Turbofan engines are still one of the loudest noise sources of modern commercial aircraft. Noise radiation from the engine is highly directional and it is, therefore, important to obtain this directivity pattern from microphone-array data from static engine noise tests. Recently, Sijtsma has shown that the deconvolution method CLEAN-SC is able to break down engine noise sources and that it is capable of determining the directivity of these sources in the far field using measurements of a DGEN380 static engine test. This study further investigates this capability of CLEAN-SC by performing acoustic experiments under controlled conditions in the anechoic chamber at the faculty of applied sciences at Delft University of Technology. The experiments consist of a variety of tests with 2 different speakers placed inside an aluminum cylindrical pipe simulating an engine. In these experiments, the location and directivity of the individual noise sources can be measured separately, so that the CLEAN-SC results can be compared to the ground-truth reference. Moreover, the results are also compared with other acoustic imaging methods, such as DAMAS and conventional beamforming.

This paper analyzes the performance of the ReSpeaker Mic Array v2.0 with a specific focus on its suitability for acoustic beamforming and aircraft tracking applications for small airports. The research methodology involves a dual approach, comprising computer simulations and practical tests, followed by a comprehensive analysis of the obtained results. The simulation step tests the performance of the ReSpeaker microphone array setup through synthetic beamforming. Methods for beamwidth calculation, addressing spectral leakage with the Hanning window, and effects of varying distance and frequency on beamforming accuracy are discussed. In preparation for airport measurements, the functionality of the ReSpeaker system is tested in an anechoic chamber, providing optimal conditions. Measurements include varying elevation and azimuth angles, with results indicating large beamwidths often exceeding 90 degrees at 2500 Hz. The results also indicate the appearance of grating lobes at frequencies of 5000 Hz and higher. The results are compared with the results from the synthetic analysis and this comparison shows that both produce similar results. Sound source localization tests were conducted at Rotterdam The Hague airport using the ReSpeaker system. Synchronization of data from two locations, 115 meters apart, involved laser range finders and Google Earth. Windy conditions introduced background noise, which was analyzed via spectrograms. As expected, the beamforming results exhibited frequency sensitivity, with higher frequencies showing smaller beamwidths. Incoherent averaging was tested to address the expected Doppler frequency shifts. Incoherent averaging was also used in order to remove outliers. Triangulation revealed a high sensitivity to a small effective array length, which has negative implications for the application of acoustic sound source localization. The study concludes that while the ReSpeaker microphone array offers a cost-effective solution for 3D acoustic sound source localization of aircraft, it fell short in accurately tracking aircraft trajectories during take-off due to the small effective array length in the evaluated array configuration. The small effective array length for the elevation angle resulted in reduced quality of the results, and an increase in the amount of outliers. Despite providing a rough estimate of aircraft location, the system's limitations indicate the need for further research which investigates a different microphone array setup in order to increase the effective array length for the elevation angle.

Minimisation of the climate impact of flights in the short term may be achieved by contrail avoidance. This involves avoiding ice supersaturated regions (ISSRs), which cause contrails to persist. ISSRs occur when the relative humidity over ice is above 1, but numerical weather prediction (NWP) models struggle to predict such regions. Below 235.15 K, solely ice supersaturation can be considered. This study validates the prediction of ISSRs in the ERA5 reanalysis using IAGOS in-situ measurements from a pressure level (350 to 175 hPa), seasonal, yearly (2011 to 2022) and regional perspective. Validation of ERA5’s temperature showed a cold bias in all extratropic regions and at low altitudes in the tropics, which can result in ERA5 predicting ISSRs when none are observed. Increasing temperature deviations between IAGOS and ERA5 were observed between the years 2020 and 2022. In terms of relative humidity over ice, ERA5 and IAGOS showed good agreement below ice supersaturation, but ERA5 struggled in simulating values close to or above a value of 1. For the latter conditions, ERA5 showed a dry bias in the extratropics below the tropopause. A moist bias was found in some regions and seasons, including South Asia, in June, July, and August. This may be due to inconsistencies in the modelling of the atmospheric ice content in ERA5. Years 2013 and 2014 also showed a possibility of a moist bias in ERA5 in some regions, but this was most likely the result of regional changes in sampling by IAGOS. The moist bias caused false detection of ISSRs in ERA5. Meanwhile, the dry bias led to an underestimation of the occurrence of ISSRs, with 25 to 50% remaining undetected. This causes an overestimation of no persistent contrail regions and an underestimation of persistent contrail and reservoir regions. When ERA5 overestimates the ISSR occurrence, it leads to an overestimation of persistent contrail and reservoir regions but an underestimation of no persistent contrail regions. Hence, improvements are necessary to successfully avoid or ensure unnecessary avoidance of ISSRs, where the latter could cause an increase in the climate impact of flights. Improvements should be done before implementation in contrail avoidance strategies, otherwise the benefit of such strategies may be defeated.

