Engineering and Technology Journal

Damage of elevated tanks during earthquakes can jeopardize the supply of drinking water and causes significant economic losses. Therefore, seismic analysis of tanks containing liquids requires special consideration. Knowledge of liquid hydrodynamic pressures developed during an earthquake is important for tank design. This paper aims to verify the dynamic reaction of structural systems of spherical elevated steel tanks containing water, and determine the natural frequencies that contribute to the physical response, as well as seismic analysis of the tank. A three dimensional Finite Element Model was developed to identify the main parameters involved in this response for three different fullness ratio (0.00%, 53.30% and 71.11%) using the ANSYS software. The model was implemented and validated based on the results of a previously conducted experimental study. Moreover, it was analyzed under the impact of the most severe earthquake that Iraq was exposed to in 2017 with a magnitude of 7.2 on the Richter scale. The results showed a very good agreement in natural frequency with a discrepancy (root mean square error) of 2% (0.05 Hz), 6.9% (0.15 Hz) and 9.5% (0.2 Hz) for the fullness ratio 0%, 53.3% and 71.11%, respectively In addition, the selected element type and the method of analysis are applicable. Moreover, results of displacement and stresses from earthquake analysis indicated that the spherical tank could lose stability in time 1.4 seconds of the proposed time for the worst part of the earthquake, when displacement records highest values in the direction of earthquake for the tank body at chosen points in the top, middle, and bottom of the tank b

Results of testing reinforced self-compacted concrete slender columns having longitudinal holes concealing PVC pipe in their cross sections under axial compression load and uniaxial bending are presented in this paper. The effect of hollow shape on the performance of slender columns having 200x200mm quadratic cross section and 1300mm long under concentric and eccentric loads was investigated. Three different shapes of central hole: circular, square, and lozenge pattern in addition to the different load eccentricity values were considered to investigate the axial loading resistance and cracking load, lateral and longitudinal deflections of the columns. Test results have showed that altering the hollow shape inside the area of column cross section does not show a great influence on the column behavior unless the hollow ratio changed. The effect of hole shape or the hollow ratio on loading capacity is insignificant but the existence of a hole embedded longitudinally in the column significantly decreases its ultimate capacity. The effect of hollow shape or hollow ratio on a slender columns behavior subjected to eccentric loading with small ratio of load eccentricity to total column thickness (e/h=.33) was more than that of large eccentricity (e/h=1.0). Accordingly, the decrease in loading column capacity of columns was (5.0%, 2.5%, and 6.6%) compared to (3.2%, 2.2%, and 4.7%) for the same hole shapes respectively

Drought is one of the most significant natural disasters in Iraq. It has a strong impact on the water resources in Iraq. Consequently, it causes massive environmental damage, economic deficiency, and social problems to the country. Therefore, more considerations towards the study and management of drought has become of vital importance in recent decades.
In this paper, three drought indices (DIs) were computed for evaluation of the spatiotemporal of drought within Derbendikhan Dam Watershed (DDW) in the Diyala River Basin, Iraq. Based on the monthly weather data for the period (1984 – 2013) downloaded from the Climate Forecast System Reanalysis (CFSR) for eight stations located within DDW. The Reconnaissance Drought Index (RDI), standardized precipitation index (SPI) and Streamflow Drought Index (SDI) at 12-month time scale were computed to assess droughts in the DDW. For each index, the temporal variations of the drought severity and Drought Frequency Patterns (DFPs) for the period (1984 – 2013) were computed and analyzed. In addition, spatial distributions of the drought severity for each index were mapped and investigated. Accordingly, the DFPs were compared to specify the dominant and/or more frequent DFPs. The results show that the performances of different DIs are strongly correlated with the dominant factors of droughts and drought duration. Also, the SPI and SDI are less accurate than the RDI when both precipitation and evaporation are the main factors controlling the drought events. However, the SPI and SDI indices are identical in the same proportions of the dry years which are less than the ratio of dry years to an RDI, but the severity of the drought from the SDI results is higher than the severity of the drought relative to the SPI and RDI. The three indices indicate that the Eastern region is drier than the Western region, which is somewhat wet.

