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Near-Optimal Feedback Guidance for Low-Thrust Earth Orbit Transfers
No full textThis research describes a near-optimal feedback guidance, based on nonlinear orbit control, for low-thrust Earth orbit transfers. Lyapunov stability theory leads to proving that although several equilibria exist, only the desired operational conditions are associated with a stable equilibrium. This ensures quasi-global asymptotic convergence toward the desired final orbit. The dynamical model includes the effect of eclipsing on the available thrust, as well as all the relevant orbit perturbations, such as several harmonics of the geopotential, solar radiation pressure, aerodynamic drag, and gravitational attraction due to the Sun and the Moon. Near-optimality of the feedback guidance comes from careful selection of the control gains. They are identified in two steps. Step (a) is an extensive table search in which the gains are changed in a large interval. Step (b) uses a numerical optimization algorithm that refines the gains found in (a), while minimizing the time of flight. For the numerical simulations, two scenarios are defined: (i) nominal conditions and (ii) nonnominal conditions, which arise from orbit injection errors and stochastic failures of the propulsion system. For case (i), gain optimization leads to obtaining numerical results very close to those corresponding to a known optimal orbit transfer with eclipse arcs. Moreover, for case (ii), extensive Monte Carlo simulations demonstrate that the nonlinear feedback guidance at hand is effective in driving a spacecraft from a low Earth orbit to a geostationary orbit, also in the presence of nonnominal flight conditions.Control & Simulatio
Unravelling microstructure-electroactivity relationships in free-standing polycrystalline boron-doped diamond: A mapping study
No full textIn this work, four different techniques were concurrently applied to study the interplay between local electroactivity and electrode surface characteristics of free-standing, polycrystalline boron-doped diamond (BDD). Scanning electron microscopy, electron back-scatter diffraction, Raman mapping and scanning electrochemical microscopy were used to probe the electrode morphology, grain orientation and boundaries, composition, and local electrochemical activity, respectively. Both nucleation and growth BDD surfaces together with the cross-section area were carefully investigated for the first time in a single study using the combination of all four techniques. This enabled us to obtain significant insights into the highly heterogeneous nature of the polycrystalline BDD material. Notably, boron dopants were confirmed to be non-uniformly distributed over the BDD material, which is characterized by a distinct columnar structure and composition of grains of various orientations. Particularly, the highest electrochemical activity was recorded on the highest doped (111) crystal orientation. In contrast, the averagely boron-doped (100)-oriented facet showed non-conductive nature. This highlights that the local electrochemical activity of the BDD surface is strongly grain-dependent and the most significant factors governing the obtained responses are crystallographic orientation and boron doping. Moreover, increased boron and sp2 carbon content in the boundary regions was recognized by Raman mapping. However, such localized enrichment in impurities did not translate into enhanced electrochemical activity, which implies that boron atoms at the inter-grain areas are predominantly inactive. Finally, it is crucial to consider all characteristics of the polycrystalline BDD including crystal orientation, which is particularly relevant if micro- and nanoscale probing is intended.Micro and Nano EngineeringTeam Arjan MolTeam Yaiza Gonzalez Garci
Predicting neurological outcomes following spinal surgery: A machine learning approach using intraoperative neuromonitoring data
No full textBackground context: Intraoperative neuromonitoring (IONM) has proven effective in reducing postoperative neurological complications. However, current understanding of IONM is limited and its precise meaning in relation to neurological outcomes remains unclear. Machine learning (ML) is a promising solution to analyze the excessive amount of IONM data quickly, objectively and in real-time. Purpose: The goal is to develop a ML algorithm that can effectively predict neurological outcomes after spinal surgery using IONM data that include both motor evoked potentials (MEPs) and somatosensory evoked potentials (SSEPs), and analyze its key predicting features. To more effectively determine the specific independent contribution of both separate modalities, a separate ML model will be created for both MEP and SSEP in addition to a combined MEP-SSEP model.Study setting: Retrospective study.Patient sample: A total of 67 patients were analyzed. Outcome measures: The neurological status three months postoperatively compared to the preoperative status, categorized into three classes: 'Neurological stable deficits', ‘Neurologically intact’ and 'Neurological improvement'.Methods: 260 features were obtained from patients who underwent spinal surgery monitored by IONM. During nested cross-validation, the data was split into five folds, for both the inner and the outer loop. The