DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms

Neural Computing and Applications - A lot of different methods are being opted for improving the educational standards through monitoring of the classrooms. The developed world uses Smart...     

Investigation of the impact of global warming on precipitation pattern of Saudi Arabia

This study has been carried out to forecast the impact of global warming on the precipitation pattern of Saudi Arabia by the end of year 2100. Simulation has been done using EdGCM model software (with available 8×10 resolution) developed at Columbia University on which there have been produced global precipitation maps for the seasonal and annual averages for the last 5 years (2096–2100). For each map, EdGCM grid values surrounding Saudi Arabia are used as input to one of the tools of Eagle point software called surface modelling (SM). SM is a new approach for downscaling global climate model results. SM software modelled out isohyets at 0.2 mm/day interval. The results indicate that the present pattern of precipitation (more in winter and less in summer) is going to change by almost equal occurrence of precipitation in all seasons for double_CO₂ (2CO₂) experiment. The 2CO₂ experiment indicates an increase of about 16.05% over the annual average precipitation across the country.     

Magnetically controlled shape-memory effects of hybrid nanocomposites from oligo(ω-pentadecalactone) and covalently integrated magnetite nanoparticles

The covalent integration of inorganic nanoparticles in polymer matrices has gained significance for improving the structural properties of polymer-based materials. Here we report on the performance of poly(ω-pentadecalactone) networks with magnetite nanoparticles as netpoints in their magnetically-controlled shape-memory capability. Hybrid nanocomposites with magnetite nanoparticle content ranging from 5 to 11 wt% were prepared by reacting two types of oligo(ω-pentadecalactone) (OPDL) based precursors with terminal hydroxy groups, a three arm OPDL (³AOPDL, M_n = 6000 g mol⁻¹) and an OPDL (M_n = 3300 g mol⁻¹) coated magnetite nanoparticle (∅ = 10 nm), with a diisocyanate. Homogenous hybrid nanocomposites were obtained independent from the weight content of the OPDL decorated nanoparticles in the samples. At 100 °C (T > T_m-OPDL) the covalent integration of the nanoparticles increased the mechanical strength with increasing weight content whereby the elasticity remained almost constant. In magnetically-controlled one-way dual-shape experiments the shape fixity decreased from 95% to 90% but the shape recovery increased slightly from 95% to 97% when the nanoparticle content was increased. In magnetically-controlled reversible dual-shape experiments the nanoparticles had a restraining effect and the maximum shape-change of 65% for hybrid nanocomposites with 5 wt% magnetite nanoparticles was reduced to 36% when the particle content was increased to 11 wt%. These results show that the performance of hybrid nanocomposites can be tailored by nanoparticle content, however in terms of their applicability either mechanical strength or actuation capability should be focussed in the material selection.     

Estimation of a Unique Pair of Nash Model Parameters: An Optimization Approach

Water resources planning and management requires hydrologic models to estimate runoff from a catchment. For catchments with limited data, the choice of model and identification of its parameters is very important for development of a direct runoff hydrograph. A method is presented to determine a unique pair of hydrologic parameters of the Nash Model, number of linear cascade (n) and storage coefficient (k), using optimization based on Downhill Simplex technique. In this study physical parameters of the catchment are derived from (SPOT) satellite imageries of the basin using ERDAS software. Four different objective functions of varying complexity are tested to find the best solution. Weighted root mean square error (RMSE) and Model Efficiency (Nash-Sutcliffe coefficient) are used to evaluate the model performance. Using the NASH model, a direct surface runoff hydrograph (DSRH) is developed. Kaha catchment is part of Indus river system and is located in the semi-arid region of Pakistan. This catchment is dominated by hill torrent flows and is used in this work to demonstrate the applicability of the proposed method. Ten randomly selected rainfall-runoff events are used for calibration and five events are used for validation. Model results during validation are very promising with model efficiency exceeding 93% and error in peak discharge under 8%. The sensitivity of the Nash model output in response to variation in hydrologic parameters n and k is also investigated. When evaluating the hydrologic response of large catchments, model output is more sensitive to n as compared to k indicating that the runoff diffusion phenomenon is dominant compared to translation flow effects.     

Nonproportionally loaded sway beam-columns with hollow rectangular section

Considerable research has been conducted in the past on the behavior of beam-columns subjected to proportional loads. Recently, Razzaq and Darbhamulla (Proc. 4th Int. Colloquium on Structural Stability, Istanbul, 1991) have conducted an investigation of the behavior and strength of nonproportionally loaded nonsway beam-columns. It was found that the behavior and strength of the beam-columns with semirigid connections, initial crookedness and residual stresses is dependent upon the sequence in which the axial load and the bending moment are applied. The present paper presents the outcome of an investigation of planar beam-column response when sidesway is permitted. The beam-column has partial restraints at both ends, a lateral spring at the top end and possesses a hollow rectangular section. The extent to which nonproportional loads can alter the behavior and strength of such members is explained.     

Effect of zirconium addition on the structure and properties of CuO/CeO2 catalysts for high-temperature water–gas shift in an IGCC system

A series of Ce_xZr_1−xO₂-based Cu catalysts was synthesized by the co-precipitation method. The influences of copper content, zirconium addition, and ratio of ceria to zirconia on the catalytic activity were investigated. BET, N₂O decomposition, XRD, TEM, SEM, EDS, Raman spectroscopy, H₂-TPR, TG/DTA, and XPS were used to characterize the catalysts. The catalytic activity was tested in terms of CO conversion and H₂ selectivity in H₂-rich coal-derived synthesis gas, simulating the actual gas composition of an integrated gasification combined cycle (IGCC) system. The long-term catalyst stability was also examined at 450 °C for 196 h. The addition of zirconium was found to be very important in enhancing catalytic performance. The surface area, copper dispersion, oxygen storage and mobility capacity, reducibility, as well as resistance to sintering all improved after zirconium addition.     

Magnetic Memory Effect of Nanocomposites

The magnetic memory effect (MME) is the ability of magneto‐sensitive materials to remember the magnetic field strength (H_def), at which they were deformed recently. They respond close to H_def either by recovering their initial shape at a switching magnetic field strength H_sw under stress‐free conditions or by building up stress with a peak maximum at H_σ,max under constant strain conditions. This paper explores whether such a MME can be created for polymer‐based nanocomposites. The concept is based on temperature‐memory polymers (TMP) as matrix, in which silica coated iron(III)oxide nanoparticles (mNP) are dispersed. The MME was explored in a cyclic magneto‐mechanical test, in which the nanocomposite sample was elongated to ?_m while being exposed to an alternating magnetic field at H_def. The magnetic memory was read out by determining H_σ,max or H_sw. A linear correlation between H_σ,max (or H_sw) and H_def in a range from 15 to 23 kA m^?1 at a fixed frequency of f = 258 kHz is observed and demonstrates the excellent magnetic memory properties of the investigated nanocomposites containing either crystallizable or amorphous, vitrifiable domains as controlling units. The deformation ?m at H_def can be fixed with an accuracy of more than 72% and the initial shape can be recovered almost completely by more than 86%. The MME allows the design of magnetically programmable devices such as switches or mechanical manipulators.