With increasing production of red mud, the environmental problems caused by it are increasingly serious, and thus the integrated treatment of red mud is imminent. This article provides an overview of ...the composition and the basic characteristics of red mud. The research progress of safe stockpiling and comprehensive utilization of red mud is summarized. The safe stockpiling of red mud can be divided into two aspects: the design and safe operation of the stocking yard. The comprehensive utilization of red mud can be further divided into three aspects: the effective recycling of components, resource utilization and application in the field of environmental protection. This paper points out that the main focus of previous studies on red mud stockpiling is cost reproduction and land tenure. The recovery of resources from red mud has a high value-added, but low level industrialization. The use of red mud as a building material and filler material is the most effective way to reduce the stockpiling of red mud. Red mud used for environmental remediation materials is a new hotspot and worth promoting for its simple processing and low cost.
•3D synchrotron and 2D in-situ SEM were used for crack closure determination.•FCG retardation was correlated with crack-tip straining, plastic zone and COD.•Crack-tip shielding effect and strain ...transfer was observed for the first time.•Load history dependence of FCG and residual compressive strain relaxation were evidenced directly.•Load transfer was proposed as the physics of near-tip straining, crack opening and FCG.•FCG retardation was mainly governed by residual compressive stress.
Fatigue crack growth retardation of AZ31 alloy under a single tensile overload was investigated by 3D synchrotron radiation, 2D in-situ SEM and digital image correlation techniques. Results showed a consistent evolution of crack closure level by both 3D and 2D methodologies. The straining and plastic zone ahead of crack-tip, and crack opening displacement behind, which were quantitative indicators of crack-tip shielding, residual stress formation and relaxation, were correlated well with the retardation behavior. Mechanistically, compressive residual stress played a dominant but time-limited role while crack closure was secondary, based on an intrinsic load transfer concept during crack growth.
Defect or shrinkage is known to have a detrimental effect on the fatigue resistance of casting lightweight alloys and additively manufactured or 3D printed materials. However, very few works focus on ...the damage mechanism of fusion welded Al alloys due to gas pores or metallurgical defects. This paper performs an investigation on the effect of porosity on the damage evolution of laser hybrid welded 7020‐T651 alloys. The critical pore size comparable with average weld grain was assumed in terms of the population and dimension of micropores. To characterize the coupling effect between gas pores and cracks, an in situ fatigue testing rig was developed to well work at the synchrotron radiation tomography system. Combining synchrotron X‐ray microtomography and fatigue resistance testing, the pore size and location were correlated with the crack initiation and crack growth path but relatively less on the long crack propagation rate. Furthermore, the interaction between the porosity and stress concentration was elucidated by using finite element simulations, which shows that the gas pore appears to be a preferred cracking site especially near the surface.
We calculated water use efficiency (WUE) using measures of gross primary production (GPP) and evapotranspiration (ET) from five years of continuous eddy covariance measurements (2009-2013) obtained ...over a primary subtropical evergreen broadleaved forest in southwestern China. Annual mean WUE exhibited a decreasing trend from 2009 to 2013, varying from ~2.28 to 2.68 g C kg H
O
. The multiyear average WUE was 2.48 ± 0.17 (mean ± standard deviation) g C kg H
O
. WUE increased greatly in the driest year (2009), due to a larger decline in ET than in GPP. At the diurnal scale, WUE in the wet season reached 5.1 g C kg H
O
in the early morning and 4.6 g C kg H
O
in the evening. WUE in the dry season reached 3.1 g C kg H
O
in the early morning and 2.7 g C kg H
O
in the evening. During the leaf emergence stage, the variation of WUE could be suitably explained by water-related variables (relative humidity (RH), soil water content at 100 cm (SWC_100)), solar radiation and the green index (Sgreen). These results revealed large variation in WUE at different time scales, highlighting the importance of individual site characteristics.
As a common condition in train operation, the out‐of‐roundness (OOR) of wheels may have a great influence on the life of cracked wheels. In this study, the I–II mixed‐mode crack growth rate of ...different angles was tested, finite element analysis was carried out by using the test results, and the influence of different wheel roundness conditions on the life of cracked wheels was revealed. The results show that the mode II stress intensity factor of mixed‐mode cracks is the main driving force for crack propagation in the process of wheel rim crack growth. With an increase in the wheel scar length and the order of the wheel polygon, the crack propagation life decreases significantly.
Highlights
Fracture mechanical properties are obtained for different crack deflection angles.
The wheel‐rail contact model for out‐of‐round wheel with crack submodel is constructed.
The remaining life of the wheel decreases as the crack angle and flat scar length increase.
The polygon phenomenon of the wheel will greatly reduce the remaining life of the wheel.
