<p>The large deflection of the cantilever plate has been the subject of considerable publications over the years having various applications in the field of constructions, mechanical, and aerospace. As per the literature, the former researchers have touched significantly to the methods and applications to resolve the subjects with for single-point loads or the complete surface loading with uniformly distributed load (UDL) and uniformly varying load (UVL) in various plate theories. &nbsp;These solutions are usually difficult to understand and may not be applicable to actual engineering problems with some special conditions. The remaining research relies on different numerical methods based on the R-K method and projectile technology, finite difference method, and finite element method (FEM) to solve large deflection problems. However, a few have provided any solutions or methods that can be easily used in real engineering applications. These complexities and limitations in existing solutions demand a detailed theoretical, numerical, and experimental analysis of cantilever members under large deflection to convey the practical applicability of the theoretical and numerical solutions. &nbsp;In the applications of pure bending of thin cantilever plates, unlike a beam, twisting arises with the bending unless it is accomplished to pure bending. Also, Springback is an implicit phenomenon in any bending operations. This paper emphases the theoretical study of integration of multiple point loadings (vertical and Inclined) over the thin plate to eliminate the twisting as well as predict the definite bending for the linearly elastic material. The cantilever plate is further studied through numerical simulations using finite element analysis (FEA) in ANSYS. This FEA helps to finalize the type of modeling approach that predicts the behavior of large deflections agreeing closely with that of theoretical solutions. Also, in the experimental approach, various artificial intelligence (AI) techniques can be used to reduce complexity; minimize the dependency on human expertise and time taken to improve the design efficiency. The artificial neural network (ANN) method is one of the most commanding tools for solving engineering problems and minimizing errors in experimental data. The method presented in this paper is inspired by Euler’s classical beam theory (moment-curvature relationship) and artificial neural network (ANN), which approximates the problem and compensates the errors. One of the interesting findings is, in a linear or small deformation, doubling the force results in double the displacement, but in a nonlinear or large deformation, one needs to triple the force to double the displacement, depending on how much the beam/plate is loaded relative to its size and other properties.</p>

Multiple Point Loading on Thin Cantilever Rectangular Plate Subjected to Pure Bending

Paper Proceedings: https://asmedigitalcollection.asme.org/ISPS/ISPS2021/volume/84799

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