In this paper, we introduce and discuss an algorithm for the numerical solution of some kinds of fractional integral and fractional integrodifferential equations. The algorithm for the numerical solution of these equations is based on iterative approach. The stability and convergence of the fractional order numerical method are described. Finally, some numerical examples are provided to show that the numerical method for solving the fractional integral and fractional integrodifferential equations is an effective solution method.

Shell-and-double concentric tube heat exchanger is one of the new designs that enhance the heat transfer process. Entransy dissipation is a recent development that incorporates thermodynamics in the design and optimization of heat exchangers. In this paper the concept of entransy dissipation is related to the shell-and-double concentric tube heat exchanger for the first time, where the experiments were conducted using hot oil with temperature of 80, 100 and 120°C, flow rate of cold water was 0.667, 1, and 1.334 kg/m³ respectively and the temperature of inlet cold water was 20°C. The entransy dissipation rate due to heat transfer and to fluid friction or pressure drop was studied.

The present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o

In low-latitude areas less than 10° in latitude angle, the solar radiation that goes into the solar still increases as the cover slope approaches the latitude angle. However, the amount of water that is condensed and then falls toward the solar-still basin is also increased in this case. Consequently, the solar yield still is significantly decreased, and the accuracy of the prediction method is affected. This reduction in the yield and the accuracy of the prediction method is inversely proportional to the time in which the condensed water stays on the inner side of the condensing cover without collection because more drops will fall down into the basin of the solar-still. Different numbers of scraper motions per hour (NSM), that is

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed