Experimental analysis of the pressure–velocity correlations of external unsteady flow over rocket launchers

Based on simultaneous wall pressure and velocity measurements, the aerodynamic load of a launcher body model is investigated. Two different configurations are considered in order to study the influence of geometrical artifacts on the after body flow and consequently on the aerodynamic load. After a brief presentation of the experimental setup used to get the unsteady wall pressure and external velocity field, a global analysis of the integrated pressure along the nozzle is presented for both configurations. It is shown that the unsteady load induced on a configuration with attachment device involves characteristic frequencies which fits the mechanical response of the structure whereas no particular behavior is observed on the configuration without attachment device. Then, a Proper Orthogonal Decomposition is successively performed from the wall pressure field and from the external velocity field highlighting the relationship between the most energetic structures of the flow and the involved phenomenon. Finally, a pressure/velocity correlation of the POD modes is presented and the most energetic structures of the velocity field are linked to the unsteady load observed on the nozzle. It is then confirmed the structural influence of the attachment device and its contribution to the unsteady loads acting on the nozzle.ESA TRP: "Unsteady Subscale Force Measurements within a Launch Vehicle Base Buffeting Environment"

Geometrical regular languages and linear Diophantine equations: The strongly connected case

AbstractGiven an arbitrarily large alphabet Σ, we consider the family of regular languages over Σ for which the deterministic minimal automaton has a strongly connected state diagram. We present a new method for checking whether such a language is semi-geometrical or not and whether it is geometrical or not. This method makes use of the enumeration of the simple cycles of the state diagram. It is based on the construction of systems of linear Diophantine equations, where the coefficients are deduced from the set of simple cycles

Multimodal teaching, learning and training in virtual reality: a review and case study

It is becoming increasingly prevalent in digital learning research to encompass an array of different meanings, spaces, processes, and teaching strategies for discerning a global perspective on constructing the student learning experience. Multimodality is an emergent phenomenon that may influence how digital learning is designed, especially when employed in highly interactive and immersive learning environments such as Virtual Reality (VR). VR environments may aid students' efforts to be active learners through consciously attending to, and reflecting on, critique leveraging reflexivity and novel meaning-making most likely to lead to a conceptual change. This paper employs eleven industrial case-studies to highlight the application of multimodal VR-based teaching and training as a pedagogically rich strategy that may be designed, mapped and visualized through distinct VR-design elements and features. The outcomes of the use cases contribute to discern in-VR multimodal teaching as an emerging discourse that couples system design-based paradigms with embodied, situated and reflective praxis in spatial, emotional and temporal VR learning environments

Stable Perfectly Matched Layers with Lorentz transformation for the convected Helmholtz equation

International audiencePerfectly Matched Layers (PMLs) appear as a popular alternative to non-reflecting boundary conditions for wave-type problems. The core idea is to extend the computational domain by a fictitious layer with specific absorption properties such that the wave amplitude decays significantly and does not produce back reflections. In the context of convected acoustics, it is well-known that PMLs are exposed to stability issues in the frequency and time domain. It is caused by a mismatch between the phase velocity on which the PML acts, and the group velocity which carries the energy of the wave. The objective of this study is to take advantage of the Lorentz transformation in order to design stable perfectly matched layers for generally shaped convex domains in a uniform mean flow of arbitrary orientation. We aim at presenting a pedagogical approach to tackle the stability issue. The robustness of the approach is also demonstrated through several two-dimensional high-order finite element simulations of increasing complexity

GPU-accelerated Convex Multi-phase Image Segmentation

Image segmentation is a key area of research in computer vision. Recent advances facilitated reformulation of the non-convex multi-phase segmentation problem as a convex optimization problem (see for example [2, 4, 9, 10, 13, 16]). Recently, [3] proposed a new convex relaxation approach for a class of vector-valued minimization problems, and this approach is directly applicable to the widely used classical Mumford-Shah segmentation model [11]. While the approach in [3] provides the much deserved convexification, it achieves this at the expense of an increased computational complexity due to the increased dimensionality of the reformulated problem; however, the algorithm proposed in [3] can indeed profit from a parallelized implementation. In this paper, we present a GPU-based implementation of the convex formulation for Mumford-Shah piecewise constant multi-phase image segmentation algorithm proposed in [3]. The main goal of this paper is to provide insights into the way the algorithm has been parallelized in order to obtain good speedup. We present multi-phase segmentation results both on synthetic and real images. The speedup of GPU based implementation is evaluated on three different GPUs. For sufficiently large images, the speedup achieved on GTX 285 GPU is around 40, compared to an optimized CPU implementation. The speedups obtained from GPU-based implementation are quite satisfactory. We also made our CUDA code available online