Journal of Engineering

The study focuses on the buckling analysis of laminated composite plates with different boundary conditions using a modified Fourier series. The analysis is based on classical laminated plate theory and employs the Rayleigh-Ritz method. The equation of motion for the plates is derived using the principle of virtual work and solved using a modified Fourier displacement function that satisfies general edge conditions. The eigenvalue problem generated by the Ritz method is solved using MATLAB for symmetric and anti-symmetric, cross and angle-ply laminated plates, considering design parameters such as aspect ratios, number of layers, lamination type, and orthotropic ratio. The results obtained show good agreement with those published by other researchers

In this paper, a robust adaptive sliding mode controller is designed for a mobile platform trajectory tracking. The mobile platform is an example of a nonholonomic mechanical system. The presence of holonomic constraints reduces the number of degrees of freedom that represents the system model, while the nonholonomic constraints reduce the differentiable degree of freedom. The mathematical model was derived here for the mobile platform, considering the existence of one holonomic and two nonholonomic constraints imposed on system dynamics. The partial feedback linearization method was used to get the input-output relation, where the output is the error functions between the position of a certain point on the platform and the desired path. The dynamic error model was considered uncertain and subjected to friction torques on the wheels. The adaptive sliding mode control was utilized to design a robust controller, that will force the platform to follow the desired trajectory. The simulation of the proposed controller was done via MATLAB to reveal the ability of the robust adaptive sliding mode controller applied as a trajectory tracker for various path shapes

Enhancement of heat transfer in the tube heat exchanger is studied experimentally by using discrete twisted tapes. Three different positions were selected for inserting turbulators along the tube section (horizontal position by α= 0°, inclined position by α= 45°, and vertical position by α= 90°). The space between turbulators was fixed by distributing

This research examines the use of vibratory treatments to reduce residual stresses in small welded parts. In this experimental investigation, a post-weld vibration treatment was applied to T- A106 steel pipe fitting specimens to study the effect of the treatment on the residual stress and the hardness of the material. The results have demonstrated that post-weld vibratory stress relief of small size fittings is possible and residual stress may be relieved, and the treatment may be an alternative method for heat treatment especially when unchange in dimensions and material stability are required

The research aims to develop an innovative technique for segmental beam fabrication using plain concrete blocks and externally bonded Carbon Fiber Reinforced Polymers Laminates (CFRP) as a main flexural reinforcement. Six beams were designed and tested under two-point loadings. Several parameters included in the fabrication of segmental beams were studied, such as bonding length of carbon fiber reinforced polymers, the surface-to-surface condition of concrete segments, interface condition of the bonding surface, and thickness of epoxy resin layers. Test results of the segmental beams specimens were compared with those gained from testing reinforced concrete beams of similar dimensions for validation. The results display the effectiveness of the developed fabrication method of segmental beams. The modified design procedure for externally bonded carbon fiber reinforced polymers ACI 440.2R-17 was developed for designing segmental beams. The experimental test values were also compared with design values, and it was 93.3% and 105.8% of the design values, which indicates the effectiveness of the developed procedure

This paper proposes a cognitive system based on a nonlinear neural controller and intelligent algorithm to guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid obstacles and reach the target position using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to find solutions to the mobile robot navigation problems in the mine by searching for optimal paths and finding the reference path equation of the optimal path. Additionally, the PSO algorithm is used to find and tune online the neural control gains values of the nonlinear neural controller to obtain the best torque actions of the wheels for the mining autonomous mobile robot. Simulation results by MATLAB showed that the proposed cognitive system is more accurate in terms of planning the reference path to avoid obstacles and online finding and tuning parameters of the controller, which generated smooth control action without saturation state for tracking the reference path equation and minimized the mobile robot tracking pose error to zero value.

