This study presents the findings of a 3D finite element modeling on the performance of a single pile under various slenderness ratios (25, 50, 75, 100). These percentages were assigned to cover the most commonly configuration used in such kind of piles. The effect of the soil condition (dry and saturated) on the pile response was also investigated. The pile was modeled as a linear elastic, the surrounded dry soil layers were simulated by adopting a modified Mohr-Coulomb model, and the saturated soil layers were simulated by the modified UBCSAND model. The soil-pile interaction was represented by interface elements with a reduction factor (R) of 0.6 in the loose sand layer and 0.7 in the dense sand layer. The study was compared with the findings of 1g shaking table tests which were performed with a slenderness ratio of 25. In the validation case, there was a clear correlation between the laboratory findings and the numerical analyses. It was observed that the failure mechanism is influenced by the soil condition and the slenderness ratio to some extent. Under the dry soil condition, no base pile deformation was observed; However, tip pile movement was observed under the saturated soil condition with pile slenderness ratios of 25 and 50. The findings of this study are also aimed to include an approximation of the long-term deformations at the ground surface which has experienced shaking.
The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
... Show MorePrecise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, me
... Show MoreAbstract: Many treatment modalities have been introduced for correction of deficient alveolar ridge width. Bone expansion through the ridge split procedure is one of them. This technique was initiated in order to overcome many problems that usually associated with grafting procedures. The present study evaluated the effectiveness of piezoelectric device in performing ridge split using single-stage approach and assessed the outcomes during a period of about 4 months after surgery. A total of 23 patients aged in range between 18 and 60 years underwent ridge split procedure with immediate insertion of dental implants. A panoramic radiograph was obtained before surgery. The gained bone was measured and surgical complications were recorded. Impl
... Show MoreCopper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the
... Show MoreThis work studied the facilitation of the transportation of Sharqi Baghdad heavy crude oil characterized with high viscosity 51.6 cSt at 40 °C, low API 18.8, and high asphaltenes content 7.1 wt.%, by reducing its viscosity from break down asphaltene agglomerates using different types of hydrocarbon and oxygenated polar solvents such as toluene, methanol, mix xylenes, and reformate. The best results are obtained by using methanol because it owns a high efficiency to reduce viscosity of crude oil to 21.1 cSt at 40 °C. Toluene, xylenes and reformate decreased viscosity to 25.3, 27.5 and 28,4 cSt at 40 °C, respectively. Asphaltenes content decreased to 4.2 wt. % by using toluene at 110 °C. And best improvement in API of the heavy cr
... Show MoreThe deposition method of perovskite solar cell layers significantly impacts device functionality and the achievement of industrial goals. Aluminum (Al) nanoparticles with rutile titanium oxide (TiO2) nanoparticle thin films are fabricated on Fluorine Tin Oxide (FTO) glass substrates by nanosecond pulsed fiber laser deposition (PLD) to be used as a plasmonic electron transport layer (ETL) in perovskite solar cell (PSC). The effect of various pulsed fiber laser parameters on the structural, optical, and surface morphology on Al/TiO2 films is extensively examined utilizing a variety of measurement techniques; X-ray diffraction (XRD), Ultraviolet–visible (UV–Vis) spectroscopy, Field emission scanning electron microscopy (FE-SEM) and Atomic
... Show MoreWe demonstrate that the selective hydrogenation of acetylene depends on energy profile of the partial and full hydrogenation routes and the thermodynamic stability of adsorbed C2H2 in comparison to C2H4.
Hypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce
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