Modeling high-temperature stress-strain behavior of cast aluminum alloys

A modified two-state-variable unified constitutive model is presented to model the high-temperature stress-strain behavior of a 319 cast aluminum alloy with a T7 heat treatment. A systematic method is outlined, with which one can determine the material parameters used in the experimentally based model. The microstructural processes affecting the material behavior were identified using transmission electron microscopy and were consequently correlated to the model parameters. The stress-strain behavior was found to be dominated by the decomposition of the metastable θ′ precipitates within the dendrites and the subsequent coarsening of the θ phase, which was manifested through remarkable softening with cycling and time. The model was found to accurately simulate experimental stress-strain behavior such as strain-rate sensitivity, cyclic softening, aging effects, transient material behavior, and stress relaxation, in addition to capturing the main deformation mechanisms and microstructural changes as a function of temperature and inelastic strain rate.     

Detecting and quantifying envelope singularities in the plane

The mathematical envelopes of families of both rigid and non-rigid moving shapes play a fundamental role in a variety of problems from very diverse application domains, from engineering design and manufacturing to computer graphics and computer assisted surgery. Geometric singularities in these envelopes are known to induce malfunctions or unintended system behavior, and the corresponding theoretical and computational difficulties induced by these singularities are not only massive, but also well documented. We describe a new approach to detect and quantify the envelope singularities induced by 2-dimensional shapes of arbitrary complexity moving according to general non-periodic and non-singular planar affine motions. Our approach, which does not require any envelope computations, is reframing the problem in terms of “fold points” and “fold regions” in the neighborhood of geometric singularities, and we show that the existence of these fold points is a necessary condition for the existence of singularities. We establish a mathematically well defined duality between the 2-dimensional Euclidean space in which the motion takes place and a 2+1 spacetime domain. Based on this duality, we recast the problem of detecting and quantifying geometric singularities into inherently parallel tests against the original geometric representation in the 2-dimensional Euclidean space. We conclude by discussing the significance of our results, and the extension of our approach to 3-dimensional moving shapes.     

The Effect of Pitching Rate on Fermentation and Flavour Compounds in High Gravity Brewing

The effect of pitching rate on fermentation and production of flavour compounds was studied in high gravity wort using a lager yeast. Fermentation performance was followed by monitoring the total sugar content and yeast growth. Volatile compounds were evaluated by analysing higher alcohols, esters and carbonyl compounds at the end of fermentation. Faster fermentation rates and higher yeast counts were observed with the higher pitching levels. Lower amounts of 2‐ and 3‐methyl‐1‐butanols and higher levels of 2‐methyl‐1‐propanol were found at the increased pitching rates. The concentration of isoamyl acetate was reduced with an increased pitching rate. Higher amounts of diacetyl and 2,3‐pentanedione were obtained at the lower pitching levels.     

High‐performance filaments by melt spinning low viscosity nylon 6 using horizontal isothermal bath process

Several techniques and treatments have been developed for the production of high‐performance nylon‐6 fibers. The inherent problems of low productivity, high production cost, and high energy consumption, complexity of chemical reaction, mass transfer, and waste recovery systems make most of them inappropriate for industrial application. Horizontal isothermal bath (hIB) is an alternative ecofriendly simple treatment that can be used during melt spinning process for production of technical textile fibers. The efficacy of hIB in improving the mechanical properties of multifilament nylon‐6 yarn is studied in this research. The results showed that such treatment can increase the molecular orientation of the amorphous and crystalline functions up to 0.54 and 0.983, respectively, and raised both the amorphous isotropy and fiber birefringence by 67 and 45%, respectively. Hot drawing of the yarn at a very low draw ratio of 1.38, increased the tenacity and modulus up to 10 and 43.9 g/den, respectively, and decreased the elongation to 27%. POLYM. ENG. SCI., 55:2457–2464, 2015. © 2015 Society of Plastics Engineers     

Characterization of Turkish Olive Oils by Triacylglycerol Structures and Sterol Profiles

A characterization study of Turkish monovarietal olive oils using chemical variables such as fatty acid, sn‐2 fatty acid, triacylglycerol, and sterol composition is presented. A total of 101 samples of Olea europaea L. fruits from 18 cultivars were collected for two crop years from west, south, and southeast regions of Turkey. Olives were processed to oil and olive oil samples were evaluated for their triacylglycerol structures and sterol composition. Oleic acid content ranged from 60.15 to 80.46 % of total fatty acids and represented 70.90–89.02 % of sn‐2 position triacylglycerols. Major triglycerides of oil samples were triolein, palmitodiolein, dioleolinolein, palmitooleolinolein, dipalmitoolein, and stearodiolein. Triolein values were between 24.72 and 48.64 % and compatible with the fatty acid composition. Total sterol content varied from 1,145.32 to 2,211.77 mg/kg and Edremit yagl?k stood out because of its high sterol content. A one‐way analysis of variance revealed significant differences for variables among cultivars. Principle component analysis enabled the classification of common varieties on the basis of analytical data. Sterol composition achieved more relevant discrimination than fatty acid and triglyceride composition. Classification according to geographical origin was performed by discriminant analysis.     

