Clear-water scour at long skewed bridge piers

Abstract

The results of an experimental study on clear-water scour at long skewed rectangular piers under steady flows at threshold velocity are presented. The scour mechanisms due to skewness effects with a wide range of angle of attack, α, and two sizes of uniform cohesionless bed sediment (d₅₀ = 0.23 and d₅₀ = 0.80 mm) have been investigated in a 50-m-long, 1.5-m-wide, and 2.0-m-deep flume. Empirical relation to demonstrate the effects of skewness in terms of dimensionless variables, such as aspect ratio (L/b), the angle of attack (α), flow shallowness (y/B_α), sediment coarseness (B_α/d₅₀), the sediment gradation coefficient (σ_g), on scour depth is presented. The empirical relation is focused on predicting the angle of attack factor, K_α. The experimental data obtained in this study and data available from the literature were used to validate the predictions of existing methods and the accuracy of the proposed method. The proposed method gives reasonable scour depth predictions and was verified with statistical methods where the mean error was reduced from 53.6 to 18.1%.     

Object detetion and image segmentation using texture pressure energy in parametric active contour models

Abstract

In recent years, Active Contour Models (ACMs) have become powerful tools for object detection and image segmentation in computer vision and image processing applications. This paper presents a new energy function in parametric active contour models for object detection and image segmentation. In the proposed method, a new pressure energy called “texture pressure energy” is added to the energy function of the parametric active contour model to detect and segment a textured object against a textured background. In this scheme, the texture features of the contour are calculated by a moment based method. Then by comparing these features with texture features of the object, the contour curve is expanded or contracted in order to be adapted to the object boundaries. Experimental results show that the proposed method has more efficient and accurate segmenting functionality than the traditional method when both object and background have texture properties.     

Deep underwater image enhancement through colour cast removal and optimization algorithm

ABSTRACT

Blue–green colour cast effect and low contrast are common problems suffered by deep underwater images. This paper introduces a new method which consists of two major steps: red channel correction based on green and blue channels (RCCGB), and simultaneous contrast stretching and mean pixel enhancement (SCSMPE). The RCCGB is designed to minimize the effect of blue–green illumination. This step considers the differences between the red channel and other channels in terms of total pixel values. The second major step, SCSMPE is specifically designed to perform contrast stretching and improve the mean pixel value simultaneously through particle swarm optimization (PSO). Based on the visual observation, the proposed method significantly reduces the effect of the blue–green colour cast and improves the image contrast. Furthermore, the average quantitative values for 300 underwater images also demonstrate the superiority of the proposed method.     

Hydrogen sensing using gold nanoclusters supported on tungsten trioxide thin films

Controlled amounts of chemically synthesised gold (Au) nanoclusters were deposited onto tungsten trioxide (WO₃) nanostructured thin films as sensors for hydrogen. The Au/WO₃ thin films were characterised by XPS, XRD, SEM and TEM. Performance of Au/WO₃ films was tested at operating temperatures varying from room temperature to 450 °C. It was demonstrated that Au metal loading plays an important role in defining enhancement of the sensor response towards hydrogen. “Less is more” principle applies to the reported here sensors as materials made using lower concentration of Au nanoclusters demonstrated significantly better response. HRTEM images of the Au/WO₃ thin films provide evidence that the more active sensors are enriched with smaller Au nanoparticles (≤5 nm). Fast response towards H₂ within a wide range of industrially relevant concentrations, excellent baseline stability and signal reproducibility at optimized operating temperature demonstrate feasibility of this novel approach toward fabrication of sensors.     

Candidates for Laser Fusion Energy with Minimized Radioactivity

The new candidates for laser fusion energy with minimized radioactivity were presented. The possibility of side-on laser ignition of H–¹¹B with negligible radioactivity encouraged to study the fusion of solid state H–⁷Li fuel which again turns out to be only about ten times more difficult than the side-on ignition of solid deuterium–tritium using petawatt-picosecond laser pulses at anomalous interaction conditions if very high contrast ratio. Updated cross sections of the nuclear reaction are included. In other words, the specific approach discussed here involves inducing a fusion burn wave without radioactivity by laser-driven impact of a relatively large block of plasma on the outside of a solid density H–¹¹B and H–⁷Li targets.     

Simulation of Cold Rolled Steel Coil Heating during Batch Annealing Process

Cold rolled coils are subjected to the annealing process in order to improve their formability and mechanical properties. A mathematical model of thermal behavior of coils during the heating cycle has been developed. Based on experimental data from several tests, the accuracy of the model has been confirmed. This model enables us to determine the coldest point of coils and the end time of furnace operation. Furthermore, the model has been used to analyze the effect of strip thickness on the heating time required. Thinner strips lead to prolonged heating time and larger temperature differences within the coil.     