In this work the possibility for use of the satellite remote sensing instrument TROPOMI to detect NOx emissions from en-route aviation is assessed. Analysis of aviation intensity, quality of satellite retrievals, and emissions from non-aviation anthropogenic sources showed that the North Atlantic, including the North Atlantic Flight Corridor, would have high detection potential. Over this corridor, emissions from telemetric observed aircraft are computed under assumption of stable meteorology leading to an upper bound for the average accumulation of emissions for the months of April 2020 and April 2021. These emissions are compared with TROPOMI NO2 observations retrieved over all sky and cloudy sky scenes. In order to reduce advection influences, TROPOMI measurements at locations of aviation observations close to the overpass time are analysed separately.

General conclusions of this first assessment are not optimistic for detection of en-route aviation emissions by means of TROPOMI observations. The maximum NOx emissions attributable to en-route aviation over the North Atlantic Flight Corridor during April 2020 and April 2021 were found to be lower than detection limits associated with TROPOMI for NO2 retrieval. Neither did inspection of TROPOMI measurements at locations of recent aircraft observations retrieve any evidence of aviation-attributable emissions. Therefore detection, documentation and quantification of actual NOx emissions from en-route aviation remains a
challenge.

Remotely Operated Vehicles (ROVs) are positioned relative to an underwater acoustic positioning system: Ultra-Short BaseLine (USBL). The accuracy is affected by refraction artifacts, caused by the variations of the sound velocity in the water column. Accurate positioning would require continuous measuring of the sound velocity profile (SVP) which is unpractical and preferably to be minimized. It requires alternative or inversion methods to obtain SVP information. In this thesis, two inversion methods are introduced: HISOM (Hull In Situ Ocean Model) and OMBES (Overlapping MultiBeam EchoSounder).

HISOM analysis whether the SVP can be approximated via other sources: 1) a constant profile based on the in situ surface (ISS) sound velocity, or 2) a profile derived from ocean model data in combination with the ISS sound velocity. These simplifications inevitably introduce a refraction error but for fallpipe ROVs operating at small incident angles (e.g. θ<6°) this error may be within acceptable margins (e.g. threshold of 0.2 m). The applicability is assessed by estimating the horizontal refraction error with a ray-tracing technique using daily-mean SVPs, derived from freely-available ocean model data. A spatiotemporal quantification for the North Sea yielded maps of sea areas where SVP measurements are necessary, and areas where constant surface SVPs suffice. The latter are the shallow parts of the North Sea (<80 m), where the error is always smaller than 0.2 m. For deeper locations, the gradients of the SVP cannot be neglected. Then, the model-based SVPs can be used with or without the use of ISS sound velocity data. Comparing a collection of observed SVPs in the North Sea revealed that these daily-mean model-based SVPs are accurate enough for the positioning of fallpipe ROVs at least up to 370 m depth.

OMBES uses the synchronous overlap in depth measurements between two dual-head multibeam echosounders (MBES). In previous studies, the overlap is obtained by sailing two adjacent tracks with one MBES on a ship. Here, we propose to use two MBESs deployed on the same ship, thereby reducing the uncertainty of the ship’s motions that affect the quality of the depth measurements. The mean sound velocity can be inverted by mathematically minimizing the depth differences in the overlap. This technique completely minimizes the refraction error with frequent updates of the inverted mean sound velocity on the flight. Subsequently, the mean sound velocity can be used to locate ROVs that operate close to the seafloor in shallow water (<80 m), even for large incident angles (e.g. θ~65°). Simulations showed that the best performance of the inversion technique is established when maximizing the distance between the multibeam heads, and by inward-tilting one or two heads. Practically, it means the deployment of MBESs on either side of the ship, rather than one pair of MBESs at mid-ship.

With increasing access to reliable ocean data, HISOM methods can potentially be run on ocean forecast model data to assess where and when refraction artifacts become dominant for fallpipe ROV positioning. This automatic assessment tool supports the SVP measuring strategy in subsea rock installation projects. OMBES can potentially be used as monitoring tool by comparing near real-time updates of the inverted mean sound velocity with the measured SVP. This data-driven decision tool can assist when to take an additional SVP. OMBES also improves the accuracy of multibeam bathymetric surveys by automatic collection of SVPs.

