Experimental analysis of the performance of fractal stirrers for impinging jets heat transfer enhancement

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.A new passive method for the heat transfer enhancement of circular impinging jets is proposed and tested. The method is based on enhancing the mainstream turbulence of impinging jets using square fractal grids, i.e. a grid with a square pattern repeated at increasingly smaller scales. Fractal grids can generate much higher turbulence intensity than regular grids under the same inflow conditions and with similar blockage ratio, at the expense of a slightly larger pressure drop. An experimental investigation on the heat transfer enhancement achieved by impinging jets with fractal turbulence promoters is carried out. The heated-thin foil technique is implemented to measure the spatial distribution of the Nusselt number on the target plate. The heat transfer rates of impinging jets with a regular grid and a fractal grid insert are compared to that of a jet without any turbulator under the same condition of power input. A parametric study on the effect of the Reynolds number, the nozzle-to-plate distance and the position of the insert within the nozzle is carried out. The results show that a fractal turbulence promoter can provide a significant heat transfer enhancement for relatively small nozzle-to-plate separation (at distance equal to 2 diameters 63% increase with respect to the circular jet at the stagnation point, and 25% if averaged over an area of radius equal to 1 nozzle diameter; respectively, against 9% and 6% of the regular grid in the same conditions of power input).dc201

The role of "localness" in sustainable food consumption: insights from sustainable coffee in Thailand

Purpose: We investigated consumers’ environmental, social, and local beliefs and their impact on attitudes, subjective norms, and willingness to pay for sustainable coffee in the understudied context of Thailand. Design: The study is based on a survey of 253 Thai consumers, analysed through an extended model of the Theory of Planned Behaviour (TPB). Findings: The study validates the TPB model in the Thai demographic, finding a significant positive impact of environmental and local beliefs and subjective norms on willingness to pay for sustainable coffee. More importantly, it proposes an extended model of TPB, stressing the central role of ‘local beliefs’ in sustainable consumption in a Global South context. Originality: This study demonstrates the importance of ‘localness’ in the practice of sustainable consumption in Thailand, namely the beliefs in the support for the local economy and prosperity for the local community. This expands our understanding of the heterogeneous meanings associated with the practice of sustainable consumption in a South-East Asian context

Sensing the turbulent large-scale motions with their wall signature

This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.This work has been partially supported by Grant No. DPI2016-79401-R funded by the Spanish State Research Agency (SRA) and the European Regional Development Fund (ERDF). A.G. acknowledges Dr. A. Sánchez for insightful discussions about CNN architecture. The authors acknowledge Dr. R. Vinuesa for insightful comments and discussions

3D Fluid Flow Estimation with Integrated Particle Reconstruction

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view video in two separate steps, utilizing either a pure Eulerian or pure Lagrangian approach. Eulerian methods perform a voxel-based reconstruction of particles per time step, followed by 3D motion estimation, with some form of dense matching between the precomputed voxel grids from different time steps. In this sequential procedure, the first step cannot use temporal consistency considerations to support the reconstruction, while the second step has no access to the original, high-resolution image data. Alternatively, Lagrangian methods reconstruct an explicit, sparse set of particles and track the individual particles over time. Physical constraints can only be incorporated in a post-processing step when interpolating the particle tracks to a dense motion field. We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization. Our hybrid Lagrangian/Eulerian model reconstructs individual particles, and at the same time recovers a dense 3D motion field in the entire domain. Making particles explicit greatly reduces the memory consumption and allows one to use the high-res input images for matching. Whereas the dense motion field makes it possible to include physical a-priori constraints and account for the incompressibility and viscosity of the fluid. The method exhibits greatly (~70%) improved results over our recently published baseline with two separate steps for 3D reconstruction and motion estimation. Our results with only two time steps are comparable to those of sota tracking-based methods that require much longer sequences.Comment: To appear in International Journal of Computer Vision (IJCV

Adverse-Pressure-Gradient Effects on Turbulent Boundary Layers: Statistics and Flow-Field Organization

This manuscripts presents a study on adverse-pressure-gradient turbulent boundary layers under different Reynolds-number and pressure-gradient conditions. In this work we performed Particle Image Velocimetry (PIV) measurements supplemented with Large-Eddy Simulations in order to have a dataset covering a range of displacement-thickness-based Reynolds-number 2300 34000 and values of the Clauser pressure-gradient parameter beta up to 2.4. The spatial resolution limits of PIV for the estimation of turbulence statistics have been overcome via ensemble-based approaches. A comparison between ensemble-correlation and ensemble Particle Tracking Velocimetry was carried out to assess the uncertainty of the two methods. The effects of beta, R e and of the pressure-gradient history on turbulence statistics were assessed. A modal analysis via Proper Orthogonal Decomposition was carried out on the flow fields and showed that about 20% of the energy contribution corresponds to the first mode, while 40% of the turbulent kinetic energy corresponds to the first four modes with no appreciable dependence on beta and R e within the investigated range. The topology of the spatial modes shows a dependence on the Reynolds number and on the pressure-gradient strength, in line with the results obtained from the analysis of the turbulence statistics. The contribution of the modes to the Reynolds stresses and the turbulence production was assessed using a truncated low-order reconstruction with progressively larger number of modes. It is shown that the outer peaks in the Reynolds-stress profiles are mostly due to large-scale structures in the outer part of the boundary layer.CSV acknowledges the financial support from Universidad Carlos III de Madrid within the program “Ayudas para la Movilidad del Programa Propio de Investigación”. RÖ, RV and PS acknowledge the financial support from the Swedish Research Council (VR) and the Knut and Alice Wallenberg Foundation. CSV, SD and AI were partially supported by the COTURB project (Coherent Structures in Wall-bounded Turbulence), funded by the European Research Council (ERC), under grant ERC-2014.AdG-669505. CSV, SD and AI have been partially supported by Grant DPI2016-79401-R funded by the Spanish State Research Agency (SRA) and European Regional Development Fund (ERDF)