Evolution of nonmetallic inclusions in 80-t 9CrMoCoB large-scale ingots during electroslag remelting process

In combination with theoretical calculations,experiments were conducted to investigate the evolution behavior of nonmetallic inclusions(NMIs)during the manufacture of large-scale heat-resistant steel ingots using 9CrMoCoB heat-resistant steel and CaF_(2)–CaO–Al_(2)O_(3)–SiO_(2)–B_(2)O_(3)electroslag remelting(ESR)-type slag in an 80-t industrial ESR furnace.The main types of NMI in the consumable electrode comprised pure alumina,a multiphase oxide consisting of an Al_(2)O_(3)core and liquid CaO–Al_(2)O_(3)–SiO_(2)–MnO shell,and M_(23)C_(6)carbides with an MnS core.The Al_(2)O_(3)and MnS inclusions had higher precipitation temperatures than the M_(23)C_(6)-type carbide under equilibrium and nonequilibrium solidification processes.Therefore,inclusions can act as nucleation sites for carbide layer precipitation.The ESR process completely removed the liquid CaO–Al_(2)O_(3)–SiO_(2)–MnO oxide and MnS inclusion with a carbide shell,and only the Al_(2)O_(3)inclusions and Al_(2)O_(3)core with a carbide shell occupied the remelted ingot.The M_(23)C_(6)-type carbides in steel were determined as Cr_(23)C_(6)based on the analysis of transmission electron microscopy results.The substitution of Cr with W,Fe,or/and Mo in the Cr_(23)C_(6)lattice caused slight changes in the lattice parameter of the Cr_(23)C_(6)carbide.Therefore,Cr_(21.34)Fe_(1.66)C_(6),(Cr_(19)W_(4)C_(6),Cr_(18.4)Mo_(4.6)C_(6),and Cr_(16)Fe_(5)Mo_(2)C_(6)can match the fraction pattern of Cr_(23)C_(6)carbide.The Al_(2)O_(3)inclusions in the remelted ingot formed due to the reduction of CaO,SiO_(2),and MnO components in the liquid inclusion.The increased Al content in liquid steel or the higher supersaturation degree of Al_(2)O_(3)precipitation in the remelted ingot than that in the electrode can be attributed to the evaporation of CaF_(2)and the increase in CaO content in the ESR-type slag.

Mineralization of the Liwu large-scale stratiform copper deposits in Sichuan Province, China: Constraints from fluid inclusions

The Liwu stratiform copper deposit is located in the northwestern Jianglang dome,western China.Current studies mainly focus on the genetic type and mineralization of this deposit.Detailed fluid inclusion characteristics of metallogenic period quartz veins were studied to reveal the ore-forming fluid features.Laser Raman analysis indicates that the ore-forming fluids is a H_(2)O-NaCl-CH_(4)(-CO_(2))system.Fluid inclusions microthermometry shows a homogenization temperature of 181-375°C and a salinity of 5.26%-16.99%for the disseminated-banded Cu-Zn mineralization;but a homogenization temperature of 142-343°C and a salinity of 5.41%-21.19%for the massive-veined Cu-Zn mineralization.These features suggest a medium-high temperature and a medium salinity for the ore-forming fluids.H-O isotopic data indicates that the ore-forming fluids were mainly from the metamorphic and magmatic water,plus minor formation water.And sulfur isotopic data indicates that sulfur was mainly derived from the formation and magmatic rocks.Metallogenesis of the disseminated-banded mineralization was mainly correlated with fluid mixing and water-rock reaction;whereas that of the massive-veined mineralization was mainly correlated with fluid boiling.The genetic type of the deposit is a medium-high temperature hydrothermal deposit related to magmatism and controlled by shear zones.This study is beneficial to understand the stratiform copper deposit.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

Addressing inclusion,innovation,and sustainability challenges through the lens of economic geography:Introducing the hierarchical regional innovation system

