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Long-time behavior of a coupled heat-wave system using a structure-preserving finite element method
Get PDFThis work is a numerical investigation of the coupling between the heat and wave equations, recast as an interconnection of open port-Hamiltonian systems (pHs).
A structure-preserving discretization suited to open pHs, based on a mixed finite element approximation space that includes boundary inputs and outputs, is shown to yield a semi-discrete power balance analogous to the continuous one. In the frequency domain, the semi-discretization captures the finite accumulation point in the spectrum, associated with highly-oscillatory eigenfunctions localized at the interconnection interface. In the time domain, the polynomial and logarithmic energy decays proved by Zhang and Zuazua (Arch. Rational Mech.Anal. 184, 2007) are recovered using a Crank-Nicolson scheme
Learning Path Constraints for UAV Autonomous Navigation Under Uncertain GNSS Availability
Get PDFThis paper addresses a safe path planning problem for UAV urban navigation, under uncertain GNSS availability. The problem can be modeled as a POMDP and solved with sampling-based algorithms. However, such a complex domain suffers
from high computational cost and achieves poor results under real-time constraints. Recent research seeks to integrate offline learning in order to efficiently guide online planning. Inspired by the state-of-the-art CAMP (Context-specific Abstract Markov decision Process) formalization, this paper proposes an offline process which learns the path constraint to impose during online POMDP solving in order to reduce the policy search space. More precisely, the offline learnt constraint selector returns the best path constraint according to the GNSS availability probability in the environment. Conclusions of experiments, carried out for three environments, show that using the proposed approach allows to improve the quality of a solution reached by an online planner, within a fixed decision-making timeframe, particularly when GNSS availability probability is low
An outer approximation bi-level framework for mixed categorical structural optimization problems
Get PDFIn this paper, mixed categorical structural optimization problems are investigated. The aim is to minimize the weight of a truss structure with respect to cross-section areas, materials and cross-section type. The proposed methodology consists of using a bi-level decomposition involving two problems: master and slave. The master problem is formulated as a mixed integer linear problem where the linear constraints are incrementally augmented using outer approximations of the slave problem solution. The slave problem addresses the continuous variables of the optimization problem. The proposed methodology is tested on three different structural optimization test cases with increasing complexity. The comparison to state-of-the-art algorithms emphasizes the efficiency of the proposed methodology in terms of the optimum quality, computation cost, as well as its scalability with respect to the problem dimension. A challenging 120-bar dome truss optimization problem with 90 categorical choices per bar is also tested. The obtained results showed that our method is able to solve efficiently large scale mixed categorical structural optimization problems
Ecodesign with topology optimization
Get PDFIn order to mitigate the impact of the transportation sector on climate change, light and ecological parts must be designed. A lifecycle oriented design methodology with C02 footprint minimization of parts used in various transports is presented in this work. Only material production and use phase are considered in this work, to have a better understanding of the different contributions. Simultaneous topological design and material choice are investigated for 2D examples. The results show that considering out-of-plane thickness as a variable, both problems can now be decoupled for simple load cases. It is shown that a very simple material index depending only on the type of transport can be used. An optimal volume fraction is obtained, specific only to each topology problem, but unrelated to the material chosen or the loads applied. The method is promising for fast ecodesign and its simple implementation enables easy future improvements
Compressibility effects on three-dimensional secondary instabilities in the cylinder periodic wake
Get PDFWith a growing interest in low Reynolds numbers compressible flows, the aim of this work is to investigate compressibility effects on the wake dynamics of the circular cylinder. In particular, our focus is made on the so called Mode A and Mode B secondary instabilities, which are responsible of the transition from a two-dimensional periodic to a three-dimensional state. Mode A appears at Re=180−190 and is associated with an elliptic instability of the primary vortex cores with large scale transverse structures at a spanwise wavelength of λz~4D, where D indicates the cylinder diameter. Mode B, which arises at Re=230−260, is instead associated with a hyperbolic instability developing in the braid region and is related to the formation of finer scale structures of characteristic wavelength λz~1D. We address the influence of compressibility on these modes. The analysis has been conducted for Reynolds numbers Re in [200; 350] and Mach numbers up to M=0.5. The two-dimensional periodic base state is found to exhibit time-averaged properties that substantially vary within the range of Reynolds and Mach numbers considered. Specifically, three different types of time-averaged flow structure are identified when varying both Reynolds and Mach numbers for three representative cases. The two-dimensional periodic flow is used as base state for a global stability analysis performed by means of Floquet theory. The global modal stability solver is based on the Krylov–Schur algorithm with a time-stepping approach. A stabilizing (decreasing Floquet multiplier μ) or a destabilizing (increasing μ) effect of compressibility is observed on Mode A depending on the Reynolds number and the mode wavelength, while Mode B is found to be stabilized by compressibility. Interestingly, the characteristic length-scales of the time-averaged base flow recirculation region are found to be relevant for the normalisation of the instability wavelengths λz. The Mach number increase is also found to promote vorticity anisotropy on Mode A at largest wavelengths, which is not
instead observed for Mode B
Regarding the COVID-19 crisis from a systems engineering perspective