Discharge Coefficients and Heat Transfer for Axisymmetric Supersonic Nozzles

Computational fluid dynamics (CFD) analysis was used to compute effective nozzle discharge coefficients for subscale sharp-edged converging/diverging nozzles, with a variety of convergence half-angles, motor operating conditions, and two propellants with different ballistics. Convergence half-angles ranged from 10° to 90°. Analysis was conducted at total temperatures from 2,946 K (5303°R) to 3,346 K (6023°R) and total pressures ranging from 2.72 MPa (395 psia) to 20.68 MPa (3,000 psia). Area ratios (A e /A*) ranged from 7.43 to 9.39. Ratio of specific heats ( n ) ranged from 1.13 to 1.18. The maximum throat and exit Reynolds' numbers based on axial diameter ranged from 6.73 2 105 to 3.61 2 106 and 3.26 2 105 to 1.99 2 106, respectively. Present results of nozzle discharge coefficients are reported and correlated as a function of nozzle convergence half-angle ( / c ), area ratios (A e /A*), and pressure ratio (P o /P X ) for a constant divergence half-angle ( / d ) of 15°. Computed discharge coefficients ranged from 0.88 to 0.97. They are compared with theory and experimental data available in the literature. Available turbulence models with respect to grid refinements and heat transfer are discussed. Heat transfer is calculated from a modified Reynolds' analogy for laminar flow over a flat plate, the Dittus - Boelter correlation for fully developed turbulent pipe flow, and the Bartz correlation for nozzle flows, and the results are compared with available experimental data.     

Fault detection of wind energy conversion systems using recurrent neural networks

Structure of wind energy conversion systems (WECSs) must be robust against faults. In order to accurately study WECSs during occurrence of faults and to explore the impact of faults on each component of the WECSs, a detailed model is required in which both mechanical and electrical parts of the WECSs are properly involved. In addition, a fault detection system (FDS) is required to diagnose the occurred faults at the appropriate time in order to ensure a safe system operation, avoid heavy economic losses, prevent damage to adjacent relevant systems and facilitate timely repair of failed components. This can be performed by subsequent actions through fast and accurate detection of faults. In this paper, by utilising a comprehensive dynamic model of the WECS, an FDS is presented using dynamic recurrent neural networks. In industrial processes, dynamic neural networks are known as a good mathematical tool for fault detection. The proposed FDS detects faults of the generator's angular velocity sensor, pitch angle sensors and pitch actuators. The presented FDS has high capability of fault detection in short time and it has much low false alarms rate. Simulation results verify validity and usefulness of the proposed fault detection scheme.     

Influence of process variables and formulation composition on sphericity and diameter of Ca-alginate-chitosan liquid core capsule prepared by extrusion dripping method

ABSTRACT

The influence of process variables and formulation composition on the sphericity and diameter of the alginate capsules which contained dual cations (Ca-and-chitosan) are characterized in this study. Capsule sphericty was not influenced by needle diameter but instead, capsule diameter increased proportionally with the needle diameter. The combined effects of the liquid core solution and alginate solution on the sphericity of the capsules are tabulated. Spherical capsules can be produced when the following criteria were fulfilled: stirring speed is in the range of 240–300 rpm; calcium chloride concentration is >5 g/L; viscosity of liquid core solution is >203 mPa.s; as well as viscosity of alginate solution is in between 47 and 386 mPa.s. The capsule diameter was predicted using a modified Tate’s law equation and an error analysis was conducted to evaluate the equation. The predicted diameter was well correlated with the experimental data with an average absolute deviation <3.6%.     

Characterization of Biogenic Silica Generated by Thermo Chemical Treatment of Rice Husk

This study presents two routes to produce amorphous silica from an Egyptian rice husk under conditions optimized for least environmental impact and low cost. The first route includes thoroughly washing of the husk sample with water, dry milling and leaching with citric acid. The leaching process was applied in two stages, that is, at 323 K for 180 min and then at 353 K for 60 min. After washing and drying, the leached sample was subjected to a heat treatment in a muffles furnace at four sequential steps. The second route includes all the previously mentioned steps, except the citric acid leaching. The final products were characterized using x-ray fluorescence analysis, carbon content analysis, x-ray diffraction, differential thermal analysis, nitrogen adsorption, mercury intrusion, and scanning electron microscopy. The results show that the citric acid leaching has many advantages with respect to silica yield and porosity as well.