Parametric optimization of pulsating jets in unsteady flow by Multiple-Gradient Descent Algorithm (MGDA)

International audienceTwo numerical methodologies are combined to optimize six design characteristics of a system of pulsating jets acting on a laminar boundary layer governed by the compressible Navier-Stokes equations in a time-periodic regime. The flow is simulated by second-order in time and space finite-volumes, and the simulation provides the drag as a function of time. Simultaneously, the sensitivity equations, obtained by differentiating the governing equations w.r.t. the six parametersare also marched in time, and this provides the six-component parametric gradient of drag. When the periodic regime is reached numerically, one thus disposes of an objective-function, drag, to be minimized, and its parametric gradient, at all times of a period. Second, the parametric optimization is conducted as a multi-point problem by the Multiple-Gradient Descent Algorithm (MGDA) which permits to reduce the objective-function at all times simultaneously, and not simply in the sense of a weighted average

Méthode de Galerkin Discontinue : Cas de l'analyse isogéométrique

International audienceThe objective of Isogeometric Analysis is to address the design and analysis with exactlythe same geometric patterns. For this, the Lagrange polynomials usually used in interpolation arereplaced by B-Splines functions. In this context, we present in this work a new Discontinuous Galerkin(DG) method applied to the numerical solution of hyperbolic equations. The method is based on thechoice of a local Bernstein basis and Gauss-Legendre formulas to approximate the different integrals.We use a Lax-Friedrichs scheme to calculate the numerical flux.L'objectif de l'Analyse IsoGéométrique est de traiter la conception et l'analyse avec exactement les mêmes modèles géométriques. Pour cela, les polynômes de Lagrange classiquement utilisés pour l'interpolation sont remplacés par des fonctions B-Splines. Dans ce cadre, nous présentons dans ce travail une nouvelle méthode de type Galerkin Discontinue (GD), appliquée à la résolution numérique des équations hyperboliques. La méthode est basée sur le choix d'une base locale de Bernstein et des formules de Gauss-Legendre pour approcher les différentes intégrales. Nous utilisons un schéma de Lax-Friedrichs pour calculer les flux numériques

Reducing Uncertainties in a Wind-Tunnel Experiment using Bayesian Updating

We perform a fully stochastic analysis of an experiment in aerodynamics. Given estimated uncertainties on the principle input parameters of the experiment, including uncertainties on the shape of the model, we apply uncertainty propagation methods to a suitable CFD model of the experimental setup. Thereby we predict the stochastic response of the measurements due to the experimental uncertainties. To reduce the variance of these uncertainties a Bayesian updating technique is employed in which the uncertain parameters are treated as calibration parameters, with priors taken as the original uncertainty estimates. Imprecise measurements of aerodynamic forces are used as observational data. Motivation and a concrete application come from a wind-tunnel experiment whose parameters and model geometry have substantial uncertainty. In this case the uncertainty was a consequence of a poorly constructed model in the pre-measurement phase. These methodological uncertainties lead to substantial uncertainties in the measurement of forces. Imprecise geometry measurements from multiple sources are used to create an improved stochastic model of the geometry. Calibration against lift and moment data then gives us estimates of the remaining parameters. The effectiveness of the procedure is demonstrated by prediction of drag with uncertainty

Virtual Shaping on NACA 0015 by Means of a High Momentum Coefficient Synthetic Jet

Results concerning flow control on a NACA 0015 airfoil using high power synthetic jets are presented for low incidences and for Reynolds numbers ranging from 132000 to 425000. The forcing was operated through a spanwise slit positioned near the leading edge at x/c=1.25% or at x/c=10% on the upper surface. Static pressure distribution measurements around the airfoil, wake surveys and smoke flow visualizations were performed. Pressure distributions were significantly modified around the injection location, showing an area of intense suction which increased the lift and strongly affected the drag. Flow visualizations highlighted that the intense suction was due to a virtual shaping effect caused by the formation of a recirculation bubble capable of displacing the streamlines. Low momentum deficits in the wake velocity distributions and, in certain conditions, jet-like flow was observed for the forced cases. Finally, a scaling law relating the bubble size to the forcing intensity is propose

An Efficient Bi-Level Surrogate Approach for Optimizing Shock Control Bumps under Uncertainty

