Tishreen University Journal -Engineering Sciences Series,

Improving the performance of photovoltaic panels by cooling them with water

2023-12-27T13:11:53+00:00

Syria is blessed with plenty of sunshine over the whole year. The solar photovoltaic system is an appropriate alternative for the production of electricity. One of the major problems of photovoltaic plates PV is high temperature due to excessive solar radiation and high ambient temperature leads to reduced efficiency in solar panels.

The hybrid photovoltaic thermal (PV/T) systems are one of the most common methods for cooling photoelectric panels and improve performance. The (PV/T) systems are an solar technology that the enables simultaneous the conversion of solar energy into electrical and thermal energy. The heat from the PV panel is transferred through working fluids such as water. The extracted heat is used in low temperature applications, including household hot water

This paper discusses indoor experimental studies of the water-based (PV/T) system and compares this system with a normal PV panel without a cooling system. The (PV/T) system combined with solar water heater.

The results of the tests showed that the value of the current and voltage of the panel (PV/T) increased compared to the reference pane (PV). As well as a decrease in the temperature of the back surface of the panel (PV/T) compared to the reference panel (PV), where the value of the decrease reached from8 [°C] to 12 [°C], and increase in the temperature of the water coming out of the solar water heater, where the value of the increase reached from 6[°C] to 10 [°C].

Design Caisson Breakwaters in the Syrian Coast Based on Goda Equations

2023-10-24T21:25:01+00:00

Ports are exposed to forces that differ from other facilities, to maintain its performance and effectiveness, the engineering designs of facilities must be carefully studied, Protection facilities are considered one of the most important elements of the port because they provide a safe water area in which loading and unloading operations are perfect, designs for this type of breakwaters have been developed at five different depths according to the expected wave heights in the Syrian coast.

The research dealt with the design of breakwaters facilities such as caisson breakwater type, due to its many advantages in protection ports. the design dimensions, pressures, forces, and moments resulting from the impact of waves on the breakwater were calculated, which helped to study the stability factors on sliding and overturning, as well as the bearing capacity of the rubble foundation at the base of the caisson block, and the study showed that the facilities according to the proposed designs are safe and capable of providing protection in the Syrian coast.

Studying the Effect of Stratified Fluid on the Resistance and Flow Field of the KVLCC2 Tanker and DARPA Suboff using CFD

2023-12-07T10:39:31+00:00

This research aims to study the effect of stratified fluid on the resistance and flow field of ships and submarines. The influence of different speeds, drift angles, and positions of the internal surface on the resistance, the velocity field in the propeller plane, and the pressure field on the hull was studied.

The CFD, URANS method, and the k-ω Shear Stress Transport (SST) model with the ANSYS program were used to solve the Navier-Stokes equations. The Volume of Fluid method was used to capture the internal surface between stratified fluid layers. The study was carried out on a KVLCC2 model and a DARPA Suboff model. The numerical results were compared with the experimental ones, which agreed well. The effect of the presence of the stratified fluid on both the resistance and the flow field around these marine vehicles was then studied. The results confirmed that sailing a ship or submarine within a stratified fluid will inevitably lead to an increase in resistance and affect the flow field's characteristics around the vehicle's hull. The study proved that submarines are less affected by stratified fluid than ships due to their streamlined shape.

Study and define the criteria for evaluating the performance of Unsignalized intersections according to HCM 2016 methodology

2024-01-17T06:20:30+00:00

Unsignalized intersections (TWSC: Two Way Stop-Control) constitute a large percentage of intersections within cities and their suburbs. They are characterized by the presence of two directions of movement, major and minor. Drivers on the major street have priority over drivers on the minor street.

In this article, the effect of conflicting movements was studied using the HCM 2016 methodology (Highway Capacity Manual) on the performance of TWSC intersections. A four-leg intersection in Latakia city was studied by conducting field observation of the intersection and collecting geometric and traffic data to determine the criteria that most affect traffic movement. We calculated control delay, queue lengths, and level of service for each minor movement and comparing them to reality.

The results showed that the intersection operates with a very good level of service, with short delays, and that a queue rarely forms with more than one vehicle, with the exception of one minor leg, and the results were acceptably close to reality.

Vermicomposting for treating household organic solid waste, agricultural waste and sewage sludge

2023-09-16T05:50:28+00:00

The current trend in the waste management and disposal field focuses on transforming waste into useful materials or energy using various recycling and reusing methods. Using composting methods on organic solid waste have reduced the amounts of solid biological waste significantly. Therefore, research efforts are being made to develop sustainable and efficient techniques to treat organic waste and sewage sludge. In the past decades, vermicomposting have become a popular technique to produce high-quality composts, higher in nutrients than traditional composts and chemical fertilizers.

