Turbulent Flow Around Obstacles: Simulation and Study with Variable Roughness

The present work aims to investigate the recirculation and incipient mixing zones in a channel flow supplied with obstacles. The main objective is to develop a new technique to control these recirculation zones by setting a variable roughness. For the purpose of varying that roughness, 4 small bars of heights 0.25H, 0.5H, 0.75H and H were placed downstream of the obstacle; H is the height of the obstacle. For this, a three-dimensional numerical approach was carried out using the ANSYS CFX computer code. In addition, the governing equations were solved using the finite volume method. The K-ω shear-stress transport (SST) turbulence model was utilized to model the turbulent stresses. In the end, we presented the time-averaged simulation results of the contours of the current lines (3D time-averaged streamlines, trace-lines), three components of the velocities: <u> (velocity u contour), <v> (velocity v contour) and <w> (velocity w contour), trace-lines, stream ribbons and mean Q-criterion iso-surface.

Optimum Design of Straight Circular Channels Incorporating Constant and Variable Roughness Scenarios: Assessment of Machine Learning Models

In this study, two machine learning (ML) models named as artificial neural network (ANN) and genetic programming (GP) were applied to design optimum canals with circular shapes. In this application, the earthwork and lining costs were considered as the objective function, while Manning’s equation was utilized as the hydraulic constraint. In this design problem, two different scenarios were considered for Manning’s coefficient: (1) constant Manning’s coefficient and (2) the experimentally proved variation of Manning’s coefficient with water depth. The defined design problem was solved for a wide range of different dimensionless variables involved to produce a large enough database. The first part of these data was used to train the ML models, while the second part was utilized to compare the performances of ANN and GP in optimum design of circular channels with those of explicit design relations available in the literature. The comparison obviously indicated that the ML models improved the accuracy of the circular channel design from 55% to 91% based on two performance evaluation criteria. Finally, application of the ML models to optimum design of circular channels demonstrates a considerable improvement over the explicit design equations available in the literature.

Visualisation of different harmonisations varying in mode, consonance & dissonance

Visual associations with auditory stimuli have been the subject of numerous studies. Colour, shape, size, and several other parameters have been linked to musical elements like timbre and pitch. In this paper we aim to examine the relationship between harmonisations with varying degrees of dissonance and visual roughness. Based on past research in which high sensory dissonance was associated with angular shapes, we argued that non-tonal and highly dissonant harmonisations will be associated with angular and rough images, while more consonant stimuli will be associated with images of low visual roughness. A fixed melody was harmonised in 7 different styles, including highly tonal, non-tonal, and random variations. Through a listening task, musically trained participants rated the stimuli in terms of enjoyment, familiarity, and matched them to images of variable roughness. The overall consonance of the stimuli was calculated using two distinct models (Wang et al., 2013; Harrison &amp; Pearce, 2020) and a variant of the aggregate dyadic consonance index (Huron, 1994). Our results demonstrate that dissonance, as calculated by all models, was highly correlated with visual roughness, and enjoyment and familiarity followed expected patterns compared to tonal and non-tonal stimuli. In addition to sensory dissonance, however, it appears that other factors, such as the typicality of chord progressions and the sense of tonality may also influence this cross-modal interaction.