The assessment of uncertainties is essential in aerodynamic shape optimization problems in order to come up with configurations that are more robust. The influence of aleatory fluctuations in flight conditions and manufacturing tolerances is of primary concern when designing shock control bumps, as their effectiveness is highly sensitive to the shock wave location. However, exploring the stochastic design space for the global robust optimum increases the computational cost, especially when dealing with nonconvex design spaces and multiple local optima. The aim of this paper is to develop a framework for efficient aerodynamic shape optimization under uncertainty by means of a bi-level surrogate approach and to apply it to the robust design of a retrofitted shock control bump over an airfoil. The framework combines a surrogate-based optimization algorithm with an efficient surrogate-based approach for uncertainty quantification. The surrogate-based optimizer efficiently finds the global optimum of a given quantile of the drag coefficient. It outperforms traditional evolutionary algorithms by effectively balancing exploration and exploitation through the combination of adaptive sampling and a moving trust region. At each iteration of the optimization, the surrogate-based uncertainty quantification uses an active infill criterion in order to accurately quantify the quantile of the drag at a reduced number of function evaluations. Two different quantiles of the drag are chosen, the 95% to increase the robustness at off-design conditions, and the 50% for a configuration that is best for day to day operations. In both cases, the optimum configurations lead to an airfoil that is more robust to geometrical and operational uncertainties, compared to the configuration obtained through classical deterministic optimization

Central role for MCP-1/CCL2 in injury-induced inflammation revealed by in vitro, in silico, and clinical studies

The translation of in vitro findings to clinical outcomes is often elusive. Trauma/hemorrhagic shock (T/HS) results in hepatic hypoxia that drives inflammation. We hypothesize that in silico methods would help bridge in vitro hepatocyte data and clinical T/HS, in which the liver is a primary site of inflammation. Primary mouse hepatocytes were cultured under hypoxia (1% O 2) or normoxia (21% O2) for 1-72 h, and both the cell supernatants and protein lysates were assayed for 18 inflammatory mediators by Luminex™ technology. Statistical analysis and data-driven modeling were employed to characterize the main components of the cellular response. Statistical analyses, hierarchical and k-means clustering, Principal Component Analysis, and Dynamic Network Analysis suggested MCP-1/CCL2 and IL-1α as central coordinators of hepatocyte-mediated inflammation in C57BL/6 mouse hepatocytes. Hepatocytes from MCP-1-null mice had altered dynamic inflammatory networks. Circulating MCP-1 levels segregated human T/HS survivors from non-survivors. Furthermore, T/HS survivors with elevated early levels of plasma MCP-1 post-injury had longer total lengths of stay, longer intensive care unit lengths of stay, and prolonged requirement for mechanical ventilation vs. those with low plasma MCP-1. This study identifies MCP-1 as a main driver of the response of hepatocytes in vitro and as a biomarker for clinical outcomes in T/HS, and suggests an experimental and computational framework for discovery of novel clinical biomarkers in inflammatory diseases. © 2013 Ziraldo et al

A “Crossomics” Study Analysing Variability of Different Components in Peripheral Blood of Healthy Caucasoid Individuals

Background: Different immunotherapy approaches for the treatment of cancer and autoimmune diseases are being developed and tested in clinical studies worldwide. Their resulting complex experimental data should be properly evaluated, therefore reliable normal healthy control baseline values are indispensable. Methodology/Principal Findings: To assess intra- and inter-individual variability of various biomarkers, peripheral blood of 16 age and gender equilibrated healthy volunteers was sampled on 3 different days within a period of one month. Complex "crossomics'' analyses of plasma metabolite profiles, antibody concentrations and lymphocyte subset counts as well as whole genome expression profiling in CD4(+)T and NK cells were performed. Some of the observed age, gender and BMI dependences are in agreement with the existing knowledge, like negative correlation between sex hormone levels and age or BMI related increase in lipids and soluble sugars. Thus we can assume that the distribution of all 39.743 analysed markers is well representing the normal Caucasoid population. All lymphocyte subsets, 20% of metabolites and less than 10% of genes, were identified as highly variable in our dataset. Conclusions/Significance: Our study shows that the intra- individual variability was at least two-fold lower compared to the inter-individual one at all investigated levels, showing the importance of personalised medicine approach from yet another perspective