Hasil untuk "Mining engineering. Metallurgy"

Xiaojie Yang, Xuhui Kang, Manchao He et al.

The 110 mining method is a novel coal mining approach that is environmentally friendly. To investigate the movement laws of the overburden strata under the mining conditions of this method, this study systematically analyzed the development characteristics and formation mechanisms of the “three zones” of the overburden strata (caving zone, fractured zone, and flexural subsidence zone). A predictive model for the development height of the “three zones” was established based on the mining damage invariant equation and the pressure arch theory, and a quantitative criterion for the boundary between the caving zone and fractured zone was proposed.To verify the reliability of the model, the 8302 working face of Jinjiazhuang Coal Mine was selected as the research object. A combination of theoretical analysis and on-site monitoring was employed to conduct prediction and in-situ monitoring experiments on the height of the “three zones” and the surface conditions of the goaf. The results show that the relative error between the predicted height of the caving zone by the model and the measured value is +0.38 ​m, and the relative error for the fractured zone height is −1.55 ​m, indicating a high prediction accuracy.The predictive model established in this study provides a theoretical basis for the safe and efficient mining as well as the overburden control in the 110 mining method. The research findings have significant engineering application value for promoting the development of green coal mining technologies.

Gang Wu, Yanjing Su, Lijie Qiao et al.

Hydrogen embrittlement critically limits the reliability of high-strength steels, where α-Fe2O3 within passive films serves as the primary barrier against hydrogen ingress. Elemental doping is an effective approach to tune the hydrogen resistance of α-Fe2O3, yet the dopants selection criterion is absent. Here, the spin-polarized density functional theory (DFT) is employed to estimate the doping formation characteristics of 24 types of elements and elucidate how the doping elements influence the vacancies characteristics and hydrogen dissolution behaviors in α-Fe2O3. The 24 types of substitutional doping elements are classified according to their formation energies of dopants, oxygen vacancies, and iron vacancies in α-Fe2O3. The orange-group elements (Al, Cr, Y, Mn, and Ga) are selected as promising dopants to effectively resist the hydrogen and maintain the integrity of oxide film. The effects of strain on the hydrogen dissolution behaviors in doping α-Fe2O3 are also analyzed and the Y doped α-Fe2O3 shows the weakest strain sensitivity. At last, the linear regression models based on seven atomic descriptors are proposed, which could accurately predict the Edoping, EOv, EFev, and Ediss (R2 = 0.70–0.88), respectively. These descriptor-property relationships provide the guidance to design doped α-Fe2O3 passive films with desired hydrogen resistance.

Yining Hong, Christopher S. Timperley, Christian Kästner

Machine learning (ML) components are increasingly integrated into software products, yet their complexity and inherent uncertainty often lead to unintended and hazardous consequences, both for individuals and society at large. Despite these risks, practitioners seldom adopt proactive approaches to anticipate and mitigate hazards before they occur. Traditional safety engineering approaches, such as Failure Mode and Effects Analysis (FMEA) and System Theoretic Process Analysis (STPA), offer systematic frameworks for early risk identification but are rarely adopted. This position paper advocates for integrating hazard analysis into the development of any ML-powered software product and calls for greater support to make this process accessible to developers. By using large language models (LLMs) to partially automate a modified STPA process with human oversight at critical steps, we expect to address two key challenges: the heavy dependency on highly experienced safety engineering experts, and the time-consuming, labor-intensive nature of traditional hazard analysis, which often impedes its integration into real-world development workflows. We illustrate our approach with a running example, demonstrating that many seemingly unanticipated issues can, in fact, be anticipated.

Haruhiko Yoshioka, Sila Lertbanjongngam, Masayuki Inaba et al.

