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Numerical investigations were conducted to determine the effectiveness of the front window visor for wind buffeting noise reduction. An unsteady flow simulation was carried out using a zonal Scale Adaptive Simulation (SAS) k-ε turbulence model. Firstly, the accuracy of the simulation method was validated based on a benchmark problem. The benchmark results, frequency, and sound pressure levels of feedback and resonance modes all matched well with the experimental data. The effect of the front window on the buffeting noise reduction was numerically investigated based on three different front side window openings. The analysis focused on the suppression effect of the front window visor. The results show that the front window visor changed the A-pillar vortex shedding trajectory and thus reduced the driver’s ear pressure fluctuation. On this basis, an optimization algorithm was employed to optimize the shape of the front window visor. The main design goal was to decrease the sound pressure level (SPL) values of the driver’s left ear. Simulation results showed that the monitoring point’s SPL of buffeting noise after the visor optimization was reduced by 12.6%, compared with that of the original visor.

To reduce aerodynamic drag of a minivan, non-smooth surfaces are applied to the minivan’s roof panel design. A steady computational fluid dynamics (CFD) method is used to investigate the aerodynamic drag characteristics. The accuracy of the numerical method is validated by wind tunnel test. The drag reduction effects of rectangle, rhombus and arithmetic progression arrangement for circular concaves are investigated numerically, and then the aerodynamic drag coefficient of the rectangle arrangement with a better drag reduction effect is chosen as the optimization objective. Three parameters, that is, the diameter D of the circular concave, the width W and the longitudinal distance L among the circular concaves, are selected as design variables. A 20-level design of an experimental study using a Latin Hypercube scheme is conducted. The responses of 20 groups of sample points are obtained by CFD simulation, based on which a Kriging model is chosen to create the surrogate-model. The multi-island genetic algorithm is employed to find the optimum solution. The result shows that maximum drag reduction effects up to 7.71% can be achieved with a rectangle circular concaves arrangement. The reduction mechanism of the roof with the circular concaves was discussed. The circular concaves decrease friction resistance of the roof and change the flow characteristics of the recirculation area in the wake of the minivan. The roof with the circular concaves reduces the differential pressure drag of the front and rear of the minivan.

Large-eddy simulation (LES) and Detached-eddy simulation (DES) were applied to a simple cavity model to calculate the wind buffeting noise respectively. The results were verified by wind tunnel experiments. The results show that LES is more suitable for wind buffeting noise calculation. LES method was employed to calculate automobile side-window buffeting noise. The correctness of results was validated by a road test. In this paper, the acoustically calculated sound pressure level (SPL) spectral curve is used as the initial signal of the acoustic post-processing. Four psychoacoustic objective parameters namely: loudness, sharpness, roughness and fluctuation were obtained by using Matlab R2016a to compile the calculation process. Sound quality evaluation (SQE) of the vehicle is performed via most frequently used SPL and four calculated vehicle comfort index. It can be concluded that with the increase of driving velocity, SPL and loudness show an increasing trend, while roughness, sharpness and fluctuation present a decreasing trend. It can be also summarised that with the increase of window opening degree, SPL and loudness show an increasing trend, sharpness presents a decreasing trend, and roughness and fluctuation display the trend of ups and downs. The main original contribution of this paper is the accurate calculation of wind buffeting noise and the summary of the changing rule of SPL, loudness, roughness, sharpness and fluctuation with the variation of velocity and window opening degree.

To investigate the aerodynamic behavior of underbody structure in crosswind conditions, two numerical simulation models have been developed by using computational fluid dynamics method. First, to validate the accuracy of these models, the wind tunnel experiment of model with simplified flat underbody has been designed. The computationally predicted results of realizable k-e model show consistency with experimental data, and the correlation deviation of aerodynamic force is less than 10%. By using such model, the aerodynamic force and flow field of car under steady crosswind are simulated using underbody structure, and the influence on the aerodynamic characteristic has been analyzed. It can be found that the aerodynamic force increased significantly under different yaw angle. The physical mechanism response has been clearly shown by investigating the flow field around car body by vortices visualization technique. The results of this study can be served as a suggestion for studying the vehicle stability of high-speed under crosswind.

