Search Results (70)

In this study, we introduce a novel 2-step compact scheme-based high-order correction method for computational fluid dynamics (CFD). Unlike traditional single-formula-based schemes, our proposed approach refines flux function values by leveraging results from high-order compact schemes on the same stencils, provided a certain smoothness condition is met. By applying this method, we achieve a more stable and efficient compact corrected Weighted Essentially Non-Oscillatory (WENO) scheme. The results demonstrate significant improvements across all enhanced schemes, particularly in capturing shock waves sharply and maintaining stability in complex scenarios, such as two interacting blast waves, as validated through 1D benchmark tests. In addition, error analysis is also provided for the two different correction configurations based on WENO. Full article

In recent years, geological disasters such as water inrush during drilling and blasting operations have posed significant challenges in tunnel engineering. This paper presents a novel continuous-discrete coupling method based on LS-DYNA, combining the finite element method (FEM) and smoothed particle hydrodynamics (SPH), to simulate the water inrush phenomenon in blasting engineering. The proposed FEM-SPH model effectively captures the propagation of explosion shock waves, simulates small deformation areas with solid grids, and models water behavior using SPH. This study systematically investigates the dynamic evolution of water inrush, divided into three distinct phases: the rupture of the water-resistant rock layer, the emergence of fluid-conducting channels, and the onset of large-scale water influx. Results indicate that under blasting load, the stress of the surrounding rock increases sharply, leading to instantaneous water inrush. The FEM-SPH model demonstrates superior performance in simulating the complex interactions between blasting stress waves, water pressure, and rock mass damage. This research provides new insights and methods for water control in tunnel engineering and offers significant potential for preventing water inrush disasters in underground construction. Full article

With the acceleration of urban renewal, directional blasting has become a common method for building demolition. Analyzing the time–frequency characteristics of blast-induced seismic waves allows for the assessment of risks to surrounding structures. However, the signals monitored are frequently tainted with noise, which undermines the precision of time–frequency analysis. To counteract the dangers posed by blast vibrations, effective signal denoising is crucial for accurate evaluation and safety management. To tackle this challenge, a dual denoising model is proposed. This model consists of two stages. Firstly, it applies endpoint processing (EP) to the signal, followed by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to suppress low-frequency clutter. High-frequency noise is then handled by controlling the multi-scale permutation entropy (MPE) of the intrinsic mode functions (IMF) obtained from EP-CEEMDAN. The EP-CEEMDAN-MPE framework achieves the first stage of denoising while mitigating the influence of endpoint effects on the denoising performance. The second stage of denoising involves combining the IMF obtained from EP-CEEMDAN-MPE to generate multiple denoising models. An objective function is established considering both the smoothness of the denoising models and the standard deviation of the error between the denoised signal and the measured signal. The denoising model corresponding to the optimal solution of the objective function is identified as the dual denoising model for blasting seismic wave signals. To validate the denoising effectiveness of the denoising model, simulated blasting vibration signals with a given signal-to-noise ratio (SNR) are constructed. Finally, the model is applied to real engineering blasting seismic wave signals for denoising. The results demonstrate that the model successfully reduces noise interference in the signals, highlighting its practical significance for the prevention and control of blasting seismic wave hazards. Full article

One of the technical problems that must be solved in coal mine production is when the coalface rapidly crosses the fault. Based on the occurrence characteristics of the F₆ fault (maximum throw: 13.5 m) in the #3_up1101 fully mechanized caving coalface at Gaozhuang Coal Mine, two different solutions allowing the coalface to pass through this fault were proposed, and the solution of pre-driven roadways with rock pillars was optimally determined. The main implementation steps of the method include designing the layout parameters of the pre-driven roadways, determining the width for rock pillars between the adjacent pre-driven roadways, construction of pre-driven roadways by smooth wall blasting, and controlling the surrounding rock deformation of the pre-driven roadways. The results of engineering practice show that it took only 23 days for this coalface to pass through fault F₆, about one month shorter than the time required by traditional methods (e.g., proactively taking a detour). Moreover, this method helped achieve stable coal production (an 8.5 × 10⁴ t increase), prevented much gangue from mixing with coal, reduced wear and tear on the mining equipment, and enhanced safety. The economic benefits delivered totaled about CNY 71.1 million. Therefore, this method can ensure continuous, safe, and efficient mining at the coalface, alleviating the tight situation of mine production succession. The results of this study can provide a good reference to help coalfaces rapidly move across faults under similar geological conditions in other mines. Full article

