Worldwide, enormous amounts of waste cause major environmental issues, including scrap tires and plastic, and large waste, a consequence of the demolition of buildings, including crushed concrete, crushed clay bricks, and crushed thermo-stone. From that point, it’s possible to consider that the recycling processes for these materials and using them in the manufacturing field will reduce the adverse effects on the environment of these wastes and the consumption of natural resources. Sustainable concrete blocks can be considered as one of the products produced by using these materials as partial volume replacement of the coarse, fine aggregate, or cement content, considering their dry density, workability, absorption, compressive strength, and thermal conductivity tests evaluate their performance- and conformity with specifications. The results of tests on samples of sustainable concrete blocks showed the feasibility of using demolished building waste as aggregates instead of natural materials for their production.
Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The predict
The novel groups of organic chromophores containing triphenylamine (TPA) (ATP-I to ATP-IV) have been constructed by structural modification of electron donors with substitution biphenyl and bipyridine rings inserting a π-linkage. Density functional theory (DFT) and time-dependent type of it (TD-DFT) have been operated to study results of donating ability of TPA and spacer on absorption, geometrical, photovoltaic, and energetic attributes of these sensitizers. Structural attributes have been revealed that incorporation of TPA, acceptor and π bridge include a perfect coplanar conformation in TPA-III. Based on frequency computations and ground-state optimization, bandgap (Eg) energy, ELUMO, EHOMO have been determined. For enlightening maximu
... Show MoreIn this work, optical system with different aperture shapes (circular, square, elliptical and triangle aperture) has been used for efficiency evaluation when the system involved moving factor in ideal case (aberration free). The optical system evaluate far moving object, therefore the image forming at image plane due to point spread function (image formula of incoherently illuminated point object). A mathematical treatment has been used to getting results by Gaussian numerical calculations method. The results show priority of circular aperture when optical system that submits of moving factor.
A winglet is devices attached at the wing tips, used to improve aircraft wing efficiency by reduction influence wing tips vortices and induct drag, increasing lift force at the wing tips and effective aspect ratio without adding greatly to the structural stress and weight in the wing structure. This paper is presented three-dimensional numerical analysis to proposed modification swept back wing by adding Raked winglets devices at the main wing tips belong the two seat trainer aircraft type Aermacchi Siai S211 by using Fluent ANSYS 13 software. CFD numerical analysis process was performed at the same flight boundary conditions indifferent wing angle of attacks with constant air flow velocity V∞ =50 (m/sec), ambient pressure Po=101325 (P
... Show MoreThis research examines the quantitative analysis to assess the efficiency of the transport network in Sadr City, where the study area suffers from a large traffic movement for the variability of traffic flow and intensity at peak hours as a result of inside traffic and outside of it, especially in the neighborhoods of population with economic concentration. &n
... Show MoreA modified chemical method was used to prepare titanium dioxide nanoparticles (TiO2 NPs), which were diagnosed by several techniques: X-ray diffraction, Fourier transform infrared, field emission scaning electron microscopy, energy disperse X-ray, and UV-visible spectroscopy, which proved the success of the preparation process at the nanoscale level. Where the titanium oxide particles have an average particle size equal to 6.8 nm, titanium dioxide particles were used in the process of adsorption of Congo red dye from its aqueous solutions using a batch system. The titanium oxide particles gave an adsorption efficiency of Congo red dye up to more than 79 %. The experimental data of the adsorption process were analyzed with kinetic models and
... Show MorePlant extracts occupied a big place in diseases treatment and preserving human health because, they contain many active substances that can be exploited in the field of pharmaceutical manufacturing from natural materials. Therefore, this study was conducted to evaluate the effect of different concentrations of plant extracts for each of Nigella sativa, Alliumsativum and Allium cepa against the fungal growth of Candida albicans that cause many skin diseases and infections to humans as well as Trichophyton mentagrophytes, which affects the hair, skin and nails. These two fungi have been isolated and diagnosed from people who have skin infection. Both fungal isolates were treated with extracts of Nigella sativa, Alliumsativum and Allium cepa
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
... Show MoreDifferent coating layers of fluorescent agent (FCA) on the solar cells were used. An increase of 35% in the energy conversion efficiency of the solar cell have been obtained. This increase is attributed to the reduction ofthe reflected light, eflection spectra show low values at higher thickness which explained the increase ofthe conversion efficiency with increases of layer thickness.