The aim of this research is to produce a safe and nutritious compost using the vermicomposting technique on organic solid household waste, agricultural waste, and sewage sludge. The studied worm species is the Eisenia Fetida, also known as the Red Wiggler worms.

The obtained compost proved to be rich in nutrients and conforming to the Syrian standard specifications for organic fertilizers. The worm species demonstrated high efficiency in decaying organic waste transforming it into a stable material, rich in nutrients, which can be safely used as an alternative to chemical fertilizers to enhance the soil nutritional levels.

Development of Spatial Model for Drinking Water Distribution in Mountain Villages in Lattakia Governorate

2024-03-03T10:28:30+00:00

The process of planning the infrastructure needed to manage drinking water in mountain villages is considered one of the complex processes facing decision-makers. This problem is evident in Syria in general and in Latakia Governorate in particular, and is represented by the spread of the phenomenon of thirsty mountain villages that lack drinking water service, as there are many standards contributing the planning process of drinking water management, and there is a clear discrepancy in the opinions of experts providing services in this field. To overcome this problem, this research is aiming to develop a mechanism for drinking water management in mountain villages, which includes combining between the Point allocation method (PAM) and GIS functions in order to produce several analytical maps reflecting our suggested criteria in the targeted area.

The study resulted with producing a combined surface map for the potential areas of intervention, which identify priority locations for interventions to serve drinking water networks, which makes following this mechanism an essential stage when planning the necessary infrastructure for drinking water management according to the real stakeholders.

New technology using Arduino and capacitive sensors to reduce olive oil waste in the mills operating in the Syrian coast

2023-08-12T08:56:34+00:00

In this research, a system was designed to monitor the quality of olive oil production within industrial facilities to ensure quality and reduce waste in secondary outputs, as well as save time and effort in training individuals and enable consumers and producers to evaluate the oil's quality and determine the amount of waste quickly and easily without the need for complex equipment, specialized expertise, or corrective actions.

To design the appropriate system, two directions were followed: the first direction includes calibration and data collection processes, while the second direction is specific to monitoring operations, data storage, and display.

The proposed system represents a new method for monitoring the quality of olive oil production, as it includes a capacitor designed with specific dimensions and measurements to work with a dedicated control circuit for measuring the dielectric constant of olive oil and determining its quality (the amount of water in the oil). It also aims to reduce olive oil waste in the olive oil water generated from the mills (the amount of oil in the olive oil water) and display the results directly on the LCD display screen, in addition to the LabView display interface, which allows for displaying the measured information in an easily readable format and remote storage and monitoring. The Arduino IDE programming environment was used to program the controller. The UART communication protocol was used to achieve communication between the smart controller and the programming interface.

The test results compared to the calibration values indicate that the designed system possesses speed, accuracy, and high efficiency in monitoring the quality of olive oil production.

Improving brain tumor classification using convolutional neural networks (CNNs) For MRI images of the brain

2024-01-07T10:03:57+00:00

Brain tumors are serious and fatal diseases, which often lead to a decrease in human life expectancy. Early and accurate detection of the nature and classification of these tumors is crucial for developing an appropriate treatment plan that can lead to prolonging the lives of patients with these tumors. Manual diagnosis of large quantities of brain MRI images is considered extremely difficult and complex, and requires the diagnosing physician to have high experience and great accuracy in classifying each type of these tumors according to its shape, dimensions, and location in the human brain. Therefore, an intelligent model based on deep learning (DL) must be developed to accurately diagnose and classify brain tumors. In this study, we will propose a new deep learning (DL) model based on convolutional neural networks (CNNs). This model uses a number of algorithms for the initial processing of MRI images and to be input to the convolutional neural network that In turn, it contains, in addition to the input layer, a number of hidden internal convolutional layers, which perform a number of mathematical operations on the input data to extract features from brain MRI images, and a number of pooling layers, which select the most important features from the total of extracted features, and full connection layers, which create paths. Additional neurons between layers. This allows the network to learn complex relationships between features and make high-level predictions. The results obtained by applying the new model achieved an accuracy rate of 99.6% on an MRI brain tumor dataset obtained from a database Kaggle Brain tumor dataset and over relatively small time frames make this model extremely useful for neurologists to help make quick and accurate diagnostic decisions.

