A tungsten inert gas (TIG) welding is one of the most popular kinds of welding used to join metals mainly for aluminum alloys. However, many challenges may be met with this kind of joining process; these challenges arise from decay of mechanical properties of welded materials. In the present study, an attempt was made to enhancing the mechanical properties of TIG weld joint of 6061-T6 aluminum alloy by hardening the surfaces using shoot peening technique. To optimize the shoot peening process three times of exposure (5, 10, and 15) min. was used. All peened and unpeened, and welded and unwelded samples were characterized by metallographic test to indicate the phase transformation and modification in microstructure occurring during welding process. Tensile test and Vickers micro-hardness measurements were performed for all samples to investigate the effect of shoot peening on mechanical properties of welded aluminum.
The results indicated a significant improvement in properties for peened welded and unwelded samples compared with those unpeened one. Also, the results showed that the tensile and microhardness properties were increased with increasing the time of exposure to 15 min. due to generation of compressive residual stresses at surface.
Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreNet pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.
This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.
The Mishrif formation was
... Show MoreIn this work, multilayer nanostructures were prepared from two metal oxide thin films by dc reactive magnetron sputtering technique. These metal oxide were nickel oxide (NiO) and titanium dioxide (TiO2). The prepared nanostructures showed high structural purity as confirmed by the spectroscopic and structural characterization tests, mainly FTIR, XRD and EDX. This feature may be attributed to the fine control of operation parameters of dc reactive magnetron sputtering system as well as the preparation conditions using the same system. The nanostructures prepared in this work can be successfully used for the fabrication of nanodevices for photonics and optoelectronics requiring highly-pure nanomaterials.
A new, Simple, sensitive and accurate spectrophotometric methods have been developed for the determination of sulfanilamide (SNA) drug in pure and in synthetic sample. This method based on the reaction of sulfanilamide (SNA) with 1,2-napthoquinone-4-sulphonic acid (NQS) to form N-alkylamono naphthoquinone by replacement of the sulphonate group of the naphthoquinone sulphonic acid by an amino group. The colored chromogen shows absorption maximum at 455 nm. The optimum conditions of condensation reaction forms were investigated by: (1) univariable method, by optimizing the effect of experimental variables; (different bases, reagent concentration, borax concentration and reaction time), (2) central composite design (CCD) including
... Show MoreThe aims of study were identify the Morphological description and histological structure of pancreas gland in the Saw-scaled viper snake, (Echis carinatus scochureki). The study was conducted on 6 snakes collected from the city of Nasiriya in Dhi Qar province, Doped snakes was dissected to isolate the pancreas gland, and the histological slides prepared after samples fixation by fixative solutions, the routine stains Haematoxylin– Eosin were used. Morphological Description study showed that the pancreas gland was compact in type with one lobe, white-pink in colure. The pancreas Located at the level of the Gall bladder associated with it’s caudal side, The spleen is adjacent to pancreas completely in the dorsal side .and duodenum l
... Show MoreThis paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.