Shape Optimization to Reduce Wind Pressure on the Surfaces of a Rectangular Building with Horizontal Limbs

The present study consists of shape optimization of a rectangular plan shaped tall building with horizontal limbs under wind attack, which would minimize the wind pressure on all the faces of the building model simultaneously. For the purpose, the external pressure coefficients on different faces of the building (Cpe) are selected as the objective functions. The position of the limbs and the wind incidence angle are taken as design variables. The design of experiment (DOE) is done using random sampling. The values of the objective functions are obtained by using Computational Fluid Dynamics method of simulated wind flow at each design point. The building model has a constant plan area 22500 mm2. The length and velocity scales are taken as 1:300 and 1:5, respectively. The results are used to construct the surrogate models of the objective functions using Response Surface Approximation method. The optimization study is done using the Multi-Objective Genetic Algorithm. The building shapes corresponding to the Pareto optimal decision variables are shown. The function values corresponding to the decision variables are verified by further introducing a CFD study

Unlocking the Secrets of Bird Conservation through Ringing: A Review

Bird ringing, a widely employed technique for marking and studying birds, plays a crucial role in bird conservation. As the human population increases and natural habitats are threatened, birds face numerous challenges that necessitate effective conservation efforts. This paper examines the significance of bird ringing in gathering vital data for conservation and outlines the process and benefits of this technique. Bird ringing provides essential information for understanding bird populations and their behaviours. By capturing and marking birds, researchers can collect data on demographics, habitat usage, feeding patterns, and breeding seasons. Advanced techniques, such as radio-labelled rings, enable tracking of bird movements and migration routes. Through ringing, researchers can examine diseases, assess the presence of microorganisms that may impact both bird and human health and contribute to the understanding of bird-related biosecurity. The process of bird ringing involves careful capture and handling of birds using various techniques tailored to different species and habitats. Rings made of appropriate materials are applied to the birds for identification purposes. Thus, bird ringing is valuable for gathering critical data on bird populations, behaviour, and health, contributing significantly to bird conservation and sustainability. By providing insights into migration patterns, habitat usage, and health status, bird ringing enables conservationists to make informed decisions and implement effective measures to protect bird species and their habitats. Continued research and collaboration in the field of bird ringing are essential for the long-term preservation of avian biodiversity and the maintenance of healthy ecosystems

Prognosis of Wind-tempted Mean Pressure Coefficients of Cross-shaped Tall Buildings Using Artificial Neural Network

The present paper focuses on the study of wind-induced responses of cross-plan shaped tall buildings. Initially, three parametric building models are studied for the purpose with a constant plan area 22500 mm2. The length and velocity scales are taken as 1:300 and 1:5, respectively. Wind angle of attack (WAA) is considered from 0° to 330° with an increment of 30°. At first, the external surface pressure coefficients (Cp) at different faces of the models are carried out for different wind occurrence angles employing Computational Fluid Dynamics method of simulated wind flow. Again, Fast Fourier Transform (FFT) fitted expressions as the sine and cosine function of WAA are proposed for attaining mean wind pressure coefficient on the building faces. The accuracy of the Fourier series expansions is justified by presenting histograms of sum square error (SSE), R2 value and root mean square error (RMSE). The results are also compared by training Artificial Neural Networks (ANN). Training is continued till Regression (R) values are more than 0.99 and Mean Squared Error (MSE) tends to 0, ensuring a close relationship among the outputs and targets. The face-wise value of (Cp) obtained using all three methods, are plotted. The error histograms of the ANN models show that the fitting data errors are spread within a reasonably good range. It is observed that the deviation in the result is not more than 5% in any case. Finally, the ANN predictions are presented for nine parametric models to cover a wide range of possible cross-shaped buildings

Synthesis of sub-5 nm Co-doped SnO2_2 nanoparticles and their structural, microstructural, optical and photocatalytic properties

A swift chemical route to synthesize Co-doped SnO$_2$ nanopowders is described. Pure and highly stable Sn$_{1-x}$Co$_x$O$_{2-\delta}$ (0 $\le$ x $\le$ 0.15) crystalline nanoparticles were synthesized, with mean grain sizes < 5 nm and the dopant element homogeneously distributed in substitutional sites of the SnO$_2$ matrix. The UV-visible diffuse reflectance spectra of the Sn$_{1-x}$Co$_x$O$_{2-\delta}$ samples reveal red shifts, the optical bandgap energies decreasing with increasing Co concentration. The Urbach energies of the samples were calculated and correlated with their bandgap energies. The photocatalytic activity of the Sn$_{1-x}$Co$_x$O$_{2-\delta}$ samples was investigated for the 4-hydroxylbenzoic acid (4-HBA) degradation process. A complete photodegradation of a 10 ppm 4-HBA solution was achieved using 0.02% (w/w) of Sn$_{0.95}$Co$_{0.05}$O$_{2-\delta}$ nanoparticles in 60 min of irradiation.Comment: 29 pages, 2 tables, 10 figure