Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation

Ghasemi, Ebrahim; Amini, Hasel; Ataei, Mohammad; Khalokakaei, Reza

doi:10.1007/s12517-012-0703-6

Cited by 109 publications

(32 citation statements)

References 34 publications

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“…In mining engineering, rock fragmentation should be performed with minimum cost and side effects (e.g., ground vibration, air blast, fly rock) [27,28]. To achieve this goal, an appropriate blast design should be applied for the loose blasting operation.…”

Section: Supporting Technique For Controlling Large Hanging Hard Roofmentioning

confidence: 99%

A Case Study of Effective Support Working Resistance and Roof Support Technology in Thick Seam Fully-Mechanized Face Mining with Hard Roof Conditions

et al. 2017

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This paper presents the engineering geological properties and roof control tecnology for a thick coal seam fully-mechanized face mining with hard roof conditions (THC) at the Jinhuagong Coal Mine (JCM), northwest China. The effective support working resistance and appropriate roof control technology are two critical factors for safe and productive mining in the THC. The load-estimate-method (LOEM) is the effective method to determine the support working resistance for normal working conditions (the mining height less than 3.5 m). In order to prevent support crushing accidents from happening and to ensure the safety and high-efficiency in the THC, the LOEM was modified based on the structure of the overlying strata in the THC. The strata which can form the voussoir beam structure in normal working conditions and will break in the form of cantilever beam in the THC is defined as the key strata in the immediate roof. Therefore, the hanging length of the key strata in the immediate roof was considered in the LOEM. Furthermore, a method for calculating the hanging length of the key strata in the immediate roof and its influencing factors were proposed using cantilever beam theory analysis of the structure of the overlying strata. Moreover, in order to fully fill the goaf area with caving roof to reduce the energy accumulation of main roof movement, it was decided to apply destress blasting technique (DEBT) at the JCM to control the large hanging length of the hard roof, so as to reduce the impact of the hard main roof movement on the working face. The key technique parameters of the roof caving borehole were also proposed. The obtained results demonstrated that the theoretical analysis is reasonable, and the chosen support type and the DEBT could meet the roof control requirements. The THC has achieved safety and high-efficiency mining.

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Section: Supporting Technique For Controlling Large Hanging Hard Roofmentioning

confidence: 99%

A Case Study of Effective Support Working Resistance and Roof Support Technology in Thick Seam Fully-Mechanized Face Mining with Hard Roof Conditions

et al. 2017

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“…Flyrock arising from blasting operations is one of the crucial and complex problems in mining industry and its prediction plays an important role in the minimization of related hazards. (Ebrahim Ghaesemi et al 2012 ).The lack of blast area security and flyrock accounted for 68.2% accidents in USA (Kecojevic and Radomsky, 2005). An analysis of blasting accidents in Indian mines indicated that more than 40% of fatal and 20% of serious accidents were caused by flyrock (Bhandari, 1997 Workman and Calder, 1994).…”

Section: Ann In Fly Rock Hazardsmentioning

confidence: 99%

Application of Artificial Neural Network for Blast Performance Evaluation

Trivedi¹

2014

IJRET

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“…by Ghasemi et al [14]. They demonstrated the capability of both models in predicting flyrock distance, but the FIS model produced higher performance compared to the ANN model.…”

Section: Introductionmentioning

confidence: 96%

Prediction of blast-induced flyrock using differential evolution algorithm

Dehghani

Shafaghi

2016

Engineering with Computers

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loading and hauling. Fragments can be thrown beyond the desired pile limit, which is normal but is considered adverse effect of blasting and is called flyrock. Fragments propelled far beyond predefined safety limit are considered security breach and are called wild flyrock [1].Due to high potential to cause damage to machinery and nearby structures and to cause injuries, even fatal, to personnel, flyrock is the most dangerous adverse effect of blasting and this phenomenon is responsible for 28.3 % of the damages and injuries in surface mining activities [2].To prevent flyrock problem, various parameters such as the physico-mechanical properties of rock mass, explosives specifications and geometrical aspects of the blasting pattern should be considered while designing a blasting pattern. For example, flyrock may occur in situations where there is insufficient stemming, too small a burden because of overbreak from the preceding or proceeding blast, planes of weaknesses in rock which reduce resistance to blasting, and finally existence of loose rock fragment on top of the bench [3]. Explosives with high energy can increase the probability of the flyrock. Most of the conventional formula used the TNT strength instead of the explosive strength.To convert this factor, usually, the ballistic mortar test was used (Fig. 1).Since this phenomenon is very dangerous, many researchers trying to establish the flyrock prediction models. Lundborg presented an equation for estimating the flyrock based on the hole diameter and specific charge as follows [4]:where L is the maximum rock projection (m), D is the hole diameter (in) and q is the specific charge (kg/m 3 ). Also, Lundborg et al. established another empirical model based on hole diameter as follows [5]:Abstract Flyrock is an undesirable phenomenon in blasting operations. Due to high potential to cause damage to machinery and nearby structures and to cause injuries, even fatal, to personnel, flyrock is the most dangerous adverse effect of blasting. For controlling and decreasing the effect of this phenomenon, it is necessary to predict it. Because of multiplicity of effective parameters and complexity of interactions among these parameters, empirical methods may not be fully appropriate for flyrock estimation. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of differential evaluation algorithm (DE) and dimensional analysis algorithm (DA). For this purpose, the parameters of 300 blasting operations were accurately recorded and flyrock distances were measured for each operation. In the next stage, two new empirical predictors were developed to predict flyrock distance. The results clearly showed the superiority of the proposed DE-DA model in comparison with the empirical approaches.

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Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation

Cited by 109 publications

References 34 publications

A Case Study of Effective Support Working Resistance and Roof Support Technology in Thick Seam Fully-Mechanized Face Mining with Hard Roof Conditions

A Case Study of Effective Support Working Resistance and Roof Support Technology in Thick Seam Fully-Mechanized Face Mining with Hard Roof Conditions

Application of Artificial Neural Network for Blast Performance Evaluation

Prediction of blast-induced flyrock using differential evolution algorithm

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