General principles of modelling physical-mechanical properties of conglomerates/Bendrieji konglomeratų fizikinių-mechaninių savybių modeliavimo principai

Abstract

A basic mathematical analogue for modelling grading of a mineral part of conglomerates is presented (1). The given method, in comparison with the ones used at present, has a number of advantages: a) it allows us to define instantly the possibility of getting the planned grading of a mineral part of the conglomerates out of mineral materials in possession: b) it enables us to get the optimal mineral part of the conglomerate, according to the property of conglomerate that is desired, for example, the cheapest conglomerate or the largest density of conglomerate; c) it enables us to get and analyse fictitious (not corresponding to the Standard) mineral material composition. The general mathematical analogue (2)–(4) for modelling mineral part composition of conglomerate and prognosis of its physical-mechanical properties is based on basic mathematical analogue (1). For both mathematical analogues the following symbols are used: c_j – weight multiplier of component j (for example, the price of one mass unit of component j); x_j – quantity of component (mineral material) j in parts of the unit: m – number of components: a_ij – quantity of component j in percent, that pass through sieve i; b_min,i ,  b_max,i – limited quantities of a mineral part of conglomerate in percent, that can be passed through sieve i_n – number of sieves d_vj – coefficient of additional inequality v; corresponding component j: h_v – limit value of additional inequality v; s – number of additional inequalities; g_wj – coefficient of physical-mechanical equality wcorresponding component j; P_w  – absolute term of physical-mechanical equality w; t – number of the physical-mechanical equalities. The general mathematical analogue (2)–(4) is multi-criterion. The final solution can be chosen by including coefficients of influence or by a person who takes part in modelling.

Article in Lithuanian.

First Published Online: 26 Jul 2012

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