Numerical Simulation of Turbulent Flow Through a Straight Square Duct

Turbulent duct flows are investigated using large eddy simulation at bulk Reynolds numbers, from 4410 to 250,000. Mean secondary flow is found to reveal the existence of two streamwise counter-rotating vortices in each corner of the duct. Turbulence-driven secondary motions that arise in duct flows act to transfer fluid momentum from the centre of the duct to its corners, thereby causing a bulging of the streamwise velocity contours towards the corners. As Reynolds number increases, the ratio of centreline streamwise velocity to the bulk velocity decreases and all turbulent components increase. In addition, the core of the secondary vortex in the lower corner-bisector tends to approach the wall and the corner with increasing Reynolds number. The turbulence intensity profiles for the low Reynolds number flows are quite different from those for the high Reynolds number flows. Typical turbulence structures in duct flows are found to be responsible for the interactions between ejections from wall and this interaction results in the bending of the ejection stems, which indicates that the existence of streaky wall structures is much like in a channel flow

On Predicting The Turbulence-induced Secondary Flows Using Nonlinear K-∈ Models

Low turbulent Reynolds number direct simulation data are used to calculate the invariants of the Reynolds stress and the turbulent dissipation rate in a square duct. The results show that, depending on the region where the analysis is carried out, the turbulent flow field comes close to one-, two-, and three-component states. Modeling such flows - even at higher Reynolds numbers - will require models that can approach all three states. A number of related nonlinear k-∈ models are tested a priori using the direct simulation data. The numerical simulation using Reynolds averaged Navier-Stokes equations with these models was performed. Their ability to predict the secondary flows, with a low-Reynolds k-∈ model, cannot be gauged from realizability. © 1996 American Institute of Physics.8718561868Speziale, C.G., Analytical methods for the developments of Reynoldsstress closures in turbulence (1991) Annu. Rev. 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Fluid Mech., 233, p. 369Bradshaw, P., Blair Perot, J., A note on turbulent energy dissipation in viscous wall region (1993) Phys. Fluids, 5, p. 3305Kim, J., Moin, P., Moser, R., Turbulent statistics in fully developed channel flow at low Reynolds number (1987) J. Fluid Mech., 177, p. 133Tennekes, H., Lumley, J.L., (1972) A First Course in Turbulence, , MIT Press, Cambridge, MALumley, J.L., Computational Modeling of Turbulent Flows (1978) Advances in Applied Mechanics, 18, p. 123. , Academic Press. New YorkGavrilakis, S., Large-scale structures in the turbulent flow near a right-angled corner (1994) 1st ERCOFTAC Workshop on Direct and Large-Eddy Simulation, , SurreyGessner, F.B., The origin of secondary flow in turbulent flow along a corner (1973) J. Fluid Mech., 58, p. 1Speziale, C.G., The dissipation rate correlation and turbulent secondary flows in noncircular ducts (1986) Trans. Am. Soc. Mech. Eng. J. Fluid Eng., 108, p. 118Durbin, P.A., Near-wall turbulence closure modeling without damping functions (1991) Theor. Comput. Fluid Dyn., 3, p. 1Rodi, W., Mansour, N.N., Low Reynolds number k-∈ modeling with the aid of direct simulation (1993) J. Fluid Mech., 250, p. 509Mompean, G., Three-equation turbulence model for prediction of the mean square temperature variance in grid-generated flows and round jets (1994) Int. J. Heat Mass Transfer, 37, p. 1165Chien, K.Y., Prediction of channel and boundary-layer flows with a low-Reynolds-number turbulence model (1982) AIAA J., 20, p. 33Lam, C.K.G., Bremhorst, K., A modified form of the k-∈ model predicting wall turbulence (1981) Trans. Am. Soc. Mech. Eng. J. Fluid. Eng., 103, p. 456Reynolds, W.C., Computation of turbulent flows (1976) Annu. Rev. Fluid Mech., 8, p. 183Lindberg, P.A., (1994), private communicationNisizima, S., A numerical study of turbulent square-duct flow using an anisotropic k-∈ model (1990) Theor. Comput. 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Characterisation of marginally turbulent square duct flow

Proceedings of the 11th EUROMECH European Turbulance Conference, June 25-28, 2007 Porto, PortugalDepto. de Análisis Matemático y Matemática AplicadaFac. de Ciencias MatemáticasTRUEpu