The approach to sustainable aviation requires effective policy and regulation, informed by accurate environmental research. Aviation emissions inventories form the basis of any environmental assessment, however they are based on simplifications and assumptions that introduce a degree of uncertainty. In terms of robust model development, it is necessary to identify significant sources of uncertainty to determine priorities for improvement.

The results of a global sensitivity analysis identifies 5 key contributors to uncertainty across fuelburn and emissions estimates: BADA Drag and Fuel Flow corrective multipliers, Takeoff Weight, Taxi Thrust and Arrival Inefficiency. Across the emitted species, uncertainty is driven by their respective EI.

EUROCONTROL flight track data allows for an analysis of lateral inefficiencies, and improved distribution fitting. The resulting distributions are more representative of actual flight behavior. The introduction of these improved distributions into the original model result in an overall reduction in fuelburn and emissions estimates.

Excessive nitrogen deposition from anthropogenic emissions has a global impact on natural biodiversity. While aviation emissions have been studied in the context of climate change and air quality, this is not true for nitrogen deposition. Meanwhile the growth of the aviation industry is likely to increase the relative contribution of aviation emissions to nitrogen deposition. Current regulatory policies aiming to mitigate nitrogen deposition are limited to local scale, and are inadequately applicable to the global nature of the aviation industry.
In this research the impact of aviation emissions from both landing and take-off and non-landing and take-off emissions are studied by perturbing emission scenarios in the GEOS-Chem chemistry transport model for 2005. Results indicate that the aviation industry is responsible for 0.71% of total nitrogen deposition worldwide. While regionally contributing up to 30%, on average only 7.7% of aviation attributable nitrogen deposition is attributable to landing and take-off emissions globally , indicating that local regulatory policies do not take into account upwards of 70% of aviation attributable nitrogen deposition.

Widespread usage of Micro Aerial Vehicles (MAVs) has led to various airspace safety breaches, including near mid-air collisions with other aircraft. To ensure safe integration into general aviation, it is paramount that MAVs are equipped with an autonomous detect and avoid system when flying beyond the visual line-of-sight of the operator. The purpose of this research is to investigate the feasibility of acoustic-based aircraft detection, which has generally been overlooked in favor of optical or radar-based technology. Effective sound-based aircraft detection on-board an MAV requires suppressing the dynamic ego-noise it generates during flight, which would otherwise pollute the recorded environmental sound. This paper proposes using a recurrent neural network to predict the generated noise, given a sequence of MAV flight data, so that it can be effectively removed from noisy recordings. For aircraft detection, a convolutional neural network in combination with Mel spectrogram features is designed to classify noise-free environmental sound as either aircraft or non-aircraft, achieving 97.5\% accuracy. To reconstruct the noisy environment of an MAV flight, these noise-free sounds are mixed with ego-noise at mix ratios up to 1.00. When evaluating in these mismatched conditions, accuracy decreases to 95.0\% and 47.5\% with- and without ego-noise suppression, respectively. Although ego-noise suppression can not prevent a drop in performance, the large difference between the mismatched conditions does demonstrate the benefits of the proposed denoising approach on aircraft detection.

The need to contribute to a sustainable future of the aviation industry has spiked an interest in turboprop engines. This is due to the higher propulsive efficiency, the better take-off and landing performance on short runways, and the new developments in propeller-driven hybrid and electric aircraft. The most significant drawback is the noise they generate, which is undesirable. To reduce the propeller noise, new advanced propeller designs are needed. Propeller noise models can be used as a valuable tool during the design phase. The models can only be confidently used when they have been properly validated. The more data is used to validate, the higher the confidence will be.

A master student that graduated from the Aircraft Noise and Climate Effects section at the TU Delft created a propeller noise model called HeliX-tool. This model is validated by another model and wind tunnel measurements from NASA but not yet by full-scale outdoor experimental data. To increase the confidence of the HeliX-tool, this model is compared to full-scale outdoor experimental data and the quality is assessed in this thesis.

The HeliX-tool models the steady loading and thickness noise and is based upon the helicoidal surface theory. This theory needs the aerodynamic and performance characteristics of the propeller blade which are obtained by implementing the two external analysis tools, XFOIL and XRotor.

The experiment is performed with the Pipistrel Velix Electro at Teuge airport to obtain the full-scale outdoor data to validate the model. The Pipistrel Velis Electro is a fully electric-powered two-seater owned by E-flight academy. The microphone array that is used to obtain the full-scale outdoor data has 64 microphones placed in an Underbrink configuration.
The propeller geometry is an important input for the HeliX-tool and is obtained by 3D scanning the propeller blade of the Pipistrel Velis Electro with the FaroBlu HD laser.

