Ponències/Comunicacions de congressos
Recent Submissions
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Assessment of tabulated chemistry models for the les of a model aero-engine combustor
(Global Power and Propulsion Society (GPPS), 2022)
Conference lecture
Open AccessTabulated chemistry methods present a compromise between computational cost and the ability to capture complex combustion physics in high-fidelity numerical simulations. The application of such models entails a number of ... -
Influence of axial air injection on the flame stability of a technically premixed hydrogen flame
(Global Power and Propulsion Society (GPPS), 2022)
Conference report
Open AccessThis work is a numerical investigation on the stability of a hydrogen flame in a swirl-stabilized burner configuration using large-eddy simulation with tabulated chemistry. Experimental results from this combustor showed ... -
Including in Situ Visualization and Analysis in PDI
(Springer Nature, 2021)
Conference lecture
Open AccessThe goal of this work was to integrate in situ possibilities into the general-purpose code-coupling library PDI [1]. This is done using the simulation code Alya as an example. Here, an open design is taken into account to ... -
RosneT: A block tensor algebra library for out-of-core quantum computing simulation
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessWith the advent of more powerful Quantum Computers, the need for larger Quantum Simulations has boosted. As the amount of resources grows exponentially with size of the target system Tensor Networks emerge as an optimal ... -
Epicentral region estimation using convolutional neural networks
(Springer Nature, 2022)
Conference report
Open AccessRecent works have assessed the capability of deep neural networks of estimating the epicentral source region of a seismic event from a single-station three-channel signal. In all the cases, the geographical partitioning ... -
A data-driven wall-shear stress model for LES using gradient boosted decision trees
(Springer Nature, 2021)
Conference report
Open AccessWith the recent advances in machine learning, data-driven strategies could augment wall modeling in large eddy simulation (LES). In this work, a wall model based on gradient boosted decision trees is presented. The model ... -
Development of the conditional moment closure with a multi-code approach in the frame of Large Eddy Simulations
(ECM, 2021)
Conference lecture
Open AccessThe Conditional Moment Closure (CMC), devised for turbulent combustion modelling, was implemented in the multiphysics code Alya, based on the Finite Element Method (FEM), in the frame of Large Eddy Simulations (LES) for ... -
Optimization of the progress variable definition using a genetic algorithm for the combustion of complex fuels
(MCM, 2021)
Conference lecture
Open AccessIn this work counterflow diffusion flamelets of n-heptane and air are used at stable and unsteady extinguishing conditions for building a thermo-chemical database for Computational Fluid Dynamics (CFD) calculations. The ... -
High-fidelity simulations of the mixing and combustion of a technically premixed hydrogen flame
(MCM, 2021)
Conference lecture
Open AccessNumerical simulations are used here to obtain further understanding on the flashback mechanism of a technically premixed hydrogen flame operated in lean conditions. Recent work from the authors (Mira et al., 2020) showed ... -
Semi implicit solver for high fidelity LES/DNS solutions of reacting flows
(MCM, 2021)
Conference lecture
Open AccessA semi-implicit/point-implicit stiff solver (ODEPIM) for integrating chemistry in context of high fidelity LES/DNS simulations is presented. A detailed overview of the algorithm and its numerical formulation is discussed. ... -
Subdivided linear and curved meshes preserving features of a linear mesh model
(Sandia National Laboratories, 2019)
Conference report
Open AccessTo provide straight-edged and curved piece-wise polynomial meshes that target a unique smooth geometry while preserving the sharp features and smooth regions of the model, we propose a new fast curving method based on ... -
Improving object detection in paintings based on time contexts
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Open AccessThis paper proposes a novel approach to object detection for the Cultural Heritage domain, which relies on combining Deep Learning and semantic metadata about candidate objects extracted from existing sources such as ...
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