Direct Numerical Simulation of the Flow in a Lid-Driven Cubical Cavity

Direct numerical simulation of the flow in a lid-driven cubical cavity has been carried out at a Reynolds number above 10 000. Both transient and steady-in-the-mean states of the flow posses long time scales requiring long integration times. A large fraction of the total kinetic energy and dissipation is concentrated in the near-lid mean flow. The flow over most of the domain is laminar with distinct wall-jet profiles found in three of the walls. The high momentum fluid near the lid transmits its energy into a downflowing nonparallel wall jet which separates ahead of the bottom wall. From the collision of this separated layer against the bottom wall two wall jets emerge. In this process the energy lost to turbulence by the impingement is partly recovered by the emerging wall jets. (C) 2000 American Institute of Physics. [S1070-6631(00)01206-X]

Strategic renewal through social media marketing : An exploratory study of challenges and opportunities of companies in Swedish rural areas

Background Social media have changed the way of communication and interaction between the organizations and the costumers. The huge merge of social media has led the companies to change their current marketing strategies into the use of social media marketing during the last years. An increasing number of companies adopt this kind of performance and there is a need to study this phenomenon more in depth and explore it through the perspective of strategic renewal. Purpose The purpose of this thesis is to analyze and explore to the phenomenon of strategic renewal through social media marketing. The authors will explore into the challenges and opportunities of strategic renewal through social media marketing in companies located in Swedish rural areas. Method Social media marketing is considered a new phenomenon. The studies held, do not examine social media marketing through a strategic renewal perspective and how rural area companies located in rural areas in Sweden face the challenges and opportunities occurred. Therefore, an abductive approach and case study method were chosen for this research. 7 companies were chosen as the interviewed companies. Within this research primary data were collected through semi- structured interviews with the investigated companies. Conclusion The authors have found that, the interviewed companies pursue strategic renewal through social media marketing, but they do not consider this strategy as the main one but as a complementary one. As a result, certain challenges are emerged, and the investigated companies should face and integrate them to the opportunities generated from this kind of strategic renewal. This will lead to a better performance of the companies since pursuing strategic renewal through social media marketing can help in every factor of the company making them competitive and able to stand out

The impact of heuristic and herding biases on portfolio construction and performance: the case of Greece

PurposeThe purpose of this paper is to identify whether heuristic and herding biases influence portfolio construction and performance in Greece. The current research determines the situation among investors in Greece, a country with several economic problems for the last decade.Design/methodology/approachA survey has been conducted covering a group of active private investors. The relationship between private investors' behavior and portfolio construction and performance was tested using a multiple regression.FindingsThe authors find that heuristic variable affects private investor's portfolio construction and performance satisfaction level positively. A robustness test on a second group, consisting of professional investors, reveals that heuristic and herding biases affect investment behavior when constructing a portfolio.Practical implicationsThe authors recommend investors to select professional's investment portfolio tools in constructing investment portfolios and avoid excessive errors, which occur due to heuristic. The awareness and understanding of heuristic and herding could be helpful for professionals and decision-makers in financial institutions by improving their performance resulting in more efficient markets.Originality/valueThe main contribution of this paper lies in the fact that it is the first study on two major behavioral dimensions that affect the investor's portfolio construction and performance in Greece. The rationale of the current research is that the results are helpful for investors in order to take rational, reliable and profitable decisions.</jats:sec

ESG performance, herding behavior and stock market returns: evidence from Europe

AbstractThis paper tests how financial performance indicators and combined ESG score for large-cap stocks impact on stock return. In particular, we examine how market capitalization, price to book value, Sharpe ratio and ESG score of large-cap firms in Europe are related to their stock performance. We consider a panel data consisting of six European countries—Portugal, Italy, Greece, Spain, France and Germany—for the period 2010–2020. For Greek and French firms, a firm’s size tends to negatively affect its stock returns. The investors in European countries (except Italy) do not jeopardize their returns by investing in highly ESG scoring firms. We argue that the benefit of not investing in highly ESG-scoring firms might lead investors to select smaller size companies with a higher price to book value and higher Sharpe ratio, as it is more likely to generate higher returns. Moreover, Italian firms are more susceptible to ESG issues, as ESG performance and stock return seem to have a significant negative correlation. This valuable result was confirmed by conducting a robustness test for Europe as a whole using the Euronext100 index. Finally, we find no evidence that ESG motivates herding in our selected sample (this is not the case for Greece and France), while we report evidence of ESG herding behavior during the Covid-19 outbreak in Portugal, Italy and Greece.</jats:p