TR-Dizin İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396

Browse

Now showing 1 - 9 of 9

Carbon Dioxide Absorption Using Different Solvents (Mea, Naoh, Koh and Mg(Oh)2) in Bubble Column Reactor
(2023) Gul, Ayse; Un, Umran Tezcan; 01. Abdullah Gül University; 02.03. İnşaat Mühendisliği; 02. Mühendislik Fakültesi
The aim of this research is to reduce emissions by capturing carbon dioxide in a solution using an absorption method. The absorption capacity, absorption rate, carbon dioxide removal efficiency, and overall mass transfer coefficient of MEA (Monoethanolamin) and alkaline solvents (NaOH, KOH, Mg(OH)2) were investigated using a bubble column gas absorption reactor with counter current flow. The effects of operational parameters such as solvent concentration (0.01, 0.05, and 0.25M) and solvent type were studied. As a result of the study, it was determined that Mg(OH)2 was less effective in capturing CO2 than KOH, NaOH, and MEA. For all solvent types, the total mass transfer coefficient, absorption rate, and CO2 removal efficiency were increased with the increase in the concentration of solvent. The solvent concentration is increased from 0.01 M to 0.25 M to obtain the highest KGa values for MEA, NaOH, and KOH, 3.75 1/min for MEA, 3.70 1/min for NaOH, and 3.93 1/min for KOH.The MEA, NaOH, and KOH absorption rates were maximum at 0.25 M solvent concentrations as 0.19x103 mol/Ls. The maximum CO2 removal efficiencies for MEA, NaOH, and KOH at 0.25 M solvent concentration are greater than 60%. The highest absorption capacity, 0.576 mol CO2/mol MEA, was obtained at a solvent concentration of 0.01M MEA.
A Comparative Analysis of Passenger Flow Forecasting in Trams Using Machine Learning Algorithms
(2024) Akbaş, Ayhan; Dedeturk, Beyhan Adanur; Dedeturk, Bilge Kagan; 01. Abdullah Gül University; 02. 04. Bilgisayar Mühendisliği; 02. Mühendislik Fakültesi
Forecasting tram passenger flow is an important part of the intelligent transportation system since it helps with resource allocation, network design, and frequency setting. Due to varying destinations and departure times, it is difficult to notice large fluctuations, non-linearity, and periodicity of tram passenger flows. In this paper, the first-order difference technique is used to eliminate seasonal structure from the time series data and the performance of different machine learning algorithms on passenger flow forecasting in trams is evaluated. Furthermore, the impact of the Covid-19 pandemic on forecasting success is examined. For this purpose, the tram data of Kayseri Transportation Inc. for the years 2018-2021 are used. Different estimation models including Linear Regression, Support Vector Regression, Random Forest, Artificial Neural Network, Convolutional Neural Network, and LongTerm Short Memory are applied and the time series forecasting performances of the models are evaluated with MAPE and R2 metrics.
A Comparison of Ensemble and Base Learner Algorithms for the Prediction of Machining Induced Residual Stresses in the Turning of Aerospace Materials
(2022) Buyrukoglu, Selim; Kesriklioglu, Sinan; 01. Abdullah Gül University; 02.06. Makine Mühendisliği; 02. Mühendislik Fakültesi
The estimation of residual stresses is essential to prevent the catastrophic failures of the components used in the aerospace industry. The objective of this work is to predict the machining induced residual stresses with bagging, boosting, and single-based machine learning models based on the design and cutting parameters used in the turning of Inconel 718 and Ti6Al4V alloys. Experimentally measured residual stress data of these two materials was compiled from the literature, including the surface material of the cutting tools, cooling conditions, rake angles, as well as the cutting speed, feed, and width of cut to show the robustness of the models. These variables were also grouped into different combinations to clearly show the contribution and necessity of each element. Various predictive models in machine learning (AdaBoost, Random Forest, Artificial Neural Network, K-Neighbors Regressor, Linear Regressor) were then applied to estimate the residual stresses on the machined surfaces for the classified groups using the generated data. It was found that the AdaBoost algorithm was able to predict the machining induced residual stresses with a mean absolute error of 18.1 MPa for the IN718 alloy and 31.3 MPa for Ti6Al4V by taking into account all the variables, while the artificial neural network provides the lowest mean absolute errors for the Ti6Al4V alloy. On the other hand, the linear regression model gives poor agreement with the experimental data. All the analyses showed that AdaBoost (boosting) ensemble learning and artificial neural network models can be used for the prediction of the machining induced residual stresses with the small datasets of the IN718 and Ti6Al4V materials.