Abstract: In order to improve the fatigue performance of a welded A-type frame in a heavy off-road mining truck, a novel method was presented to implement lifetime and weight collaborative optimization while considering uncertainties in geometry dimension, material properties, and bearing load. The mechanical and cyclic material parameters were obtained from experimental work to characterize the base metal and the weldment. The finite element model of a welded A-type frame was constructed to analyze stress distribution and predict fatigue life, the force time histories of which were acquired from multi-body dynamics simulation. The simulated failure position and fatigue life had a good agreement with the actual results. Then, both structural lifetime and weight were considered as optimization objectives. The thickness of main steel plates and elastic and cyclic material parameters were chosen as uncertain design variables as well as main loads at connection locations. The fifty sample points in the light of Latin hypercube sampling method and its responses calculated by finite element analysis were supposed to build the approximation model based on the Kriging approximation method. After its fitting precision was guaranteed, the non-dominated sorting genetic algorithm II (NSGA-II) was utilized to find the optimal solution. Finally, the fatigue life of a welded A-type frame was increased to 2.40×105 cycles and its mass was lessened by 8.2%. The optimized results implied that good fatigue performance of this welded A-type frame needs better welding quality, lower running speed for downhill and turning road surface, and thicker front plates.

High-silicon iron ore tailings, typically regarded as a byproduct of iron ore processing, are utilized innovatively in this study for the extraction of 99.99% high-purity quartz (HPQ). An innovative process consisting of Wet High-Intensity Magnetic Separation (WHIMS) with refined two-stage mixed acid leaching was developed. Hazardous impurities, such as heavy metals, were significantly reduced by this approach, achieving a notable SiO2 purity of 99.99%. Significant outcomes include achieving a SiO2 purity of 99.99%, a total recovery rate of 38.04% from raw materials, and significant removal efficiencies for critical contaminants such as Fe (90.45%), Al (78.89%), and Ca (68.15%) after the two-stage acid treatment. Analytical techniques like SEM-EDS (Scanning Electron Microscopy with Energy-Dispersive X-ray Spectroscopy), XRD (X-ray Diffraction), XPS (X-ray Photoelectron Spectroscopy), ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry), and FTIR (Fourier-Transform Infrared Spectroscopy) were utilized to monitor the migration of these impurities throughout the purification process, ensuring a safe and controlled treatment of the tailings. A viable method for HPQ extraction has been demonstrated and a model for sustainable mining waste management practices has been established through this research.

The utilization of sulfur acid residue is an urgent problem confronting sulfuric acid production enterprises, especially the application of sulfur acid residue (SAR) containing lead and zinc. A method combining chlorination roasting using CaCl2 with pelletizing for processing SAR containing lead and zinc was used in this study, and the effect of calcium chloride on pelletizing performance was studied; in addition, the removal behavior of lead and zinc was also studied by using polarized light microscopy (Zeiss double Axioskop 40A), X ray diffraction, SEM and EDS. The results showed that CaCl2 migrated to the surface of the pellets during drying, and this phenomenon resulted in a lower removal rate of lead and zinc inside the pellets than outside the pellets during the preheating phase. When the roasting temperature was 1220 °C, with an increase in the basicity of pellets, the silicate minerals in the pellets gradually decomposed, the hematite particles were gradually refined, and more lead or zinc minerals were exposed, which further increased the removal rate of lead and zinc in the pellets. Finally, the SAR pellets with Pb and Zn removal rates up to 91.33 and 97.88%, and a compressive strength of 2789 N, could be obtained, which is very beneficial to the sustainable development of sulfuric acid mills.