The world is facing dramatic challenges related to environmental sustainability at an accelerating pace.In this context,the field of economic geography(EG)has been playing an important role in understanding both the socioeconomic and technological dimensions of these challenges,as it deals with a variety of complementary notions and perspectives.Departing from this lens,our aim is to explore a conceptual framework that can help us to understand environmental changes relating to multi-dimensional territorial development,notably in eco-nomic contexts where inequality is high,and stratification based on hierarchies regulate social and economic life.Based on the territory concept,we propose the original notion of a hierarchical regional innovation system(HRIS)that emphasises the pervasive role of hierarchies(powers)in regional innovation systems and illustrate its value with evidence and case studies from extant literature on sustainability transitions.The HRIS can help us understand and promote development paths considering the contribution of inclusive eco-innovations(another original conceptual amalgam).Through some empirical cases from other studies in low-carbon transitions,we show the application of the HRIS(and inclusive eco-innovation)framework.In conclusion,we provide incen-tives to explore new regional innovation systems,alongside the HRIS,adapted to different regions worldwide and centred on the inclusiveness of people and places.

Effect of hafnium and molybdenum addition on inclusion characteristics in Co-based dual-phase high-entropy alloys

Specific grades of high-entropy alloys(HEAs)can provide opportunities for optimizing properties toward high-temperature applications.In this work,the Co-based HEA with a chemical composition of Co_(47.5)Cr_(30)Fe_(7.5)Mn_(7.5)Ni_(7.5)(at%)was chosen.The refractory metallic elements hafnium(Hf)and molybdenum(Mo)were added in small amounts(1.5at%)because of their well-known positive effects on high-temperature properties.Inclusion characteristics were comprehensively explored by using a two-dimensional cross-sectional method and extracted by using a three-dimensional electrolytic extraction method.The results revealed that the addition of Hf can reduce Al_(2)O_(3)inclusions and lead to the formation of more stable Hf-rich inclusions as the main phase.Mo addition cannot influence the inclusion type but could influence the inclusion characteristics by affecting the physical parameters of the HEA melt.The calculated coagulation coefficient and collision rate of Al_(2)O_(3)inclusions were higher than those of HfO_(2)inclusions,but the inclusion amount played a larger role in the agglomeration behavior of HfO_(2)and Al_(2)O_(3)inclusions.The impurity level and active elements in HEAs were the crucial factors affecting inclusion formation.

Large-scale model testing of high-pressure grouting reinforcement for bedding slope with rapid-setting polyurethane

Bedding slope is a typical heterogeneous slope consisting of different soil/rock layers and is likely to slide along the weakest interface.Conventional slope protection methods for bedding slopes,such as retaining walls,stabilizing piles,and anchors,are time-consuming and labor-and energy-intensive.This study proposes an innovative polymer grout method to improve the bearing capacity and reduce the displacement of bedding slopes.A series of large-scale model tests were carried out to verify the effectiveness of polymer grout in protecting bedding slopes.Specifically,load-displacement relationships and failure patterns were analyzed for different testing slopes with various dosages of polymer.Results show the great potential of polymer grout in improving bearing capacity,reducing settlement,and protecting slopes from being crushed under shearing.The polymer-treated slopes remained structurally intact,while the untreated slope exhibited considerable damage when subjected to loads surpassing the bearing capacity.It is also found that polymer-cemented soils concentrate around the injection pipe,forming a fan-shaped sheet-like structure.This study proves the improvement of polymer grouting for bedding slope treatment and will contribute to the development of a fast method to protect bedding slopes from landslides.