A novel comparative study for detection of Covid-19 on CT lung images using texture analysis,machine learning,and deep learning methods

The Covid-19 virus outbreak that emerged in China at the end of 2019 caused a huge and devastating effect worldwide. In patients with severe symptoms of the disease, pneumonia develops due to Covid-19 virus. This causes intense involvement and damage in lungs. Although the emergence of the disease occurred a short time ago, many literature studies have been carried out in which these effects of the disease on the lungs were revealed by the help of lung CT imaging. In this study, 1.396 lung CT images in total (386 Covid-19 and 1.010 Non-Covid-19) were subjected to automatic classification. In this study, Convolutional Neural Network (CNN), one of the deep learning methods, was used which suggested automatic classification of CT images of lungs for early diagnosis of Covid-19 disease. In addition, k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM) was used to compare the classification successes of deep learning with machine learning. Within the scope of the study, a 23-layer CNN architecture was designed and used as a classifier. Also, training and testing processes were performed for Alexnet and Mobilenetv2 CNN architectures as well. The classification results were also calculated for the case of increasing the number of images used in training for the first 23-layer CNN architecture by 5, 10, and 20 times using data augmentation methods. To reveal the effect of the change in the number of images in the training and test clusters on the results, two different training and testing processes, 2-fold and 10-fold cross-validation, were performed and the results of the study were calculated. As a result, thanks to these detailed calculations performed within the scope of the study, a comprehensive comparison of the success of the texture analysis method, machine learning, and deep learning methods in Covid-19 classification from CT images was made. The highest mean sensitivity, specificity, accuracy, F-1 score, and AUC values obtained as a result of the study were 0,9197, 0,9891, 0,9473, 0,9058, 0,9888; respectively for 2-fold cross-validation, and they were 0,9404, 0,9901, 0,9599, 0,9284, 0,9903; respectively for 10-fold cross-validation.

     

Comparison of microwave and conventionally heated reactor performances in catalytic dehydrogenation of ethane

In the present study, non-oxidative dehydrogenation of ethane was carried out by using conventional heated (CHRS) and microwave heated (MWHRS) reactor systems. Reactions were conducted in the presence of SBA-15 supported Cr or Mo catalysts, and the activity of the catalysts were evaluated in terms of ethane conversion and C₂H₄/H₂ ratio. The physicochemical properties of synthesized catalysts were determined by XRD, N₂ adsorption/desorption, ICP-OES, TPR, SEM, and EDS analysis. XRD pattern of reduced catalysts revealed the formation of metallic Mo and Eskolaite Cr₂O₃ over the catalysts. The mesoporous structure of SBA-15 was confirmed using N₂ adsorption/desorption analysis. Activity test results showed higher ethane conversion in the presence of Mo than Cr in both reactor systems. However, more side reaction took place over Mo than Cr based catalysts. Cr based catalyst showed better activity in terms of ethylene formation and C₂H₄/H₂ ratio. Results proved the superior performance of microwave heated reactor over the conventionally heated reactor. Significantly higher conversion was obtained over Cr based catalysts in MWHRS than CHRS due to the occurrence of micro-plasmas (hot spots) in the catalyst bed. The performance of 5Cr@SBA-15 in CHRS was poor due to negligible ethane conversion below 650 °C, while almost complete conversion could be achieved in MWHRS with this catalyst at identical conditions. The ethane conversion values obtained at 650 °C in CHRS were achieved at 450 °C, in MWHRS.     

Self-assembled fibrillar polyethylene crystals with tunable properties

Due to its simple linear chain structure, crystal morphology of linear low-density polyethylene (LLDPE) fibers can be controlled to fulfill the needs of diverse advanced applications. This study presents a simple two-step method to produce LLDPE fibers with self-assembled fibrillar crystals and highly oriented amorphous phase. Rather than conventional melt spinning, fibers were treated in a two-step eco-friendly bath without drawing after extruded fibers emerge from the spinneret. Treated fibers through the baths demonstrated lower crystallinity, but significantly higher degree of crystal orientation when compared to control fibers of traditional melt spinning. Morphological analysis revealed that a unique microstructure was formed after spinning through a two-step eco-friendly bath. As-spun fibers demonstrated spherulitic morphology which can be transformed into a fibrillar structure followed by post-drawing process. Cross sectional images of the treated LLDPE fibers produced at 400 m/min showed fibrillar PE crystals which can be more dominant upon post-drawing. After two-step bath treatment, produced fibers need low draw ratios to exhibit high performance. Our novel modification followed by hot drawing process can manipulate internal structure with performance of PE fibers to an outstanding level of 0.35 GPa strength and 3 GPa modulus at a production speed of 400 m/min.