of the non-detections could be explained by the existence of a near-station acoustic shadow zone. It must thus be concluded that the applied atmospheric model is more often than expected unable to correctly explain infrasound propagation and observation at regional distances.

In the last few decades, several innovations have been implemented in internal combustion engines to meet stricter emissions legislation and challenging targets related to energy efficiency. In this context, gasoline direct injection (GDI) engines adoption has been growing in the market as an economical and technically feasible route. These engines run on accurate fuel injection strategies, including multiple high pressure in-cylinder injections that improve mixture formation, expanding the possibilities for lean burn operation. In general, these strategies contribute to reduce fuel consumption and emissions. GDI fuel injectors have smaller mechanical tolerances and injection orifices diameters than those of PFI engines, which can lead to a higher sensitivity for obstruction by deposits. The GDI engine release in Brazil is relatively new, but included flex-fuel version innovations, allowing the use of Brazilian gasoline (25–27% v / v of anhydrous ethanol), hydrous ethanol, or any mixture of these fuels. Due to Brazilian market characteristics and the lack of information available in the literature, it is important to evaluate flex-fuel GDI injectors deposit formation. This investigation used an in-house patented engine test methodology, and the results showed the good quality of the Brazilian gasoline regarding low levels of injector deposits formation, under different engine operating conditions and, also, under critical fuel storage conditions (quality stress). The higher ethanol content in the gasoline, the fuel quality stress, the use of an in-house patented engine test methodology and the adoption of a flex-fuel engine in different operating conditions, including soak periods, contribute to this work novelty compared to the available literature. The paper also shows preliminary investigations of the deposit’s physicochemical nature, aiming to identify their characteristics and sources. Further research is recommended to improve knowledge in this area.

During hot fire rocket engine testing, non-contacting measurements are superior to bonded gauges because they are immune to burning, shaking loose, or damage due to the harsh testing conditions. Additionally, when compared to instruments which register at single points, Digital Image Correlation (DIC) has the added benefit in that it collects full-field displacement and strain maps over the duration of the test. However, for certain materials and paints under some circumstances of temperature and camera sensitivity, portions of the speckle pattern which were darker at room temperature may emit more light compared to the initially lighter portions of the pattern, resulting in a high temperature pattern which is inverted in comparison with that at room temperature. To address this inversion, a post-processing method is introduced wherein an inverted image containing only emitted light is subtracted from an image containing both emitted and reflected light, thereby generating an un-inverted image. The artificial high temperature image is subsequently correlated against the room temperature image to obtain full-field strains. The subtraction technique is then validated using optical bandpass filters to prevent significant amounts of emitted light from reaching the camera sensor. The two methods are mapped onto common coordinates and shown to produce comparable results. The subtraction method sufficiently mitigates speckle pattern inversion, but its key drawback is that it only works when there is negligible displacement between the subtracted images (i.e. quasi-static loading). It is therefore preferable to eliminate inversion from reaching the camera in the first place by using optical bandpass filters.

The feasibility of 3D-printed molds for complex solid fuel block geometries of hybrid rocket engines is investigated. Additively produced molds offer more degrees of freedom in designing an optimized but easy to manufacture mold. The solid fuel used for this demonstration was hydroxyl-terminated polybutadiene (HTPB). Polyvinyl alcohol (PVA) was chosen as the mold material due to its good dissolving characteristics. It is shown that conventional and complex geometries can be produced reliably with the presented methods. In addition to the manufacturing process, this article presents several engine tests with different fuel grain geometries, including a short overview of the test bed, the engine and first tests.

For the research demand of reusable LOX/kerosene variable thrust liquid rocket engine, a test system with electric displacement pumps is designed and a multidisciplinary modular dynamic simulation method based on AMESim platform is used to analyze the system. The method comprehensively considers the characteristics of complex components in the engine and realizes the fast module assembly and variable step size solution. Considering the combustion model of thrust chamber, the positive displacement pump model with complex leakage channels, and the cooling jacket heat transfer model, the component dynamic equations are deduced and the final model simulation results reveal that the system has a smooth ignition, stage turning, and shutdown process. The thrust can reach 6900 N in high working condition and the variable thrust ratio is 5 : 1. The dynamic characteristics of the system show that the performance error of main pump components is less than 5%, the maximum average temperature rise of the thrust chamber coolant is about 28°C, and the time of stage adjustment is within 300 ms, which mean the overall design of the system is reasonable. Although the accumulation of LOX before kerosene injection can adversely affect the temperature of the thrust chamber, large pressure pulses do not occur due to the ignitor’s duty flame. Moreover, the pintle injectors based on PID control can effectively stabilize the pressure drop at lower conditions. The system and the simulation method provide important support for the actual engine test and the general LRE dynamic characteristics analysis.

