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Introduction : Au Sud-Kivu, en République démocratique du Congo, le système de santé est sous-financé dû à de nombreuses contraintes. Plusieurs initiatives ont été testées mais restent insuffisantes pour augmenter et pérenniser le financement de la santé.But de l’étude : Analyser le système de financement de la santé au Sud-Kivu, par une cartographie et une analyse quantitative et qualitative des mécanismes de financement.Résultats : Le système de financement de la santé de la province est fragmenté, avec des mécanismes et interventions peu coordonnés, suscitant des duplications d’activités d’appui au système de santé, en plus de la quasi-absence de mécanisme de mise en commun des appuis extérieurs. Le recouvrement des coûts et les financements extérieurs sont les mécanismes les plus utilisés alors que l’État contribue très faiblement au financement du système provincial de santé. Les mutuelles de santé sont censées améliorer l’accès aux soins, mais leur taux de couverture reste extrêmement faible. Le financement basé sur les résultats et la gratuité des soins, intégralement compensés par les donateurs extérieurs, sont irréguliers et insuffisamment pérennes.Conclusions : Il serait essentiel d’adopter au Sud-Kivu un modèle d’achat stratégique, ancré dans les institutions locales, approprié par l’ensemble des parties prenantes, qui intègre l’ensemble des mécanismes de financement existants et qui soit appuyé par un fonds commun d’appui au système provincial de santé. L’initiative du Contrat unique développée pour harmoniser, mettre en commun et pérenniser les programmes extérieurs peut servir de base pour élaborer un tel modèle. Ceci impliquerait de renforcer le dialogue politique, d’élaborer un dossier d’investissement pour soutenir la mobilisation des ressources et de créer une plateforme conjointe de suivi et d’évaluation des décaissements, pilotée par les autorités provinciales de santé., SCOPUS: ar.j, info:eu-repo/semantics/published

Insect wings can undergo significant deformation during flapping motion owing to inertial, elastic and aerodynamic forces. Changes in shape then alter aerodynamic forces, resulting in a fully coupled Fluid-Structure Interaction (FSI) problem. Here, we present detailed three-dimensional FSI simulations of deformable blowfly (Calliphora vomitoria) wings in flapping flight. A wing model is proposed using a multi-parameter mass-spring approach, chosen for its implementation simplicity and computational efficiency. We train the model to reproduce static elasticity measurements by optimizing its parameters using a genetic algorithm with covariance matrix adaptation (CMA-ES). Wing models trained with experimental data are then coupled to a high-performance flow solver run on massively parallel supercomputers. Different features of the modeling approach and the intra-species variability of elastic properties are discussed. We found that individuals with different wing stiffness exhibit similar aerodynamic properties characterized by dimensionless forces and power at the same Reynolds number. We further study the influence of wing flexibility by comparing between the flexible wings and their rigid counterparts. Under equal prescribed kinematic conditions for rigid and flexible wings, wing flexibility improves lift-to-drag ratio as well as lift-to-power ratio and reduces peak force observed during wing rotation.

The proper orthogonal decomposition (POD) is a powerful classical tool in fluid mechanics used, for instance, for model reduction and extraction of coherent flow features. However, its applicability to high-resolution data, as produced by three-dimensional direct numerical simulations, is limited owing to its computational complexity. Here, we propose a wavelet-based adaptive version of the POD (the wPOD), in order to overcome this limitation. The amount of data to be analyzed is reduced by compressing them using biorthogonal wavelets, yielding a sparse representation while conveniently providing control of the compression error. Numerical analysis shows how the distinct error contributions of wavelet compression and POD truncation can be balanced under certain assumptions, allowing us to efficiently process high-resolution data from three-dimensional simulations of flow problems. Using a synthetic academic test case, we compare our algorithm with the randomized singular value decomposition. Furthermore, we demonstrate the ability of our method analyzing data of a 2D wake flow and a 3D flow generated by a flapping insect computed with direct numerical simulation., Comment: The algorithm can be found as a post processing tool in the open source software package wabbit (https://github.com/adaptive-cfd/WABBIT). Please note, that this paper is a working paper and is not reviewed yet. It was submitted to ACOM Journal at the 10th of November 2020

We present a wavelet-based adaptive method for computing 3D multiscale flows in complex, time-dependent geometries, implemented on massively parallel computers. While our focus is on simulations of flapping insects, it can be used for other flow problems, including turbulence, as well. The incompressible fluid is modeled with an artificial compressibility approach in order to avoid solving elliptical problems. No-slip and in/outflow boundary conditions are imposed using volume penalization. The governing equations are discretized on a locally uniform Cartesian grid with centered finite differences, and integrated in time with a Runge--Kutta scheme, both of 4th order. The domain is partitioned into cubic blocks with equidistant grids with different resolution and, for each block, biorthogonal interpolating wavelets are used as refinement indicators and prediction operators. Thresholding the wavelet coefficients allows to generate dynamically evolving grids, and an adaption strategy tracks the solution in both space and scale. Blocks are distributed among MPI processes and the global topology of the grid is encoded using a tree-like data structure. Analyzing the different physical and numerical parameters allows balancing their individual error contributions and thus ensures optimal convergence while minimizing computational effort. Different validation tests score accuracy and performance of our new open source code, WABBIT (Wavelet Adaptive Block-Based solver for Interactions with Turbulence), on massively parallel computers using fully adaptive grids. Flow simulations of flapping insects demonstrate its applicability to complex, bio-inspired problems.