Cross-Modal Associations Between Harmonic Dissonance and Visual Roughness

Visual associations with auditory stimuli have been the subject of numerous studies. Colour, shape, size, and several other parameters have been linked to musical elements like timbre and pitch. In this article, we aim to examine the relationship between harmonisations with varying degrees of dissonance and visual roughness. Based on past research in which high sensory dissonance was associated with angular shapes, we argued that nontonal and highly dissonant harmonisations will be associated with angular and rough images, while more consonant stimuli will be associated with the images of low visual roughness. A fixed melody was harmonised in 7 different styles, including highly tonal, nontonal, and random variations. Through a listening task, musically trained participants rated the stimuli in terms of enjoyment, familiarity, and matched them to images of variable roughness. The overall consonance of the stimuli was calculated using two distinct models (Harrison & Pearce, 2020; Wang et al., 2013 ) and a variant of the aggregate dyadic consonance index ( Huron, 1994 ). Our results demonstrate that dissonance, as calculated by all models, was highly correlated with visual roughness, and enjoyment and familiarity followed expected patterns compared to tonal and nontonal stimuli. In addition to sensory dissonance, however, it appears that other factors, such as the typicality of chord progressions and the sense of tonality may also influence this cross-modal interaction.

Wave Forecasting in Shallow Water: A New Set of Growth Curves Depending on Bed Roughness

Forecasting relationships have been recognized as an important tool to be applied together, or not, with complete numerical modelling in order to reconstruct the wave field in coastal areas properly when the available wave data is limited. In recent years, the literature has offered several comprehensive sets of field experiments investigating the form of the asymptotic, depth-limited wind waves. This has made it possible to reformulate the original deep water equations, taking into account the effects of water depth, if wind waves are locally generated in shallow and confined basins. The present paper is an initial attempt to further contribute to the shallow water forecasting curves which are currently available, also considering the role on the wave generation of a variable equivalent bottom roughness. This can offer the possibility of applying shallow growth curves to a broad variety of contexts, for which bed composition and forms can be different. Simple numerical tests have been conducted to reproduce the fully developed conditions of wave motion with variable roughness values. To validate the new set of equations, they have been applied to a real shallow lake for which both experimental and numerical wave data is available. The comparison of the obtained results is very encouraging in proceeding with this approach.

Zero-Coupon, Forward, and Par Yield Curves for the Nigerian Bond Market

The Nigerian bond market is currently one of the most liquid in sub-Saharan Africa. Many African countries regard it as a model from which to learn and based on which to develop their respective bond markets. The developments achieved in the Nigerian bond market are of particular interest to both investors and fixed income analysts—both domestic and international. One of the important tools required for fixed income analysis, pricing, and trading is the yield curve. To the best of our knowledge, even though the Nigerian bond market has a secondary market yield curve, the yield curve is a yield-to-maturity curve, and not zero-coupon yield curve. The purpose of this study is to model the zero-coupon, par, and forward yield curves for the Nigerian bond market. We use various methods such as the piecewise cubic Hermite method, the piecewise cubic spline method (with not-a-knot end condition), the Nelson–Siegel–Svensson method, and the variable roughness penalty method. Data are obtained from the FMDQ OTC website. The results show that the piecewise cubic Hermite method is very suitable for producing the Nigerian par and zero-coupon yield curves. Our best recommended method for producing the Nigerian zero-coupon yield curve is therefore the piecewise cubic Hermite method, followed by the Nelson–Siegel–Svensson method. For the forward yield curve, the results show that the best method is the Nelson–Siegel–Svensson method, followed by the variable roughness penalty method.

Numerical Simulation of Shear Behavior and Permeability Evolution of Rock Joints with Variable Roughness and Infilling Thickness

The mechanical properties and permeability evolution of sand-infilled rock joints during the shear process is an important issue in rock engineering, such as it pertains to hydraulic fractures filled with proppant. Shear can disrupt the preexisting hydraulic and mechanical equilibrium conditions, thus affecting fluid flow. In this study, we simulate the shear behavior of rock joints with variable roughness and sand infilling thickness using the discrete element code PFC2D. Rock joint roughness is evaluated by the joint roughness coefficient (JRC), and sand infilling thickness is evaluated by a thickness ratio (i.e., ratio of infill thickness to rock height) ranging from 0.02 to 0.20. The results show that peak shear strength decreases with the thickness ratio in a relation that can be expressed by a hyperbolic function. We also measure the permeability evolution during shearing and find that the permeability of infilled rock joints increases with both the thickness ratio and JRC.