This paper studies the behavior of axially loaded RC columns which are confined with carbon fiber reinforced polymers’ sheet (CFRP) and steel jackets (SJ). The study is based on twelve axially loaded RC columns tested up to failure. It is divided into three schemes based on its strengthening type; each scheme has four columns. The main parameters in this study were the compressive strength of the concrete and steel reinforcement ratio. Furthermore, the results of the experimental test showed a substantial enhancement in the column's load-carrying capacity. When compared to the original columns, the CFRP sheet had a significant effect on improving the ductility of the column by increasing the axial deformation by about 59.2 to 95.7

This study focuses on studying the effect of reinforced steel in detail, and steel reinforcement (tensile ratio, compression ratio, size, and joint angle shape) on the strength of reinforced concrete (compressive strength) Fc' and searching for the most accurate details of concrete divisions, their behavior, and corner resistance of reinforced concrete joint. The comparison of this paper with previous studies, especially in the studied properties. The conclusions of the chapter are summarized that these effects had a clear effect and a specific effect on the behavior and resistance of the reinforced concrete corner joints under the negative moments and under their influence and the resulting stress conditions. The types of defects that can

In this study, experimental mortar combinations with 1% micro steel fibers, were examined to create geopolymer mortars. To test the effect of the fibers on the mortar's resistance, the geopolymer mortar was designed with various proportions of more environmentally friendly materials fly ash and slag. The percentage of fly ash by weight was 50, 60, and 70% of the slag. The best results were obtained when a 50:50 ratio of fly ash and slag were mixed with 1% micro steel fibers. The results showed that the mixtures containing fibers performed better in the considered tests (toughness index, ductility index, and resilience index). In the impact resistance test, the mixture contained 50% fly ash by weight of the slag with a temperature of

Abstract

In the present work, thermal diffusivity and heat capacity measurements have been investigated in temperature range between RT and 1473 K for different duplex stainless steel supplied by Outokumpu Stainless AB, Sweden. The purpose of this study is to get a reliable thermophysical data of these alloys and to study the effect of microstructure on the thermal diffusivity and heat capacity value. Results show the ferrite content in the duplex stainless steel increased with temperature at equilibrium state. On the other hand, ferrite content increased with increasing Cr/Ni ratio and there is no significant effect of ferrite content on the thermal diffusivity value at room temperature. Furthermore, the heat capacity of all sam

Derivatives of Schiff-bases possess a great importance in pharmaceutical chemistry. They can be used for synthesizing different types of bioactive compounds. In this paper, derivatives of new Schiff bases have been synthesized from several serial steps. The acid (I) was synthesized from the reaction of dichloroethanoic acid with 2 moles of p-aminoacetanilide. New acid (I) converted to its ester (II) via the reaction of (I) with dimethyl sulphate in the present of anhydrous of sodium carbonate and dry acetone. Acid hydrazide (III) has been synthesized by adding 80% of hydrazine hydrate  to the new ester using ethanol as a solvent. The last step included the preparation of new Schiff-bases (IV-VIII) by the reaction of acid hydrazide with

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

Derivatives of Schiff-bases possess a great importance in pharmaceutical chemistry. They can be used for synthesizing different types of bioactive compounds. In this paper, derivatives of new Schiff bases have been synthesized from several serial steps. The acid (I) was synthesized from the reaction of dichloroethanoic acid with 2 moles of p-aminoacetanilide. New acid (I) converted to its ester (II) via the reaction of (I) with dimethyl sulphate in the present of anhydrous of sodium carbonate and dry acetone. Acid hydrazide (III) has been synthesized by adding 80% of hydrazine hydrate  to the new ester using ethanol as a solvent. The last step included the preparation of new Schiff-bases (IV-VIII) by the reaction of acid hydrazide with app