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1

Research on the Effect of the Mine Waste Dump on the Stability of Tunnels Below in the Quangninh Coal Area by Numecical Method

Van Kien Dang, Vo Trong Hung, Bui Xuan Nam, Nguyen Huu Sa

Inżynieria Mineralna

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2023

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no. 2, vol. 1

49--56

EN

Nowadays, there are many underground coal mines in Quang Ninh, Vietnam have been exploiting coal seams below the mine waste dump such as Khe Cham II, Mong Duong, Mao Khe, and Ha Lam… Coal Company. Many mine waste dumps have reached the height of dumping from 400m, especially up to over 400m. The rock mass pressure due to the weight of the rock mass in the mine waste dump is considered an artificial pressure formed from the process of dumping soil and rock, it will be part of the pressure acting on the furnace lines located under the mine waste dump. The paper presents the current status of the mine waste dump and the coal seams that have been and will be exploited located below the mining waste dump in Cam Pha Quang Ninh and based on the actual conditions of the Bang Nau, Khe Cham II coal mine waste dump. The studies used the 2D FEM RS2 program to create simulation models with the mine waste dump to study the primary stress distribution in the rock mass. The objective of this study is to highlight the influence of the relationship location of tunnels below with the inclined coal/rock mass layer on the rock support behavior of the underground tunnels in the Quang Ninh coal area. The simulation results will help the consulting and construction companies to calculate the rock pressure acting on the tunnels located under the mining waste dump.

2

Fuzzy Multi-Attribute Decision Model for the Optimal Mine Closure Option to Contribute to Sustainable Development in Binh Duong Province, Vietnam

Phan Hong Viet, Do Ngoc Tuoc, Bui Xuan Nam

Inżynieria Mineralna

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2023

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no. 2, vol. 1

249--256

EN

Binh Duong is the leading industry development province of Vietnam. In particular, quarries in Di An, Phu Giao and Tan Dong Hiep districts have contributed significantly to the demand for construction and transportation in the locality and vicinity. The quarries in Binh Duong province are exploited by the open-pit mining method. The mining depth is from 100m to 150 m. The mine surface area is hundreds of hectares. At the end of the quarries will leave huge pits. The current regulations of Vietnam on mine closure are mainly aimed at ensuring the stability of the physical and chemical factors of the mine, while the land use after the mine closure is permanent. Binh Duong province has a rapid urbanization rate, the use of land after mining here is very important and has a significant influence on the sustainable development of the region. Depending on the occupied area of the mine or mine cluster, there are many options to close the mine after mining based on the required technical, economic, social and environmental criteria. The paper uses fuzzy multi-attribute decision model to calculate the optimal solution selection. The selected option is to use the mine lake for tourism, entertainment and water storage at Nui Nho mine, Di An city, Binh Duong province with the highest total score of economic, social and environmental criteria.

3

Flight Height of UAV and Its Influence on the Precise Digital Elevation Model at Complex Terrain

Nguyen Quoc Long, Goyal Ropesh, Le Van Canh, Cao Xuan Cuong, Pham Van Chung, Bui Ngoc Quy, Bui Xuan Nam, Bui Khac Luyen

Inżynieria Mineralna

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2020

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no. 1, vol. 1

179--186

EN

The application of lightweight Unmanned Aerial Vehicle (UAV) has been increasingly common in 3D topographic surveys. Especially in the complex terrains such as open-pit mines, where the elevation is rapidly undulating, the UAV based mapping is more efficient, economic and safe compared to the conventional methods. However, one of the most important factors in UAV mapping of complex terrain is the flight altitude which needs to be seriously considered because of the safety and accuracy of generated DEMs. This paper aims to evaluate the influence of flight height on accuracy of DEMs generated for open-pit mines. For this purpose, the selected study area is a quarry with complex terrain located in the Northern Vietnam. The investigation was conducted with five flight heights of 50 m, 100 m, 150 m, 200 m, and 250 m. To assess the accuracy of resulting DEMs, 10 ground control points and 385 checkpoints measured by both GNSS/RTK and total station methods were used. The accuracy of DEM was assessed by using root-mean-square error (RMSE) in X, Y, Z, XY, and XYZ components. The result showed that the DEM models generated at the flight heights of less than 150 m have high accuracy, RMSEs on the 10 GCPs increased from 1.8 cm to 6.2 cm for vertical (Z), and from 2.6 cm to 6.3 cm for horizontal (XY), whereas RMSE on 385 checkpoints increases gradually from 0.05 m to 0.15 m for vertical (Z) when the height flight increased from 50 m to 250 m.

