Dynamic optimization design of open-pit mine full-boundary slope considering uncertainty of rock mass strength.

Rock and soil strength profoundly influences the stability of open-pit mine slopes. Traditional slope design, based on limited drilling data, often disregards inherent uncertainties. Effectively utilizing new sample information from mining operations poses a challenge, hindering dynamic and differentiated design for the entire perimeter slope. To address this, we propose a dynamic optimization method considering rock mass strength uncertainty for the entire perimeter slope. Our approach involves designing slope angles separately in different zones, while thoroughly considering decision-makers' preferences. Furthermore, we delegate the final adjustment authority of slope angles within the safety permissible range to on-site decision-makers. Compared to traditional methods, our dynamic design method incorporates rock mass strength uncertainty into slope evaluation while also accounting for decision-makers' safety and economic preferences. Through a case study of a specific open-pit mine, our proposed dynamic design method increases the overall slope angle by approximately 2.5°, fully accommodating the influence of on-site decision-making preferences on slope design. This article introduces a new method of dynamic optimization of open-pit mine slope based on simplified observation method, which improves the flexibility of decision-making and realizes the differential design of the whole surrounding slope.

Creep characteristics and discharge optimization of overlying river inner dump: A case study of Yuanbaoshan open-pit coal mine in China.

Overlying river can accelerate the creep of the inner dump, so to master the creep characteristics of the overlying river can provide a theoretical basis for mine safety and discharge optimization. Taking the overlying river inner dump of Yuanbaoshan open-pit coal Mine in China as the research object, a design scheme is proposed to divide it into rolling zone and non-rolling zone. Based on the creep model obtained by in-situ deformation monitoring and laboratory rheological test, the creep evolution law and deformation of overlying channel after soil discharge, slope morphology and advancing position are simulated and analyzed. The results showed that the creep variable in the (non-) rolling zone had a nonlinear upward trend with time, and the initial upward trend was large. The maximum vertical and horizontal creep in the rolling area was located in the middle and upper part of the rolling line, while the maximum vertical and horizontal creep in the dump was located in the middle and upper part of the non-rolling area, respectively. The post-construction settlement and horizontal discharging increased with the increase of the discharge height, and the convergence creep of the top ten years after construction increased approximately linearly with the decrease of the distance from the shoulder of the inner dump. The rolled sand and gravel backfill belonged to the foundation of uniform settlement deformation in general, and the change of slope shape had little effect on the deformation of the slope top in the rolled area. The geoglage elongation in the dam area met the requirements. On the premise of ensuring the stability of the dump, the slope angle of the inner dump can be appropriately increased to increase the capacity of the inner dump. The research results can provide guidance for the construction of inner dump in open pit.

Mid-long term boundary dynamic optimization of open-pit coal mine considering coal price fluctuation.

The delineation of the open-pit mining boundary, particularly in the context of medium to long-term planning, forms the foundation of mining design. However, due to the non-linear and dynamic nature of the economic and technical parameters influencing boundary delineation, determining the optimal mining boundary can be exceedingly challenging. Currently, most boundary optimization methods assume that block parameters remain fixed, which results in enterprises assuming a certain level of risk when facing changes in internal and external conditions. In this regard, this paper introduces the concept of "achievement degree" to reflect the risk associated with the results of boundary design. Using coal prices as an example, this article applies the predicted coal price curve to boundary optimization adjustments by specifying the "achievement degree" requirements for various time periods, thereby facilitating risk-controlled and economically optimal boundary decisions. Taking the illustrative case of an idealized small-scale inclined coal seam open-pit mine, adjustments to the boundary closely track variations in coal prices, further enhancing returns. The results demonstrate that the method proposed in this paper can increase overall revenue by approximately 51.15% within the forecast period, while effectively managing risks.

Prediction method for the truck's fault time in open-pit mines based on exponential smoothing neural network.

The transport truck is one of the important equipment for open-pit mines, and predicting the truck's fault time is of great significance in improving the economic benefits of open-pit mines. In this paper, we discuss the reason for the large prediction error of the exponential smoothing method. Then, we propose a novel nonlinear exponential smoothing method (ESNN) for predicting the truck's fault time, and demonstrate the equivalence between our approach and the neural network structure. Finally, based on the augmented Lagrange function, the solving method of ESNN is proposed. We conduct experiments on real-world datasets and our results demonstrate the effectiveness of ESNN in comparison to existing state-of-the-art methods. Our approach makes it easier for maintenance personnel to predict fault situations in advance and provides a basis for enterprises to develop preventive maintenance plans.

Boundary optimization of inclined coal seam open-pit mine based on the ISSA-LSSVR coal price prediction method.

As an important link in the complex system engineering project of open pit mining, the quality of the boundary determines the performance of the project to a large extent. However, changes in economic indicators may raise doubts about the optimality of mining boundaries. In this article, a coal price time series forecasting model that considers some amount of redundancy is proposed, which combines an improved sparrow search algorithm (ISSA) and a least squares support vector regression machine regression (LSSVR) algorithm. The optimal values of the penalty factor and kernel function parameter of the LSSVR model are selected by ISSA, which improves the prediction accuracy and generalization performance of the forecasting model. A multistep decision optimization method under fluctuating coal price conditions is proposed, and the model prediction results are applied to the boundary optimization design process. Using the widely applied block model as the basis, a set of optimal production nested pits is obtained, allowing the realm design results to fit the coal price fluctuation trend and further enhance enterprise efficiency. The applicability and effectiveness of this method were verified by taking an ideal two-dimensional model and an inclined coal seam open-pit coal mine in Xinjiang as an example.