four ML classifiers developed were support vector machine, K-nearest neighbors, random forest and extreme gradient boosting, and tested along the three modalities MEP, SSEP, and MEP-SSEP combination.Results: Extreme gradient boosting outperformed the other classifiers on all performance metrics. The combined MEP-SSEP model exhibited the highest scores for sensitivity: 70.4%, specificity: 88.3% and accuracy: 87.1%, while the MEP model exhibited the highest performance for precision: 75.6%. Highest predicting scores per individual class were also obtained by this XGBoost classifier on the combined MEP-SSEP model. Key predicting features were the presence or absence of preoperative neurological deficits and last measured signal latency compared to baseline, with a contribution of 29% and 13.5% in the best performing model, respectively. Conclusion: A reliable prediction of neurological outcomes three months postoperatively can be made combining MEP and SSEP IONM features, provided that the patient's preoperative status is accurately documented and included in the prediction. Though either MEP or SSEP features alone offer predictive value, MEP features show superior predictive values compared to SSEP features when both modalities are accessible, with latency emerging as a prominent predictive IONM feature.TM30004; 35 ECTSTechnical Medicine | Sensing and Stimulatio
Evaluating the impact of prediction accuracy on Continuous Descent Operations: The added value of Trajectory Predictor performance through Air-Ground Datalink
No full textThis research investigates the role of time prediction accuracy in optimizing Continuous Descent Operations (CDO) within the aviation sector, with a specific focus on assessing the additional benefits brought forth by the integration of Air-Ground Datalink technologies. Continuous Descent Operations, characterized by uninterrupted and efficient descent profiles, hold promise for reducing fuel consumption, emissions, noise, and overall operational costs. However, the extent to which accurate time predictions contribute to the success of CDO remains a critical yet understudied aspect.Aerospace Engineerin
Pull-out force of grippers with initially-curved fingers based on Pseudo-Rigid Body modelling
No full textThis thesis presents the state-of-the art gripping literature and the implementation and extension of an existing Pseudo-Rigid Body Modelling (PRBM) method for modelling initially-curved compliant grippers out of which a circular object is extracted. From the existing literature, challenges are found in the design and evaluation of concepts of initially-curved compliant grippers, mainly involving the relevant design parameters, such as the thickness and enclosing angle of the finger.The main goal of this thesis is therefore to present and validate the pull-out force modelling for these fingers within defined load conditions to provide comprehensive insights into the relation between important design parameters, such as the enclosing angle and thickness of the finger. This goal is accomplished by extending an existing 3R PRB-model for initially-curved beams with a fifth link that represents the object and analysing the kinematics and kinetics to determine the relation for the pull-out force of a gripper finger with defined dimensions and a known load case. This model is validated by designing and building an experimental test setup in which the reaction forces of a initially-curved testpiece of PLA and stainless steel material are measured. Errors for the kinetics between 12 and 32 percent were determined, consisting primarily of systematic errors. The validated model is used for a parametric study, where relations between relevant design parameters, such as the enclosing angle and thickness of an initially-curved compliant gripper finger, are determined and visualized in a design chart that are be applied in the design of an initially-curved enclosing gripper prototype.Mechanical Engineering | Mechatronic System Design (MSD
Pressure drop non-linearities in material extrusion additive manufacturing: A novel approach for pressure monitoring and numerical modeling
No full textFused Filament Fabrication is an additive manufacturing technique in which molten thermoplastic polymers are extruded through a nozzle. Therefore, the interplay between the viscoelastic nature of the polymer melt, temperature, printing conditions and nozzle shape may lead to inconsistent extrusion. To improve the extrusion control and optimize the print-head performance, a better understanding of the flow process of the polymer melt both in the nozzle and the liquefier is needed. However, several challenges need to be overcome due to the complexity of gathering experimental data on the melt pressure in the nozzle and the lack of numerical models able to capture the full rheology of the molten polymer. This research introduces an innovative approach for monitoring the pressure within a material extrusion 3D printer's nozzle. This method involves utilizing a pin in direct contact with the molten material, which then transmits the applied force from the material to an externally mounted load cell. The setup provides reliable, repeatable pressure data in steady-state conditions for two nozzle geometries and at different extrusion flows and temperatures. Moreover, the Giesekus model enabled capturing the viscoelastic rheometric features of the melt, and the numerical predictions have been compared with the experimental data. Results show that the numerical model accurately describes the flow conditions in the nozzle and allows the estimation of the behavior of the melt in the liquefier zone, the area of the print-head where the filament is molten. It could be concluded that the backflow, which is the backward flow of the molten polymer in the gap between the filament and the liquefier towards the cold end, caused significant non-linearities in the total pressure drop measured in the feeders, which were related to normal forces induced by shear in that region.Micro and Nano Engineerin