Computational Fluid Dynamics (CFD) Analysis of 3D Printer Nozzle Designs
(2024) Hajili, Rasul; Temirel, Mikail; 01. Abdullah Gül University; 02.06. Makine Mühendisliği; 02. Mühendislik Fakültesi
Additive manufacturing, particularly 3D printing, has gained significant attention recently due to its flexibility, precision, and sustainability. Among the various 3D printing technologies, Fused Deposition Modeling (FDM) stands out as one of the most popular due to its affordability, ease of use, and print quality. However, a major drawback of FDM-based 3D printers is their relatively low print resolution. One of the key factors influencing print quality is the nozzle design, especially its geometry. As a result, numerous studies in literature have focused on improving 3D printing performance by optimizing nozzle design. In this study, we investigated the effects of nozzle geometry from a Computational Fluid Dynamics (CFD) perspective, examining three aspects: die angle, outlet size, and outlet shape. The CFD analysis revealed that the die angle primarily influences the shear stress within the nozzle, while the outlet size has a significant impact on velocity and pressure difference. The outlet shape affects shear stress, velocity, and pressure difference to a lesser extent than the die angle and size.
In Silico Evaluation of the Potential of Natural Products From Chili Pepper as Antiviral Agents Against DNA-Directed RNA Polymerase of the Monkeypox Virus
(2024) Fidan, Ozkan; Mujwar, Somdutt; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
This study focused on the discovery of new drug candidates effective against the monkeypox virus. Virtual screening was performed to evaluate the potential of chili pepper natural products against homology-modeled DNA-directed RNA polymerase of the monkeypox virus using molecular docking. Our findings revealed that structurally similar triterpenes such as α-amyrin, β-amyrin, and β-sitosterol had strong binding affinities towards the DNA-directed RNA polymerase and can inhibit this pivotal viral enzyme. The stability of one of the drug candidate molecules, α-amyrin with the strongest binding affinity towards the binding cavity of the enzyme was also confirmed via molecular dynamics simulation. This study showed that α-amyrin is a promising DNA-directed RNA polymerase inhibitor to treat monkeypox disease. It also paves the way for the idea of the potential dietary supplement candidate for monkeypox patients.
Investigation of Antiviral Potential of Food Carotenoids and Apocarotenoids Against RNA-Dependent RNA Polymerase of Hepatitis C Virus
(2022) Fidan, Ozkan; 01. Abdullah Gül University; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
Hepatitis C disease have been a global health threat and affects a significant portion of world population. Hepatitis C have also been a silent health threat for Turkiye, where there are around half million people infected with Hepatitis C Virus (HCV). Disease burden and mortality are expected to increase gradually in the next 20 years in Turkiye. Unavailability of enough data on the currently-available drugs in routine clinical practice, their side effects and interactions with other drugs, and their efficacies on the less common genotypes indicates the necessity of alternative treatment options. Natural products from herbal and medicinal plants can indeed provide an alternative as being drug-like dietary supplements. In particular, the carotenoids and apocarotenoids are underexplored in their antiviral potential, including anti-HCV activities. Therefore, we focused on the virtual screening of various carotenoids and apocarotenoids against the RNA-dependent RNA polymerase (RdRp) of HCV. Molecular docking experiments showed strong binding affinities of the ligands to both palm and thumb domains of RdRp of HCV. In fact, some of them such as neoxanthin, crocin, canthaxanthin and cryptoflavin bound quite strongly to both domains compared to native ligands and current antiviral drugs. MD simulation for neoxanthin-RdRp complex confirmed the stability of the ligand within the binding cavity of RdRp throughout 100 ns simulation. This clearly indicated the potential of carotenoids, specifically neoxanthin, as RdRp inhibitor in treating HCV. Thus, this study not only discovered anti-HCV drug candidates with the properties of easy-to-access and low cost, but also paved the way for the development of carotenoid or apocarotenoid based dietary supplement candidates for the prevention and treatment of HCV.
Optimal Location Determination of Electric Vehicle Charging Stations: A Case Study on Turkey's Most Preferred Highway
(2022) Gülbahar, İbrahim Tümay; Sütçü, Muhammed; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi
