21549 research outputs found
Sort by
Modelling the impact of fuel in aeronautical gas turbines
Get PDFThe rise of climatic hazards, due to the human contribution, has led some governments and industries of the aeronautical sector to think about solutions to reduce combustion emissions. To create a less environmentally demanding aviation, electrical storage does not fill the power criteria and other promising fuels such as hydrogen require a change of the whole plane engine. Another short-run solution is the use of drop-in alternative fuel, which, despite some drawbacks, would reduce the emissions of the sector in the nearer future. The European H2020-JETSCREEN project, that funded this PhD, falls within this context. Indeed, the development of Large-Eddy Simulations (LES) and Analytically Reduced Chemistries (ARC) coupled with the rise of computer resources has enabled precise kinetics to be used in turbulent combustion chambers. The main topic of this PhD is the development of a methodology to analyse a stabilised turbulent two-phase flow flame with complex chemistry and heat losses for three multi-component fuels : one conventional and two alternative fuels. Before the computation, questions on the chemistry and the evaporation properties of the fuels remain. At first, ARC were developed and validated against the detailed mechanism, testifying the capability of the kinetic reduction code ARCANE to retrieve the chemical fuel sensitivities. Fuels were then analysed on every canonical case concluding that the fuel composition had an influence on the global combustion but little on the pollutants. Furthermore, the simulation of 1D ARC premixed flame explained why such complex kinetics need very few points in the flame front in order to give accurate results and underlined the prominent role of the flame foot and especially the fuel consumption that is monitoring the flame convergence. Second, evaporation properties comparisons led to results close to the experimental work of the DLR and retrieving the two-phase fuel sensitivities. Based on those results, a twophase premixed flame was computed and the flame characteristic variables were found to depend on the degree of pre-evaporation. Furthermore, the spray counter-flow diffusion flame structure was investigated. The polydisperse two-phase flow initiating a change of the flame regime explained the exotic structure observed. Once those canonical analyses studied, the real combustion chamber simulation was tackled. Differences in terms of averaged solutions have then been drawn, showing the capability of the LES code, AVBP, to globally reproduce the experimental behaviour of those fuels whether for the dynamic quantities, the thermal fields or the two-phase flow properties. The comparison between a simple and a complex surrogate for Jet-A1 resulted in a similar stabilisation point, but a different flame structure, assessing the capability of the Takeno sensor to visualise the right flame regime. A Lean Blow-Out(LBO) methodology was suggested on the simple chemistry, starting by the evaluation of the characteristic timescales, key quantities for the transient flame evolution and followed by the right variable choice for the LBO detection. The LBO was detected slightly below the experimental value, following a flame stabilisation by hot gases process. Finally, the flame structure was compared for the three fuels and depicted differences in terms of flame structure mainly due to the evaporation properties that are impacting the thermal field and the local flame regime
Bayesian estimation of the parameters of the joint multifractal spectrum of signals and images
Get PDFMultifractal analysis has become a reference tool for signal and image processing. Grounded in the quantification of local regularity fluctuations, it has proven useful in an increasing range of applications, yet so far involving only univariate data (scalar-valued time series or single channel images). Recently the theoretical ground for multivariate multifractal analysis has been devised, showing potential for quantifying transient higher-order dependence beyond linear correlation among collections of data. However, the accurate estimation of the parameters associated with a multivariate multifractal model remains challenging, severely limiting their actual use in applications. The main goal of this thesis is to propose and study practical contributions on multivariate multifractal analysis of signals and images. Specifically, the proposed approach relies on a novel and original joint Gaussian model for the logarithm of wavelet leaders and leverages on a Whittle-based likelihood approximation and data augmentation for the matrix-valued parameters of interest. This careful design enables efficient estimation procedures to be constructed for two relevant choices of priors using Bayesian inference. Algorithms based on Monte Carlo Markov Chain and Expectation Maximization strategies are designed and used to approximate the Bayesian estimators. Monte Carlo simulations, conducted on synthetic multivariate signals and images with various sample sizes, numbers of components and multifractal parameter settings, demonstrate significant performance improvements over the state of the art. In addition, theoretical lower bounds on the variance of the estimators are designed to study their asymptotic behavior. Finally, the relevance of the proposed multivariate multifractal estimation framework is shown for two real-world data examples: drowsiness detection from multichannel physiological signals and potential remote sensing applications in multispectral satellite imagery
