This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

In this work, an investigation for the dynamic analysis of thin composite cylindrical and spherical shells is presented. The analytical solution is based upon the higher order shear deformation theory of elastic shells from which the developed equations are derived to deal with orthotropic layers. This will cover the determination of the fundamental natural frequencies and mode shapes for simply supported composites cylindrical and spherical shells.

      The analytical results obtained by using the derived equations were confirmed by the finite element technique using the well known Ansys package. The results have shown a good agreement with a maximum percentage of discrepancy, which gives a confidence o

Abstract

In this paper presents two dimensional turbulent flow of different nanofluids and ribs configuration in a circular tube have been numerically investigation using FLUENT 6.3.26. Two samples of CuO and, ZnO nanoparticles with 2% v/v concentration and 40 nm as nanoparticle diameter combined with trapezoidalribs with aspect ratio of p/d=5.72 in a constant tube surface heat flux were conducted for simulation. The results showed that heat flow as Nusselt number for all cases raises with Reynolds number and volume fraction of nanofluid, likewise the results also reveal that ZnO with volume fractions of 2% in trapezoidal ribs offered highest Nusselt number at Reynolds number of Re= 30000.

Key

The heat transfer and flow resistance characteristics for air flow cross over circular finned tube heat exchanger has been studied numerically and experimentally. The purpose of the study was to improve the heat transfer characteristics of an annular finned-tube heat exchanger for better performance. The study has concentrated on the effect of the number of perforations and perforations shapes on the heat transfer and pressure drop across a staggered finned tube heat exchanger. The Numerical part of present study has been performed using ANSYS Fluent 14.5 using SST Turbulent model, while the experimental study consist from a test rig with different models of heat exchangers and all required measurement devices were build

In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be