Hasil untuk "Mining engineering. Metallurgy"

Yizhou Sun, Jiawei Han

Deren CHEN, Chi ZHANG, Meng WANG et al.

The uniaxial compression experiment under low pressure environment was carried out by using tectonic coal samples. The acoustic emission response characteristics of coal fracture in low pressure environment were obtained by using fast Fourier transform (FFT) and wavelet packet decomposition. The results show that when the loading stress of coal increases, the acoustic emission spectrum becomes more abundant, and the overall trend shows a left shift. When the gas pressure increases, the frequency spectrum of the acoustic emission signal gradually transitions from the initial low-frequency high-energy state to the high-frequency low-energy state, and its frequency range gradually narrows. At the same time, the original complex multi-peak shape is gradually simplified into a single peak shape. As the stress increases, the proportion of acoustic emission energy in the frequency band of 0-4.38 kHz gradually increases, while the acoustic emission energy in other frequency bands gradually decreases. The signal energy proportion in the two frequency bands of 2.92-4.38 kHz and 4.38-5.84 kHz has the most obvious response trend to stress change. When the air pressure changes, the proportion of acoustic emission energy in the three frequency bands of 2.92-4.38 kHz, 4.38-5.84 kHz and 7.30-8.76 kHz shows a significant response trend with the change of air pressure. This phenomenon shows that the two frequency bands of 2.92-4.38 kHz and 4.38-5.84 kHz are the characteristic frequency bands of tectonic coal fracture process.

Yerbolat Makhambetov, Sultan Kabylkanov, Saule Abdulina et al.

This study investigates the thermodynamic and experimental aspects of producing a chromium–manganese ligature under high-temperature smelting conditions using low-grade iron–manganese ore and ferrosilicochrome (FeSiCr) dust as both a reducing agent and a chromium source. Thermodynamic modeling of the multicomponent Fe–Cr–Mn–Si–Al–Ca–Mg–O system was carried out using the HSC Chemistry 10 and FactSage 8.4 software packages to substantiate the temperature regime, reducing agent consumption, and conditions for the formation of a stable metal–slag system. The calculations indicated that efficient reduction of manganese oxides and formation of the metallic phase are achieved at a smelting temperature of 1600 °C with a reducing agent consumption of approximately 50 kg. Experimental smelting trials conducted in a laboratory Tammann furnace under the calculated parameters confirmed the validity of the thermodynamic predictions and demonstrated the feasibility of obtaining a concentrated chromium–manganese ligature. The resulting metallic product exhibited a high total content of alloying elements and had the following chemical composition (wt.%): Fe 35.41, Cr 41.10, Mn 8.15, and Si 4.31. SEM–EDS microstructural analysis revealed a uniform distribution of chromium and manganese within the metallic matrix, indicating stable reduction behavior and favorable melt crystallization conditions. The obtained results demonstrate the effectiveness of an integrated thermodynamic–experimental approach for producing chromium–manganese ligatures from low-grade mineral raw materials and industrial by-products and confirm the potential applicability of the proposed process for complex steel alloying.

Volodymyr V. Kukhar, Yevhen Chuprinov, I.Yu. Navolniev et al.

The article investigates energy consumption during the drying stage of iron ore pellets, a critical process in ensuring energy efficiency in mining and metallurgical production. Particular attention is given to the influence of charge material moisture content and the application of SAS (SAS) on the specific consumption of energy resources, namely electricity and natural gas. Industrial trials were conducted at one of the leading mining and processing enterprises in the Kryvyi Rih region, focusing on the transition from the baseline (in-house) concentrate to raw material from another regional enterprise, pre-treated with non-ionic SAS. It was established that the increased dispersity and hydrophilicity of the new raw material concentrate necessitate additional moistening of the charge, significantly affecting thermal regimes and energy expenditures during drying. Based on collected experimental data, regression models were developed to quantitatively predict the specific consumption of electricity and gas as a function of technological parameters. The primary factors influencing energy consumption were identified as the moisture content of the charge and the daily throughput of the drying unit. An increase in specific electricity consumption by 17.73% and natural gas consumption by 33.25% was recorded, accompanied by a simultaneous reduction in productivity by 9.55%. The findings are relevant for specialists in energy management, electrical engineering, and thermal analysis in metallurgy, particularly in the development of strategies for optimizing energy consumption under industrial conditions.