This study aims to estimate the accuracy of digital elevation models (DEM) created using open source Google Earth data and compare them with widely available DEM datasets, such as Shuttle Radar Topography Mission (SRTM) version 3 and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) version 2. The GPS technique was used to produce a high-accuracy digital elevation raster as a reference, compared to the DEM datasets. The study area was Baghdad University, Al Jadriya campus, with 151 reference points created within the area to evaluate the results based on RMS values. The Geographic Information System (GIS) was utilized to analyze, visualize, and interpolate data. The statistical analysis revealed that the RMSE of DEM related to the differences between the reference points and Google Earth, SRTM DEM, and ASTER GDEM are 6.9, 5.5, and 4.8, respectively. The study found that the level of accuracy for all open sources used was convergent.

Asphaltene is a component class that may precipitate from petroleum as a highly viscous and sticky material that is likely to cause deposition problems in a reservoir, in production well, transportation, and in process plants. It is more important to locate the asphaltene precipitation conditions (precipitation pressure and temperature) before the occurring problem of asphaltene deposition to prevent it and eliminate the burden of high treatment costs of this problem if it happens. There are different models which are used in this flow assurance problem (asphaltene precipitation and deposition problem) and these models depend on experimental testing of asphaltene properties. In this study, the used model was the equation of state (EOS) model and this model depends on PVT data and experimental data of asphaltene properties (AOP measurement) and its content (asphaltene weight percent). The report of PVT and flow assurance of the live oil from the well (HFx1) of the zone of case study (Sadi formation in Halfaya oil field) showed that there is a problem of asphaltene precipitation depending on asphaltene onset pressure (AOP) test from this report which showed high AOP greater than local reservoir pressure. Therefore, this problem must be studied and the conditions of forming it determined. In the present work, the asphaltene precipitation of Halfaya oil field was modeled based on the equation of state (EOS) by using the Soave-Redlich-Kwong (SRK) equation which gave the best matching with the experimental data. The main result of this study was that the reservoir conditions (pressure and temperature) were located in the asphaltene precipitation region which means that the asphaltene was precipitated from the oil and when the pressure of the reservoir decreases more with oil production or with time it will cause asphaltene deposition in the reservoir by plugging the pores and reducing the permeability of the formation.

In this study, composite materials consisting of Activated Carbon (AC) and Zeolite were prepared for application in the removal of methylene blue and lead from an aqueous solution. The optimum synthesis method involves the use of metakaolinization and zeolitization, in the presence of activated carbon from kaolin, to form Zeolite. First, Kaolin was thermally activated into amorphous kaolin (metakaolinization); then the resultant metakaolin was attacked by alkaline, transforming it into crystalline zeolite (zeolitization). Using nitrogen adsorption and SEM techniques, the examination and characterization of composite materials confirmed the presence of a homogenous distribution of Zeolite throughout the activated carbon. It has also shown the carbonization process did not destroy the crystalline structure of the zeolite, which was revealed to be intact. Experiments in batch mode were conducted (using three differently-prepared composites, zeolite and activated carbon), to investigate the removal of methylene blue and lead from the aqueous solution of the sorbents. Key experimental parameters (initial concentration, pH, contact time and adsorbent dosage) from the obtained results were measured and analysed. Freundlich and Langmuir models were used to describe the adsorption isotherms, and the observed adsorption kinetic adhered to pseudo-second order

The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors affecting water quality. Tigris river water salinity increases with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research is to develop a salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plants along the Tigris River in Baghdad city using an artificial neural network model (ANN). The parameters used in the model are turbidity, electrical conductivity (Ec), total solids (T.s), suspended solids (S.s), and total dissolved solids (TDS) to predict the salinity (TDSout). Results showed that the effectiveness of the artificial neural network model in predicting the salinity is in good agreement between observed and predicted values of TDS, with determination coefficients of 0.998, 0.966, 0.997, 0.998, 0.996, and 0.996 for Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda respectively. This indicates that ANN is a successful tool for predicting the nonlinear equation of salinity under different and complicated environmental conditions along the river