Frequently, Load associated mode of failure (rutting and fatigue) as well as, occasionally, moisture damage in some sections poorly drained are the main failure types found in some of the newly constructed road within Baghdad as well as other cities in Iraq. The use of hydrated lime in pavement construction could be one of the possible steps taken in the direction of improving pavement performance and meeting the required standards. In this study, the mechanistic properties of asphalt concrete mixes modified with hydrated lime as a partial replacement of limestone dust mineral filler were evaluated. Seven replacement rates were used; 0, 0.5, 1, 1.5, 2, 2.5 and 3 percent by weight of aggregate. Asphalt concrete mixes were prepared at their optimum asphalt content and then tested to evaluate their engineering properties which include moisture damage, resilient modulus, permanent deformation and fatigue characteristics. These properties have been evaluated using indirect tensile strength, uniaxial repeated loading and repeated flexural beam tests. Mixes modified with hydrated lime were found to have improved fatigue and permanent deformation characteristics, also showed lower moisture susceptibility and high resilient modulus. The use of 2 percent hydrated lime as a partial replacement of mineral filler has added to local knowledge the ability to produce more durable asphalt concrete mixtures with better serviceability.
Reinforced concrete (RC) slabs strengthened with carbon fibre reinforced polymer (CFRP) and subjected to flexural actions may experience many types of failure, including FRP debonding, FRP rupture and concrete crushing. Of these different types of failure modes, FRP debonding stands out as the most predominant type of failure because of its dependence on the relatively weak bond interface between the soffit of the RC member and the FRP sheet attached to it. Many anchorage systems have been developed to enhance the performance of strengthened systems, one of which is the hybrid anchor, which combines the effects of patch anchors and spike anchors. Hybrid anchors have shown significant enhancement when used with RC members subjected to shear
... Show MoreIndustrial and urban development has resulted in the spread of plastic waste and the increase in the emissions of carbon dioxide resulting from the cement manufacturing process. The current research aims to produce green (environmentally friendly) concrete by using plastic waste as coarse aggregates in different proportions (10% and 20%) and nano silica sand powder as an alternative to cement in different proportions (5% and 10% by weight). The results showed that compressive strength decreased by 12.10% and 19.23% for 10% and 20% plastic waste replacement and increased by 12.89% and 20.39% for 5% and 10% silica sand replacement respectively at 28 days. Flexural strength decreased by 12.95% and 19.64% for 10% and 20% plastic waste r
... Show MoreTo decrease the impact on the environment of building waste, the recycled aggregate may be used in various sustainable engineering applications, such as roller compacted concrete pavement (RCCP). This research examined how using recycled aggregate as a partial replacement for natural aggregate as coarse or fine affected the mechanical properties of roller-compacted concrete pavement. The recycled aggregate was crushed and sieved to coarse and fine aggregate before being used in the roller-compacted concrete pavement. Compressive strength, splitting tensile strength, and flexural strength were all evaluated after the samples were prepared at 28 and 90 days of curing. According to the study's findings, the partial replacem
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreObjective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction. Results: DOX and CS-Ag
... Show MoreModern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
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