Abstract
This paper presents a procedure for an accurate and reliable stress analysis in a conical pick used in mining operations, aiming to improve their wear resistance. This is achieved by (1) establishment of a three-dimensional (3D) edge-based smoothed finite element method (ES-FEM), and algorithms of creating the smoothing domain for accurate solution in terms of stress and strain distributions; and (2) use of experimentally measured actual forces using a full-scale rotary cutting machine. In our 3D ES-FEM model, the physical domain for the pick is first discredited using linear triangular elements that can be generated easily for complicated geometries. The smoothing domains are then constructed based on edges of these elements in an automated fashion. In order to create the smoothing domains for the smoothed strain computation in the ES-FEM, an algorithm is presented for establishing connection between nodes, edges, faces, and elements. Each smoothing domain is bounded by a set of enclosed line-segments, besides, leading to a connectivity list for later effective computation. To show the effectiveness and accuracy of the strain energy and the displacement solution of ES-FEM, based on the actually measured forces from the laboratory rock cutting tests with a single pick, a comparison study is carried out against the standard finite element method (FEM). It can be concluded that ES-FEM has a higher convergence in energy norm and better accuracy than FEM using the same mesh from the comparison results. The 3D ES-FEM model solves the problem of the lower solution accuracy, caused by the poor quality of mesh, by using the standard FEM in solving the stress distribution of mining machinery parts, such as picks, and offers accurate and reliable solutions that are critical for improving the wear resistance of the pick for the mining industry.
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Fan, Q., Zhang, Q., & Liu, G. (2019). A stress analysis of a conical pick by establishing a 3D ES-FEM model and using experimental measured forces. Applied Sciences (Switzerland), 9(24). https://doi.org/10.3390/app9245410
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