Infrared microthermometry of fluid inclusion in sphalerite:A case study of the Xinqiao deposit in the Middle-Lower Yangtze metallogenic belt

Infrared microthermometry allows direct measurement of fluid inclusions hosted in opaque ore minerals and can provide direct constraints on the evolution of ore-forming fluids.This study presents infrared microthermometry of spherite-hosted fluid inclusions from the Xinqiao deposit in the Middle-Lower Yangtze Metallogenic Belt and sheds new light on the ore genesis of the deposit.Considering that infrared light may lead to non-negligible temperature deviations during microthermometry,some tests were first conducted to ensure the accuracy of the microthermometric measurements.The measurement results indicated that using the lowest light intensity of the microscope and inserting an optical filter were effective in minimizing the possible temperature deviations of infrared microthermometry.All sphalerite-hosted fluid inclusions from the Xinqiao deposit were aqueous.They show homogenization temperature ranging from~200 to 350℃,but have two separate salinity groups(1.0 wt%-10 wt%and 15.1 wt%-19.2 wt%NaCl equivalent).The low-salinity group represents sedimentary exhalative(SEDEX)-associated fluids,whereas the high-salinity group results from modification by later magmatic hydrothermal fluids.Combined with published fluid inclusion data,the four-stage fluid evolution of the Xinqiao deposit was depicted.Furthermore,our data suggest that the Xinqiao deposit was formed by twostage metallogenic events including SEDEX and magmatic-hydrothermal mineralization.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Critical precipitation behavior of MnTe inclusions in resulfurized steels during solidification

Te treatment is an effective method for modifying sulfide inclusions,and MnTe precipitation has an important effect on thermal brittleness and steel corrosion resistance.In most actual industrial applications of Te treatment,MnTe precipitation is unexpected.The critical precipitation behavior of MnTe inclusions was investigated through scanning electron microscopy,transmission electron microscopy,machine learning,and first-principles calculation.MnTe preferentially precipitated at the container mouth for sphere-like sulfides and at the interface between MnS grain boundaries and steel matrix for rod-like sulfides.The MnS/MnTe interface was semicoherent.A composition transition zone with a rock-salt structure exhibiting periodic changes existed to maintain the semicoherent interface.The critical precipitation behavior of MnTe inclusions in resulfurized steels involved three stages at varying temperatures.First,Mn(S,Te)precipitated during solidification.Second,MnTe with a rock-salt structure precipitated from Mn(S,Te).Third,MnTe with a hexagonal NiAs structure transformed from the rock-salt structure.The solubility of Te in MnS decreased with decreasing temperature.The critical precipitation behavior of MnTe inclusions in resulfurized steels was related to the MnS precipitation temperature.With the increase in MnS precipitation temperature,the critical Te/S weight ratio decreased.In consideration of the cost-effectiveness of Te addition for industrial production,the Te content in resulfurized steels should be controlled in accordance with MnS precipitation temperature and S content.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Dissolution behavior of Al_(2)O_(3)inclusions into CaO-MgO-SiO_(2)-Al_(2)O_(3)-TiO_(2)system ladle slags

To investigate the dissolution behaviors of Al_(2)O_(3)inclusions in CaO-5wt%MgO-SiO_(2)-30wt%Al_(2)O_(3)-TiO_(2)system ladle slags,confocal scanning laser microscopy was conducted on the slags with different TiO_(2)contents(0-10wt%),and scanning electron microscopy was performed to study the interfacial reaction between Al_(2)O_(3)and this slag system.The results disclose that the dissolution of Al_(2)O_(3)inclusions does not result in the formation of new phases at the boundary between the slag and the inclusions.In TiO_(2)-bearing and TiO_(2)-free ladle slags,there is no difference in the dissolution mechanism of Al_(2)O_(3)inclusions at steelmaking temperatures.Boundary layer diffusion is found as the controlling step of the dissolution of Al_(2)O_(3),and the diffusion coefficient is in the range of 4.18×10^(-10)to 2.18×10^(-9)m^(2)/s at 1450-1500℃.Compared with the solubility of Al_(2)O_(3)in the slags,slag viscosity and temperature play a more profound role in the dissolution of Al_(2)O_(3)inclusions.A lower viscosity and a lower melting point of the slags are beneficial for the dissolution.Suitable addition of TiO_(2)(e.g.,5wt%)in ladle slags can enhance the dissolution of Al_(2)O_(3)inclusions because of the low viscosity and melting point of the slags,while excessive addition of TiO_(2)(e.g.,10wt%)shows the opposite trend.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