While numerous studies have explored the mineralogical characteristics and purification techniques of high-purity quartz (HPQ), discussions on impurity control during various purification processes and their applications in photovoltaics, electronics, and optics remain limited. This review delves into the adverse effects of impurities such as aluminum, iron, and sodium in the manufacturing processes of these industries, emphasizing their critical role as these impurities can degrade material performance. This paper focuses on analyzing the types of impurities found in quartz and evaluates existing purification technologies such as acid washing, ultrasonic acid washing, chlorination roasting, and calcination quenching. It highlights the limitations of current technologies in processing quartz ore and discusses the advantages of different impurity types under various technological treatments. Moreover, it explores the environmental and economic impacts of these high-purity processes, underlining the necessity for more environmentally friendly and cost-effective purification techniques. The purpose of this review is to provide a comprehensive technical and strategic framework for the use of high-purity quartz in high-tech applications, supporting future research and industrial applications in this critical material field.

Stainless steel solid wastes (SSSW) treatment and recycling has attracted wide attention in recent years because of more stringent environment laws and regulations. Recycling of SSSW through carbothermal reduction of chromite (SRC)-electric furnace (EF) process is favorable to the effective treatment of SSSW and recovery of valuable elements. In this paper, SSSW are used to manufacture sufficiently strong oxidized pellets with the coexistence of chromite concentrates for ferrochrome production based on the SRC-EF process. The induration characteristics and harmful element migration behavior during oxidation of pellets are investigated and revealed. It is found that the oxidized pellets made from 100% SSSW possess low mechanical strength. Increasing the ratio of chromite concentrate from 0% to 80% can significantly improve the pellet strength from 460 N/pellet to 1868 N/pellet when preheating at 1000 °C for 12min and roasting at 1275 °C for 15min. Oxidized pellets made from SSSW and chromite are mainly dominated by the solid-phase consolidation due to the recrystallization of iron-rich spinel phases and sesquioxide derived from oxidation of ferrous oxides. In addition, slag bonding of CaO–CaF2–SiO2–FeO system also plays an important role in the consolidation of oxidized pellets. As for pellets made from 32% SSSW and 68% chromite concentrate, 39.96% F, 91.06% S, 66.73% Cl can be removed from the pellets when preheating at 1000 °C for 12 min and roasting at 1275 °C for 15 min.

The reduction behaviors of fired vanadium titanomagnetite (VTM) pellets must be fully ascertained for the effective utilization of VTM concentrates via the coal-based rotary kiln direct reduction-electric furnace smelting process. This paper investigates the effects of the reduction conditions on the reduction behaviors of three types of fired VTM pellets, i. e., Pellets 1, 2 and 3 assaying 13.02%, 11.70% and 5.25% TiO2, respectively, as well as the differences among their reduction behaviors. The results indicate that the highest metallization degree of Pellets 1, 2 and 3 increases sequentially when fully reduced at high temperature for long duration. Pellet 1 shows a good resistance to volume swelling under any reduction conditions, while both Pellets 2 and 3 exhibit the abnormal volume swelling during reduction, with the maximum volume swelling up to 43.78% and 36.45%, respectively. The compressive strength of reduced pellets of Pellet 1 is about 1000N/pellet, whereas below or only close to 500N/pellet for Pellets 2 and 3. Mechanism analysis shows that the minerals compositions and microstructure of fired VTM pellets have great effect on their reduction behaviors. Moreover, the reduction behaviors of fired VTM pellets can be improved by addition of ordinary magnetite in the pellet feeds.

In this paper, a process of pre-oxidation and magnetization roasting followed by low-intensity magnetic separation and acid leaching (OMLA) was developed to separate and recover iron from siderite ore with high-magnesium and high-manganese. The pre-oxidation of siderite ore was performed in a tube furnace at 800 °C for 45 min, improving the iron recovery by 6%. The effects of conditions of magnetization roasting, magnetic separation and acid leaching on the separation indices were studied. Under the optimum parameters, the iron concentrate, assaying 62.01% Fe, 8.74% MgO, 2.41% MnO with comprehensive recovery of 96.9%, were obtained through the OMLA process. Phase and microstructure transformation of the samples in OMLA process were investigated by SEM-EDS. The results indicated that pre-oxidation of siderite ore can cause porous structure of raw sample, improving reduction efficiency in magnetization roasting process. Most of gangue minerals (dolomite, ankerite, quartz and muscovite) could be removed in the process while Mn and part of Mg which existed in the iron oxides in the form of isomorphous substitution throughout the OMLA process would remain in the final concentrate.

