Prediction of blast‑induced ground vibrations in quarry sites: a comparison of GP, RSM and MARS

Hosseini, Seied Ahmad; Tavana, Amir; Abdolahi, Seyed Mohamad; Darvishmaslak, Saber

doi:10.1016/j.soildyn.2019.01.011

Cited by 43 publications

(12 citation statements)

References 54 publications

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“…In this study, the cosine amplitude method (CAM) was used to assess the sensitivity of each input parameter used in the ANN analyses. Several researchers [ 69 , 70 , 71 , 72 , 73 ] also adopted this method (see Equation (6)) to evaluate the sensitivity degree of each input parameter by determining the correlation degree ( r ij ) between the input and output pairs. The higher the value of r ij , the greater is the effect of the relevant input parameter.…”

Section: Resultsmentioning

confidence: 99%

Assessment of Böhme Abrasion Value of Natural Stones through Artificial Neural Networks (ANN)

Strzałkowski

Köken

2022

Materials

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This present study explored the Böhme abrasion value (BAV) of natural stones through artificial neural networks (ANNs). For this purpose, a detailed literature survey was conducted to collect quantitative data on the BAV of different natural stones from Turkey. As a result of the ANN analyses, several predictive models (M1–M13) were established by using the rock properties, such as the dry density (ρd), water absorption by weight (wa), Shore hardness value (SHV), pulse wave velocity (Vp), and uniaxial compressive strength (UCS) of rocks. The performance of the established predictive models was evaluated by using several statistical indicators, and the performance analyses indicated that four of the established models (M1, M5, M10, and M11) could be reliably used to estimate the BAV of natural stones. In addition, explicit mathematical formulations of the proposed ANN models were also introduced in this study to let users implement them more efficiently. In this context, the present study is believed to provide practical and straightforward information on the BAV of natural stones and can be declared a case study on how to model the BAV as a function of different rock properties.

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Section: Resultsmentioning

confidence: 99%

Assessment of Böhme Abrasion Value of Natural Stones through Artificial Neural Networks (ANN)

Strzałkowski

Köken

2022

Materials

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“…The pressure induced by blast wave propagation in a soil medium is different from the incident pressure. Many studies have investigated the blast-induced vibration parameters for a soil medium [4][5][6]. The peak pressure in different soil types can be obtained by Equations ( 5) and ( 6) [15].…”

Section: Blast Loadingmentioning

confidence: 99%

“…A noteworthy point in the results is a sudden increase in peak blast pressure at the base of the mixture layers, as shown in Figure 3a-c. Equation (5) states that soil density directly impacts the peak pressure; therefore, this increase at the interface of two layers is due to the higher density of sand in the mixture layer. These results indicate that peak blast pressure decreased with depth for pure sand and the mixture layer.…”

Section: Effect Of Sand-tire Shred Mixture On Peak Blast Pressurementioning

confidence: 99%

“…A surface explosion can cause damage to underground structures; therefore, soil behavior must be evaluated under explosion hazards so that we may be able to create a blast-resistant design for these structures [1][2][3]. Blast-induced vibration parameters have received attention from many researchers [4][5][6]; amongst the findings is that peak blast pressure is the most critical parameter for underground structures [7][8][9]. This parameter is directly related to peak particle velocity, with different empirical equations defining them [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Sand–Tire Shred Mixture Performance in Controlling Surface Explosion Hazards That Affect Underground Structures

et al. 2021

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Blasting is an unavoidable activity in geotechnical engineering, road and tunnel construction, and mining and quarrying. However, this activity can expose the environment to various hazards that are challenging to control and, at the same time, critical for the safety of site workers, equipment, and surrounding structures. This research aims to evaluate the ability of sand–tire shred mixtures to reduce peak blast pressure, which is the leading cause of damage to underground structures under surface explosion. ABAQUS software is used to model the material behavior under explosion and is validated using the results of previous studies and an empirical equation. Different scenarios are created by using mixture layers with different thicknesses (2, 4, and 6 m) and tire shred contents (10%, 20%, and 30%) that are subjected to various surface explosion charges (100, 500, 1000, and 5000 kg). The thickness of the mixture layer is found to be directly related to the dissipation of explosion energy. However, the percentage of the rubber content in the mixture is only significant in reducing peak blast pressure when a thick enough mixture layer is used. The results confirm the adequate performance of the correctly chosen sand–tire shred mixtures in reducing peak blast pressure and protecting the underground structure from surface explosion hazards.

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“…Azimia et al [15] proposed a new hybrid evolutionary artificial neural network (ANN) optimized by a genetic algorithm (GA) to predict peak particle velocity (PPV). Hosseini et al [16] explored the possibility of using three methods of soft computing, namely, genetic programming (GP), response surface methodology (RSM) and multivariate adaptive regression splines (MARS), to predict the peak particle velocity (PPV) values. Zhang et al [17] used a particle swarm optimization (PSO) and extreme gradient boosting machine (XG Boost) to create the PSO-XG Boost mode.…”

Section: Introductionmentioning

confidence: 99%

Research of the Technical Seismicity Due to Blasting Works in Quarries and Their Impact on the Environment and Population

et al. 2021

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Vibrations caused by blasting works have an impact not only on buildings but also the internal environment of the buildings. If these buildings are situated in the surroundings of quarries, the citizens can perceive these vibrations negatively. By applying an appropriate millisecond timing interval, it is possible to lower the intensity of vibrations to the levels that the citizens will not perceive as negative effects inside the buildings. The limit values for this vibration intensity have not been defined to date. For the protection of the building from the vibrations, normative values of the particle velocity and frequency were determined. Hygienic standards for the inhabitants of the housing were applied, which assessed the impact of the vibration on humans through the measurement of the vibration acceleration in the housing. In this article, the results of the research carried out in Trebejov Quarry are presented. The experimental blasts carried out in Trebejov Quarry proved that the reduction in the vibration intensity under the value 2 mm.s−1 led to the satisfaction of the inhabitants.

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Prediction of blast‑induced ground vibrations in quarry sites: a comparison of GP, RSM and MARS

Cited by 43 publications

References 54 publications

Assessment of Böhme Abrasion Value of Natural Stones through Artificial Neural Networks (ANN)

Assessment of Böhme Abrasion Value of Natural Stones through Artificial Neural Networks (ANN)

Sand–Tire Shred Mixture Performance in Controlling Surface Explosion Hazards That Affect Underground Structures

Research of the Technical Seismicity Due to Blasting Works in Quarries and Their Impact on the Environment and Population

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