563 research outputs found
Artificial neural network modelling for polyethylene FSSW parameters
No full textIn a Friction Stir Spot Welding (FSSW) process, welding parameters (the tool rotational speed, tool plunge depth, and stirring time) affect the nugget formation in high-density polyethylene (HDPE) sheets. The size and microstructure of the nugget determine the resistance of the joint to outer forces. The optimization of these parameters is vital to obtaining high-quality welds. Feed forward back-propagation artificial neural network models are developed to optimize the FSSW parameters for HDPE sheets. Input variables of these models include tool rotation speed (rpm), the plunge depth (mm), and the stirring time (s) that affect lap-shear fracture load (N) output. Prediction performances of 6 models in different specifications are compared. These models differ in terms of the training dataset used (80%-100%) and the number of neurons (5-10-20) in a hidden layer. The best prediction performances are obtained using 20 neurons in a hidden layer in both training dataset. There is good agreement between developed models' predictions and the experimental data. (c) 2018 Sharif University of Technology. All rights reserved
THE MODELING OF TENSILE TEST IN VIRTUAL LABORATORY DESIGN USING ARTIFICIAL INTELLIGENCE
No full textIn the future, Virtual Laboratories will have a very important place for distant education which has real applications of laboratory tests and experiment applications. It is fact that virtual laboratories necessity is inevitable because the requirements of materials, place, staff and above all, time and financial requirements for establishment of real laboratories. Virtual Laboratories, if its visuality qualifications are convenient, can easily provide like real laboratories which's users can observe the experiments with making changes on the parameters. In this study tensile test was examined for virtual laboratories and it is also aimed at designing the tensile test in virtual environments for different tensile speeds. An artificial neural network was generated from the values of a material which was stressed in different speeds and intermediate speed values were predicted by this artificial neural network
Modeling of surface temperature distributions on powered e-textile structures using an artificial neural network
No full textAn artificial neural network (ANN) model is constructed to derive the surface temperature of e-textile structures developed for cold weather clothing. A series of textile transmission lines made of different types of conductive yarns, insulated by using different types of seam tapes, were enclosed in a thermoplastic textile structure via hot air welding technology, and then they were powered with different levels of specific voltages in order to obtain different heating levels. The surface temperatures of the powered e-textile structures were measured using a thermal camera. The experimental input variables, sample type, temperature, feeding speed, resistance of samples, applied voltage and current were used to construct an ANN model and the outputs of surface temperature and electric power dissipated were used to test the prediction performance of the developed model. It was concluded that the ANN provided substantial predictive performance. Simulations based on the developed ANN model can estimate the surface temperature distributions of powered e-textile structures under different conditions. The ANN model developed for prediction of electric power dissipated was very successful and can be useful for e-textile product designers as well as textile manufacturers, particularly for cold weather protection products such as jackets, gloves and outdoor sleeping mats
Artificial neural networks modeling for the prediction of Pb(II) adsorption
No full textThe work presents an artificial neural network (ANN) model predicting the efficiency of Pb(II) adsorption on polyamine-polyurea polymer modified with pyromellitic dianhydride. Adsorption percentages of Pb(II) ions, as calculated using the results of batch experiments, are used as data inputs for the ANN model. In the developed model, the contact time (5-240 min.), pH (1-7), the initial Pb(II) concentration (50-300 mg/L), amount of adsorbent (20-75 mg) and temperature (25-55 degrees C) values constitute the input layer, while adsorption percentage values constitute the output layer. Simulation-based development of ANN models was carried out with eight values for neurons in the hidden layer (2, 3, 5, 10, 20, 30, 50 and 100). The best results were obtained with 10 neurons. The prediction data of ANN models were statistically compared to experimental data. With the developed model's trial period and cost savings, the adsorption ratio was estimated with an error rate of about 2%. The results show that the multilayer perception ANN model (R-2 = 0.9858) justified the prediction of adsorption percentage
2D modeling temperature development of mass concrete structures at early age - 2018
No full textAlper Yıkıcı (MEF Author)In this paper, a 2D finite volume analysis methodology was used to predict temperature development within three different bridge pier caps. MATLAB® was employed to generate a program that solves the governing heat transfer equation where development of thermo-physical concrete properties was defined as a function of degree of hydration. The rate of heat generation was obtained experimentally via adiabatic calorimetry and the activation energy was determined following the ASTM C 1074 procedure to implement equivalent age concept. 2D finite volume analysis results were presented in comparison with the recorded concrete temperatures from the field. Accordingly, temperature time histories at the center and the side surface of the bridge pier caps were predicted reasonably well using the concrete mixture information and the measured concrete hydration properties.WOS:0005502533000742-s2.0-85134814600Conference Proceedings Citation Index- ScienceProceedings PaperHaziranYÖK - 2017-1
A Web-Based Virtual Experiment in Material Science: Tensile Test Laboratory Application
No full textVirtual laboratories have a very important place for distant education which has real applications of laboratory tests and experiment applications. It is fact that virtual laboratories necessity is inevitable because of the requirements of materials, place, staff and above all, time and financial requirements for establishment of real laboratories. The main concept of virtual laboratory is to replace real machines with their virtual simulations. Real investigative equipment is not often available for students, researchers, and practitioners as users in addition to their expensive costs in usage. Virtual laboratories are cheap and safe in use because all mistakes can be easily erased by web-based application or simulation reset without any consequences. Furthermore users can easily make many tests regardless of place in any time on the web. In this study AISI 4140 steel was used, since AISI 4140 steel is the most well-known type of steel used in industries. Tensile test of the steel was examined regarding to different tensile speeds. The study aimed to design the web-based virtual tensile test laboratory. The uniqueness of this study is generating an artificial neural network model by using the values of the material which is stressed in different speeds. Thanks to this model, intermediate speed values were predicted. Besides that, this model was used to design web-based virtual tensile test laboratory application. With the help of this application, users can easily realize the yield strength, ultimate strength and fracture strength on stress-strain diagram
Effects of Curing Temperature on Chloride Migration and Electrical Resistivity of Concrete, Materials, Systems and Structures in Civil Engineering
No full textAlper Yıkıcı (MEF Author)##nofulltext##..
