Predicting and minimizing the blasting cost in limestone mines using a combination of gene expression programming and particle swarm optimization

• Autorzy: Bastami Reza , Bazzazi Abbas Aghajani , Shoormasti Hadi Hamidian , Ahangari Kaveh

Identyfikatory

DOI

10.24425/ams.2020.135180

• Języki publikacji: EN

Abstrakty

EN

Blasting cost prediction and optimization is of great importance and significance to achieve optimal fragmentation through controlling the adverse consequences of the blasting process. By gathering explosive data from six limestone mines in Iran, the present study aimed to develop a model to predict blasting cost, by gene expression programming method. The model presented a higher correlation coefficient (0.933) and a lower root mean square error (1088) comparing to the linear and nonlinear multivariate regression models. Based on the sensitivity analysis, spacing and ANFO value had the most and least impact on blasting cost, respectively. In addition to achieving blasting cost equation, the constraints such as frag-mentation, fly rock, and back break were considered and analyzed by the gene expression programming method for blasting cost optimization. The results showed that the ANFO value was 9634 kg, hole dia-meter 76 mm, hole number 398, hole length 8.8 m, burden 2.8 m, spacing 3.4 m, hardness 3 Mhos, and uniaxial compressive strength 530 kg/cm2 as the blast design parameters, and blasting cost was obtainedas 6072 Rials/ton, by taking into account all the constraints. Compared to the lowest blasting cost among the 146-research data (7157 Rials/ton), this cost led to a 15.2% reduction in the blasting cost and optimal control of the adverse consequences of the blasting process.

Słowa kluczowe

EN

blasting cost; limestone mine; gene expression programming; non-linear multivariate regression; particle swarm optimization algorithm; environmental impacts

PL

kopalnia wapienia; wybuch detonacyjny; regresja nieliniowa

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2020
• Tom: Vol. 65, no. 4
• Strony: 835--850
• Opis fizyczny: Bibliogr. 42 poz., rys., tab., wykr.

Twórcy

autor

Bastami Reza

• Department of Mining Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

autor

Bazzazi Abbas Aghajani

• Department of Mining Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran

autor

Shoormasti Hadi Hamidian

• Department of Mining Engineering, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran

autor

Ahangari Kaveh

• Department of Mining Engineering, Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)