Shock-induced energy localization and reaction growth considering chemical-inclusions effects for crystalline explosives

Chemical inclusions significantly alter shock responses of crystalline explosives in macroscale gap experiments but their microscale dynamics origin remains unclear.Herein shock-induced energy localization,overall physical responses,and reactions in a-1,3,5-trinitro-1,3,5-triazinane(a-RDX)crystal entrained various chemical inclusions were investigated by the multi-scale shock technique implemented in the reactive molecular dynamics method.Results indicated that energy localization and shock reaction were affected by the intrinsic factors within chemical inclusions,i.e.,phase states,chemical compositions,and concentrations.The atomic origin of chemical-inclusions effects on energy localization is dependent on the dynamics mechanism of interfacial molecules with free space volume,which includes homogeneous intermolecular compression,interfacial impact and shear,and void collapse and jet.As introducing various chemical inclusions,the initiation of those dynamics mechanisms triggers diverse decay rates of bulk RDX molecules and hereby impacts on growth speeds of final reactions.Adding chemical inclusions can reduce the effectiveness of the void during the shock impacting.Under the shockwave velocity of 9 km/s,the parent RDX decay rate in RDX entrained amorphous carbon decreases the most and is about one fourth of that in RDX with a vacuum void,and solid HMX and TATB inclusions are more reactive than amorphous carbon but less reactive than dry air or acetone inclusions.The lessdense shocking system denotes the greater increases in local temperature and stress,the faster energy liberation,and the earlier final reaction into equilibrium,revealing more pronounced responses to the present intense shockwave.The quantitative models associated with the relative system density(RD_(sys))were proposed for indicating energy-localization mechanisms and evaluating initiation safety in the shocked crystalline explosive.RD_(sys)is defined by the density ratio of defective RDX to perfect crystal after dynamics relaxation and reveals the global density characteristic in shocked systems filled with chemical inclusions.When RD_(sys)is below 0.9,local hydrodynamic jet initiated by void collapse dominates upon energy localization instead of interfacial impact.This study sheds light on novel insights for understanding the shock chemistry and physical-based atomic origin in crystalline explosives considering chemical-inclusions effects.

Genesis of the Jianbeigou Gold Deposit on the Southern Margin of the North China Craton: Insights from Fluid Inclusions, H-O-S Isotopes, and Pyrite in situ Trace Element Analyses

The Jianbeigou gold deposit is a typical lode gold deposit in the Qinling metallogenic belt, located on the southern margin of the North China Craton. Three stages of the hydrothermal process can be distinguished, including the quartz ± pyrite, quartz-polymetallic sulfide, and quartz-carbonate ± pyrite stages. From the early to late stages, the homogenization temperatures of primary fluid inclusions are 281–362°C, 227–331°C, and 149–261°C, respectively. The corresponding salinities estimated for these fluids are 3.9–9.9 wt%, 0.4–9.4 wt%, and 0.7–7.2 wt% Na Cl equiv. Combined with laser Raman spectroscopy data, the ore-forming fluid belongs to a H_(2)O-CO_(2)-Na Cl ± CH_4 system with medium–low temperature and salinity. The δ~(18)Ofluid and δD values for the quartz veins are-1.0‰ to 6.0‰ and-105‰ to-84‰, respectively, which indicates that the ore-forming fluid is of mixed source, mainly derived from magma, with a contribution from meteoric water. Pyrite has been identified into three generations based on mineral paragenetic sequencing, including Py1, Py2, and Py3. The pyrites have δ~(34)S sulfur isotopic compositions from three stages between 3.7‰ and 8.4‰, indicating that sulfur mainly originated from magma. Te, Bi, Sb, and Cu contents in pyrite were all high and showed a strong correlation with Au concentrations. Native gold and the Au-Ag-Bi telluride minerals were formed concurrently, and the As concentration was low and decoupled from the Au content. Therefore, Te, Bi, Sb and other low-melting point chalcophile elements play an important role for gold mineralization in arsenic-deficient ore-forming fluid. Combined with the geological setting, evolution of pyrite, and ore-fluids geochemistry, we propose that the Jianbeigou deposit can be classified as a magmatic–hydrothermal lode gold deposit. Gold mineralization on the southern margin of the North China Craton is related to Early Cretaceous magmatism and formed in an extensional setting.