The validation metrics are the SPL and OSPL values. The frequency spectra are generated for both the full-scale outdoor data and the HeliX-tool when the aircraft is overhead the microphone array and are compared to each other. In general, the HeliX-tool gives higher SPL values compared to the full-scale outdoor data, which also results in higher OSPL values from the HeliX-tool.
The location of the most dominant noise source can be found, with beamforming, although the resolution is limited by the Rayleigh limit. Functional beamforming is used to reduce the side lobes and it can be seen that the dominant noise source shifts in location. It can be concluded that there might be a noise source present within the Rayleigh limit but this cannot be confirmed.

The values of the validation metrics are within 4 dB and from this can be concluded that the confidence in the HeliX-tool is increased. It can be used as a tool in the design phase of new advanced propellers but is limited to Mach numbers below 0.7 due to the Prandtl­Glauert compressibility correction used in XRotor.

With increasing UAV operations, tailored measures need to be implemented to integrate the massive employment of these vehicles in day-to-day operations. One of the current issues of UAVs is the noise emitted by these vehicles. The purpose of this research is to offer a doorway towards understanding the behavior of drone noise with changing operational and design parameters.
The radiated noise from four selected drones was experimentally measured under realistic environmental settings in an open field. The study dives through spectral analysis of a series of maneuvers, assesses the suitability of acoustic imaging algorithms for drone noise sources, explores adequate noise metrics, and lastly, identifies influential drone parameters essential for the modeling of drone noise in the future. Spectrogram and power spectral density analyses unravel the frequency range of interest between 200 Hz to 3000 Hz with dominant harmonics of the rotors’ blade passage frequencies. Above this range, the ground reflection hinders the proper identification of noise sources. Further investigation is done with 4 beamforming algorithms. As drone noise may exhibit complex radiation patterns due to interference of multiple rotors, sophisticated beamforming techniques (i.e. Functional (FB), Dipole (DB), and Quadrupole Beamforming (QB)) were implemented which are potentially superior to Conventional Beamforming (CB) in the setting of drone noise. The results of the beamforming algorithms have been verified with synthetic data. Notably, FB was found to perform best on a source if a correction for the expected source type is applied first, however, it is outperformed by other methods if the source type is not known a priori. While all implemented algorithms yielded excellent results on synthetic data, their accuracy greatly decreases when applied to real-life data. This can be attributed to the multitude of external factors and imperfection in vehicle design, as well as the dependency of DB and QB on prior information regarding the pole orientation on the rotors. In conclusion, only CB could be applied reliably. Analysis of CB over snapshots of drones during different maneuvers shows that the rotors prove to be the main sources of noise in hovering and increasing height from Hover. The source identification, however, becomes unreliable with the change in height. To yield a complementary view on the sound characteristics of drones in specific maneuvers, the sound pressure levels and various sound quality metrics have been computed. The metrics reveal the effects of drone parameters (i.e. rotor size, distance to the observer, thrust settings, etc.), thus leading to a selection of possible candidates for a future noise model. This may be useful to assess the human psychoacoustic annoyance of drone noise in an environment where drones become a part of our everyday life.

Because of the expected return of civil supersonic flight, research is required to update supersonic noise regulations to allow public acceptance of civil supersonic flights. To advise ICAO on whether future supersonic aircraft will be able to comply with current regulations this thesis predicts the noise production of future supersonic transport aircraft. For this a low-fidelity aircraft design program was created. This program was validated successfully and based on five produced aircraft designs a noise analysis was performed. This analysis shows that supersonic aircraft will be unlikely to meet the subsonic airport noise regulations. The reason for this is that optimisation for supersonic flight inevitably results in changes that produce more noise compared to subsonic aircraft. The sonic boom noise level of future supersonic transport aircraft can be greatly reduced compared to the levels of Concorde by optimising the aircraft’s shape. However, this will result in increased drag, fuel burn and weight. Therefore it is unlikely that near future supersonic transport aircraft will be acceptable in terms of noise.