Aleksandr Vladimirov, Yury Tsygankov

The study objective is to find the possibility of using intelligence systems together with vibration turning technology to ensure the quality of the surface layer and improve the performance properties of products in industries such as automotive, aircraft, space technology, mining and metallurgical engineering, etc. The task to which the paper is devoted is to ensure the operational properties of machine parts by vibration turning. To a greater extent, the operational properties depend on the quality parameters of the surface layer, which determine the wear resistance, fatigue strength and other operational properties of machine parts. Research methods. Theoretical analysis of literature references on the formation of regular microrelief on the contacting surfaces of machine parts, which makes it possible to improve the operational properties of machine parts and equipment. The novelty of the work is in the fact that neural network models will be obtained that allow determining surface treatment modes based on a given shape of a regular microrelief, degree, and depth of the surface layer. The practical significance is in the development of a technology that will allow obtaining the required regular microrelief, degree, and depth on the surface of the parts, providing them with the necessary operational characteristics. Study results. As a result of the theoretical analysis, the prospects of using vibration turning together with intelligence systems to ensure the quality of the surface layer of machine parts during the formation of a regular microrelief are presented. Conclusions: one of the main directions of developing modern mechanical engineering is creating automated product lifecycle management systems based on artificial intelligence. Special attention is paid to the prospects of using vibration cutting to form a regular microrelief. The assumption is substantiated about the expediency of creating an intelligence quality assurance system for the surface layer of machine parts based on artificial neural networks, which makes it possible to provide a regular microrelief of a given shape on the surface of the part at the required degree and depth.

Yuzhen Yu, Weikang Ding, Xi Wang et al.

65 Mn is a high-quality carbon structural steel that exhibits excellent mechanical properties and machinability. It finds broad applications in machinery manufacturing, agricultural tools, and mining equipment, and is commonly used for producing mechanical parts, springs, and cutting tools. Fe901 is an iron-based alloy that exhibits excellent hardness, structural stability, and wear resistance. It is widely used in surface engineering applications, especially laser cladding, due to its ability to form dense and crack-free metallurgical coatings. To enhance the surface hardness and wear resistance of 65 Mn steel, this study employs a laser melting process to deposit a multi-layer Fe901 alloy coating. The phase composition, microstructure, microhardness, and wear resistance of the coatings are investigated using X-ray diffraction (XRD), optical microscopy, scanning electron microscopy (SEM), Vickers hardness testing, and friction-wear testing. The results show that the coatings are dense and uniform, without visible defects. The main phases in the coating include solid solution, carbides, and α-phase. The microstructure comprises dendritic, columnar, and equiaxed crystals. The microhardness of the cladding layer increases significantly, with the multilayer coating reaching 3.59 times the hardness of the 65 Mn substrate. The coatings exhibit stable and relatively low friction coefficients ranging from 0.38 to 0.58. Under identical testing conditions, the wear resistance of the coating surpasses that of the substrate, and the multilayer coating shows better wear performance than the single-layer one.

G. A. Sorokin, S. A. Syurin, M. N. Kiryanova

Introduction. With the combined and complex action of harmful occupation factors, traditional methods fail to allow an objective assessing of age-related changes in health. The purpose of the work. To analyze and give a hygienic assessment of the age trend in prevalence in miners and metallurgists of the Kola Arctic. Materials and methods. There were examined three groups of workers of the Kola Arctic region including 1758 workers from the mining complex with harmful working conditions (degree of harm 3.1.–3.3); 2181 workers of the metallurgical enterprise (degree of harm 3.1.–3.3); 242 engineering and technical staff (hazard classes 2 and 3.1). There were investigated 12 classes of diseases, established according to the data of periodic medical examinations. The average values of morbidity indices and linear regression indice were calculated as “disease risk = annual gain in risk (AGR) · age + const”. The relative assessment of the AGR was carried out in relation to the actual value to the control, background value. Results. For each class of diseases in four age groups of employees (20–29; 30–39; 40–49; 50–59 years). These linear regressions were calculated. The obtained AGR values were compared with the control values and the values in the report. The obtained values ​​of the AGR were compared with the control values ​​and literature data. The highest AGR for diseases of the circulatory system, musculoskeletal system, and chronic diseases was found in workers in the mining complex. The highest annual increase in the risk of diseases of the respiratory, genitourinary and endocrine systems was observed in workers in metallurgical production. The annual rise in the risk of diseases of the organs of vision was the highest in the group of specialists. The differences in the prevalence in the examined groups of workers are due to the differences in the annual increases. Limitations. The limitation of the study may be the insufficient amount of data to calculate the AGR in women due to the legislative prohibition of the use of female labour in underground work and in some types of metallurgical industries. Conclusion. The workers at the mining complex have the highest annual gain in the risk for diseases of the circulatory system, musculoskeletal system, and in the number of chronic diseases. Metallurgical workers have the highest annual increase in the risk of diseases of the respiratory system, genitourinary, and endocrine systems. The annual increase in the risk of diseases of the visual organs is of the greatest importance in the group of specialists. The differences in the disease levels of the surveyed groups of workers are due to differences in their annual increases.