In this study, copper slag and low-grade nickel laterite were synergistically utilized via an innovative sintering process with multi-force fields. Their sintering performance and the reduction and softening dripping characteristics of Fe–Ni–Cu product sinter were determined. The strengthening mechanism of the innovative sintering technology was revealed. The obtained Fe–Ni–Cu alloy and smelting slag from the melting dripping process were characterized. Carbon emissions reduction and other valuable elements treatment were also discussed. Due to the formation of the denser sinter microstructure and the reduction of high smelting components, sintering performances in the innovative sintering process are substantially improved. Compared with the base case, tumble index and productivity are improved by 24.87% and 19.59%, respectively. Solid fuel consumption is reduced by 27.14%. The reduction and softening dripping characteristics of Fe–Ni–Cu product sinter are excellent as well. The obtained Fe–Ni–Cu alloy with high purity can be used as the high-quality burden for copper-bearing stainless steel and high-strength alloy steel and its quality can be further improved by optimizing the smelting process parameters in the near future. In addition, the obvious carbon emissions reduction in sintering-blast furnace production can be achieved and other valuable elements such as S, Zn and Pb can be conveniently recycled in form of sulphuric acid and Pb–Zn dust, respectively.

At present, deep learning is a hot topic in the field of the classification of hyperspectral image (HSI), and it has aroused wide attention. However, in fine-grained classification tasks, such as tree species classification, the uncertain spectrum remains the major factor restraining the classification performance. In order to solve the dilemma of forest tree species classification, a dual-concentrated network with morphological features (DNMF) is proposed. First, mathematical morphology is used to extract the morphological features of HSI. Then, coarse-grained information is extracted from the original hyperspectral data, and fine-grained information is extracted from morphological features. After that, both morphological representations and spectral inputs are fed into DNMF, and the overall evaluation index and visual image are obtained. The advantage of DNMF is that it decouples the spatial and spectral information, and a multisource information fusion process is then simulated. Accordingly, DNMF obtains high tree species classification accuracy. In order to verify the superiority of DNMF, we choose Gaofeng State-owned Forest Farm in Guangxi Province and the Belgium dataset, which was collected near the western part of Belgium as the research area. Related experiments demonstrate that the DNMF model achieves clearly better classification performance over other competitive baselines.

Iron ores always contain several forms of alumina, which may have different effect on sintering performance. In this paper, sinter pot tests were systematically conducted with various alumina types and contents by means of alumina additives substituting for the corresponding types of alumina, and the relevant action mechanism on sintering performance was clarified by the mineralogy of product sinter. The results show that kaolinite is beneficial to the granulation process rather than other three alumina types. In addition, it contributes to relatively better sintering performance while aluminous goethite ranks the only next, followed by gibbsite and free alumina. Mechanism analysis indicates that kaolinite and aluminous goethite are preferable to achieve relatively lower sinter porosity and higher amount of silico-ferrite of calcium and alumina (SFCA) compared with gibbsite and free alumina. Besides, the former two alumina types are apt to promote the formation of higher strength SFCA such as dendritic and acicular SFCA. Furthermore, much tighter interlocking texture in product sinter is formed as alumina occurs in kaolinite or aluminous goethite. Kaolinite and aluminous goethite are the preferably desirable alumina types for sintering rather than free alumina and gibbsite.

