Abstract

Metals in deep-sea polymetallic nodules are indispensable for battery production and play a crucial role in facilitating the socio-economic green transition. A three-dimensional laser scanning model of nodules in the northwest Pacific Ocean has yielded an amount of data on volume, shape, and particle size. To deeply mine the correlation between the characteristics of the nodules, a joint probability density function (JPDF) based on copula theory is used. A univariate probability density function (PDF) linked to the particle size, burred depth, shape factor, and mass of the ores is established. The trend of nodule density with particle size is analyzed. Then, bivariate joint distribution using the copula method is constructed for mass and particle size. Furthermore, trivariate joint distribution using the copula method for nodule mass, particle size, and shape factor is derived. The results of this paper provide data to support the resource assessment of polymetallic nodules and optimize the design of mining systems.

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