A conceptual framework for cloud-based integration of Virtual laboratories as a multi-agent system approach
No full textWith the rapid development in information technologies, numerous Virtual laboratory (VL) studies are being conducted in various fields such as material science, computer science, chemistry and education. While the number of VL studies are rising, possible interactions between these VLs have not been studied yet. The aim of this study is to create a framework in order to gather all VLs in a common base by building interactions between VLs via a multi-agent system (MAS) approach. Cloud-Based Integrated Virtual Laboratories (CIVIL) model has been proposed as a conceptual framework of collaborative networks of a cloud system with the help of MAS. The boundaries of the integrated problem are determined and schematized within the scope of conceptual modeling. Thereafter probable entities that may interact in the framework are included in the MAS model. Communications and interactions between these entities, aims and performance indicators of defined agents are also listed. (C) 2016 Elsevier Ltd. All rights reserved
Microfluidics for microalgal biotechnology
No full textOzdalgic, Berin/0000-0003-0113-541X; Kiraz, Alper/0000-0001-7977-1286; Ustun, Merve/0000-0002-3883-4065; Tasoglu, Savas/0000-0003-4604-217X; Haznedaroglu, Berat Zeki/0000-0002-0081-8801; Rahmani Dabbagh, Sajjad/0000-0001-8888-6106Microalgae have expanded their roles as renewable and sustainable feedstocks for biofuel, smart nutrition, biopharmaceutical, cosmeceutical, biosensing, and space technologies. They accumulate valuable biochemical compounds from protein, carbohydrate, and lipid groups, including pigments and carotenoids. Microalgal biomass, which can be adopted for multivalorization under biorefinery settings, allows not only the production of various biofuels but also other value-added biotechnological products. However, state-of-the-art technologies are required to optimize yield, quality, and the economical aspects of both upstream and downstream processes. As such, the need to use microfluidic-based devices for both fundamental research and industrial applications of microalgae, arises due to their microscale sizes and dilute cultures. Microfluidics-based devices are superior to their competitors through their ability to perform multiple functions such as sorting and analyzing small amounts of samples (nanoliter to picoliter) with higher sensitivities. Here, we review emerging applications of microfluidic technologies on microalgal processes in cell sorting, cultivation, harvesting, and applications in biofuels, biosensing, drug delivery, and nutrition.Alexander von Humboldt-StiftungAlexander von Humboldt Foundation; Marie Sklodowska-Curie Individual Fellowship award [101003361]; Royal Academy Newton-Katip Celebi Transforming Systems Through Partnership Award [120N019]; TUBITAK 2232 International Fellowship for Outstanding Researchers AwardTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [118C391]Alexander von Humboldt-Stiftung, Grant/Award Number: Research Fellowship for Experienced Researchers; Marie Sklodowska-Curie Individual Fellowship award, Grant/Award Number: 101003361; Royal Academy Newton-Katip Celebi Transforming Systems Through Partnership Award, Grant/Award Number: 120N019; TUBITAK 2232 International Fellowship for Outstanding Researchers Award, Grant/Award Number: 118C39
AKDOĞAN, Ali; ERDEN, Abdulsamet; FIRAT ŞENTÜRK, Esra; KILIÇ, Levent; SARI, Alper; ARMAĞAN, Berkan; KARADAĞ, Ömer; KİRAZ, Sedat
No full textBackground/aim Abnormal capillaroscopic findings have been reported in vasculitic syndromes such as Behçet’s disease, Henoch–Schönlein purpura, and Wegener’s granulomatosis. This study was conducted to define the capillaroscopic changes in patients with Takayasu arteritis (TA). Materials and methods We studied 28 TA patients (27 females). The nail folds from the 2nd to 5th fingers on both hands were examined with video capillaroscopy for all. A patient was defined as having an abnormal capillaroscopic examination if more than 1 morphologic abnormality was present in at least 2 nail folds. Results The median capillary density of TA patients was 9 (range: 9–11). There were no patients with capillary disorganization or avascular areas. Tortuous capillaries were detected in all patients. The other common morphological capillary abnormalities included enlarged/dilated capillaries (39.3%), branching capillaries (35.7%), and hemorrhages (32.1%). Only 1 patient had giant capillaries with early scleroderma-like pattern. Overall, there were 11 (39.3%) patients with abnormal capillaroscopic findings. There were more patients with abnormal capillaroscopic findings in the subgroup of TA patients whose upper extremity blood pressure could not be measured as compared to those whose blood pressure could be measured (66.7% vs. 26.3% patients; P = 0.04). Conclusion Capillaroscopic abnormalities are frequently seen in TA patients. We consider that abnormal capillaroscopic findings in TA patients reflect the impaired blood flow due to narrowed or occluded arteries rather than the primary capillary involvement of the disease process.PubMedWoSScopu
- …
