Fragment Size Distribution of Blasted Rock Mass

Jug, Jasmin; Strelec, Stjepan; Gazdek, Mario; Kavur, Boris

doi:10.1088/1755-1315/95/4/042013

Cited by 14 publications

(3 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Measuring fragmentation is a critical aspect of evaluating the efficiency of blasting operations in quarrying and mining. Several techniques have been developed to assess the size distribution and characteristics of fragmented material including WipFrag software [26]. One common method is sieving analysis, where the crushed or blasted rock is passed through a series of screens with different mesh sizes, and the percentage of material passing through each sieve is determined, providing information on particle size distribution [27].…”

Section: Techniques For Measuring Fragmentationmentioning

confidence: 99%

Evaluation of Rock and Explosive Properties for Fragmentation Characterization: An Application of WipFrag

Otokiti,

Adebayo

2024

IJEATS

View full text Add to dashboard Cite

This study investigates the rock explosive properties in selected Lokoja quarries, Nigeria, with the goal of characterizing fragmentation for optimized downstream operations. The analysis includes porosity, UCS values, and permeability assessment in Gitto quarry, highlighting advantages in material application. Comparisons between rock formations (Q1 and Q2) reveal varying compressive strengths, crucial for determining appropriate explosive energy for efficient fragmentation. Blast design parameters from Q1 and Q2 indicate consistent values, aiding in operational planning. Fragmentation analysis, conducted using WipFrag software, delineates size ranges and classifies the blast as having a moderate distribution. Correlations between blast fragmentation size and powder factor underscore the impact on efficiency. A classification chart and table are presented for convenient interpretation of results, providing valuable insights for enhancing blasting practices in Lokoja quarries and ultimately improving productivity. The fragmentation analysis result carried out in this study using WipFrag software shows that the 50%, 80% and Maximum block size passing size ranges from 539.94 – 1349.53 mm, 690.07 – 1907.81 mm, 808-2280 mm respectively. The blast fragmentation sizes are classified as moderate distribution blast based on the uniformity index value ranging from 1.95 to 2.4. The relationship between blast fragmentation size and powder factor was evaluated using linear correlation coefficient. It was noted that, X20, X50, X80 has high R2 values greater than 60% respectively

show abstract

Section: Techniques For Measuring Fragmentationmentioning

confidence: 99%

Evaluation of Rock and Explosive Properties for Fragmentation Characterization: An Application of WipFrag

Otokiti,

Adebayo

2024

IJEATS

View full text Add to dashboard Cite

show abstract

“…Rock mass fragmentation by blasting is the process of breaking up rock into smaller pieces by using explosives [1]. Blast fragmentation is the critical construction step that breaks the in-situ rock mass into smaller fragments suitable for further processing, and analysis to optimize the blast design to improve efficiency.…”

Section: Introductionmentioning

confidence: 99%

Influence of rock mass properties and powder factor on the fractal dimension of the natural rock mass blocks during blasting

Tomar,

Panthee,

Dahal

et al. 2024

Preprint

View full text Add to dashboard Cite

The rock mass fragmentation in discontinuous rock mass is a concern issue in rock mass blasting. The purpose of the study is to find out the influencing parameters of rock mass and blast design in degree of fragmentation of natural block during blasting. The fragmentation conditions were evaluated by block fragmentation method in three different rock types. Blasted block size reduction from in-situ block size distribution (ISBD) to blasted block size distribution (BBSD) were analyzed based on modified Kuz-Ram models and other empirical models which were used to predict D50 of the blocks. Similarly, blastability index (BI), blastability designation (BD), and Fragmentation index (FI) were used to analyzed fractal dimension of block (i.e. volume reduction) from in-situ to blasted rock blocks where average reduction amount in block fragmentation were found 80.3%, 76.41% and 60.14% in Gneiss, Phyllite, and Metasandstone respectively. The result of this study revealed that the blastability and fragmentation index of rock mass depends on in-situ block size, rock mass strength, and powder factor used during blasting. Based on the outcome of the study rock fragmentation and fragmented block size can be predicted by understanding of the discontinuity characteristics of the rock mass along with rock mass class and powder factor of that blasting. Therefore, desired level of block fragmentation, blastability and fragmentation index of blasting rock mass can be got by modifying the blasting design according to the natural block size and rock mass strength of the rock mass.

show abstract

“…Blasting is a critical step in the mining operation sequence; good blasting necessitates proper preblast assessment to ensure high productivity and safety [1][2][3]. Making blast activity profitable is one method of limiting the cost implications of extra downstream tasks such as mucking, stacking, loading, pulverizing, and processing, according to Jug [4]. Fuerstenau et al also discovered that the costs of blasting and material processing/ore beneficiation influenced the mining activity cost [5].…”

Section: Introductionmentioning

confidence: 99%

Improvementof small scale dolomite mine blast fragmentation efficiency using hybrid artificial intelligence and soft computing approaches-A case study

Taiwo

2022

Preprint

View full text Add to dashboard Cite

Blast fragmentation efficiency prediction can improve blast productivity, but it is capital intensive when done with available software. Soft computing models based on artificial intelligence approaches and multivariate regression techniques were proposed in this study to predict small diameter hole blast fragmentation efficiency at the Akoko Edo dolomite quarry. WipFrag software was used to analyze and evaluate blast fragmentation performance based on images of blast muck piles. The proposed model's performance was evaluated using five model performance indices, comprising the average bias error, root mean square error, correlation coefficient, and average absolute error. The obtained results indicate that the proposed model of the Adaptive Neuro-fuzzy inference system (ANFIS) is proficient of accurate prediction of blast fragmentation efficiency when compared to artificial neural networks and multivariate regression models.

show abstract

Fragment Size Distribution of Blasted Rock Mass

Cited by 14 publications

References 4 publications

Evaluation of Rock and Explosive Properties for Fragmentation Characterization: An Application of WipFrag

Evaluation of Rock and Explosive Properties for Fragmentation Characterization: An Application of WipFrag

Influence of rock mass properties and powder factor on the fractal dimension of the natural rock mass blocks during blasting

Improvementof small scale dolomite mine blast fragmentation efficiency using hybrid artificial intelligence and soft computing approaches-A case study

Contact Info

Product

Resources

About