Study of the scale effect on the resistance components and the flow field around the bulk carrier ship

2024-01-28T05:29:17+00:00

In order to create environmentally friendly ships, it is crucial to estimate the hydrodynamic behavior of the hull accurately. The main factors to consider are the ship resistance and the flow field around the ship, as these directly impact the ship's energy efficiency. Therefore, it is important to understand how the ship's scale affects its resistance components and flow field. In this study, CFD was used to conduct the numerical calculations of the bulk carrier ship at various scales at Froud number 0.142. To analyze the scale effects, the total resistance was separated into individual components. The simulation results were compared with experimental data to validate their accuracy. Finally, the hydrodynamic characteristics of the ship were studied and analyzed at different scales.

A Numerical Study for Predicting the Spread of Marine Pollution Using the Finite Elements Method

2024-01-17T11:42:28+00:00

The phenomenon of pollution in the field of maritime transport is considered one of the most significant topics that drive maritime organizations to set the standards and conditions necessary to reduce its negative effect with the aim of preserving the environment. The predictability of the spread of pollutants in seas allows good control of those. In this study; a numerical model is proposed to solve the differential equations of pollutants diffusion using the finite element method, where the numerical solution of Laplace equation of an irrotational flow is combined with the numerical solution of the diffusion equation, the last one is considered as an unsteady equation, which requires the use of an algorithm to ensure the stability of the numerical solution after taking into account both the boundary and initial conditions. The result of this study allows evaluating the distribution of streamlines within the flow field as well as determining the new coordination of pollutants after a specified period of time, or vice versa, i.e., calculating the time demanded by the pollutant to reach a specific area of the flow.

Comparison between convolutional neural networks (CNNs) and support vector machine algorithm (SVM) in classifying brain MRI tumors.

2024-02-04T08:47:11+00:00

Brain tumors are among the diseases that endanger human health. This disease not only harms people physically, but also puts financial and emotional obstacles to family and professional life. The key to early diagnosis of brain tumors is to draw conclusions from doctors' observation of MRI images of the brain. Brain tumors are divided into high-grade tumors and low-grade tumors. However, because each doctor has different experience and approaches to treating tumors, doctors have no way to have a uniform classification standard for brain tumors. In this research, a large number of brain MRI images were obtained from the 2019 Brain Tumor Segmentation challenge dataset. We process the brain MRI image data through a computer, and then train the data through a machine learning algorithm, which can classify tumors. brain effectively. In the experiment, convolutional neural network and support vector machine were used as the model training algorithm. The accuracy of the support vector machine on the test set was 84.3%, while the performance of the convolutional neural network on the test set was 77.6%. From the two experimental results, it can be concluded that the performance of SVM is better than that of CNN in both brain tumor classifications. In addition, in this study we also tried to improve the model performance through different model parameters. This research can be applied to the system for diagnosing brain tumors as well as other tumors. We hope that this paper will provide researchers with useful experience in this field.

Study of the consolidation and creep behavior of marl soil in the Rastain area

2024-02-05T16:43:29+00:00

The marly soil in the Rastin-Latakia region is a sedimentary soil with a consistency between hard and semi-hard. It is spread in large thicknesses and in different colors in the sloping land of Rastin adjacent to the 6th Tishreen Dam.

The settlement behavior of this soil is affected by the values of pre-stress, and its creep behavior on slopes is affected by the amount of its viscosity. index.

The settlement values are related to the value of the Oedometric deformation modulus, taken in terms of stresses. In order to characterize the behavior of deformation, stress experiments were conducted on 19 samples taken from the boreholes in the studied area.

The triaxial experiment was computer-modeled using the PLAXIS2020 program, and the values of n , w the constants of the Oedometer deformation modulus equation and the relationship between them and the moisture content and porosity were determined. Also, the values of the viscosity index I_v for the tested soil and its relationship to the liquid limit were determined to conclude the extent to which the results influence the assessment of the behavior of deformation and creep and the possibility of moving slopes in the area.

Determine the Best Location for Maintenance Centers and Breakdown Management for Drinking water Supply Network for the City of Jableh using GIS

2024-01-17T06:43:28+00:00

The crisis has left Syria with numerous impacts, left its impact on all the Syrian governorates, and its results have been reflected on the economic and service realities of the population. The water sector is considered one of the sectors affected by the effects of this crisis, from cutting water to damaging water networks, and the suspension of many major pumping stations and wells. This research aims to identify how to manage and maintain the drinking water network in cities by using geographic information systems technology GIS in order to assist decision makers in reaching less costly and timely solutions, especially in the circumstances of the crisis that Syria suffers in general, through collecting, entering, treating and managing the rules Spatial and descriptive data for the drinking water network in the city of Jableh as a case study with a focus on the system for managing and maintaining this network based on the spatial analysis of the faults of this network over three years (2017-2018-2019) and choosing the ideal place for maintenance centers in this city.