Settlement success of European flat oyster (Ostrea edulis) on different types of hard substrate to support reef development in offshore wind farms
No full textThe native European flat oyster (Ostrea edulis) is an ecosystem engineer providing important ecosystem services, but became nearly extinct from the North Sea due to diseases and overfishing. There's a growing interest to restore these oyster reefs for their valuable contribution in re-establishing a rich ecosystem in the North Sea. In order to reintroduce the flat oyster population, the availability of hard substrate is crucial for initial settlement and reef development. Such substrate is offered by the infrastructure in offshore wind farms, by means of quarried rock placed at the base of the wind turbine foundations and on top of cable crossings to prevent scouring of the seabed. Further anthropogenic disturbances of the seabed are largely restricted, making wind farm areas promising sites for oyster reef restoration. For successful oyster reef initiation, offering a suitable type of substrate for larvae settlement is important. Here, we assess the settlement preference of flat oysters on 9 different types of substrate, by comparing total settlement, spat densities and spat survival. Oyster larvae settlement preference based on the total number of spat per surface area of the substrate was the highest for granite, a rock type conventionally used as scour protection in offshore wind farms. The lowest settlement preference was observed for steel and the biodegradable polymer BESE. The experiments were performed in a spatting pond and in a natural bay to be able to compare spat collection under controlled and natural conditions. Settlement rates in the spatting pond were much higher than in the natural environment, though survival rates were lower. Our results provide insight in the settlement preference of the European flat oyster for different types of substrate under controlled and natural conditions. Knowing these favorable substrates and conditions for oyster larvae settlement allows for the selection of pro-active measures that contribute to flat oyster reef restoration in the North Sea.Rivers, Ports, Waterways and Dredging Engineerin
Damage Detection of Gantry Crane with a Moving Mass Using Artificial Neural Network
No full textGantry cranes play a pivotal role in various industrial applications, and their reliable operation is paramount. While routine inspections are standard practice, certain defects, particularly in less accessible components, remain challenging to detect early. In this study, first a finite element model is presented, and the damage is introduced using random changes in the stiffness of different parts of the structure. Contrary to the assumption of inherent reliability, undetected defects in crucial structural elements can lead to catastrophic failures. Then, the vibration equations of healthy and damaged models are analyzed to find the displacement, velocity, and acceleration of the different crane parts. The learning vector quantization neural network is used to train and detect the defects. The output is the location of the damage and the damage severity. Noisy data are then used to evaluate the network performance robustness. This research also addresses the limitations of traditional inspection methods, providing early detection and classification of defects in gantry cranes. The study’s relevance lies in the need for a comprehensive and efficient damage detection method, especially for components not easily accessible during routine inspections.Materials and Environmen
Identifying the most important facilitators of open research data sharing and reuse in Epidemiology: A mixed-methods study
No full textTo understand how open research data sharing and reuse can be further improved in the field of Epidemiology, this study explores the facilitating role that infrastructural and institutional arrangements play in this research discipline. It addresses two research questions: 1) What influence do infrastructural and institutional arrangements have on open research data sharing and reuse practices in the field of Epidemiology? And 2) how could infrastructural and institutional instruments used in Epidemiology potentially be useful to other research disciplines? First, based on a systematic literature review, a conceptual framework of infrastructural and institutional instruments for open research data facilitation is developed. Second, the conceptual framework is applied in interviews with Epidemiology researchers. The interviews show that two infrastructural and institutional instruments have a very