Monitoring tapping states, which reflects the smoothness of blast furnace (BF) production, is important in the blast furnace ironmaking process. Currently, these monitoring data are often recorded manually, which has limitations such as low reliability and high delays. In this study, we propose an automatic recognition approach for tapping states based on object detection, using furnace front monitoring videos combined with learning-based image processing technology. This approach addresses crucial aspects such as automatically recognizing the start and end times of iron tapping and slag discharging, accurately calculating their duration, and logging tapping sequences for multi-taphole operations. The experimental results demonstrate that this approach can meet the requirements of accurate and real-time recognition of tapping states and calculation of key monitoring data in industrial applications. The automatic recognition system developed based on this approach has been successfully applied in engineering projects, which provides real-time guidance for comprehensive monitoring, intelligent analysis, and operational optimization in blast furnace production. Full article

The solder burrs on the 304V wire surface can easily scratch the vascular tissue during interventional treatment, resulting in complications such as medial tears, bleeding, dissection, and rupture. Abrasive blasting is often used to remove solder burr and obtain a smooth surface for the interventional device. This study conducted an abrasive blasting experiment to explore the effects of process parameters (air pressure, lift-off height, abrasive volume, and abrasive type) on processing time, surface roughness, and mechanical properties to reveal the material removal mechanism. The results indicated that the resin abrasive can remove the SAC burr and keep the 304V integrity due to the proper hardness and Young’s module. Impaction pits are the main material removal mode in abrasive blasting. The processing time decreases with the increase in air pressure. The surface roughness increases with the increase in abrasive volume. The primary and secondary factors affecting the surface roughness of the 304V wire after abrasive blasting are the abrasive type and air pressure, followed by the abrasive volume and lift-off height. Blasting leads to a decrease in yield strength, and Young’s modulus and the hardness of the abrasive will affect the tensile strength. This study lays a foundation for understanding abrasive blasting and different cutting mechanisms. Full article

The natural caving method, as a new technique in underground mining, has been promoted and applied in several countries worldwide. The destruction of the bottom rock mass structure directly impacts the structural stability of underground engineering, resulting in damage and collapse of underground tunnels. Therefore, based on the principles of explosion theory and field monitoring data, a scaled three-dimensional numerical simulation model of underground blasting was constructed using LS-DYNA19.0 software to investigate the attenuation patterns of underground blasting vibrations and their impact on nearby tunnels. The results show that the relative error range between the simulated blasting vibration velocities based on the FEM-SPH (Finite Element Method–Smoothed Particle Hydrodynamics) algorithm and the measured values is between 7.75% and 9.85%, validating the feasibility of this method. Significant fluctuations in blasting vibration velocities occur when the blast center increases to within a range of 10–20 m. As the blast center distance exceeds 25 m, the vibration velocities are increasingly influenced by the surrounding stress. Additionally, greater stress results in higher blasting vibration velocities and stress wave intensities. Fitting the blasting vibration velocities of various measurement points using the Sadovsky formula yields fitting correlation coefficients ranging between 0.92 and 0.97, enabling the prediction of on-site blasting vibration velocities based on research findings. Changes in propagation paths lead to localized fluctuations in the numerical values of stress waves. These research findings are crucial for a deeper understanding of underground blasting vibration patterns and for enhancing blasting safety. Full article