Log4j has become a widely adopted logging library for Java programs due to its long history and high reliability. Its widespread use is notable not only because of its maturity but also due to the complexity and depth of its features, which have made it an essential tool for many developers. However, Log4j 1.x, which reached its end of support (deprecated), poses significant security risks and has numerous deprecated features that can be exploited by attackers. Despite this, some clients may still rely on this library. We aim to understand whether clients are still using Log4j 1.x despite its official support ending. We utilized the Mining Software Repositories 2025 challenge dataset, which provides a large and representative sample of open-source software projects. We analyzed over 10,000 log entries from the Mining Software Repositories 2025 challenge dataset using the Goblin framework to identify trends in usage rates for both Log4j 1.x and Log4j-core 2.x. Specifically, our study addressed two key issues: (1) We examined the usage rates and trends for these two libraries, highlighting any notable differences or patterns in their adoption. (2) We demonstrate that projects initiated after a deprecated library has reached the end of its support lifecycle can still maintain significant popularity. These findings highlight how deprecated are still popular, with the next step being to understand the reasoning behind these adoptions.

Hashini Gunatilake, John Grundy, Rashina Hoda et al.

Empathy, defined as the ability to understand and share others' perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

Michael R. Koblischka, Anjela Koblischka-Veneva

The superconducting transition temperature, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>T</mi><mi>c</mi></msub></semantics></math></inline-formula>, of the graphite intercalation compound, Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="normal">C</mi><mn>6</mn></msub></semantics></math></inline-formula>, was calculated using the Roeser–Huber (RH) formalism. This method was adapted to alloys with complex crystal structures by identifying symmetric paths for the superconducting charge carriers (Cooper pairs) and incorporating interactions with neighboring atoms through phonon coupling. The evaluation of the lowest energy levels, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mo>Δ</mo><mrow><mo>(</mo><mn>0</mn><mo>)</mo></mrow></msub></semantics></math></inline-formula>, along all relevant crystallographic directions reveals a slight anisotropy between the in-plane and out-of-plane directions, consistent with the experimental observation of the gap anisotropy by point contact spectroscopy. The <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>T</mi><mi>c</mi></msub></semantics></math></inline-formula> values obtained for Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="normal">C</mi><mn>6</mn></msub></semantics></math></inline-formula>, Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="normal">C</mi><mn>6</mn></msub></semantics></math></inline-formula> with applied high pressure, and Yb<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi mathvariant="normal">C</mi><mn>6</mn></msub></semantics></math></inline-formula> show good agreement with experimental data, thereby supporting both the validity of the RH approach and its predictive capability in describing superconductivity within complex crystal structures.

Jing LIU, Huiyi CHEN, Huiyu LIU et al.

In recent years, the increase in people’s demand for energy has led to the development of secondary batteries. Because of its high theoretical capacity and low electrochemical potential, lithium metal has gradually become the preferred negative electrode material for high-energy-density secondary batteries and has great application prospects in the field of energy storage technology. However, the practical application of lithium metal anodes faces major challenges mainly because of the inevitable formation of lithium dendrites and dead lithium during the charge–discharge cycle. These problems considerably reduce the Coulomb efficiency and service life of lithium metal batteries and constitute a substantial obstacle to the development and wide application of lithium metal batteries. Lithium dendrites are tree-like structures formed by uneven lithium deposition during the charging of lithium metal. These dendrites can penetrate the diaphragm and reach the cathode, causing a short circuit that can lead to catastrophic battery failure. Dead lithium refers to lithium that is separated from the anode during the discharging of a lithium battery and no longer participates in subsequent electrochemical reactions. The accumulation of dead lithium reduces the inventory of active lithium, causing battery capacity and efficiency to decline over time. Addressing these challenges requires an in-depth understanding of the formation mechanisms of lithium dendrites and dead lithium and their influencing factors. This study focuses on analyzing these mechanisms and influencing factors from the perspective of the phase field, which is a powerful computational method to simulate microstructure evolution, providing insights into the complex dynamics of lithium deposition and the conditions and influencing factors for the formation of lithium dendrites and dead Lithium. The latest research progress on the inhibition of dead lithium by temperature, pressure, diaphragm, bubble, and high active electrolyte was reviewed. First, the influence of temperature and pressure on the formation of dead lithium and the effect of two coupling fields on dead lithium are discussed. Second, starting from the diaphragm and electrolyte, the results of researchers in recent years are reviewed. For example, selecting a diaphragm with the appropriate pore size can promote the uniform deposition of lithium, better prevent the penetration of dendrites, and promote the resurrection of dead lithium. The highly active electrolyte can enhance the smooth deposition of lithium and inhibit the formation of dead lithium. These factors can regulate the deposition form of lithium to a certain extent and slow down or avoid the formation of lithium dendrites and dead lithium. By optimizing these factors, researchers can better control the deposition morphology of lithium, alleviating or even avoiding the formation of lithium dendrites and dead lithium. The phase field method is used to determine how the formation of dead lithium affects the overall life of the battery. The phase field is also used to simulate the long-term behavior of lithium metal anodes to predict the battery life under various operating conditions. Finally, this paper discusses and summarizes the shortcomings of the existing phase field method in the study of the radical elimination of dead lithium and the prospects for future development.

