Finite element approach

This paper investigates flexural behavior and analytical approach for predicting the load and deflection at critical performance points of reinforced concrete (RC) beams strengthened with prestressed carbon fiber-reinforced polymer (CFRP) sheets. A finite element model is developed to simulate the interaction between the RC beam and the CFRP sheets, capturing key aspects such as failure modes, ultimate load, and mechanical behavior across the three phases of failure.

7p vibenya 31-12-2024 3 1   Download

This thesis derives closed form equations to describe electromagnetic device characteristics for a toroid, solenoid and a case study induction machine. By considering stored magnetic field energy, this approach allows the relationship between electrical, magnetic and kinetic energy to be quantified and analyzed in ways that allows improved accuracy compared with conventional magnetic circuit modeling methods. This thesis also provides insights into how geometric parameters impact energy transfer and operational characteristics of electromagnetic devices.

112p runthenight04 02-02-2023 13 2   Download

An approximated crack growth direction and coalescence of the multiple cracks were obtained for an aluminum alloy plate by the finite element approach (FEA). Self-similar as well as non-self-similar crack growths were observed based on relative position of multiple cracks.

14p tohitohi 19-05-2020 13 0   Download

This paper presents an approach of linking finite element method with artificial neural network to predict J-Integral parameter in desirable airfoil condition. Finite Element (FE) and Artificial Neural Network (ANN) have been employed for the purpose.

8p tohitohi 19-05-2020 6 0   Download

(BQ) This paper reports an intelligent approach for process modeling and optimization of electric discharge machining (EDM). Physics based process modeling using finite element method (FEM) has been integrated with the soft computing techniques like artificial neural networks (ANN) and genetic algorithm (GA) to improve prediction accuracy of the model with less dependency on the experimental data.

13p xuanphuongdhts 27-03-2017 57 2   Download