Objectives: Hybrid implants commonly exhibit decreased corrosion resistance and fatigue due to differences in compressive residual stresses between the smooth and rough surfaces. The main objective of this study was to investigate the influence of an annealing heat treatment to reduce the residual stresses in hybrid implants. Methodology: Commercially pure titanium (CpTi) bars were heat-treated at 800 °C and different annealing times. Optical microscopy was used to analyze the resulting grain growth kinetics. Diffractometry was used to measure residual stress after heat treatment, corrosion resistance by open circuit potential (E_OCP), corrosion potentials (E_CORR), and corrosion currents (I_CORR) of heat-treated samples, as well as fatigue behavior by creep testing. The von Mises distribution and the resulting microstrains in heat-treated hybrid implants and in cortical and trabecular bone were assessed by finite element analysis. The results of treated hybrid implants were compared to those of untreated hybrid implants and hybrid implants with a rough surface (shot-blasted). Results: The proposed heat treatment (800 °C for 30 min, followed by quenching in water at 20 °C) could successfully homogenize the residual stress difference between the two surfaces of the hybrid implant (−20.2 MPa). It provides better fatigue behavior and corrosion resistance (p ˂ 0.05, ANOVA). Stress distribution was significantly improved in the trabecular bone. Heat-treated hybrid implants performed worse than implants with a rough surface. Clinical significance: Annealing heat treatment can be used to improve the mechanical properties and corrosion resistance of hybrid surface implants by homogenizing residual stresses. Full article

With the increasing awareness of environmental protection, the rotary hearth furnace system has emerged as a key technology that facilitates a win-win situation for both environmental protection and enterprise economic benefits. This is attributed to its high flexibility in raw material utilization, capability of directly supplying blast furnaces, low energy consumption, and high zinc removal rate. However, the complexity of the raw material proportioning process coupled with the rotary hearth furnace system’s reliance on human labor results in a time-consuming and inefficient process. This paper innovatively introduces an intelligent formula method for proportioning raw materials based on online clustering algorithms and develops an intelligent batching system for rotary hearth furnaces. Firstly, the ingredients of raw materials undergo data preprocessing, which involves using the local outlier factor (LOF) method to detect any abnormal values, using Kalman filtering to smooth the data, and performing one-hot encoding to represent the different kinds of raw materials. Afterwards, the affinity propagation (AP) clustering method is used to evaluate past data on the ingredients of raw materials and their ratios. This analysis aims to extract information based on human experience with ratios and create a library of machine learning formulas. The incremental AP clustering algorithm is utilized to learn new ratio data and continuously update the machine learning formula library. To ensure that the formula meets the actual production performance requirements of the rotary hearth furnace, the machine learning formula is fine-tuned based on expert experience. The integration of machine learning and expert experience demonstrates good flexibility and satisfactory performance in the practical application of intelligent formulas for rotary hearth furnaces. An intelligent batching system is developed and executed at a steel plant in China. It shows an excellent user interface and significantly enhances batching efficiency and product quality. Full article

Discarded rubber tires (DSRTs) have become a significant landfill and environmental problem that needs to be solved to reduce health risks, fires, and other environmental issues. The inclusion of such rubber can enhance the ductility of concrete and increase its resistance to dynamic loads, as well as enhancing the concrete’s durability and lifespan by modifying its impact resistance (IR). However, the smooth surface and low bond strength with cement pastes directly lead to a decrease in the strength of the proposed concrete, restricting its range of use in the construction industry. The inclusion of pozzolanic materials with high hydraulic capacity in the concrete matrix as partial cement replacements, such as granulated blast furnace slag (GBFS), has led to enhanced performance of the modified rubberized concretes (MRCs) in terms of bond strength and other mechanical properties. Based on these facts, this study aimed to evaluate the effects of including 20% GBFS and various levels (5–25%) of metakaolin (MK) as replacements for ordinary Portland cement (OPC), on the engineering properties of newly designed rubberized concretes. For this purpose, twenty-two mixes of MRCs were prepared by replacing the OPC and natural aggregates with various contents of GBFS, MK, and DSRTs. The results indicated that the MRC specimens prepared with a ternary blend of OPC-GBFS-MK illustrated significant improvements in strength performance, wherein the compressive strength (CS) after the curing age of 56 days (46.5 MPa) was higher than that of the OPC control mix (41.2 MPa). Moreover, the mix designed with high amounts of MK-GBFS-DSRTs significantly enhanced the engineering properties of the proposed MRCs by increasing the IR and reducing the total porosity. It can be asserted that, by using MK, GBFS, and DSRTs as renewable resources for construction materials, the environmental problems can significantly be reduced, with excellent benefits in the engineering properties of the designed rubberized concretes. Full article