Nikolaos A. Fountas, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

This study examined machinability aspects in terms of the main cutting force and surface roughness in dry CNC turning of graphene-reinforced composite aluminum with 0.5 wt%. The cutting speed, feed rate and depth of cut influence were investigated in regard to the responses of main cutting force <i>Fz</i> and surface roughness <i>Ra</i> when turning high-purity aluminum (Al 96.83%) and graphene-reinforced aluminum with 0.5% graphene nanoplatelets for comparative analysis. A customized central composite design of the experiments with nine runs was established, and the results were assessed through analysis of variance and response surface regression. Full quadratic prediction models were generated based on the experimental results and they were examined for their validity and efficiency in predicting the response of the main cutting force and surface roughness of the machined graphene-reinforced composite aluminum. The NSGA-II algorithm was finally applied for simultaneously minimizing the main cutting force and surface roughness by providing a well-spread Pareto front of non-dominated solutions. The results indicated that the feed rate was the dominant parameter affecting both objectives, namely the main cutting force and surface roughness, while the NSGA-II algorithm was capable of delivering advantageous solutions for enhancing machinability with less than 10% error predictions when comparing simulated and actual machining results.

Leonova Yu.Yu., Negadaev V.A.

The increase in the cost of energy resources makes it necessary to take into account measures to reduce non-production losses of electricity when building an electricity supply network. It is possible to reduce power losses by increasing the power factor. Despite a significant amount of research on the optimization of methods for selecting reactive power compensation devices, their placement and management, the installation costs of such devices are often determined approximately, without taking into account the nature of the dependencies between cost and their parameters. This article presents the results of research on the dependence of the cost of reactive power compensation devices on their parameters: reactive power, permissible current and capacitance. To clarify the nature of the relationship between the cost of capacitor banks and the value of reactive power, regression equations describing this relationship (in prices of 2023) are defined. The method of correlation analysis is used to find the regression equations. Based on the value of the Fisher criterion, a regression equation was chosen that best describes the relationship between the specified parameters of capacitor banks. The use of a deflator index to predict the cost of capacitor banks is proposed. To determine the values of the reactive power of a capacitor bank, at which it is advisable to turn on capacitors through a step-up transformer, the cost of reactive power compensation methods at reactive power values of 50 kVAr and above and a comparison of reactive power compensation methods using a step-up transformer and without its use was carried out. Based on the results of the study, conclusions were drawn: on the existence of a relationship between the cost of capacitor banks and reactive power, described by a polynomial regression equation; on the influence of voltage values on the cost of a unit of capacitance of capacitor banks. It is noted that if the required reactive power exceeds the value of 300 kVAr, it is advisable to consider switching on static capacitors using a step-up transformer.