This study is aimed to obtain better-quality Ni–Cr composite sinter for the production of 300 series stainless steel via the sintering-blast furnace process at lower cost. Based on the complementary advantages of limonitic nickel laterite and chromite, co-sintering pot tests of the two ores were conducted in various chromite proportions and then strengthened by multi-force fields. Mechanistic analysis was performed, including the chemistry and mineralogy of product sinter and the thermodynamic and kinetic conditions of the co-sintering process. The results indicate that the addition of chromite effectively improves tumble index and productivity, especially at a chromite ratio of 15%, due to the improvement of sinter microstructure and the thermodynamic and kinetic conditions during sintering. However, solid fuel rate is increased gradually because of the greater amount of high smelting minerals. With the application of multi-force fields, higher tumble index is obtained owing to the further densification of sinter bed and the formation of tighter interlocking texture. Solid fuel rate is greatly decreased due to the efficient supply of extra physical heat. Productivity is weakened to some extent as the flame fronts speed is reduced. In addition, excellent metallurgical performance is achieved. The co-sintering process of limonitic nickel laterite and chromite is significantly improved via multi-force fields.

Recovery of valuable metals from red mud smelting separation slag is important for environmental protection and saving of natural resources. In this paper, we propose a recycling process of red mud smelting separation slag by mineral phase reconstruction conducted under an air atmosphere. In this process, NaOH and Ca(OH)2 roasting of Al2O3 and NaAlSiO4 was performed, and Al2O3 and SiO2 were converted into alkaline-soluble NaAlO2 and Ca2SiO4, respectively. In the consequent steps, more than 80% of Al2O3 was selectively dissolved into a leaching solution using a NaOH solution under 95 °C, and the obtained NaAlO2 solution can be used as a source for extracting alumina. Then, a 20 wt.% HCl solution was used to remove SiO2 from the residue, obtaining a SiO2-containing solution and a concentrated residue of undissolved TiO2 and CaO. Finally, this mineral phase reconstruction process can enable a higher metal leaching rate, and this study provides a novel, clean, and sustainable method for recycling valuable metals from red mud smelting separation slag.

The alumina content of iron ores for sintering is gradually increasing with the growing depletion of high-grade iron ores, which is harmful to the sintering process. Therefore, it is essential to reveal the action mechanism of alumina on sinter quality. In this paper, the aluminum occurrence of various iron ores was determined by applying X-ray diffraction (XRD), optical microscopy, scanning electron microscopy and energy dispersive spectrum analysis (SEM-EDS). Then, the effects of iron ore type, aluminum occurrence (free alumina, gibbsite, diaspore, alumogoethite and kaolinite) and alumina content on formation characteristics of SFCA bonding phases as well as sinter matrix strength were investigated based on laboratory compact sintering tests. The results show that the discrepancy of aluminum occurrence contributes to different SFCA formation characteristics and then sinter matrix strength, due to different reactivity of various aluminum-containing minerals with iron oxides and fluxes. Increasing alumina content generally results in an increase in the porosity of sinters and deterioration of sinter matrix strength for all aluminum occurrence. Aluminum in the form of kaolinite is more conducive to form dendritic or acicular SFCA with superior sinter matrix strength compared with other aluminum occurrences. In contrast, aluminum occurring in free alumina presents greatest adverse impacts on sinter matrix strength due to its poor reactivity and high porosity of resultant sinters.

Direct reduction-magnetic separation process (DRMSP) is a highly effective and clean method to upgrade the complex resources, which has been widely used to recovery the value metals in copper slag (CS) and nickel laterite (NL) in recent years. Adequate growth of the alloy particles is a key parameter influencing the complete extraction of alloys from CS and NL in this process. Therefore, the liquid phase formation mechanism, growth kinetics of the alloy particles, and the correlation between the alloy particle growth and liquid phase formation were studied to reveal the synergistic effect of the co-reduction of CS and NL. The results indicated that fayalite in the copper slag reacted with forsterite in nickel laterite to form augite group minerals with low melting points, resulting in more liquid phase formation in the reductive roasting process. A comparison with the reduction kinetic parameters of the single nickel laterite showed that the growth index and activation energy decreased significantly from 2.85 and 272.98 KJ/mol to 2.08 and 171.99 KJ/mol, respectively, after the addition of 40% copper slag, which confirmed that copper slag promoted the particle growth. Moreover, the liquid phase increased the total cohesive force between the alloy particles, revealing the correlation between alloy particle growth and liquid phase.