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production. Full article

Blast furnace slag is an industrial waste. Its disposition is generally by means of landfilling or stacking, which goes against the concept of sustainable development. In order to maximize its reuse and abate its adverse effects on the natural environment, this study innovated a solution of using blast furnace slag to produce 3D printing materials. Blast furnace slag was mixed with desulfurization gypsum to adapt to the operation of 3D printers. The mixture has fluidity, viscosity, and hydraulicity. Fluidity allows the mixture to smoothly pass through the transportation pipeline and nozzle of the machine; viscosity ensures that the extruded mixture is gradually stacked and settled; hydraulicity guarantees that the mixture solidifies and forms completely solid objects after dehydration and drying. Fully suitable 3D printers are rare in the market. Therefore, the printing nozzle and reserve device of the 3D printer were designed and improved in this study according to the material characteristics, enhancing the smoothness of the mixture during 3D printing. The sustainable application of blast furnace slag in the field of 3D printing not only favors diminishing environmental pollution and resource consumption but also provides a further sustainable production method for human beings. Full article

In tunnel smooth blasting, optimizing the water interval charging structure of peripheral holes is of great significance in improving the effect of smooth blasting and reducing the unit consumption of explosives. Addressing the issue of a single traditional evaluation standard, this paper proposes a composite index evaluation method for rock blasting damage in different zones, and the best charging structure is optimized according to the evaluation results. Taking Liyue Road Tunnel Light Smooth Blasting Project in Chongqing as the Research Background, the numeric models were established with ten kinds of charge structures, the charge structures and explosive quantity were optimized according to the evaluation results, and then the field tests were conducted. The results show that when the length of the water medium at the bottom of the hole is 20 cm, the damage range of the retained rock mass can be controlled while ensuring rock fragmentation. If the length of the water medium at the orifice and in the center of the hole is more than 30 cm, it will affect the superposition effect of the blast stress wave, resulting in under-excavation; in the preferred charge structure, the ratio of the length of the upper and lower explosives reaches 1:3, and the ratio of the length of the water medium is 2:2:1, which achieves a better rock-breaking effect in the field test. Full article

This study introduces a novel method to enhance numerical simulation accuracy for high-speed flows by refining the weighted essentially non-oscillatory (WENO) flux with higher-order corrections like the modified weighted compact scheme (MWCS). Numerical experiments demonstrate improved sharpness in capturing shock waves and stability in complex conditions like two interacting blast waves. Key highlights include simultaneous capture of small-scale smooth fluctuations and shock waves with precision surpassing the original WENO and MWCS methods. Despite the significantly improved accuracy, the extra computational cost brought by the new method is only marginally increased compared to the original WENO, and it outperforms MWCS in both accuracy and efficiency. Overall, this method enhances simulation fidelity and effectively balances accuracy and computational efficiency across various problems. Full article

Coke plays a key role as the skeleton of the charge column in BF. The gas path formed by the coke layer in the BF has a decisive influence on gas permeability. At high temperatures, the interface between coke and ore undergoes a melting reaction of coke and a reduction reaction of ore. The better the reducibility of the ore, the more conducive it is to the coupling reaction of ore and coke. The melting loss reaction of coke becomes more intense, and the corresponding strength of coke will decrease, which will affect the permeability of the blast furnace and is not conducive to the smooth operation of the blast furnace. Especially with a deterioration in iron ore quality, BF operation faces severe challenges, which makes it necessary to find an effective way to strengthen BF operation. In this study, a melting-dropping furnace was used to develop and clarify the high-temperature interaction between coke and iron ores with different layer thicknesses. The influencing factors were studied by establishing a gas permeability mathematical model and observing the metallographic microscope images of samples after the coke solution loss reaction. The relationships between coke layer thickness, distribution of gas flow, and pressure drop were obtained. The results showed that, under certain conditions, the gas permeability property of a furnace burden has been improved after the coke layer thickness increased. Upon observing the size of coke particles at the interface reaction site, the degree of melting loss reaction can be determined. A smaller particle size indicates more melting loss reaction. A dripping eigenvalue for molten metal was introduced to evaluate the dynamic changes in the comprehensive dripping properties of molten metal of furnace burden, which showed that the dripping eigenvalue for the molten metal could deteriorate because of the unruly thickness and the coke layer thickness should be limited through considering the operational indicators of the blast furnace. Full article