Sergio Rico

Case studies are a popular and noteworthy type of research study in software engineering, offering significant potential to impact industry practices by investigating phenomena in their natural contexts. This potential to reach a broad audience beyond the academic community is often undermined by deficiencies in reporting, particularly in the context description, study classification, generalizability, and the handling of validity threats. This paper presents a reflective analysis aiming to share insights that can enhance the quality and impact of case study reporting. We emphasize the need to follow established guidelines, accurate classification, and detailed context descriptions in case studies. Additionally, particular focus is placed on articulating generalizable findings and thoroughly discussing generalizability threats. We aim to encourage researchers to adopt more rigorous and communicative strategies, ensuring that case studies are methodologically sound, resonate with, and apply to software engineering practitioners and the broader academic community. The reflections and recommendations offered in this paper aim to ensure that insights from case studies are transparent, understandable, and tailored to meet the needs of both academic researchers and industry practitioners. In doing so, we seek to enhance the real-world applicability of academic research, bridging the gap between theoretical research and practical implementation in industry.

Siyu Teng, Xuan Li, Yuchen Li et al.

One critical bottleneck that impedes the development and deployment of autonomous transportation in open-pit mines is guaranteed robustness and trustworthiness in prohibitively extreme scenarios. In this research, a novel scenarios engineering (SE) methodology for the autonomous mining truck is proposed for open-pit mines. SE increases the trustworthiness and robustness of autonomous trucks from four key components: Scenario Feature Extractor, Intelligence & Index (I&I), Calibration & Certification (C&C), and Verification & Validation (V&V). Scenario feature extractor is a comprehensive pipeline approach that captures complex interactions and latent dependencies in complex mining scenarios. I&I effectively enhances the quality of the training dataset, thereby establishing a solid foundation for autonomous transportation in mining areas. C&C is grounded in the intrinsic regulation, capabilities, and contributions of the intelligent systems employed in autonomous transportation to align with traffic participants in the real world and ensure their performance through certification. V&V process ensures that the autonomous transportation system can be correctly implemented, while validation focuses on evaluating the ability of the well-trained model to operate efficiently in the complex and dynamic conditions of the open-pit mines. This methodology addresses the unique challenges of autonomous transportation in open-pit mining, promoting productivity, safety, and performance in mining operations.

V.V. , T.O. , I.H.

The article reveals the problems that arose in the field of foreign trade policy formation and implementation as a result of the Russian invasion of the territory of Ukraine. Foreign trade is one of the components of the formation of the national economy, and its state affects the gross national product, the country's balance of payments and other socio-economic indicators of the country's development. Using the methods of analysis and synthesis, comparison and generalization, an analysis of the commodity and geographical structure of foreign trade in goods was carried out before and after the full-scale invasion of Russia into the territory of Ukraine. The consequences of the changes that occurred in the structure of export-import operations were analyzed. Reduction of export and import volumes for almost all groups of goods and reduction of shares of all regions of the world in favor of EU countries. The leading place in the product structure of exports is occupied by goods of agricultural industry, and in imports – mineral products. The directions for the formation of state policy in the field of regulation of foreign trade operations in the short-term, medium-term and strategic dimensions, which are determined by the National Council for the Recovery of Ukraine from the Consequences of the War, are substantiated. Foreign trade policy, which is formed under the influence of risks and threats of war, is aimed at developing and increasing the volume of foreign trade with EU countries and the USA, Japan and Canada. The priority areas of foreign trade development are: defense-industrial complex; metallurgy and metalworking; agro-industrial complex; engineering; mining industry; furniture and woodworking industries. An important place is also defined for the development of innovative enterprises and knowledge-intensive production, which will ensure the transition to a developing economy.

Jiacheng XIE, Ziying ZHENG, Xuewen WANG et al.