As is well known, the process of direct reduction and magnetic separation is effective route to deal with low-grade saprolite laterite, but generally limited by the reduction of nickel (iron)-bearing minerals and growth of Fe-Ni alloy particles in the reduction process, causing the low recovery of nickel and iron. To improve beneficiation of nickel and iron from low-grade saprolite laterite with 1.29 wt.%Ni and 16.31 wt.%Fe, co-reduction with limonitic laterite ore and basicity optimization were adopted as strengthening measures in this paper with better economic efficiency than before. The enhancing mechanism was investigated via the thermodynamics analysis and mineralogical study. The phase transformation and growth behaviors of metallic alloy particles during reduction process were revealed as well. The results indicated that co-reduction with limonitic laterite ore is capable of promoting phase transformation from Ni2SiO4 in saprolite laterite to NiFe2O4. CaCO3 can not only destroy the structure of magnesium silicate to release nickel(iron)-bearing phase, but also enhance the reduction of Fe2SiO4 to form efficiently iron-based eutectoid with nickel and liquid phases to accelerate the growth of Fe-Ni fine particles larger than 40 μm. A superior crude alloy was obtained with 5.11 wt.%Ni and 82.15 wt.%Fe with corresponding recovery rates of 91.89% and 85.15% respectively. Keywords: Nickel laterite ore, Co-reduction, Basicity, Phase transformation, Particle growth, Fe-Ni alloy

The forest tree height and aboveground biomass (AGB) are important indicators for monitoring changes and trends in forest carbon storage and terrestrial carbon fluxes. Accurate large-scale wall-to-wall mapping of the forest tree height and AGB remain challenging due to the limited data availability for extraction tree height and the data signal saturation problem in AGB estimation. In this study, we explored the potential of forest tree height mapping using stereo imageries, and analyzed whether accounting for such information, in addition to optical sensor data, could improve the performance of AGB estimations of coniferous forests in a case study in North China. First, a spatially continuous tree height product was obtained using Ziyuan-3 satellite (ZY-3) stereo images combined with a digital elevation model (DEM) obtained from Advanced Land Observing Satellite (ALOS) data. Second, two AGB estimation models were established by combining the forest tree height with vegetation index, spectral, biophysical (from Sentinel-2 images), and topographic variables. A random forest algorithm was utilized to evaluate the effect of including the tree height variable in the AGB estimation. The results showed that the tree height estimation using the nadir and forward views of the ZY-3 stereo images was more accurate than that based on the nadir and backward views from the same images. The AGB estimation model incorporating the tree height variable with a coefficient of determination value of 0.7789, a root mean square error (RMSE) value of 29.815 Mg/ha and a relative RMSE of 23.42% was more robust and effective, thereby demonstrating that the tree height variable can be used to alleviate the data signal saturation issue successfully. The proposed approach can provide new insight into forest tree height mapping and AGB products obtained from satellite stereo images and freely accessible Sentinel-2 multispectral images.

In this paper, an innovative method is proposed to upgrade iron and remove phosphorus from high-phosphorus oolitic hematite ore by the sodium magnetization roasting–magnetic separation–sulfuric acid and sodium hydroxide leaching process. The process parameters of sodium magnetization roasting, acid leaching, and alkaline leaching were optimized. The results show that by only adopting traditional magnetization roasting–magnetic separation, an iron ore concentrate containing 57.49% Fe and 1.4% P2O5 at an iron recovery rate of 87.5% and a dephosphorization rate of 34.27% was produced, indicating that it is difficult to effectively dephosphorize and upgrade iron by the conventional magnetization roasting–magnetic separation process. The obtained rough magnetic concentrates were then subjected to acid and alkaline leaching steps, and the final product, assayed at 64.11% iron and 0.097% P2O5, was manufactured successfully. Moreover, the added NaOH could promote the mineral phase reconstruction of aluminum- and silica-bearing minerals during magnetization roasting and intensify the upgrading of iron as well as enhance the growth of iron grains.