Qiujie MENG, Yixiang SONG, Da HUANG et al.

The sensitivity of the ice-water transition in glacial debris to temperature rise has become a significant concern. In recent years, there has been an increase in reports of ice avalanches caused by the thawing of glacial debris, which can be attributed to the impact of global warming. To study the temperature-dependent degradation of shear strength in glacial debris, a Finite Discrete Element Model (F-DEM) was developed. This model consists of solid permafrost and gravel elements and cohesive elements, as well as cohesive elements. The strength degradation law of the glacial debris, as observed in tests, is described as a strength degradation process of the cohesive elements. Initially, cohesive elements using the “traction-separation” criterion are set in between solid elements to represent interstitial ice. Subsequently, a strength degradation law governing the degradation law is implemented through the development of the VUSDFLD subroutine in Abaqus. The strength degradation of the cohesive elements is controlled by temperature field variables. The macroscopic numerical results obtained from the simulation were compared to experimental results. The simulated shear characteristics, including peak shear strength, deformation mode, and failure mode closely matched the experimental findings. The influence of three different factors, namely the thawing rate, gravel content, and stress magnitude on shear behavior was investigated. When the thawing rate is less than or equal to 2%, the failure mode exhibits a rough “serrated” pattern; as the thawing rate increases (> 2%), the shear surface gradually transitions to a smoother “circular arc” shape. The significant difference in strength at the permafrost-gravel interface can easily lead to stress concentration, resulting in cracks propagating along the interface. Increasing gravel content leads to a decrease in the shear strength of glacial debris, and the sensitivity of the shear strength to gravel content decreases with increasing thawing ratio. Under high shear loading, even a slight increase in temperature can cause sudden changes in shear strain. The deformation under constant load can be divided into three stages: the initial stage, the developmental stage, and the rapid deformation stage. In the initial stage, shear strain initially increases and then stabilizes; and during the developmental stage, there is a critical point in strain; during the rapid deformation stage, shear strain increases rapidly. The temperature of the critical point decreases with an increase in initial shear stress, and they are approximately linearly related. At higher shear stress levels, the shear strain of glacial debris is highly sensitive to temperature changes. Further studies should be conducted on model simplification, variation laws of parameters, phase transitions, and size effects to better simulate the shear strength degradation behavior under actual glaciers.

Xiaoting Li, Jin Wang

Laser melting deposition (LMD) has great advantages and broad development prospects in the manufacture of high-performance complex aluminum alloy components. In this paper, AlSi10Mg was deposited by 5 kW diode laser, and the effects of shielding gas flow, scanning layer thickness, scanning line spacing and powder drying on the density and mechanical properties of the deposited samples formed parts were investigated in details. The results indicated that the bulk density increased significantly with the increase of the shielding gas flow rate. Meanwhile, when the powders were dried in advance, the density could reach to the 99.5 %. The maximum tensile strength was 237.81 MPa, and the elongation was 9.88 %. The columnar dendrites were observed along the boundary line and fine dendritic structure was formed in the molten pool interior. Three phases were identified in the as-fabricated bulk, including primary α-Al, eutentic Si, and Mg2Si. Eutentic Si distributed around the columnar α-Al with a circular shape at the fusion lines, while it was uniformly distributed in the molten pool. A small amount of Mg2Si precipitated within the α-Al matrix, which exhibited needle-like morphology.

Chaolei Wu, Lishuai Jiang, Yang Li et al.