The key to promoting intelligent construction is to integrate the digital twin technology form the operation mode of virtual and real integration. And the industrial metaverse based on digital twin is the future development direction of intelligent mining face. The concept of virtual and real integration operation mode of fully-mechanized mining face based on virtual reality-digital twin-cyber physical system-industrial metaverse is proposed. It has six connotation characteristics, such as display and off-line simulation, monitoring and auxiliary operation, online simulation and preview. It is an evolution process from low-level display simulation to high-level deep integration function. Finally, it have four abilities : the ability of reproduction mapping from real to virtual precision, the ability of reasoning and forecasting decision-making in virtual iteration, the ability of reproduction control from virtual to real, the ability of seamless cooperation between virtual and real human-computer, and the ability of lean management. The four capabilities of industrial metaverse and the key technologies to realize industrial metaverse are analyzed.Based on the existing monitoring, decision-making and control capabilities, AR remote assistance technology that can strengthen the cooperation ability between field operators and remote operators, robot cooperation technology that can strengthen the safety of operators, and virtual human technology that can use AI-driven operation in virtual space are integrated to build a hydraulic support adjusting experimental system based on industrial metaveise,and preliminary understanding of the application of industrial metaverse in coal mining.

Yaya Wu, Yan Wen, Anan Guo et al.

This work used electroshocking treatment (EST) plus external loading to regulate the microstructure of titanium matrix composites (TMCs). The external loading was 0.3 MPa. After EST plus external loading with 0.3 MPa, the α was reduced to 2.53 μm in size. The percentage of high angle grain boundaries (HAGBs) in α increased first and then decreased. The percent of HAGBs in TiB decreased, mainly due to the introduction of abundant dislocations in the TiB/matrix interface after EST. After EST, the maximum texture strength of TiB decreased from 13.09 to 12.97, and that of α decreased from 3.11 to 1.58. After EST under external loading with 0.3 MPa, the maximum texture strength of TiB decreased to 8.10. The orientation of TiB experienced significant variation. TEM results showed that TiB and α formed a distorted interface after EST under external loading with 0.3 MPa. The interplanar spacing of TiB and α was varied. All results show that the texture of TMCs can be relieved by EST plus external loading with 0.3 MPa. It is mainly attributed to the thermal and athermal effects and the imposed external loads with EST. EST plus external loading provides a new method for manipulating the microstructure of TMCs.

Saeed Hassani Sadrabadi, Hojat Naderi, Hamid Reza Zare et al.

Removal of copper from synthesized and real dilute sulfuric acid solutions was investigated. Effects of copper, iron concentrations and applied potential were studied. In pure copper solutions, increasing the Cu2+ concentration from 1000 to 5000 mg.L-1 increased the copper recovery from about 30-300% depending on the cathode potential and decreased the energy consumption by about 30%. Also, with increasing the acid concentration from 15 to 50 g.L-1 an about 25% increase in copper recovery and a 30% decrease in energy consumption were observed. The addition of Fe2+ to the solution improved the ionic conductivity and so that the copper recovery. The specified energy consumption for the real leaching solutions increased to 31-47 KWh.kg-1. The diffusion coefficients for several synthesized and real copper electrowinning electrolytes were determined. Moreover, the maximum value of the diffusion coefficient (D) was obtained 2.27*10-4 cm2.s-1 for the pure copper solution at a concentration of 1000 mg.L-1 Cu2+ which was higher than impure and real solutions.

Lena Kästner, Markus Langer, Veronika Lazar et al.

Recently, requirements for the explainability of software systems have gained prominence. One of the primary motivators for such requirements is that explainability is expected to facilitate stakeholders' trust in a system. Although this seems intuitively appealing, recent psychological studies indicate that explanations do not necessarily facilitate trust. Thus, explainability requirements might not be suitable for promoting trust. One way to accommodate this finding is, we suggest, to focus on trustworthiness instead of trust. While these two may come apart, we ideally want both: a trustworthy system and the stakeholder's trust. In this paper, we argue that even though trustworthiness does not automatically lead to trust, there are several reasons to engineer primarily for trustworthiness -- and that a system's explainability can crucially contribute to its trustworthiness.