Analysis and Evaluation of Piezometric Measurements in Al- Basel Dam in Tartous

2024-01-03T04:37:05+00:00

Piezometric measurements contribute to giving a clear idea of the levels of seepage water and their changes over time, and provide a suitable database for analysis and to show any emergency structural or hydraulic problem resulting from the seepage, interpret it, and determine its causes.

This study aims to analysis the piezometric measurements in in Al- Basel dam in Tartous, by studying the changes in water levels in the piezometric wells in relation to the storage levels in the reservoir, and link them to a specific relationship, to form a guideline that enables us to detect any emergency problem or any wrong measurement and take or suggest the necessary measures to confirm and process them.

The study revealed that significant changes in water levels occurred in some of the crest wells, requires investigation and identification of the causes. Therefore, three scenarios were proposed to find out the cause of the problem and build mathematical models using the SEEP/W program. Analysis the results showed the presence of a clogging in the first filter layer as a result of soft, erosion materials being placed in it, coming from the core or materials resulting from the oxidation of water with soil compounds, accurate analysis requires collecting samples water from wells and conducting the necessary analyses.

Design and Modeling of a Single and Matrix Printed Band Antenna Using HFSS Software

2023-06-26T17:52:32+00:00

The research includes an introduction to the antennas and parameters of the study of each antenna in general, and definition of the types of antennas according to a simplified explanation before reaching the study of the printed slat antennas, their types methods of manufacturing and feeding them in the method of the transmission line model. then we continue to present the array antennas of which the second part of research is the practical section which includes a practical design study of a single segmental antenna using the HFSS simulation program and an array design of these antennas. the biggest problem facing this research is the difficulty of practical implementation of the required antennas, as a result of the unavailability of the required insulting materials to form the base layer, and the lack of laboratories necessary to measure, and test these antennas if they are designed. Therefore, we resorted to a design similar to the patch antennas found in the antenna laboratory at the university and compared the results obtained in the simulation with the practical results.

Improving Performance Of Motor Imagery Systems Using Ensemble Classifier

2023-09-30T10:28:12+00:00

The algorithms and methods used in the field of recognizing brain signals have varied, especially the motor imagery systems based on the electroencephalogram, whether in the pre-processing stage or in the classification stage, but these systems still lack sufficient accuracy to implement them practically, so it is necessary to improve the recognition rate and on several standard data sets to ensure the effectiveness of these systems.

This research proposes a hybrid recognition system to recognize brain signals based on the electroencephalogram (EEG), using the Ensemble classifier, Where two ensemble classifiers were designed, the first consisting of four sub-classifiers, SVM, Fandom Forest, Logistic Regression, and KNN, and the second classifier consisting of two sub-classifiers, Random Forest and Logistic Regression, and using FBCSP in the pre-processing stage. The proposed system was tested on three datasets, IV2a. , IV2b, and AlexMI, reaching recognition rates of 88.69%, 82.71%, and 87.18%, respectively.

Enhancing the urban identity of coastal public spaces in the city of Lattakia- South Corniche case study

2024-02-27T07:45:20+00:00

Coastal public space is considered one of the important and distinctive characteristics of cities and urban coastal communities. Recently, as a result of rapid growth, most coastal public spaces have become similar and lost their identity.

Lattakia city has many coastal public spaces. However, it suffers from the absence of meaning in the identity of the coastal public space, and the weak role of its current planning in enhancing that identity. Therefore, the question that arises is to what extent is the current planning of coastal public spaces in the city of Lattakia able to enhance its identity?

This paper aims to provide reference guidelines for the future planning and design of coastal public spaces in the city of Latakia, in a way that enhances its identity.

Research Methodology: The research method used is a descriptive analytical method, relying on studies, observation and interviews as sources of data, and identifying forms of identity of the space, including all relevant elements.

Results: The results of this research showed that the studied state suffers from a set of problems that limit its ability to enhance its urban identity.

The research concluded with recommendations that could contribute to the development of coastal public space planning.

Using blockchain technology in Intelligent Control Systems

2024-01-09T07:40:05+00:00

Data security is especially important in automation systems that require the exchange of data over large distances through both telecommunications and telecommunications, which in turn is a fertile environment for piracy, not far from the attack on the Manouchehr nuclear reactor in Iran.

