EDM SEMINAR

DOAJ: Directory of Open Access Journals - DOAJ, 2013

The finite element method (FEM) is a numerical analysis technique for obtaining approximate solutions to a wide variety of engineering problems. A finite element model of a problem gives a piecewise approximation to the governing equations. The basic premise of the FEM is that a solution region can be analytically modeled or approximated by replacing it with an assemblage of discrete elements (discretization). Since these elements can be put together in a variety of ways, they can be used to represent exceedingly complex shapes.

2006

the paper presents some cases of study using the FEA method in the design activity; the study shows the different stages of the 3D model, the loads and constrains applied on the digital product; Stress Analysis was used to simulate the behavior of a mechanical part under structural loading conditions.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

Finite Element Analysis or FEA is the simulation of a physical phenomenon using a numerical mathematic technique referred to as the Finite Element Method or FEM. This process is at the core of mechanical engineering, as well as a variety of other disciplines. It also is one of the key principles used in the development of simulation software. Engineers can use these FEM to reduce the number of physical prototypes and run virtual experiments to optimize their designs. Finite Element Analysis is used in various fields like structural, fluid flow, heat transfer to estimate the behavior of a component in real environment. There now exists growing body of knowledge connected with the development of mathematical models and numerical simulations of physical model. There are various software packages like Ansys, OptiStruct, COMSOL, Solidworks and many more which provide a close estimate in simulation models. Apart from these software MATLAB also has a Partial Differential Equation (PDE) toolbox which enables us to perform these simulations using some built-in functions and codes. However, a computational numerical technique is not an end of design rather it just provides a great estimate of the final component for which the results are only as good as the input provided and the final component in most of the cases require a physical testing in environment which it is meant to perform as a validation.

Chapter 01

Me Graw-Hill, New York, 1993

IJCSMC, 2019

Multimodal user interface (MUI) plays a key role in the future of mobile technology. After having a comprehensive review of the previous researches to determine the research problem, the researcher collected the relevant data by face to face interview with dyslexia students, teachers and experts from learning difficulty domain. This research developed a multimodal user interface in mobile learning application, for dyslexic students. The Researcher implement an Arabic letter mobile application to taught dyslexic students in a Sudanese primary school. Firstly, the application was developed on android platforms. Secondly, the application implemented in students sampling of size 30 students. Finally, the application was evaluated in two stages. The first one is to evaluate the enhancement of student who was taught a multimodal user interface; the second stage is an evaluation by using the technology acceptance model (TAM). The evaluation stage show increasing in education level for dyslexia students in significant degrees. Multi-mode learning has a good effect in dyslexia students on this study, there was a significant difference between student's marks after using the mobile application in teaching alphabet letters and the student's degrees before using the mobile application, which means the multimode user interface improved the reading skills for most dyslexic students who are involved in our study.

Arxiv preprint arXiv: …, 2009

Cosmology from the Highly-Redshifted 21 cm Line ... Steven R. Furlanetto1, Adam Lidz2, Abraham Loeb2, Matthew McQuinn2, Jonathan R. Pritchard2, Paul R. Shapiro3, James Aguirre4, Marcelo A. Alvarez5, Donald C. Backer6, Judd D. Bowman7, Jack O. Burns8, Chris L. Carilli9, ...

Abstract: Principal Component Analysis(PCA) is a data analysis tool that is used to reduce the dimensionality of a large number of interrelated variables while retaining as much of the information as possible. In this paper, PCA has been utilized on the crime data of Nigeria to discover the distinct influential variables; in addition which variables have silence in the identification of State being safe or dangerous. From the result, four Principal Components (PCs) have been retained using both scree plot and Kaiser’s criterion which accounted for 75.024% of the total variation