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    Robustness Levels of Critical Infrastructures Against Global Navigation Satellite System Signal Disturbances
    (MDPI, 2023) Bos, A. ; Snijders, M. ; Zevenbergen, A. ; Drost, K. ; Zelle, H.D. ; Hoeven, B. van der
    Resilience against signal disturbances is an important characteristic of GNSS-based PNT solutions. In particular, for critical infrastructures, failure to provide correct PNT information in these domains may have a major societal impact. The Resilience Framework by the Department of Homeland Security (DHS) provides a set of requirements and guidelines to design a PNT solution of a certain level of resilience. Over the lifetime of the applications, it will be of prime importance to assess the resilience of the PNT solutions on a regular basis. Given how often GNSS-based solutions are being applied, partly automating the assessment process will be needed to make this task feasible. To automate the generative process, a machine-readable structure with well-established meaning is required. In this work, the use of fault trees as a formal system to encode the resilience framework is investigated.
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    Evaluating the climate impact of aviation emission scenarios towards the Paris agreement including COVID-19 effects
    (Springer Nature, 2022) Grewe, V. ; Rao, A.G. ; Gronstedt, T. ; Xisto, C. ; Linke, F. ; Melkert, J. ; Middel, J. ; Ohlenforst, B.A. ; Blakley, S. ; Christie, S. ; Matthes, S. ; Dahlmann, C.
    Aviation is an important contributor to the global economy, satisfying society’s mobility needs. It contributes to climate change through CO2 and non-CO2 effects, including contrail-cirrus and ozone formation. There is currently significant interest in policies, regulations and research aiming to reduce aviation’s climate impact. Here we model the effect of these measures on global warming and perform a bottom-up analysis of potential technical improvements, challenging the assumptions of the targets for the sector with a number of scenarios up to 2100. We show that although the emissions targets for aviation are in line with the overall goals of the Paris Agreement, there is a high likelihood that the climate impact of aviation will not meet these goals. Our assessment includes feasible technological advancements and the availability of sustainable aviation fuels. This conclusion is robust for several COVID-19 recovery scenarios, including changes in travel behaviour.
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    Towards improved porous models for solid/fuid topology optimization
    (Springer, 2023) Theulings, M.J.B. ; Langelaar, M. ; Keulen, F. van ; Maas, R.
    Modeling of fluid flows in density-based topology optimization forms a longstanding challenge. Methods based on the Navier–Stokes equations with Darcy penalization (NSDP equations) are widely used in fluid topology optimization. These methods use porous materials with low permeability to represent the solid domain. Consequently, they suffer from flow leakage in certain areas. In this work, the governing equations for solid/fluid density-based topology optimization are reevaluated and reinterpreted. The governing equations are constructed using the volume averaged Navier–Stokes (VANS) equations, well known in the field of porous flow modeling. Subsequently, we simplify, interpret and discretize the VANS equations in the context of solid/fluid topology optimization, and analytically derive lower bounds on the Darcy penalization to sufficiently prevent flow leakage. Based on both the NSDP and VANS equations, two flow solvers are constructed using the Finite Volume method. Their precision and the lower bound on the Darcy penalization are investigated. Subsequently, the solvers are used to optimize flow channels for minimal pressure drop, and the resulting designs and convergence behavior are compared. The optimization procedure using the VANS equations is found to show less tendency to converge to inferior local optima for more precise flow solutions and is less sensitive to its parameter selection.
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    The evaluation of cEEGrids for fatigue detection in aviation
    (Oxford Academic, 2024) Klaren, C. van ; Maij, A. ; Marsman, L.A. ; Drongelen, A. van
    Operator fatigue poses a major concern in safety-critical industries such as aviation, potentially increasing the chances of errors and accidents. To better understand this risk, there is a need for noninvasive objective measures of fatigue. This study aimed to evaluate the performance of cEEGrids, a type of ear-EEG, for fatigue detection by analyzing the alpha and theta power before and after sleep restriction in four sessions on two separate days, employing a within-participants design. Results were compared to traditional, highly validated methods: the Karolinska Sleepiness Scale (KSS) and Psychomotor Vigilance Task (PVT). After sleep restriction and an office workday, 12 participants showed increased alpha band power in multiple electrode channels, but no channels correlated with KSS scores and PVT response speed. These findings indicate that cEEGrids can detect differences in alpha power following mild sleep loss. However, it should be noted that this capability was limited to specific channels, and no difference in theta power was observed. The study shows the potential and limitations of ear-EEG for fatigue detection as a less invasive alternative to cap-EEG. Further design and electrode configuration adjustments are necessary before ear-EEG can be implemented for fatigue detection in the field.