Investigation on the bulk growth of $${\upalpha }$$-$$\hbox {LiIO}_{3}$$LiIO3 single crystals and the influence of pH on its structural,morphological and optical characteristics

\(\upalpha \)-\(\hbox {LiIO}_{3}\) is an excellent optical material exhibiting strong nonlinear optical, piezoelectric and elasto-optic properties. However, its practical applications are limited by the insufficient reproducibility of the mentioned properties caused by the strong influence of the growth conditions, and, in particular, pH of the solution from which \(\upalpha \)-\(\hbox {LiIO}_{3}\) crystal is grown. Herein, we investigate to grow bulk size good quality crystals of \(\upalpha \)-\(\hbox {LiIO}_{3}\) based on the observed problems during its crystallization process. A systematic investigation was carried out to find the effect of pH on solubility, crystal growth, structural, surface and laser damage properties of \(\upalpha \)-\(\hbox {LiIO}_{3}\) single crystals. The structure and phase of \(\hbox {LiIO}_{3}\) were confirmed by powder X-ray diffractometer analysis. The functional groups of the compound were identified using Fourier transform infrared spectroscopy. Surface defects of the grown crystals were studied by etch patterns. The crystal grown at pH 10 showed 10% optical transmission enhancement in comparison to the crystals grown at pH 2. The indirect optical bandgap of the crystal was reinvestigated using ultraviolet–Visible–near-infrared transmittance spectrum. The laser damage threshold studies of the crystals grown at pH 10 reveal the higher optical radiation stability against 532 nm laser. The second-order nonlinear optical behaviour of \(\upalpha \)-\(\hbox {LiIO}_{3}\) crystals grown at different pH conditions have been investigated by using Kurtz and Perry powder technique with Nd:YAG laser pulses at the wavelength of 1064 nm.     

Development of FEA-ANN hybrid model for Equivalent Stress prediction of automobile structural member

Chassis serves as a backbone by supporting the body and diverse parts of the automobile. It ought to be sufficiently rigid to endure the shock, twist, vibration and extra stresses. Then, a vital consideration in chassis design is the strength (Equivalent Stress) for sufficient bending stiffness (Deflection). The primary goal of the research is to build up an Artificial Neural Network (ANN) model for identical stress prediction. Two side members joined to a series of cross members to make the chassis frame. The number of cross members and their locations, cross-section and the sizes of the side and the cross members turn into the design variables. The chassis frame model is created in Creo 3.0 and dissected using Ansys. Since, the number of parameters and levels are more, so the probable models are too much. By changing the Parameters, using the orthogonal array the weight of the sidebar is decreased. Then, FEA is performed on those models. ANN model is prepared by using the results of FEA. For training the ANN model, the standard back-propagation algorithm is observed to be the best. A multi-layer perception network is used for non-linear mapping between the input and the output parameters. FEA-ANN hybrid model can save material used, production cost and time.     

An analysis of the performance of Artificial Neural Network technique for apple classification

The purpose of this paper is to develop Artificial Neural Network (ANN)-based apple classifier. Testing effort is calculated using ANN method. The complete system is divided into two modules. In the first module, input (surface level apple quality parameter) from the different sources is collected by the software developed in Visual Basic through different input device like web camera, weight machine, etc. In the second module, the input data are used by ANN simulator to classify the apple according to their quality. The final result of an ANN model for apple classification is discussed; however, the modeling results showed that there is excellent agreement between the experimental data and predicted values. A low level of error prediction confirmed the fact that the Neural Network model is an effective instrument of the apple quality estimation. There is not any misclassification during testing. The paper presents alternative method for quality assessment of apple and provides consumers with a safer food supply.     