The past decade has seen a continuous increase of Earth observation missions, since they are regarded as an important tool to address global problems such as climate change or disaster mitigation. A commercial trend exists now towards higher resolution imagery, which drives the use of agile satellites. Nevertheless, a disadvantage of agile satellites is the increased complexity to compute the optimal imaging schedule. In fact, the problem can be interpreted as a time-dependent selective travelling salesman problem for which the travel between the cities is also a constrained optimal control problem. Considering the simplifying assumptions in literature, this MSc thesis presents a novel method which approximates the optimal control problem between the targets using an artificial neural network. This approach provides a significant improvement over any previous research resulting in an increase in scheduling performance of around 10%. Considering the high cost of agile Earth observation satellites, this advancement can offer important profit increases for satellite operators. Additionally, a new exact scheduling algorithm was developed based on dynamic programming logic. The algorithm is shown to be able to plan up to one hundred targets for a given restricted number of visible targets at each epoch, while previous research was only able to solve problem sizes of up to twelve targets. Furthermore, the new exact scheduling algorithm is also shown to have unmatched performance for cases of up to twelve targets, such that this should not be considered a difficult problem anymore.

As global warming has become a prominent issue for mankind, scientists are working on every possible aspects to slow down its pace. Aviation emission contributes more and more to the anthropogenic climate impact. Contrails contribute to about 30% of the aviation induced RF. Among the options that are proposed to mitigate the formation of contrails, one of it is to reroute the aircraft in a way to avoid flying through the contrail formation regions (CFRs). To carry out this option, it is necessary to have a better understanding of the distribution of the CFRs as well as their seasonal variation and future trend. The CFRs analyzed in this thesis are simulated by EMAC model, the CFRs' characterisations studied include their zonal and meridional coverage length, stretch factor, direction in the vertical and horizontal planes as well as their seasonal variations and future trend.

Feadship yachts are designed for the leisure and cruising across the oceans. These luxury yachts are mostly powered by diesel engines or in some cases, a diesel-hybrid system. To prevent the inconvenience and the discomfort arising from the diesel exhaust gases for passengers, Feadship yachts are equipped with an underwater exhaust outlet. These underwater exhaust outlets are located on the side of the hull close to the dynamic waterline. It consists of an external appendage called "scoop" which creates a low pressure region for the exhaust outlet. During recent sea trials of the Feadship yachts, undesirable variations in the exhaust back-pressure were observed at the underwater outlet. These undesirable variations led to a situation with either too high back-pressure or too low back-pressure. An excessive back-pressure will increase the fuel consumption and will damage the diesel engine. Contrary, an extremely low back-pressure will give a visible exhaust flow above water thereby discolouring the hull and contaminating the deck with exhaust gases and steam.

An ideal scoop design would substantially reduce the above described problems. To investigate the optimal design for a scoop, a numerical method will be used. The method applicable in this study will be the Mutiphase Flow models from the commercial Computational Fluid Dynamics (CFD) software called Star CCM+. A multiphase fluid interaction between the exhaust gases and sea water will be examined to find the physical phenomenon affecting the back-pressure at the underwater outlet. In return, this phenomenon will be useful for a thorough analysis of the different scoop designs and how this design could impact the back-pressure. Furthermore, the validation of the numerical method will be carried out against the data procured from sea trials of the yachts with current scoop design.

To conclude, design recommendations for an optimal scoop geometry will be provided such that it can reduce the excessive back pressure, have a low resistance and prevent the discolouring of the hull.

The EU goals to decrease wind energy prices are driving the wind energy industry to give more attention to monitoring and improving turbine performance. Meanwhile, as turbines grow bigger and more are placed offshore, performance monitoring costs are increasing, making it more interesting to consider novel devices to measure turbine performance. The purpose of this study was to investigate the applicability of these devices in power performance monitoring and evaluating the potential gains which can be achieved. A comparative study of the measurement accuracies was performed of the nacelle-based Lidar (WindIris) and a spinner anemometer (iSpins) against an IEC-compliant met-mast. Accuracies of both devices in measuring wind speeds, yaw misalignment and power curves were found to be comparable to a met-mast and therefore could be worthy replacements of met-masts for power performance measurements in the future. The impact of non-ideal wind conditions, like yaw misalignment, turbulence and wind shear, on power performance was also investigated using both experimental and Bladed simulated results. No conclusive results were found on the relationship between yaw misalignment and performance loss. The ideal yaw error was found to increase with increasing wind shear, caused by higher angles of attack in the top of the rotor area. The direct impact of turbulence intensity and wind shear on power curves was found to be wind speed dependent and not that significant on overall energy production. Finally, combining the knowledge acquired about yaw misalignment and device accuracies, a financial feasibility study was performed to evaluate future implementation of the novel devices for yaw misalignment correction. Since no conclusive evidence was presented that correcting for yaw misalignment could increase power performance significantly, current implementation of such a correction campaign is not recommended. If a deliberate yaw misalignment campaign were to be performed, however, the impact of yaw misalignment on turbine performance should be quantifiable and expectations are that implementation of novel devices should be financially feasible.