Finite Element Analysis (FEA) is a helpful tool for finding solutions to civil engineering problems. In this paper, the numerical analysis was performed by simulating an experimental test by using FEA tools, Abaqus /CAE2019 was used to develop and retrofit solutions to sustain existing structures for seismic hazard. The 3D building was modeled, and nonlinear analysis was adopted. This experimental building was tested at the Joint Research Centre (JRC) of the ELSA facility that is in Ispra-Italy. This model was a building of a full-scale four-story tested using the pseudo-dynamic (PsD) techniques. The retrofitting model was done by adding new RC walls with different connection details to the existing building. This building corresponding in gravity design only. The goal of the experimental test was to study the effectiveness of adding RC infill walls as retrofitting method, including designing it and the contribution of dowels that connect the new infill wall to the existing RC building. In other words, it is a strengthen method carry out by conversion of selected bays into new infilled RC walls. The results of analytical modeling of the RC structure in the Abaqus software show that the percentage of differences of X- Direction in top story displacement between Abaqus software and Experimental tested at ELSA results are 2.47% in positive and 3.12% for negative X direction, which refer to a very good similarity and accurate building simulation

Electric discharge machine (EDM) or may be call electric spark machine is one of the most important cutting process or manufacturing process because it gives high accurate dimension and can be produced the most complex shape. In this present material removal rate and surface roughness for tool steel AISI L2 studied. The input parametric for this process is current, pulse on time (Ton) and pulse off time (Toff).A full factorial method is used to formulate machine parameters and find the optimal process parameters of an electric spark. The result shows that the Surface roughness increasing with increasing current and pulse on time is increases while no effect by increase in pulse off time. Best surface roughness when using low current and pulse in time. The material removal rate is increasing with increasing in current and pulse on time while decreasing when pulse of time is increased. The experimented and predicted values by using Minilab17 software of this process are approximately equal.

Copper Sulfide CuS thin film was prepared using pulsed laser deposition PLD technique and characterized by X-ray and SEM. The optical, structural, and morphological properties are examined at different energies 500 mJ, 600 mJ, 700 mJ, and 800 mJ. The best result was 600 mJ which annealed at various annealing temperatures 300°C, 350°C, 400°C, and 450°C. The effect of thermal annealing on CuS thin film was examined X-ray and SEM. CuS Film was simulated using a prism-based SPR optical sensor. This paper introduces the optical test study of CuS thin film deposited by pulsed laser deposition technique on the quartz substrate and supported by theoretical application study under the effect of surface plasmon resonance (SPR). In this research field, the optical and morphological characteristics of the CuS thin film were deposited by PLD at different laser energies. The annealing process was applied for better-deposited thin-film; the XRD results, SEM images, transmittance T%, and energy gap Eg were analyzed thoroughly and compared to evaluate the thin-film. This effort was made in an in-depth analysis of CuS thin film deposited by PLD on the quartz substrate and applied theoretically in surface plasmon application.

The current work is conducting an experimental investigation into the effect of those technical parameters, called nanomaterial, bath temperature and plating time on the micro-hardness and corrosion rate of electroless plated low carbon steel undergoing electroless deposition operation. It was used to prepare (Ni-P/ Nano TiO2), (Ni-P/ Nano Al2O3) and (Ni -P/ Nano SiO2) alloys in this research. The Taguchi design is used to describe the variations located within the corrosion and mechanical properties. To achieve a comprehensive study, a Taguchi-based design was used to account for all applicable combinations of factors. Experimental models had been advanced that linking the response and method parameters to the results of those experiments. Validation of these models is done using analysis of variance (ANOVA). The desirability function is used to simultaneously optimize all the response. Finally, the optimum combination of method parameters resulting (bath temperature=90 oC, plating time =120 min. and Nanomaterial=(Al2O3)), nanomaterial was observed to be the major process parameter on the responses of the electroless-plated low carbon steel with an impact ratio of (47%) based on the (ANOVA) results.