Prediction of Bulk Metallic Glass Formation in Cu–Zr–Ag–Hf System by Thermodynamic and Topological Modeling

Cu based bulk metallic glasses (BMGs) are widely studied because of their high glass forming ability (GFA) and interesting combination of properties such as high strength coupled with good ductility and low cost. With these attributes, Cu based BMGs are being projected as promising materials for practical applications. The process of glass formation in metallic systems is a challenging task and alloys should be cooled from the liquid state at rates faster than a critical cooling rate (R_c) to resist crystallization. Interestingly, composition plays an important role in achieving easy glass formation, which is usually measured in terms of R_c. In the present work, attempt has been made to identify the composition for easy glass formation in Cu based quaternary system by theoretical approach. A GFA parameter P_HS, which is a product of enthalpy of chemical mixing (?H_chem) and mismatch entropy normalized with Boltzmann??s constant (?S_??/k_B) is used to identify the best glass forming composition in Cu?CZr?CAg?CHf system. Further, a new parameter P_HSS, which is a product of P_HS and configurational entropy (??S_config/R) is found to illustrate strong correlation with GFA. An attempt has also been made to correlate P_HSS parameter with critical diameters and R_c using reported data in Cu?CZr?CAg?CHf system.     

Environmental impact assessment of river valley projects in upper Teesta basin of Eastern Himalaya with special reference to fish conservation: a review

Teesta river basin in Eastern Himalaya is being subjected to cascade hydropower development. To assess the impacts of this developmental activity on fish fauna of the basin, fish habitats of the four largest tributaries in the basin were selected for the present study. A total of 18 large hydroelectric projects are planned on these rivers. Here, a total of 11 EIAs and 2 carrying capacity studies in Teesta basin were reviewed. Our investigations show that after commissioning all the projects, 52–88% of the free-flowing river stretches will be diverted and 7.6–24% of the riverine ecosystems will be converted into semi lacustrine ecosystems in different rivers. The cascade hydropower development is likely to affect more than 100 fish species. All the EIA reports reviewed have investigated fish species richness, impacts on fish fauna and fishery management plans. EIA studies and management plans, however, do not adequately address important ecological and conservation issues due to various limitations. An integrated fish conservation plan for the upper Teesta basin is suggested in this contribution.     

Criteria for Crack Deflection-Penetration in EBC Coated Ceramics: A Parametric Study

This article discusses results obtained from a parametric study to analytically evaluate the impingement of a crack at the interface of an environmental barrier coating (EBC) and a monolithic Silicon nitride (Si₃N₄) layered ceramics substrate. The study establishes a correlation that leads to determine if the crack is arrested or advanced by either penetrating or deflecting along the EBC/substrate interface. A finite-element-based fracture mechanics methodology is utilized to perform these calculations. Critical parameters determining penetration-deflection conditions in relation to EBC's physical characteristics, such as porosity level, voids, and mini cracks, are determined for a single layer and multi-layered coating system coordinating the interactions between the EBCs (Mullite, Mullite mixture, Silicon nitride, etc.) and the substrate structure. Results showing thermo-mechanical stresses and stress/strain energy release relations with respect to crack penetration-deflection are presented and discussed as the crack is advanced.     

Inference of COVID-19 epidemiological distributions from Brazilian hospital data

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (N = 21 000 − 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2 and 17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalized lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.     

Dynamic participation of doubly fed induction generator in automatic generation control

Increasing levels of wind generation have resulted in an urgent need for the assessment of their impact on frequency control of power systems. The displacement of conventional generation with wind generation will result in erosion of system frequency. The paper analyzed the dynamic participation of doubly fed induction generator (DFIG) to system frequency responses of two-area interconnected power system having variety of conventional generating units. Frequency control support function responding proportionally to frequency deviation is proposed to take out the kinetic energy of turbine blades in order to improve the frequency response of the system. Impacts of different wind penetrations in the system and varying active power support from wind farm on frequency control have been investigated. Integral gains of AGC loop are optimized through craziness-based particle swarm optimization (CRPSO) in order to have optimal transient responses of area frequencies, tie-line power deviation and DFIG parameters.