This article shows how a hardware in the loop (HIL) simulation can be formulated in such a way that the quality of the simulation can be assessed by evaluating the total energy residual (TER). The validity of this approach was checked with the standard co-simulation to show that TER can be used to compare non-iterative Jacobi and Gauss-Seidel co-simulation masters. The given example with the known global error shows that the value of TER can correctly determine which of the co-simulation masters is better. In the experimental part of the article, the example of a HIL simulation with an engine test bench in the loop is presented. The experiments show that such a quality assessment approach can be used to determine the speed controller parameters for the engine test bench.

It is a great challenge to apply a diagnostic system for sensor fault detection to engine test beds. The main problem is that such test beds involve frequent configuration changes or a change in the entire test engine. Therefore, the diagnostic system must be highly adaptable to different types of test engines. This paper presents a diagnostic method consisting of the following steps: residual generation, fault detection and fault isolation. As adaptability can be achieved with residual generation, the focus is on this step. The modular toolbox-based approach combines physics-based and data-driven modeling concepts and, thus, enables highly flexible application to various types of engine test beds. Adaptability and fault detection quality are validated using measurement data from a single-cylinder research engine and a multicylinder diesel engine.

As the turbine inlet total temperature of the turbofan engine continues to increase, it is key to ensuring the long-term reliability of aeroengines that the components matching effectively to achieve the expected average gas temperature. However, over temperature in turbine inlet is a common challenge in advanced engine development. To solve this problem, this paper proposes a new idea of a component matching optimization method to control average gas temperature. This method couples the optimization method with the adaptive performance model, which is built using accurate component characteristics and internal/external bypass mass flow rate within the engine test. Experiment methods of component characteristics measurement in different operating status under the condition of the whole engine are also developed, which capture the entire characteristics maps rather than the mini maps along the operating line. It also establishes calculation method of the core mass flow rate based on the critical characteristics of the high-pressure turbine. Tests have shown that by applying the component matching optimization method, the turbine inlet average gas temperature of a high-performance twin-spool mixed turbofan engine was reduced by 50 K–60 K under the same thrust, ensuring fulfillment of the performance indexes.

During the development stage of a space vehicle, instrumented tests are carried out on the ground to prove the operational capacity of each liquid-propellant rocket engine, which is installed in this type of vehicle. The task of elaborating a Test Bench project for a propulsion unit with this application is complex and involves several steps, one of these steps being related to the analysis of this bench capacity to meet the algorithms for the liquid-propellant rocket-engine full run of tests, which is considered fundamental for this project’s operational success. Due to the high costs involved in this project’s elaboration and execution, it is strategic to use computational resources to evaluate, by simulation, the main operational functionalities that are previously established for this bench to perform. In this context, this work presents a model proposal through Petri Nets to evaluate, by computer simulation, an architecture capacity that was designed for the Test Bench to meet an algorithm dedicated to the liquid-propellant pipelines purge during the run of hot tests with the liquid-propellant rocket engine. The method used in this work to carry out the simulation shows the operational response of each module of this architecture, in accordance with the steps contained in the purge algorithm, which allows for analyzing, for each event of the process, the Petri Nets properties, mainly those related to the conservativeness, liveliness, deadlock-type, and confusion-type conflicts. The simulation carried out with the proposed model allows for the portrayal of the physical architecture and the operational states of the purge system according to the steps foreseen in the algorithm, showing that the conservation property is met because the number of marks remains constant, the vivacity property is also met since all positions have been reached, and there is no mortal-type conflict, as the simulation is not stopped; only confusion-type conflict is identified, which was solved with the strategic insertion of resources in the model in order to fix crashes related to the competition for tokens in the transition-enabled entries. The satisfactory results obtained in these simulations suggest that the modules provided for this architecture are sufficient and appropriate for carrying out all the steps contained in the purge algorithm, which will minimize or even eliminate the disorders that may be caused by the presence of foreign elements in the propellant supply lines during the tests with the rocket engine.