Abstract The shear behavior of fractured rock masses critically influences engineering stability, particularly in slope engineering. Overcoming limitations of conventional preparation methods, this study utilizes sand-powder 3D printing to fabricate rock-like specimens with controlled internal fractures. Direct shear tests systematically investigate fracture radius and number effects on strength evolution under constant density, with quantitative analysis revealing their differential contributions. The results show that: (1) The failure of sand-powder 3D-printed fractured rock-like specimens exhibits brittle characteristics. The shear stress–shear displacement relationship can be divided into five stages: compaction, elasticity, unstable development, peak, and post-peak. Crack initiation and propagation primarily occur from the late elastic stage to the peak stage. (2) An increase in fracture radius significantly reduces pre-peak shear stiffness, resulting in a smoother curve progression, while changes in fracture number have minimal impact on the stage-specific characteristics of the shear curve. (3) Shear strength decreases exponentially with increasing fracture radius, whereas an increase in fracture number leads to a linear reduction in shear strength. Moreover, the weakening effect of fracture number on shear strength becomes more pronounced with larger fracture radius. (4) Quantitative analysis shows that the influence of fracture radius on shear strength is 2.4 times greater than that of fracture number. This study broadens the understanding of the shear behaviors of fractured rock masses and reveals the key influence mechanism of fracture density on rock mass deformation and failure, and provides theoretical guidance for slope stability analysis and rock mass engineering design.

Maarten Vlaswinkel, Duarte Antunes, Frank Willems

Decarbonization of the transport sector sets increasingly strict demands to maximize thermal efficiency and minimize greenhouse gas emissions of Internal Combustion Engines. This has led to complex engines with a surge in the number of corresponding tunable parameters in actuator set points and control settings. Automated calibration is therefore essential to keep development time and costs at acceptable levels. In this work, an innovative self-learning calibration method is presented based on in-cylinder pressure curve shaping. This method combines Principal Component Decomposition with constrained Bayesian Optimization. To realize maximal thermal engine efficiency, the optimization problem aims at minimizing the difference between the actual in-cylinder pressure curve and an Idealized Thermodynamic Cycle. By continuously updating a Gaussian Process Regression model of the pressure's Principal Components weights using measurements of the actual operating conditions, the mean in-cylinder pressure curve as well as its uncertainty bounds are learned. This information drives the optimization of calibration parameters, which are automatically adapted while dealing with the risks and uncertainties associated with operational safety and combustion stability. This data-driven method does not require prior knowledge of the system. The proposed method is successfully demonstrated in simulation using a Reactivity Controlled Compression Ignition engine model. The difference between the Gross Indicated Efficiency of the optimal solution found and the true optimum is 0.017%. For this complex engine, the optimal solution was found after 64.4s, which is relatively fast compared to conventional calibration methods.

Shraddha Surana, Ashwin Srinivasan, Michael Bain

Engineering information systems for scientific data analysis presents significant challenges: complex workflows requiring exploration of large solution spaces, close collaboration with domain specialists, and the need for maintainable, interpretable implementations. Traditional manual development is time-consuming, while "No Code" approaches using large language models (LLMs) often produce unreliable systems. We present iProg, a tool implementing Interactive Structured Inductive Programming. iProg employs a variant of a '2-way Intelligibility' communication protocol to constrain collaborative system construction by a human and an LLM. Specifically, given a natural-language description of the overall data analysis task, iProg uses an LLM to first identify an appropriate decomposition of the problem into a declarative representation, expressed as a Data Flow Diagram (DFD). In a second phase, iProg then uses an LLM to generate code for each DFD process. In both stages, human feedback, mediated through the constructs provided by the communication protocol, is used to verify LLMs' outputs. We evaluate iProg extensively on two published scientific collaborations (astrophysics and biochemistry), demonstrating that it is possible to identify appropriate system decompositions and construct end-to-end information systems with better performance, higher code quality, and order-of-magnitude faster development compared to Low Code/No Code alternatives. The tool is available at: https://shraddhasurana.github.io/dhaani/

Shalini Chakraborty, Sebastian Baltes

The IT industry provides supportive pathways such as returnship programs, coding boot camps, and buddy systems for women re-entering their job after a career break. Academia, however, offers limited opportunities to motivate women to return. We propose a diverse multicultural research project investigating the challenges faced by women with software engineering (SE) backgrounds re-entering academia or related research roles after a career break. Career disruptions due to pregnancy, immigration status, or lack of flexible work options can significantly impact women's career progress, creating barriers for returning as lecturers, professors, or senior researchers. Although many companies promote gender diversity policies, such measures are less prominent and often under-recognized within academic institutions. Our goal is to explore the specific challenges women encounter when re-entering academic roles compared to industry roles; to understand the institutional perspective, including a comparative analysis of existing policies and opportunities in different countries for women to return to the field; and finally, to provide recommendations that support transparent hiring practices. The research project will be carried out in multiple universities and in multiple countries to capture the diverse challenges and policies that vary by location.