Jennifer Hehn, Daniel Mendez

Effective Requirements Engineering is a crucial activity in softwareintensive development projects. The human-centric working mode of Design Thinking is considered a powerful way to complement such activities when designing innovative systems. Research has already made great strides to illustrate the benefits of using Design Thinking for Requirements Engineering. However, it has remained mostly unclear how to actually realize a combination of both. In this chapter, we contribute an artifact-based model that integrates Design Thinking and Requirements Engineering for innovative software-intensive systems. Drawing from our research and project experiences, we suggest three strategies for tailoring and integrating Design Thinking and Requirements Engineering with complementary synergies.

Dulaji Hidellaarachchi, John Grundy, Rashina Hoda et al.

Requirements Engineering (RE) requires the collaboration of various roles in SE, such as requirements engineers, stakeholders and other developers, and it is thus a highly human dependent process in software engineering (SE). Identifying how human aspects such as personality, motivation, emotions, communication, gender, culture and geographic distribution might impact RE would assist us in better supporting successful RE. The main objective of this paper is to systematically review primary studies that have investigated the effects of various human aspects on RE. A systematic literature review (SLR) was conducted and identified 474 initial primary research studies. These were eventually filtered down to 74 relevant, high-quality primary studies. Among the studies, the effects of communication have been considered in many RE studies. Other human aspects such as personality, motivation and gender have mainly been investigated to date related to SE studies including RE as one phase. Findings show that studying more than one human aspect together is beneficial, as this reveals relationships between various human aspects and how they together impact the RE process. However, the majority of these studied combinations of human aspects are unique. From 56.8% of studies that identified the effects of human aspects on RE, 40.5% identified the positive impact, 30.9% negative, 26.2% identified both impacts whereas 2.3% mentioned that there was no impact. This implies that a variety of human aspects positively or negatively affects the RE process and a well-defined theoretical analysis on the effects of different human aspects on RE remains to be defined and practically evaluated. Findings of this SLR help researchers who are investigating the impact of various human aspects on RE by identifying well-studied research areas, and highlight new areas that should be focused on in future research.

Zhong Xu, Jun Huang, Hongyan Wu et al.

In the long history of science and technology development, one goal is to diffuse solid alloy elements into the surface of steel materials to form surface alloys with excellent physical and chemical properties. On the basis of plasma nitriding technology, double glow plasma surface metallurgy technology has answered this challenge. This technology, which seems to be a modern-day alchemy, can use any element in the periodic table of chemical elements, including solid metal elements and their combinations, to form many types of surface alloyed layers with high hardness, wear resistance, corrosion resistance and high temperature oxidation resistance on various metal materials. For examples, nickel base alloys, stainless steels and high speed steels are formed on the surfaces of ordinary carbon steels; and high hardness, wear resistance and high temperature oxidation resistance alloy are formed on the surface of titanium alloy.This article briefly introduces the formation and principle of double glow plasma surface metallurgy technology, and summarizes the experimental results and industry application. The significance and development prospect of this technology are discussed.

Yuantian Sun, Guichen Li, Nong Zhang et al.

In the loose and fractured coal seam with particularly low uniaxial compressive strength (UCS), driving a roadway is extremely difficult as roof falling and wall spalling occur frequently. To address this issue, the jet grouting (JG) technique (high-pressure grout mixed with coal particles) was first introduced in this study to improve the self-supporting ability of coal mass. To evaluate the strength of the jet-grouted coal-grout composite (JG composite), the UCS evolution patterns were analyzed by preparing 405 specimens combining the influential variables of grout types, curing time, and coal to grout (C/G) ratio. Furthermore, the relationships between UCS and these influencing variables were modeled using ensemble learning methods i.e. gradient boosted regression tree (GBRT) and random forest (RF) with their hyperparameters tuned by the particle swarm optimization (PSO). The results showed that the chemical grout composite has higher short-term strength, while the cement grout composite can achieve more stable strength in the long term. The PSO-GBRT and PSO-RF models can both achieve high prediction accuracy. Also, the variable importance analysis demonstrated that the grout type and curing time should be considered carefully. This study provides a robust intelligent model for predicting UCS of JG composites, which boosts JG design in the field.