Effects of environmental factors on the adhesion and durability characteristics of epoxy-bonded concrete prisms

This work is concerned with the effects of environmental factors on the adhesion and durability characteristics of epoxy-bonded concrete prisms. The results indicate that the presence of liquid water at the interfacial zone during the epoxy injection process disrupts the initial bond configurations. The freezing and thawing up to about 40 cycles do not have a significant effect on the bond stability. An adequate degree of chemical stability is maintained in the bond line by the epoxy adhesives after 120 days of exposure to corrosive environments such as MgSO₄ and MgCl₂. However, there is a pronounced effect of these chemical substances on the concrete strength. The load-bearing capacity of epoxy-bonded concrete prisms decreases with increasing temperature. Despite this fact, the EP3-bonded concrete prisms give relatively high joint strengths at temperatures up to 100 °C.     

Modification of cyclohexanone-formaldehyde-resin

The reactions of cyclohexanone-formaldehyde-resin via its hydroxy and carbonyl functional groups with a number of different reagents such as acetic anhydride, benzoyl chloride, hydroxylamine, semicarbazide, and phenyl hydrazine were studied. Melting points, IR spectrums, and solubilities in various solvents of the products were determined.     

Digital Image Analysis in Geotechnical Engineering Education

Existing research has shown that visual input significantly contributes to learning, therefore, it is paramount to use visual tools to help demonstrate engineering concepts. One of these tools, digital image analysis, can help effectively communicate complex concepts to students in a simple and understandable format as a supplement to traditional lecturing, while simultaneously enabling students to have hands-on experience. This note describes a series of activities to incorporate digital image analysis into engineering education. The undergraduate students worked in research projects that involved image-based analysis of geomaterials. Based on these activities and the students’ response to a questionnaire, it was recognized that digital image analysis can enhance the understanding of engineering phenomena for undergraduate students. The hands-on experience and visual demonstration improved the students’ grasp of fundamental concepts in research projects. The research experience allowed the students to build a connection between the classroom and the solution of state-of-the-art engineering scientific problems. It also taught them about cooperation and teamwork, as well as academic independence.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Investigation of the Microstructural,Mechanical and Corrosion Properties of Grade A Ship Steel-Duplex Stainless Steel Composites Produced <Emphasis Type="Italic">via</Emphasis> Explosive Welding

Grade A ship-building steel-AISI 2304 duplex stainless steel composite plates were manufactured via explosive welding. The AISI 2304 plates were used to clad the Grade A plates. Optical microscopy studies were conducted on the joining interface for characterization of the manufactured composite plates. Notch impact, tensile-shear, microhardness, bending and twisting tests were carried out to determine the mechanical properties of the composites. In addition, the surfaces of fractured samples were examined by scanning electron microscopy (SEM), and neutral salt spray (NSS) and potentiodynamic polarization tests were performed to examine corrosion behavior. Near the explosion zone, the interface was completely flat, but became wavy as the distance from the explosion zone increased. The notch impact tests indicated that the impact strength of the composites decreased with increasing distance from the explosion zone. The SEM studies detected brittle behavior below the impact transition temperature and ductile behavior above this temperature. Microhardness tests revealed that the hardness values increased with increasing distance from the explosion zone and mechanical tests showed that no visible cracking or separation had occurred on the joining interface. The NSS and potentiodynamic polarization tests determined that the AISI 2304 exhibited higher corrosion resistance than the Grade A steel.     

An application of the degree-hours method to estimate the residential heating energy requirement and fuel consumption in Istanbul

Cold season heating energy requirements in buildings can be estimated with the degree-hours method based on human comfort levels and available meteorological temperature records for a given area. Such estimations are especially significant for cities where fossil fuel consumption must be eliminated in favor of clean energy alternatives to reduce air pollution. This paper considers the city of Istanbul in Turkey and presents a detailed account for practical energy requirements and fuel consumption calculations.     

Adaptive three-dimensional cellular genetic algorithm for balancing exploration and exploitation processes

This paper presents a new adaptive algorithm that aims to control the exploration/exploitation trade-off dynamically. The algorithm is designed based on three-dimensional cellular genetic algorithms (3D-cGAs). In this study, our methodology is based on the change in the global selection pressure induced by dynamic tuning of the local selection rate. The parameter tuning of the local selection method is a way to define the global selection pressure. A diversity speed measure is used to guide the algorithm. Therefore, the integration of existing techniques helps in achieving our aims. A benchmark of well-known continuous test functions and real world problems was selected to investigate the effectiveness of the algorithm proposed. In addition, we provide a comparison between the proposed algorithm and other static and dynamic algorithms in order to study the different effects on the performance of the algorithms. Overall, the results show that the proposed algorithm provides the most desirable performance in terms of efficiency, efficacy, and speed for most problems considered. The results also confirm that problems of various characteristics require different selection pressures, which are difficult to be identified.     

A study on soil-structure interaction analysis in canyon-shaped topographies

In this paper, a coupled finite and infinite element system is used to study the effects of canyon-shaped topography and geotechnical characteristics of the soil on the dynamic response of free surface and of 2-D soil-structure systems under ground motion. A parametric study is carried out for canyon-shaped topographies. It is concluded that topographic conditions may have important effects on the ground motion along the canyon. Geotechnical properties of the soil also have significant amplification effects on the whole system motion, which cannot be neglected for design purposes. Thus, the dynamic response of both free surface and a soil-structure system are primarily affected by surface shapes and geotechnical properties of the soil. Location of the structure is another parameter affecting the whole system response.     

Modification of Leather Surface with Atmospheric Pressure Plasma and Nanofinishing

In this study, the effect of plasma treatment and nanofinishing on leather properties was investigated. O₂ and N₂ gases were used for activating the leather surface, and thin layers were deposited by hexamethyldisiloxane and tetraethyloxysilane. Nanofinishing process was performed using TiO₂–SiO₂ nanocomposite solution. The surface properties of the treated leathers were characterized by scanning electron microscopy and atomic force microscopy. The results showed that the hydrophobicity of leather was clearly improved after plasma end treatment with hexamethyldisiloxane, while treatment with tetraethyloxysilane increased its hydrophilic property. Moreover, the fastness properties and water vapor permeability of leathers were improved.     

Form-Stabilized Polyethylene Glycol/Palygorskite Composite Phase Change Material: Thermal Energy Storage Properties,Cycling Stability,and Thermal Durability

In this work, polyethylene glycol (PEG) as a phase change material (PCM) was incorporated with palygorskite (Pal) clay to develop a novel form-stable composite PCM (F-SCPCM). The Pal/PEG(40 wt%) composite was defined as F-SCPCM and characterized using SEM/EDS, FT-IR, XRD, DSC, and TGA techniques. The DSC results revealed that the F-SCPCM has a melting temperature of 32.5°C and latent heat capacity of 64.3 J/g for thermal energy storage (TES) applications. Thermal cycling test showed that the F-SCPCM had good cycling thermal/chemical stability after 500 cycles. The TGA data proved that that both cycled and non-cycled F-SCPCMs had considerable high thermal durability. Consequently, the created F-SCPCM could be considered as an additive material for production of green construction components with TES capability. POLYM. ENG. SCI., 60:909–916, 2020. © 2020 Society of Plastics Engineers