The use of Blockchain technology may increase the security of the data exchanged because it is difficult to intercept its messages through its encryption system, and it also ensures the integrity of this data.

In this research, a blockchain algorithm was proposed that works on the same microcontroller and uses the RS322 serial connection and was tested by using the Atmega2560 controller (an 8-bit processor with 8 KB SRAM memory) for a smart home system that measures temperature and humidity, as well as senses the presence of gas and measures the intensity of lighting in order to control the equipment of this house, the results proved that it is not possible to Use this technique on microcontrollers.

Detection of vivax and falciparum malaria using deep learning techniques

2024-01-17T18:03:39+00:00

Although malaria is uncommon in temperate climates, malaria is still common in tropical and subtropical countries. Every year, approximately 290 million people are infected with malaria, and more than 400,000 people die from this disease.

In this research, the dataset was downloaded from the Kaggle website, which consists of 27,558 images of infected people and healthy people, divided into: 13,779 images of healthy people, 6890 images of people infected with falciparum malaria, and 6889 images of people infected with vivax malaria. Initially, the images were pre-processed (fogification - noise removal - morphological operations), after which the convolutional neural network (CNN) was built, trained and tested, where the data was divided into two groups, 80% training and 20% testing, and then comparison was made between several pre-trained models. The proposed model achieved the best evaluation accuracy among the pre-trained models, and the results gave an accuracy rate of 96.5%, a sensitivity rate of 95%, and a specificity rate of 97.6%. Thus, the results demonstrate the effectiveness of the proposed algorithm as an assistive model for doctors in diagnosing malaria.

Suggest Algorithms to Solve the Problems of Assembly System Balancing Using Computer

2023-09-16T05:48:06+00:00

The twenty-first century witnessed a staggering development in industrial production processes, as international companies began to support computer-aided manufacturing and assembly systems in their production to keep pace with the development of modern knowledge and science. Hence, it is necessary to study these systems more deeply if we want to compete with other companies.. Perhaps the most important cause of these problems is the wasted time due to the absence of planning and standard instructions on the assembly line. All this prompted the need for researchers to develop many methods and algorithms that help manage assembly lines more efficiently. The term of Production Line Balancing refers to arranging and allocating assembly operations with the aim of ensuring a regular flow when the assembly line is operating. Moreover, balancing is an effective tool used to develop assembly line productivity in various fields as it helps to eliminate bottlenecks, and also helps to increase production rate and efficiency. First, we conducted a comprehensive literature review of the subject, then looked at how to classify assembly line problems, then introduced the COMSOAL algorithm, which is one of the most important methods directed at solving assembly system balancing problems. As for the applied study, we developed three proposed and hybrid algorithms, starting with the COMSOAL algorithm, where the aim was to find ways to solve all types of ordinary assembly line problems within proposed flow charts, based on previous studies..Then we tested the proposed algorithms and compared them with a reference case and the results were identical.

Distance Protection Using Fuzzy Logic

2023-12-27T10:57:18+00:00

When there is a malfunction, the protection is sensitive to the malfunction. If the disconnection command is sent instantaneously, it is possible to disconnect the transmission line without a malfunction requiring disconnection. Another way to give an unconsidered time limit may lead to the malfunction continuing for a long enough period to cause damage to the equipment, so it must be determined. The exact value of the fault current that must be detected by the protection, in addition to the appropriate choice of time delay depending on the type of fault. All of these questions were the reason for our choice of fuzzy logic in controlling this protection to study the effect of this control on the performance of the protection, as some references suggest the presence of a time delay between 0 and 4.5 seconds depending on the type of fault.

A Hybrid Approach for Congestion Control in Vehicular Ad-Hoc Networks

2024-01-30T08:06:46+00:00

In this research, mobile vehicle networks and congestion in this type of networks were identified, and a group of congestion control algorithms was reviewed. A hybrid algorithm that works to adapt the data transmission rate and the transmission power capacity for vehicles in Ad-Hoc networks is proposed. The proposed hybrid algorithm is based on data rate control together with transmission power adaptation to improve the network performance. Simulation results show that the proposed hybrid algorithm achieves better performance, compared to the reference studies, in terms of four parameters. Higher network throughput, higher PDR (Packet Delivery Ratio), lower PLR (Packet Loss Ratio), and lower CBR (Channel Busy Ratio) were obtained, compared to the reference algorithms that deal separately with data transmission rate or power transmission capacity.