PL

Zastosowanie lekkich bezzałogowych statków powietrznych (UAV) jest coraz bardziej powszechne w badaniach topograficznych 3D. Zwłaszcza w skomplikowanych terenach, takich jak kopalnie odkrywkowe, w których wzniesienie gwałtownie faluje, mapowanie oparte na UAV jest bardziej wydajne, ekonomiczne i bezpieczne w porównaniu z metodami konwencjonalnymi. Jednak jednym z najważniejszych czynników w mapowaniu UAV złożonego terenu jest wysokość lotu, którą należy poważnie rozważyć ze względu na bezpieczeństwo i dokładność generowanych DEM. Niniejszy artykuł ma na celu ocenę wpływu wysokości lotu na dokładność DEM generowanych dla kopalni odkrywkowych. W tym celu wybranym obszarem badawczym jest kamieniołom o złożonym terenie położony w północnym Wietnamie. Badanie przeprowadzono przy pięciu wysokościach lotu 50 m, 100 m, 150 m, 200 m i 250 m. Aby ocenić dokładność uzyskanych DEM, wykorzystano 10 naziemnych punktów kontrolnych i 385 punktów kontrolnych mierzonych zarówno metodami GNSS/RTK, jak i metodami stacji całkowitej. Dokładność DEM oceniono za pomocą błędu pierwiastkowego średniego kwadratu (RMSE) w komponentach X, Y, Z, XY i XYZ. Wynik pokazał, że modele DEM generowane na wysokościach lotu poniżej 150 m mają wysoką dokładność, RMSE na 10 GCP wzrosły z 1,8 cm do 6,2 cm dla pionu (Z) i od 2,6 cm do 6,3 cm dla poziomu (XY), podczas gdy RMSE na 385 punktach kontrolnych wzrasta stopniowo z 0,05 m do 0,15 m dla pionu (Z), gdy lot na wysokości wzrósł z 50 m do 250 m.

4

A comparison of advanced computational models and experimental techniques in predicting blast induced ground vibration in open pit coal mine

Nguyen Hoang, Bui Xuan Nam, Moayedi Hossein

Acta Geophysica

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2019

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Vol. 67, no. 4

1025--1037

EN

Green mining is an essential requirement for the development of the mining industry. Of the operations in mining technology, blasting is one of the operations that signifcantly affect the environment, especially ground vibration. In this paper, four artificial intelligence (AI) models including artificial neural network (ANN), k-nearest neighbor (KNN), support vector machine (SVM), and classification and regression tree (CART) were developed as the advanced computational models for estimating blast-induced ground vibration in a case study of Vietnam. Some empirical techniques were applied and developed to predict ground vibration and compared with the four AI models as well. For this research, 68 events of blasting were collected; 80% of the whole datasets were used to build the mentioned models, and the rest 20% were used for testing/checking the models’ performances. Mean absolute error (MAE), determination coefficient (R2 ), and root-mean-square error (RMSE) were used as the standards to evaluate the quality of the models in this study. The results indicated that the advanced computational models were much better than empirical techniques in estimating blast-induced ground vibration in the present study. The ANN model (2-6-8-6-1) was introduced as the most superior model for predicting ground vibration with an RMSE of 0.508, R2 of 0.981 and MAE of 0.405 on the testing dataset. The SVM, CART, and KNN models provided poorer performance with an RMSE of 1.192, 2.820, 1.878; R2 of 0.886, 0.618, 0.737; and MAE of 0.659, 1.631, 0.762, respectively.