In the field of structural health monitoring (SHM), with the mature development of artificial intelligence, deep learning-based structural damage identification techniques have attracted wide ...attention. In this paper, the convolutional neural network (CNN) is used to extract the damage feature of simple supported steel beams. Firstly, the transient dynamic analysis of the steel beam is carried out by finite element software, and the acceleration response signals under different damage scenarios are obtained. Then, the acceleration response signal is decomposed by wavelet packet decomposition (WPD) to extract the wavelet packet band energy ratio variation (ERV) index as the training sample of CNN. Subsequently, the vibration experiment of a simple supported steel beam was carried out, and the results were compared with the numerical simulation results. The characteristic indexes were obtained by making corresponding changes to the vibration signal, and then, the experimental data were input into the CNN to predict the effect of damage detection. The results show that the method can successfully detect the intact structure, single damage, and multiple damages with an accuracy of 95.14% under impact load, and the performance is better than that of support vector machine (SVM), with good robustness.
Defects in pile foundations, such as neck defects, bulge imperfections, weak concretes, cracks, and broken piles, can cause a decrease in the bearing capacity and the structural stability of the ...foundation. Identification of the type of defect is vital in formulating a reasonable repair plan for the pile foundation. In this study, the authors proposed a scheme to identify the types of defects in concrete piles based on a convolution neural network and a low-strain pile integrity test (LSPIT). A batch modeling method of defective pile foundations using Python script was also proffered. The different degrees of signals of five types of defective pile foundations were simulated by this method. The original data were decomposed and reconstructed by wavelet packet decomposition (WPT). To prevent the data from losing too much information after WPT, the data of 400 × 1 after decomposition and reconstruction were processed by dimension-raising to obtain the data of 20 × 20 × 1. Then, the multidimensional feature index of 20 × 20 × 2 was generated by index fusion with the original data. Finally, the data were input onto convolutional neural network (CNN) as a training parameter. Following an improvement of the dataset, the recognition accuracy of the type of defect in the pile foundation by the proposed identification scheme reached 94.4%.
Without any root contact with the soil, epiphytic bryophytes must experience and explore poor, patchy, and heterogeneous habitats; while, the nitrogen (N) uptake and use strategies of these organisms ...remain uncharacterized, which obscures their roles in the N cycle. To investigate the N sources, N preferences, and responses to enhanced N deposition in epiphytic bryophytes, we carried out an in situ manipulation experiment via the (15)N labelling technique in an Asian cloud forest. Epiphytic bryophytes obtained more N from air deposition than from the bark, but the contribution of N from the bark was non-negligible. Glycine accounted for 28.4% to 44.5% of the total N in bryophyte tissue, which implies that organic N might serve as an important N source. Increased N deposition increased the total N uptake, but did not alter the N preference of the epiphytic bryophytes. This study provides sound evidence that epiphytic bryophytes could take up N from the bark and wet deposition in both organic and inorganic N forms. It is thus important to consider organic N and bark N sources, which were usually neglected, when estimating the role of epiphytic bryophytes in N cycling and the impacts of N deposition on epiphytic bryophytes in cloud forests.
Chlorophyll content in lichens is routinely used as an accurate indicator of lichen vigor, interspecific differences, and the effect of site-related environmental parameters. Traditional methods of ...chlorophyll extraction are destructive, time-consuming, expensive, and inoperable, especially when measuring large quantities of chlorophyll. However, non-destructive methods of measurement using portable chlorophyll meters are rarely used for lichens. Considering the characteristics of lichens such as rough blade surface and absence of chlorophyll b in cyanolichens, we compared the non-destructive methods with traditional methods and evaluated their applicability in studying lichen pigment content. Two instruments, SPAD-502 and CCM-300, were used to measure the pigment content of seven foliose lichen species. These pigment readings were compared with those determined using the dimethyl sulphoxide (DMSO) extraction method. Significant correlations were observed between SPAD/CCM values and pigments (chlorophyll and total carotenoids) extracted from chlorolichens, especially species with a smooth surface. The CCM-300 was more accurate in detecting the pigment content of foliose chlorolichens. However, both instruments showed certain limitations in the determination of pigment content in cyanolichens, especially gelatinous species. For example, CCM-300 often failed to give specific values for some cyanolichen samples, and both instruments showed low measurement accuracy for cyanolichens. Based on the high correlation observed between chlorophyll meter readings and pigments extracted from chlorolichens, equations obtained in this study enabled accurate prediction of pigment content in these lichens.
Defects in different positions and degrees in pile foundations will affect the building structure’s safety and the foundation’s bearing capacity. The efficiency and accuracy of using traditional ...methods to identify multi-defect types of pile foundations are very low, so finding suitable methods to improve their related indicators for pile foundation safety and engineering applications is necessary. In this paper, under the condition of secondary development of finite element software ABAQUS to obtain the time-domain signal database of six kinds of multi-defect pile foundations, a multi-defect type identification method of pile foundations based on two-channel convolutional neural network (TC-CNN) and low-strain pile integrity test (LSPIT) is proposed. Firstly, simulated time-domain signals of the dynamic measurements that match the experimental results performed wavelet packet denoising. Secondly, the 1D time-domain signals before and after denoising and the corresponding 2D wavelet time–frequency maps are inputs to retain more data information and prevent overfitting. Finally, TC-CNN achieved the multi-defect type identification of concrete piles. Compared with the single-channel convolutional neural network, this method can effectively fuse 1D and 2D features, extract more potential features, and make the classification accuracy reach 99.17%.
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