Artificial neural networks modeling of mechanical property and microstructure evolution in the Tempcore process

In this study, the microstructures and the mechanical properties of steel bars treated by the Tempcore process have been investigated. In the Tempcore process, AISI 1020 steel bars of various diameters were used. In bars, unlike the self-tempering temperature and the extent of elongation, an increase in the amount of martensite was observed, which caused a consequential increase in yield and tensile strength as a function of quenching duration. The amounts of martensite, bainite. pearlite and the values of elongation, self-tempering temperature. yield and tensile strength could be obtained by a new and fast method. by using artificial neural networks. A PASCAL computer program has been developed for this study

A finite element based prediction of the microstructural evolution of steels subjected to the Tempcore process

In this study, it is proposed that the internal structures of steel bars after having been treated by the Tempcore method can be predicted by using a finite element method. In bars treated by the Tempcore method, it is seen that the amount of martensite increases and the self-tempering temperature decreases with increasing duration of quenching. The amount of martensite, the changes in the internal structure, and the self-tempering temperatures, which are determined by finite element method, give an idea of the mechanical properties of steel bars. In this study, the steel bars having 0.17% C, 0.22% Si, 0.79% Mn, 0.036% P, and 0.041% S in various diameters have been used. By using a finite element method, the heat transfer equations have been solved and the amount of phases after transformation has been determined. A Fortran 77 computer program has been developed for the study. A quenching simulation has been made utilizing the finite element method for different quenching duration; the changes in the internal structures and self-tempering temperatures have been determined for each node. The numerical results obtained via the finite element method have been compared with the experimental results. It has been seen that the agreement is reasonably good. (C) 2000 Elsevier Science Ltd. All rights reserved

Factors affecting doctor visits of postmenopausal women with urinary incontinence

Objective This study analyzed the reasons for avoiding visiting a doctor among women aged >= 50 years with urinary incontinence (UI), as well as factors influencing visits to the doctor. Methods In all, 402 women aged >= 50 years who were enrolled in Bursa healthcare centers, 150 with UI and 252 without UI, participated in the study. This study was conducted between January 2018 and August 2018. Participants were asked to complete the International Consultation on Incontinence Questionnaire - Short Form (ICIQ-SF) questionnaire. Quality of life was evaluated using the Incontinence Impact Questionnaire, Short Form (IIQ-7) questionnaire. Results The prevalence of UI was 37%. Of the women with UI, 52 (34.67%) visited a doctor for complaints. The most frequent reason for seeing a doctor because of UI was that it had started to affect activities of daily living. The most frequent reason for avoiding visiting a doctor was the belief that UI was normal. Scores on the ICIQ-SF were higher among women who visited a doctor. Physical activity, social relationships, and mental health scores on the IIQ-7 were also higher among patients who visited a doctor. Conclusions Patients who suffer from severe UI and whose quality of life is affected more negatively are more likely to visit a doctor. Women who believe that UI is normal are less likely to visit a doctor. Awareness about UI should be increased in order to increase the rate of visiting a doctor for this condition