The addition of agricultural and industrial solid wastes and nanomaterials to concrete combined with steel fibers to improve the mechanical and electrical properties of concrete was investigated. This approach could be used in advanced applications in electromagnetic shielding and conductive concrete. Steel fibers were used at 2%wt. of sand and (induction furnace slag (EIF), carbon nanotube (CNT), steel wool fibers, prepared corn husks) at 0.5 and 1 wt.%. of cement. Obtained results of using 1% for both carbon nanotube and steel wool with steel fibers in the mixture 4 and 6, respectively, showed the highest rates of compressive strength. A similar result was shown when tested at 3,7 and 28 days of age and compressive strength was 47.4MPa,47.34MPa for the mixture 4 and 6 respectively. The electrical conductivity and electrical resistance of the samples were measured at the age of 7 days. The findings have also shown that adding steel wool as well as( CNT) gave the best results and the sample containing the furnace slag achieved satisfactory results as well.

Localization is one of the potential challenges for a mobile robot. Due to the inaccuracy of GPS systems in determining the location of the moving robot alongside weathering effects on sensors such as RGBs (e.g. rain and light-sensitivity ( . This paper aims to improve the localization of mobile robots by combining the 3D LiDAR data with RGB-D images using deep learning algorithms. The proposed approach is to design an outdoor localization system. It is divided into three stages. The first stage is the training stage where 3D LiDAR scans the city and then reduces the dimensions of 3D LiDAR data to 2.5D image. This is based on PCA method where these data are used as training data. The second stage is the testing data stage. RGB and depth image in IHS method are combined to generate 2.5D fusion image. The training and testing of these datasets are based on using Convolution Neural Network. The third stage consists of using the K-Nearest Neighbor algorithm. This is the classification stage to get high accuracy and reduces the training time. The experimental results obtained prove the superiorly of the proposed approach with accuracy up to 97.52%, Mean Square of Error of 0.057568, and Mean error in distance equals 0.804 meters.

Hydroxyapatite is one of the most bioactive materials used in tissue engineering due to its excellent biocompatibility and chemical composition which is equivalent to the mineral element of bone. In this study, polymer sponge replication method was used to fabricate porous hydroxyapatite scaffolds. Pure phase of hydroxyapatite scaffolds and the chemical bonding were verified via Fourier Transform Infrared and X-ray diffraction. Emission scanning electron microscopy (F E S E M) examination showed that the proposed scaffold has high interconnected pores that were achieved just after sintering at temperatures 1350 ºC for 2 hours. The percentage porosity values were estimated to be between 75–78 percent. The bioactivity of porous scaffolds was also investigated. They were submerged in a slurry of simulated body fluid (S B F) for seven, fourteen, and twenty-one days, respectively. Both FESEM and XRD analysis have confirmed the bioactivity of the prepared porous hydroxyapatite scaffold through the formation of a dense layer of apatite on its surface. Based on the results, the porous hydroxyapatite scaffolds could be recommended as a critical option for bone defects as well as replacement applications.

In this paper, study the effects of magnetite nanomaterial Fe3O4 on the mechanical properties of epoxy. Dispersion of Fe3O4 nanoparticles in the epoxy resin was performed by ultrasonication. The samples of the nanocomposites were prepared using the casting method. The nanocomposites contain epoxy resins as a matrix material incorporated by different weight percentages of magnetite Fe3O4 that varies from 0wt.% to 15wt.% as a reinforcing material. The epoxy with the additive reinforcement materials Fe3O4 was slowly mixed in a sonication bath for 15 minutes, then the mixture poured into silicon molds. Field Emission Scanning Electron Microscopy FESEM and X-ray diffraction spectra XRD were used to characterize the morphological and structural properties of preparing samples and the distribution of Fe3O4 nanoparticles to the epoxy resin. Mechanical testing consists of tensile, hardness shore, and three-point flexural tests were performed on the samples at room temperature according to ASTM standards. The results showed that reinforcement by 15wt.% of Fe3O4 nanoparticles maximizes these mechanical properties of nanocomposites compared with pure epoxy except for the young modulus's preferred weight at 9 wt.%, this is due to aggregation of the additives nanomaterials in epoxy resin above 9 wt.%.