Anne-Françoise Garçon

Based on two rarely compared corpora — the archives of the police court of Rennes (mid-eighteenth century) and the travel diaries of mining engineering students (early nineteenth century) — this article offers a situated history of the gestures and rites of artisanal excellence. It shows, on the one hand, how a key moment in the metallurgical operating chain (the cupellation) was sacralized and protected by secrecy ; on the other hand, how the ceremony of the masterpiece in the Rennes craft communities stages a secrecy of manufacturing, legally framed, and yet adaptable to the changes of an expanding market (the case of master tailors). Finally, it proposes to go beyond the overly frustrated tacit/explicit opposition in favor of an analysis of the economies of the utterance and the recording media (image/word/gesture) that make the skills practicable, transmissible and opposable. The discussion is grounded in the conceptual framework of the “modes of existence of technical gesture,” where the social inscription of gesture, its technical and legal guarantees, and its operative regime form a specific gestural milieu.

Kolli Venkatesh, Sushree P. Mohapatra, Trinath Talapaneni et al.

Yevhen Lapshyn, O. Shevchenko

As a result of the activities of mining, processing and energy complexes, a huge amount of waste has accumulated on the territory of Ukraine. These wastes are promising in terms of their resource value, are embedded and constantly replenished with mineral raw materials of technogenic origin. They are considered as an integral part of the country's mineral raw material base of ferrous, non-ferrous, metallic, energy and rare valuable minerals. An analysis of the possibilities and prospects for obtaining secondary raw materials containing valuable components from technogenic waste was performed by fine classification by size using the example of waste from the enrichment of titanium-zirconium sands, metallurgy (slags and sludges), and energy (slags and fly ash). It is established by which size class it is necessary to divide the raw materials in order to obtain a product that is in demand by consumers, and how this division can be ensured. The need to use fine classification during processing is shown. The production waste of the Vilnohirsk Mining and Metallurgical Plant (VMMK) and its technogenic deposit are mainly represented by the mineral’s ilmenite, disten-sillimanite, staurolite, and tourmaline. During secondary processing of VMMK waste, it is possible to obtain a collective concentrate of these minerals and quartz sand with a heavy fraction content of less than 0.1% and Fe2O3 of no more than 0.025%, which will allow it to be effectively used as a high-quality quartz raw material in the glass industry. Processing of metallurgical waste allows obtaining such marketable products as iron, zinc, scandium, etc. The use of metallurgical waste by manufacturers of dry building mixes, cement, and road surfaces reduces the cost of these products and increases their quality. Processing of ash and slag waste (ASW) from the energy industry allows obtaining low-ash coal concentrate for the energy industry, a silicate fraction suitable for the construction sector, as well as other useful minerals such as iron, germanium, vanadium, and alumina for further production of aluminum, in quantities of industrial interest. The prospects of using a vibrating impact screen designed by the Institute of Mechanical Engineering and Materials Technology of the National Academy of Sciences of Ukraine in the processing of various technogenic wastes are proposed and shown. His tests showed quite high screening rates: for dry materials, the extraction of the class less than 0.02 mm into the sub-screen product was 75-80%; for wet materials from the accumulator – 65-70%, while the humidity of the super-screen material was reduced from 30 to 7-8%. Comprehensive recycling will reduce the amount of waste sent to storage facilities, reduce the areas that are currently being alienated for them and become uninhabitable, ensure increased profitability of enterprises, significantly preserve natural resources, and reduce the shortage of various materials.

Ivan Kolodiy, Oleksii Lanets, O. Vambol et al.