Magmatic-hydrothermal Evolution and Mineralization Mechanisms of the Wangjiazhuang Cu(-Mo)Deposit in the Zouping Volcanic Basin,Shandong Province,China:Constraints from Fluid Inclusions

The Wangjiazhuang Cu(-Mo)deposit,located within the Zouping volcanic basin in western Shandong Province,China,is unique in this area for having an economic value.In order to expound the metallogenetic characteristics of this porphyry-like hydrothermal deposit,a detailed fluid inclusion study has been conducted,employing the techniques of representative sampling,fluid inclusion petrography,microthermometry,Raman spectroscopy,LA-ICP-MS analysis of single fluid inclusions,as well as cathode fluorescence spectrometer analysis of host mineral quartz.The deposit contains mainly two types of orebodies,i.e.veinlet-dissemination-stockwork orebodies in the K-Si alteration zone and pegmatiticquartz sulfide veins above them.In addition,minor breccia ore occurs locally.Four types of fluid inclusions in the deposit and altered quartz monzonite are identified:L-type one-or two-phase aqueous inclusions,V-type vapor-rich inclusions with V/L ratios greater than 50%-90%,D-type multiphase fluid inclusions containing daughter minerals or solids and S-type silicate-bearing fluid inclusions containing mainly muscovite and biotite.Ore petrography and fluid inclusion study has revealed a three-stage mineralization process,driven by magmatic-hydrothermal fluid activity,as follows.Initially,a hydrothermal fluid,separated from the parent magma,infiltrated into the quartz monzonite,resulting in its extensive K-Si alteration,as indicated by silicate-bearing fluid inclusions trapped in altered quartz monzonite.This is followed by the early mineralization,the formation of quartz veinlets and dissemination-stockwork ores.During the main mineralization stage,due to the participation and mixing of meteoric groundwater with magmatic-sourced hydrothermal fluid,the cooling and phase separation caused deposition of metals from the hydrothermal fluids.As a result,the pegmatitic-quartz sulfide-vein ores formed.In the late mineralization stage,decreasing fluid salinity led to the formation of L-type aqueous inclusions and chalcopyrite-sulfosalt ore.Coexistence of V-type and D-type inclusions and their similar homogenization temperatures with different homogenization modes suggest that phase separation or boiling of the ore-forming fluids took place during the early and the main mineralization stages.The formation P-T conditions of S-type inclusions and the early and the main mineralization stages were estimated as ca.156-182 MPa and 450-650℃,350-450℃,18-35 MPa and 280-380℃,8-15 MPa,respectively,based on the microthermometric data of the fluid inclusions formed at the individual stages.

Factorized Smith Method for A Class of High-Ranked Large-ScaleТ-Stein Equations

We introduce a factorized Smith method(FSM)for solving large-scale highranked J-Stein equations within the banded-plus-low-rank structure framework.To effectively reduce both computational complexity and storage requirements,we develop techniques including deflation and shift,partial truncation and compression,as well as redesign the residual computation and termination condition.Numerical examples demonstrate that the FSM outperforms the Smith method implemented with a hierarchical HODLR structured toolkit in terms of CPU time.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.