Sizing and optimization of a more electric aircraft integrating short-term incremental technologies
Get PDFIn order to reduce the environmental impact of aviation, one of the solutions is to develop more efficient aircraft. These gains can be achieved in different fields such as propulsion, aerodynamics or electrification of systems. This paper focuses on the sizing and optimization of BEITA, a short-medium range aircraft architecture available in the short term by 2025-2030. The aircraft is based on incremental technologies for propulsion, aerostructure and bleedless systems. Light-weight models are proposed for the different improvements, particularly for more electric systems. FAST-OAD, an open source framework for rapid overall aircraft design based on multidisciplinary design analysis and optimization, is used to size the new architecture and a specific life cycle assessment module is used to estimate the environmental impacts. BEITA allows a reduction in fuel consumption of 15% compared to the CeRAS reference aircraft. Optimizations of this architecture are
achieved minimizing different cost functions. This study ends with a sizing on a shorter range based on specific
payload-range diagrams
Ecological measures of cognitive impairments in aeronautics: theory and application
No full textThe objective of this chapter is to focus on the use of unobtrusive easy-to-use electrophysiological systems for neuroergonomic research. In a first section, we describe the challenges and limits related to the use of such systems. Electrode localization and signal processing solutions are then proposed to overcome some of the raised issues. In a second section, we explore the feasibility to measure pilots’ auditory attention in a flight simulator using an unobtrusive EEG system [1] on a small number of participants. This study aims at measuring the cerebral activity associated with inattentional deafness in an ecological context with varying degrees of workload. The end goal was to assess the possibilities of such a system to be transferred to real-flight conditions. Our results illustrate this paradox: we were able to reproduce some of the results observed in the literature, but we also faced difficulties in terms of signal processing and measure identifications. We show that despite the lower signal-to-noise ratio observed with this kind of devices, we are able to detect event-related potentials (ERPs) and frequency features. In a last part we discuss our results with regards to Neuroadaptive Systems challenges, and how we were able to overcome some of the current limits in neuroergonomics
A few upstream bifurcations drive the spatial distribution of red blood cells in model microfluidic networks
Get PDFThe physics of blood flow in small vessel networks is dominated by the interactions between Red Blood Cells (RBCs), plasma and blood vessel walls. The resulting couplings between the microvessel network architecture and the heterogeneous distribution of RBCs at network-scale are still poorly understood. The main goal of this paper is to elucidate how a local effect, such as RBC partitioning at individual bifurcations, interacts with the global structure of the flow field to induce specific preferential locations of RBCs in model microfluidic networks. First, using experimental results, we demonstrate that persistent perturbations to the established hematocrit profile after diverging bifurcations may bias RBC partitioning at the next bifurcations. By performing a sensitivity analysis based upon network models of RBC flow, we show that these perturbations may propagate from bifurcation to bifurcation, leading to an outsized impact of a few crucial upstream bifurcations on the distribution of RBCs at network-scale. Based on measured hematocrit profiles, we further construct a modified RBC partitioning model that accounts for the incomplete relaxation of RBCs at these bifurcations. This model allows us to explain how the flow field results in a single pattern of RBC preferential location in some networks, while it leads to the emergence of two different patterns of RBC preferential location in others. Our findings have important implications in understanding and modeling blood flow in physiological and pathological conditions
Elucidating Curvature-Capacitance Relationships in Carbon-Based Supercapacitors
Get PDFNanoscale surface curvatures, either convex or concave, strongly influence the charging behavior of supercapacitors. Rationalizing individual influences of electrode atoms to the capacitance is possible by interpreting distinct elements of the charge-charge covariance matrix derived from individual charge variations of the electrode atoms. An ionic liquid solvated in acetonitrile and confined between two electrodes, each consisting of three undulated graphene layers, serves as a demonstrator to illustrate pronounced and nontrivial features of the capacitance with respect to the electrode curvature. In addition, the applied voltage determines whether a convex or concave surface contributes to increased capacitance. While at lower voltages capacitance variations are in general correlated with ion number density variations in the double layer formed in the concave region of the electrode, for certain electrode designs a surprisingly strong contribution of the convex part to the differential capacitance is found both at higher and lower voltages
Bio-inspired vortex lift for enhanced manoeuvrability
Get PDFInspired by highly manoeuvrable species of birds like
the peregrine falcon and the swift, static and dynamic
computational fluid dynamics (CFD) simulations were
conducted to investigate vortex lift in unsteady flows.