This paper presents the development of an automatic tuning of conventional PI-D controllers for Quadrotor system. The most critical problem of tuning the parameters of the PID, is that they can drastically affect the performance of the system. Accordingly, Extremum seeking (ES) algorithm is utilized here to reduce a selected cost function that brings the required performance aspects. The results show that the ES-PID controller provides better stability and performance as compared with only PI-D controller. The parameters of ES-PID controller have been successfully tuned and modified to reach the desired destination with significantly less overshoot, oscillations, and faster convergence.

Nickel oxide (NiO) microparticles were synthesized by pulsed laser ablation in double deionized water and intensively studied using Nd:YAG laser. The obtained sample was examined by X-ray diffraction, XRD measurement which tests the existence of polycrystalline. The structural parameters introduced and surface morphology was studied using field emission scanning electron microscopy devices. The optical properties of microparticles in a liquid were investigated through UV-VIS spectroscopy. The CO/CO2 sensing properties of the NiO microstructure sensors were systematically investigated, and the effects of different laser fluencies on the CO/CO2 sensing characteristics were analyzed. XRD measurements reflected the existence of polycrystalline, the optical result shows that The absorption spectra peak centered around 360 nm and a tail extending to the red region (600 nm), the scanning electron microscopy images showed that the morphologies of NiO thin films have microspheres in various. The sample affected by laser fluence 1.9 J/cm2 which exhibits the best sensitivity for CO2 gas

This paper intends to develop a methodology for helping amputees and crippled people old, by ongoing voice direction and association between patient and personal computer (PC) where these blends offer a promising response for helping the debilitated people. The major objective of this work is accurately detected audio orders via a microphone of an English language (go, stop, right and left) in a noisy environment by the proposed system. Thus, a patient that utilizes the proposed system can be controlling a wheelchair movement. The venture depends on preparing an off-line dataset of audio files are included 10000 orders and background noise. The proposed system has two important steps of preprocessing to get accurate of specific audio orders, accordingly, the accurate direction of wheelchair movement. Firstly, a dataset was preprocessed to reduce ambient noise by using Butterworth (cutoff 500-5000 Hz) and Wiener filter. Secondly, in the input (a microphone) of the proposed discriminative model put a procedure of infinite impulse response filter (Butterworth), passband filter for cutoff input microphone from 150-7000 Hz for back-off the loud and environment noise and local polynomial approximation (Savitzky-Golay) smoothing filter that plays out a polynomial regression on the signal values. Thus, a better for filtering from ambient noise and keeping on a waveform from distortion that makes the discriminative model accurate when voice orders were recognized. The proposed system can work with various situations and speeds for steering; forward, stop, left and right. All datasets are trained by using deep learning with specific parameters of a convolutional neural network (CNN). These capacities are dependent on code written in MATLAB. The prototype uses Arduino UNO and a microphone (M

Hand gesture recognition is one of communication in which used bodily behavior to transmit several messages. This paper aims to detect hand gestures with the mobile device camera and create a customize dataset that used in deep learning model training to recognize hand gestures. The real-time approach was used for all these objectives: the first step is hand area detection; the second step is hand area storing in a dataset form to use in the future for model training. A framework for human contact was put in place by studying pictures recorded by the camera. It was converted the RGB color space image to the greyscale, the blurring method is used for object noise removing efficaciously. To highlight the edges and curves of the hand, the thresholding method is used. And subtraction of complex background is applied to detect moving objects from a static camera. The objectives of the paper were reliable and favorable which helps deaf and dumb people interact with the environment through the sign language fully approved to extract hand movements. Python language as a programming manner to discover hand gestures. This work has an efficient hand gesture detection process to address the problem of framing from real-time vide