Percolation theory is applied to interpret the patterns formed on the surface of sieves by blinding. A stochastic model has been developed to simulate the blinding process. The results from this model are compared with predictions using statistical theory, giving rise to polynomials in P, the probability of blinding of an aperture, and with experimental results. The agreement between these models is good, indicating that the approach is valid in describing conditions of a sieve after processing. The critical probability computed from the model is in excellent agreement with published data for a square lattice. Under certain conditions experimental results were found to deviate from the predictions of the model. The frequency of formation of linear clusters was much higher than expected. This was shown to be due to displacement of wires on the surface of the sieves and was probably due to the method used to clean the sieves, that of brushing the surface. Subsequent experiments have proved this to be the case and careful cleaning with air jets was shown to overcome this problem. By modifying the simulation model to account for displacement of wires identical results were obtained, confirming both the experimental observations and the applicability of the model to this process. General wear over a sieve brought about by erosion was also investigated. This was shown to have little effect on the cluster pattern produced. This analysis is able to detect defects in a sieve or screen by analysing the blinding pattern and it could be used to assess the quality of material for manufacture of sieves or to check the performance of sieves in use.
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