Get PDFIn the beginning of 2022, the world is still fighting the crisis caused by the COVID-19 outbreak. The scientific community is still dedicating significant efforts to identify which are the better strategies to mitigate the pandemic and establish how and when to apply them. Modeling and simulation are a common method to replicate and foresee the behavior of the epidemic curve, but traditional analytical models are not capable to explain and reproduce the real evolution of the number of infections and deaths as they only concentrate in the epidemiological aspects of the virus. The COVID-19 crisis has an impact in all fundamental levels of society, and this is the reason why its modeling requires a global perspective and a holistic approach. Though the engineering scope is not common in the study of public health crises, this paper concludes that some engineering tools such as systems analysis and control theory may be the answer to build a high-fidelity model to support the decision-making facing the emergency
Thermal Imaging of the Face: Mental Workload Detection in Flight Simulator
Get PDFThermography-based physiological measurement is a contact-free approach that can be particularly helpful for detecting pilots’ mental state in operational settings. In particular, thermal infrared imaging of the face is a powerful, unobtrusive and non-invasive tool that enables rapid and automatic analysis of changes in regional facial blood flow. These blood flow changes index sympathetic activity and are measured by capturing thermal imprints of particular facial regions such as nose or forehead. Although several studies suggest a relationship between mental workload and facial thermoregulation profile, evidence about this link has not yet been sufficiently investigated. In this work, we investigated how thermal measures can allow robust and continuous assessment of mental workload variations of pilots undergoing simulated flight tasks. We analyzed thermal data and heart rate of 20 participants in a flight simulator. Mental workload was modulated by the difficulty of the landing scenario or by an in-flight N-back task. Participants also performed a resting task (called cool-off) in the flight simulator. Thermal imprints did not vary significantly with landing difficulty or N-back difficulty. However, we found that the nose tip and nose area became significantly colder (signal slope was negative) during all piloting scenarios vs the rest period. Heat rate was slightly more sensitive to the piloting difficulty since it was marginally higher during the difficult vs easy landing. Results are promising but further analysis is needed to confirm that the thermal measures could identify fine-grained mental workload variations in a flight simulator setting
Effect of sharp edges on the unsteady flow and aerodynamic performances of a Boxfish, towards bio-inspired low-drag bluff bodies
Get PDFSeveral studies have revealed that boxfishes, tropical
fishes living in shallow waters, show exceptional aerodynamic
performances despite their large volume and crosssectional
area. These characteristics make the boxfish
shape an interesting topic of study for drag optimisation
of bluff bodies. This study focuses on the aerodynamic
analysis of several mathematical shape representations of
the boxfish. The effect of the edges is studied since they
are responsible for the generation of vortices, which play
a role in potentially manipulating the wake, resulting in
an overall decrease in the drag coefficient. The effect of
the sharpness or roundness of the edges on the aerodynamic
performance is investigated. Aerodynamic coefficients
are obtained numerically and experimentally for
a range of Reynolds numbers between 3000 and 300000
and at pitch angle from −16◦ to +20◦
An innovative kinetic model allowing insight in the moderate temperature chemical vapor deposition of silicon oxynitride films from tris(dimethylsilyl)amine
Get PDFAn apparent kinetic model is developed for a novel chemical vapor deposition (CVD) process of silicon oxynitride
(SiOxNy) films from tris(dimethylsilyl)amine (TDMSA) and O2, operating at moderate temperature (600–650 ◦C)
and at atmospheric pressure. The definition of reaction pathways and the extraction of kinetic information is
based on recently reported results of the gas phase composition, complemented by solid phase characteristics
obtained by spectroscopic ellipsometry (SE) and ion beam analyses (IBA). Incorporation of carbon (up to 20 at.
%) is considered alongside nitrogen (up to 25 at.%) for variable O2 flow rates (0.3–1.2 sccm). This combined gasand
solid-phase analysis is utilized to identify the main gaseous species and provide insight into the deposition
mechanism. A silicon- and a nitrogen-centered radical intermediates are considered as the primary species of the
mechanism, based on evidence from gas phase characterizations. A third, fictitious, nitrogen- and carboncontaining
molecule is also conceptualized to account for carbon incorporation. Eight chemical reactions are
defined alongside their respective kinetic parameters and are implemented in the ANSYS® FLUENT® computational
fluid dynamics (CFD) code. Upon validation, the model allows for the successful prediction of local deposition rates and SiOxNy film composition containing non-negligible carbon, marking it as the first kinetic model able to represent the main chemical mechanisms involved in the CVD of a four-component material. The reported combined approach could be applied to other existing or new CVD chemistries forming multicomponent thin films, favoring their implementation in original applications
Multifidelity Orbit Uncertainty Propagation using Taylor Polynomials
Get PDFA new multifidelity method is developed for nonlinear orbit uncertainty propagation. This
approach guarantees improved computational efficiency and limited accuracy losses compared
with fully high-fidelity counterparts. The initial uncertainty is modeled as a weighted sum of
Gaussian distributions whose number is adapted online to satisfy the required accuracy. As
needed, univariate splitting libraries are used to split the mixture components along the direction of maximum nonlinearity. Differential Algebraic techniques are used to propagate these
Gaussian kernels and compute a measure of nonlinearity required for the split decision and
direction identification. Taylor expansions of the flow of the dynamics are computed using a
low-fidelity dynamical model to maximize computational efficiency and corrected with selected
high-fidelity samples to minimize accuracy losses. The effectiveness of the proposed method is
demonstrated for different dynamical regimes combining SGP4 theory and numerical propagation as low- and high-fidelity models respectively