Today, electric vehicles are seen as one of the most suitable and environmentally friendly alternatives to internal combustion engine vehicles. An important issue related to the dissemination of electric vehicles is the location of the vehicle charging network and specifically the optimum location selection of the charging stations. Generally, most of the studies focus on popular destinations such as city centers, shopping areas, bus stations, and airports. Although these places are often used in normal life, they can usually provide an adequate solution for daily charging needs due to the number of alternative charging stations. However, finding adequate charging stations is not possible in intercity travels especially in highways. In this paper, we proposed a decision model to determine the location of electric car charging stations in highways. We create an optimization model to decide the optimum locations for the charging stations that can meet the customer demands on the Istanbul-Ankara highway. The proposed model determines optimum charging stations that enable passengers traveling with their electric vehicles to travel in Istanbul-Ankara highway in the shortest time.
Optimization of Warehouse Location and Inventory Management for an Industrial Textile Manufacturer Company in Türkiye
(2024) Kaya, Rukiye; Tutkun, Tutku; Nergiz, İrem Nur; Satic, Ugur; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi
In this study, we consider the demand forecasting, facility location, and inventory management problems of an industrial textile manufacturer company in Türkiye. First, we begin with the demand forecasting problem for thirty-two different products and employ ABC analysis to categorise the products. Then we test multiple forecasting methods and find out that Exponential Smoothing and Croston's TSB methods perform better in our categories. Using the demand forecast results in the facility location problem, we search for a location in Europe for a warehouse. For the facility location problem, we use a mixed-integer nonlinear mathematical model to minimise the transportation cost, and warehouse rental cost. We solve the model by using GAMS Solver. Then, we handle the inventory management problem and determine the quantity of the products that are sent from the factory and the warehouse to the customer. We propose a genetic algorithm approach that generates reorder quantities and reorder points for both the factory and the warehouse to minimise the total logistics costs, including holding, ordering and stockout costs. We use simulation models to calculate the logistics costs then we use these costs as fitness values to choose the best reorder quantities and reorder points. The proposed approach offers improvement in demand forecasting, inventory management, and facility location problems and brings up a 26% reduction in total logistic costs.
Symbolic Aggregate Approximation-Based Clustering of Monthly Natural Gas Consumption
(2024) Söylemez, İsmet; Ünlü, Ramazan; Nalici, Mehmet Eren; 01. Abdullah Gül University; 02.02. Endüstri Mühendisliği; 02. Mühendislik Fakültesi; 07. Fen Bilimleri Enstitüsü; 07.03. Endüstri Mühendisliği Anabilim Dalı
Natural gas is an indispensable non-renewable energy source for many countries. It is used in many different areas such as heating and kitchen appliances in homes, and heat treatment and electricity generation in industry. Natural gas is an essential component of the transportation sector, providing a cleaner alternative to traditional fuels in vehicles and fleets. Moreover, natural gas plays a vital role in boosting energy efficiency through the development of combined heat and power systems. These systems produce electricity and useful heat concurrently. As nations move towards more sustainable energy solutions, natural gas has gained prominence as a transitional fuel. This is due to its lower carbon emissions when compared to coal and oil, thus making it an essential component of the global energy framework. In this study, monthly natural gas consumption data of 28 different European countries between 2014 and 2022 are used. Symbolic Aggregate Approximation method is used to analyse the data. Analyses are made with different numbers of segments and numbers of alphabet sizes, and alphabet vectors of each country are created. These letter vectors are used in hierarchical clustering and dendrogram graphs are created. Furthermore, the elbow method is used to determine the appropriate number of clusters. Clusters of countries are created according to the determined number of clusters. In addition, it is interpreted according to the consumption trends of the countries in the determined clusters.

Browse

Browsing TR-Dizin İndeksli Yayınlar Koleksiyonu by Journal "Bitlis Eren Üniversitesi Fen Bilimleri Dergisi"