high influence on open research data sharing and reuse practices in the field of Epidemiology, namely (a) access to a powerful search engine that meets open data search needs and (b) support by data stewards and data managers. Third, infrastructural and institutional instruments with a medium, high, or very high influence were discussed in a research workshop involving data stewards and research data officers from different research fields. This workshop suggests that none of the influential instruments identified in the interviews are specific to Epidemiology. Some of our findings thus seem to apply to multiple other disciplines. This study contributes to Science by identifying field-specific facilitators and challenges for open research data in Epidemiology, while at the same time revealing that none of the identified influential infrastructural and institutional instruments were specific to this field. Practically, this implies that open data infrastructure developers, policymakers, and research funding organizations may apply certain infrastructural and institutional arrangements to multiple research disciplines to facilitate and enhance open research data sharing and reuse.Information and Communication Technolog
The climate impact of hypersonic transport
No full textAt speeds roughly between five and ten thousand km/h, hypersonic aircraft offer the promise of an extremely fast means of transport. Growing concerns about climate warming, however, direct attention to sustainability. This thesis focuses on atmospheric composition and radiation changes by considering a range of individual hypersonic aircraft designs on trajectory and route network level. State-of-the-art Earth system models are used for simulations, and results calculated with the EMAC model are subsequently compared with simulations performed elsewhere with the LMDZ-INCA model. The comparison to a third model, i.e. WACCM, with a very similar – but independent – model setup allows even further clarification. For model validation satellite measurements (ozone, water vapor) and aircraft measurements (ozone, water vapor, temperature) are taken into account. After the introduction in the first chapter, the second chapter is a general description of the Earth system including anthropogenic perturbations, in particular perturbations from subsonic, supersonic and hypersonic aircraft emissions followed by a detailed explanation of methods and the EMAC model setup in the third chapter. A new research finding in the context of middle atmospheric chemistry is the increased methane and nitric acid oxidation following hypersonic emissions. This effect results in a (photo-)chemical net production of water vapor and eventually increases water vapor perturbations further, which is described in detail in chapter 4. In chapter 5 an analysis of atmospheric dynamics and transport of emitted trace gases in the middle atmosphere underlines the importance of the Brewer-Dobson circulation and shows the impact of polar stratospheric clouds on water vapor perturbations during polar winter. The evaluation of multiple hypersonic aircraft designed for different cruise altitudes shows that their climate impact increases with cruise altitude and can be approximately 10-20 times as much as a conventional aircraft (chapter 6). Emissions at different hypersonic cruise altitude and latitude regions show that the climate impact can vary more with latitude of emission than with altitude of emission (chapter 7). With rf_of_hypersonic_trajectories() a software was developed to estimate the climate impact of aircraft design and flight trajectory/network options in seconds based on robust results from Earth system modelling. Using the software it is shown that a cruise altitude optimization loop can reduce the overall climate impact of a state-of-the-art aircraft design (chapter 8).There are two methodological highlights to mention in the context of the EMAC model. The first is a new MESSy submodel H2OEMIS, which was created as part of this thesis. H2OEMIS is an interface to include water vapor emissions in EMAC model simulations, which was not possible before. This submodel will generally be of interest for future evaluations of e.g. any vehicles emitting water vapor and the impact of volcanic eruptions with EMAC. The secondmethodological highlight is the application of a novel speed-up technique during simulation runs, which reduces the simulated years by twothirds. To conclude the summary, the four following points are important to take away. This thesis brought • A new research finding on middle atmospheric chemistry: The identification of a chemical feedback that enhances the water vapor perturbation lifetime albeit an increasing chemical water vapor destruction • A robust estimate of the climate impact of hypersonic aircraft for both specific aircraft designs and general atmospheric and radiative sensitivities showing a large altitude and latitude dependence • An easily accessible tool for researchers and companies to estimate the climate impact of new hypersonic aircraft designs with low cost and low time • An estimate how the development of hypersonic aircraft would contribute to a road map to a climate optimal aircraft industry compared to conventional aircraft Aircraft Noise and Climate Effect
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