The article addresses excessive energy consumption in resonance vibration machines with inertial drives, widely used in mechanical engineering, construction, chemical, metallurgical, and mining industries. Conventional design approaches limit energy efficiency, motivating the modernization of one- and two-mass resonance systems into three-mass inter-resonance configurations. Using a method for determining inertia–stiffness parameters, the study ensures synchronous inter-resonance oscillatory modes, enhancing dynamic amplification and reducing drive power. Analytical modeling of the three-mass system, comprising active, intermediate, and reactive masses connected by elastic and damping elements, yields closed-form expressions for steady-state amplitudes and stiffness parameters. A phase-synchronization criterion is applied to determine the reactive mass, enabling convergence of resonance peaks and maximal dynamic gain. The proposed methodology provides a unified framework for upgrading existing resonance machines, achieving significant energy savings—up to an order of magnitude—while maintaining required oscillation amplitudes. These results offer a practical tool for energy-efficient modernization of industrial vibratory machinery with inertial drives.

Bing Deng, Shichen Xu, Lucas J Eddy et al.

Yuchen ZHANG, Haibin DUAN, Chen WEI

Unmanned aerial vehicle (UAV) swarms have found extensive applications in various fields, playing a crucial role in cluster collaboration. These swarms involve multiple UAVs that work together to achieve common objectives. A key challenging task in swarm operations is collision-free formation control of UAVs. To solve this problem, applying deep reinforcement learning methods has received significant attention, but their application on autonomous UAVs poses challenges, including dependency on global information during training, difficulties in sampling, and excessive resource utilization. To overcome these challenges, in this work, a novel approach based on multi-agent deep reinforcement learning (MARL) is proposed for collision-free formation control of UAV swarms. MARL allows each UAV to interact with a dynamic environment that includes other UAVs, enabling collaborative decision-making and adaptive behavior. We focus on leveraging local information to establish a state space for individual UAVs. To train the policy network, we employ the multi-agent proximal policy optimization (MAPPO) algorithm, allowing robust learning and policy optimization in a multi-agent setting. Also, we address the issues of sampling difficulties and resource constraints by utilizing digital twin technology, serving as a bridge between physical entities and virtual models, which offers a novel approach to the intelligent collaborative control of drone swarms. By establishing models in virtual space, digital twin technology enables the simulation of real-world spaces for pre-training the reinforcement learning algorithm by generating synthetic experiences. We construct multiple digital twin environments to facilitate interactive sampling and pre-train the swarm with basic task capabilities. Then, we supplement the training using real-world data collected in actual environments, enhancing the ability of the swarm to perform optimally in real-world scenarios. To evaluate the effectiveness of our approach, we compare the performance of the two-stage training architecture with other policy algorithms. To validate the sample efficiency of the on-policy algorithm MAPPO, we conducted a comparative analysis with other policy algorithms, particularly off-policy algorithms. The results reveal the superior sample efficiency and stability of MAPPO in addressing the challenges of collision-free formation control. Finally, we conduct a real-flight validation test to validate the practicality and reliability of the strategy model derived from the digital twin environments. Overall, this work demonstrates the effectiveness of our proposed approach in enabling UAV swarms to navigate complex environments and achieve collision-free formation control.

Zhaolu Zhang, Minglei Yang, Guangyu He

This paper investigates the fatigue failure mechanism of mono- and multilayer coatings on the fatigue performance of TC11 titanium alloy under tension-tension. The morphology, phase composition, mechanical properties were measured by scanning electron microscope, X-ray diffractometer and nanoindentation. Electron back scatter diffraction was employed to investigated the failure mechanism. Fatigue limits obtained of uncoated TC11, TC11 with TiN coating, TiN/Ti multilayer (ML-6, ML-3, ML-1) and after 1 × 107 cycles are 855 MPa, 550 MPa, 525 MPa, 500 MPa and 400 MPa. Under fatigue loading, the hard-coating/TC11 substrate experiences fatigue failure through coating cracking hastens the substrate's fatigue failure. EBSD analysis results indicate that the main slip system of TC11 titanium alloy under tension-tension fatigue load is α phase (10-10)[-12-10]. After 1 × 107 cycles at fatigue limits, the average dislocation density on the surface of the TC11 with TiN coating is lower than that of TC11. Due to the surface defect induced by coating preparation and high crack propagation velocity, the hard coating significantly deteriorates fatigue property of TC11 by reducing fatigue crack initiation period. Therefore, instead of approaching from the perspective of coating structure design to increase the fatigue crack propagation cycles, it is more effective to reduce the surface roughness of the coating and enhance the fatigue crack initiation cycles.