The configuration corresponds to a 50◦ sweep delta wing
with sharp leading edge at Re= 5.0×104. CFD simulations
were performed using a Direct Numerical Simulation
(DNS) approach with a Lattice-Boltzmann Method as well as Unsteady Reynolds Averaged Navier-Stokes (URANS) simulations. Aerodynamic forces as well as the overall structure of the leading edge vortices were compared with existing literature. The evolution of the flow structures was studied when the wing performs a pitching manoeuvre from 0◦ to 20◦ angle of attack. Close agreement between both methods was found for the static and pitching lift curves, with the URANS solver presenting substantial limitations to capture complex unsteady phenomena such as the vortex breakdown. A time lag was observed in the flow dynamics during the manoeuvre, with the vortex breakdown delayed during pitch-up resulting in an improved aerodynamics performance, but more present and intense when pitching down. A sinusoidal motion was tested with the URANS solver and compared with the linear ramp case, showing performance advantages as well as higher similarity to real manoeuvres
Behavioral and Physiological Assessment of a Virtual Reality Version of the MATB-II Task
Get PDFThe goal of this research was to examine the possible benefits of adapting the Multi-Attribute Task Battery
(MATB-II) in a virtual reality (VR) environment to provide an immersive and ecological platform for studies
on mental workload in the aerospace domain. The original desktop MATB-II has many advantages, but the
level of immersion remains moderate, and the computer screen greatly reduces the spatial dimension existing
in real environments such as the cockpit. Thirty-one participants performed an experiment during which we
compared the original MATB-II with the new virtual version, called “MATB-II VR”. We used subjective,
performance, and cardiovascular measurements. The virtual MATB-II was performed without (“MATB-II VR
No Touch”) and with tactile feedback (“MATB-II VR Touch”). In general, the results showed that mental and
physical efforts were higher and performances lower with the virtual version. Heart rate was higher with the
virtual version, supporting the idea that such environment is more challenging. The individual performance
in the desktop and the virtual environments correlated well, showing that our virtual version engaged analog
physical and cognitive abilities as compared with the original version. Interestingly, performance during
MATB-II VR was well predicted by basic mental rotation performance assessed with a neuropsychological
task
The cooling efficiency of s‐CO₂ microchannel heat sink compared with a water‐based design
Get PDFHigh-pressure drops characteristic of microchannel heat sinks (MCHS) is an issue that needs to be addressed to reduce the size of heat-removing devices in compact electronic devices. Supercritical carbon dioxide (s-CO2) is a suitable candidate being proposed as an alternative coolant to enhance the cooling of the microchannel heat sink (MCHS), with high heat flux, due to its favorable thermophysical properties near its critical point. In this study, numerical simulations are conducted to evaluate the thermal and hydraulic performance of a channel for a designed heat sink with s-CO2 (at constant P=8MPa) and compare it with conventional liquid coolant (water). The effect of coolants mass flow rate (Q), channel aspect ratio (AR), and inlet temperatures on the thermal and hydraulic performance of one channel is studied by varying Q from 0.004 to 0.03 kg/s and AR from 0.33 to 10. The results show that, for the same aspect ratio, same geometry, and constant heat flux, s-CO2 offers a higher overall heat transfer coefficient (32%) with a lower friction factor (pumping power) compared with the water at the same inlet temperature (T=32°C)The results of pumping power comparison between two coolants reveal that for CO2 in supercritical conditions (P=8MPa, T=32°C) the consumed power varies by change of the aspect ratio, which is 1.85 times lower than water for AR = 0.33 and is 3.6 times higher for AR=10. However, in the subcooled state, the reverse effect of the aspect ratio is seen
Modeling Inclusive Systems in SysML
Get PDFOver the past few years, inclusion of disabilities and
gender has become an issue in systems design. Design techniques, and model-based ones in particular, need to evolve accordingly. A survey of the literature indicates that little work has been published on modeling inclusive systems in a MBSE context. How to make systems inclusive and model them in SysML isthe subject of this paper. Mind maps facilitate thinking about inclusive systems in general before focusing discussion on SysML modeling of these systems. The proposed approach covers the early stages of the life cycle of systems, with need expression, requirement capture, analysis and design. An Electronic Voting Machine serves as case study