An efficient and accurate forest sample plot survey is of great significance to understand the current status of forest resources at the stand or regional scale and the basis of scientific forest management. Close-range photogrammetry (CRP) technology can easily and quickly collect sequence images with high overlapping to reconstruct the 3D model of forest scenes and extract the individual tree parameters automatically and, therefore, can greatly improve the efficiency of forest investigation and has great application potential in forestry visualization management. However, it has some issues in practical forestry applications. First, the imaging quality is affected by the illumination in the forest, resulting in difficulty in feature matching and low accuracy of parameter extraction. Second, the efficiency of 3D forest model reconstruction is limited under complex understory vegetation or the topographic situation in the forest. In addition, the density of point clouds by dense matching directly affects the accuracy of individual tree parameter extraction. This research collected the sequence images of sample plots of four tree species by smartphones in Gaofeng Forest Farm in Guangxi and Wangyedian Forest Farm in Mongolia to analyze the effects of image enhancement, feature detection and dense point cloud algorithms on the efficiency of 3D forest reconstruction and accuracy of individual tree parameter extraction, then proposed a strategy of 3D reconstruction and parameter extraction suitable for different forest scenes. First, we compared the image enhancement effects of median–Gaussian (MG) filtering, single-scale retinex (SSR) and multi-scale retinex (MSR) filtering algorithms. Then, an improved algorithm combining Harris corner detection with speeded-up robust features (SURF) feature detection (Harris+SURF) is proposed, and the feature matching effect is compared with that of a scale invariant feature transform (SIFT) operator. Third, according to the morphological characteristics of the trees in the sequence images, we used the iterative interpolation algorithm of a planar triangulation network based on geometric constraints (GC-based IIPTN) to increase the density of point clouds and reconstruct the 3D forest model, and then extract the position and DBH of the individual trees. The results show that MSR image enhancement can significantly increase the number of matched point pairs. The improved Harris+SURF method can reduce the reconstruction time of the 3D forest model, and the GC-based IIPTN algorithm can improve the accuracy of individual tree parameter extraction. The extracted position of the individual tree is the same as the measured position with the bias within 0.2 m. The accuracy of extracted DBH of Eucalyptus grandis, Taxus chinensis, Larix gmelinii and Pinus tabuliformis is 94%, 95%, 96% and 90%, respectively, which proves that the proposed 3D model reconstruction method based on image enhancement has great potential for tree position and DBH extraction, and also provides effective support for forest resource investigation and visualization management in the future.

Waste copper slag is a typical hazardous solid waste containing a variety of valuable elements and has not been effectively disposed of so far. In this paper, a stepwise extraction process was proposed to recover valuable elements (copper, iron, lead and zinc) from waste copper slag. The specific procedures are as follows: (1) A flotation process was adopted to enrich copper, and when the copper grade in the flotation concentrate was 21.50%, the copper recovery rate was 77.78%. (2) The flotation tailings were pelletized with limestone, then the green pellets were reduced, and the magnetic separation process was carried out. When the iron and copper grades in the magnetic concentrate were 90.21% Fe and 0.4% Cu, 91.34% iron and 83.41% copper were recovered, respectively. (3) Non-magnetic tailings were mixed with clinker and standard sand to produce common Portland cement. Several products were obtained from the waste copper slag through the proposed process: flotation concentrate, measured 21.50% Cu; magnetic concentrate, containing 90.21% TFe and 0.4% Cu; direct reduction dust, including 65.17% ZnO and 2.66% PbO; common Portland cement for building construction. The comprehensive utilization method for waste copper slag achieved zero tailing and has great potential for practical application.