This study investigated the application of the crystallization process for oilfield produced water from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). Zero liquid discharge system (ZLD) consists of several parts such as oil skimming, coagulation/flocculation, forward osmosis, and crystallization, the crystallization process is a final part of a zero liquid discharge system. The laboratory-scale simple evaporation system was used to evaluate the performance of the crystallization process. In this work, sodium chloride solution and East Baghdad oilfield produced water were used as a feed solution with a concentration of 177 and 220 g/l. The impact of temperature (70, 80, and 90 °C), mixing speed (300, 400, and 500 rpm), feed concentration (177 and 220 g/l), and time (0.5-9.5 h) on the crystallization performance for oilfield produced water treatment were investigated on evaporation rate and recovery. The recovery increased with increasing temperature and mixing speed while decreasing with an increase in feed concentration. Pure water and salts were recovered from the concentrated produced water, the recovery of pure water at 80 °C, 400 rpm, and 220 g/l feed concentration was 82.22 and 81.35% after 5.5 h for NaCl solution (i.e., simulated oilfield produced water) and oilfield produced water, respectively.
Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste
... Show MoreThis paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.
Due to the intensity of competition between economic units that run the trade in durable goods had to pay a lot of these companies to follow the new selling methods aimed at attracting customers to be able to increase its sales and thereby increase their profits , these methods are installment sales, which had been in great demand by the customers with limited income, who provides them with the possibility of possession and use of such goods and to postpone the full amount of the payment to the seller, This transaction sales have grown even became installment sales system at the present time of the common types of sales transactions and deployed a lot in our environment and in many sectors of the market, and in some cases m
... Show MoreThe rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreWildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show More
The organizational culture is an effective control mechanism that dictates the behavior of employees and according to their intellectual and social orientations, so it is considered a more powerful way to control employee orientations and determine their management according to organizational rules and regulations, as it was one of the most important factors determining the performance of organizations, while organizational performance is a measure of what the organization has achieved from the objectives of the scheme To ensure that it faces various changes and remains within the global competition, and to reach that it was necessary to identify the most prominent and most important research problems in knowing the extent of com
... Show MoreA Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and
... Show MoreThis work aims to study the exploding copper wire plasma parameters by optical emission spectroscopy. The emission spectra of the copper plasma have been recorded and analyzed The plasma electron temperature (Te), was calculated by Boltzmann plot, and the electron density (ne) calculated by using Stark broadening method for different copper wire diameter (0.18, 0.24 and 0.3 mm) and current
of 75A in distilled water. The hydrogen (Hα line) 656.279 nm was used to calculate the electron density for different wire diameters by Stark broadening. It was found that the electron density ne decrease from 22.4×1016 cm-3 to 17×1016 cm-3 with increasing wire diameter from 0.18 mm to 0.3 mm while the electron temperatures increase from 0.741 to