The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the multiple discriminant model (MDM) and neural network model (NNM). Zublin trunk sewer in Baghdad city was selected as a case study. The deterioration model based on the NNDM provide the highest overall prediction efficiency which could be attributed to its inherent ability to model complex processes. The MDDM provided relatively low overall prediction efficiency, this may be due to the restrictive assumptions by this model. For the NNDM the confusion matrix gave overall prediction efficiency about 87.3% for model training and 70% for model validation, and the overall conclusion from these models may predict that Zublin trunk sewer is of a poor condition.
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This study focused on the synthesis of novel polymers incorporating the 1,3,4-oxadiazole ring. Four polymers were specifically prepared by blending polymers (6-9) with polyvinyl alcohol (PVA) in defined ratios, resulting in the formation of blended polymers (10-13). The synthesized polymers were characterized using Fourier Transform Infrared (FTIR) spectroscopy and proton nuclear magnetic resonance (1H-NMR). The results showed that the structure aligned with the proposed synthetic polymers. Furthermore, the physical and thermal properties were studied using scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC). Additionally, the biological activity was examined against two s
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<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO<sub>2</sub> and NO mass fractions and decreased CO emission values un
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Azo-Schiff base compounds (L1 and L2) have been synthesized from the reaction of m-hydroxy benzoic acid with 1,5-dimethyl-3-[2-(5-methyl-1H-indol-3-yl)-ethylimino]-2-phenyl-2,3- dihydro-1H-pyrazol-4-ylamine and with 3-[2-(1H-indol-3-yl)-ethylimino]-1,5-dimethyl-2-phenyl- 2,3-dihydro-1H-pyrazol-4-ylamine. The free ligands and their complexes were characterized based on elemental analysis, determination of metal, molar conductivity, (1H, 13C) NMR, UV–vis, FT-IR, mass spectra and thermal analysis (TGA). The molar conductance data revealed that all the complexes are non-electrolytes. The study of complex formation via molar ratio in DMF solution has been investigated and results were consistent to those found in the solid complexes with a rat
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Resilient polymeric materials such as silicone elastomers are currently used for maxillofacial prostheses construction but the strength of these materials and their clinical performance need to be optimized with the addition of reinforcing fillers. This study investigates the effect of zirconia nanopowder addition on tear strength, tensile strength, elongation at break, Shore A hardness, surface roughness and cytotoxicity of VST-50 maxillofacial silicone. Silicone base was mixed with different amounts (1%, 2% and 3%) of zirconia nanopowder using a vacuum mixer. Silicone without filler was used as control for comparison. Scanning Electron Microscopy and Atomic Force Microscopy were utilized to assess the efficiency of high-shear vacuum mixin
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