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The deformation behavior of a dam can comprehensively reflect its structural state. By comparing the actual response with model predictions, dam deformation prediction models can detect anomalies for effective advance warning. Most existing dam deformation prediction models are implemented within a single-step prediction framework; the single-time-step output of these models cannot represent the variation trend in the dam deformation, which may contain important information on dam evolution during the prediction period. Compared with the single value prediction, predicting the tendency of dam deformation in the short term can better interpret the dam’s structural health status. Aiming to capture the short-term variation trends of dam deformation, a multi-step displacement prediction model of concrete dams is proposed by combining the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm, the k-harmonic means (KHM) algorithm, and the error minimized extreme learning machine (EM-ELM) algorithm. The model can be divided into three stages: (1) The CEEMDAN algorithm is adopted to decompose dam displacement series into different signals according to their timing characteristics. Moreover, the sample entropy (SE) method is used to remove the noise contained in the decomposed signals. (2) The KHM clustering algorithm is employed to cluster the denoised data with similar characteristics. Furthermore, the sparrow search algorithm (SSA) is utilized to optimize the KHM algorithm to avoid the local optimal problem. (3) A multi-step prediction model to capture the short-term variation of dam displacement is established based on the clustered data. Engineering examples show that the model has good prediction performance and strong robustness, demonstrating the feasibility of applying the proposed model to the multi-step forecasting of dam displacement.

In order to reduce the damage sustained by the substructure of bridges during an earthquake, reduce economic loss, avoid casualties, and ensure the quick repair of bridges after an earthquake, this paper, inspired by the good seismic performance of the rhombic opening in the shear wall structure, proposes a precast segmental concrete-filled steel tubular (PSCFST) pier with external replaceable energy-dissipating links (EREDL).Through finite element simulation analysis, it can be found that the energy dissipation capacity of a PSCFST pier with external EREDL is increased by 104% compared with that of a PSCFST pier without EREDL, and the lateral bearing capacity is increased by 76.9%. Through parameter analysis, it can be found that the change of initial prestress has little effect on the energy dissipation capacity of PSCFST piers, and the seismic performance of PSCFST piers can be improved by properly increasing the ultimate tensile strength of the energy dissipator materials. Compared with the energy dissipators made of Q235 steel, the energy dissipation capacity of PSCFST piers made of Q435 steel energy dissipators is increased by about 85.4%; At the same time, the thicker the energy dissipator, the stronger the energy dissipation capacity of the PSCFST pier, and the lateral bearing capacity is further improved.

In order to further promote the application of segment-assembled bridge piers in medium- and high-intensity areas, and to reduce the post-earthquake damage and repair cost of bridge piers, in this paper, a precast segmental concrete-filled steel-tube bridge pier (PSCFSTBP) with an external arched energy dissipation device (AEDD) is proposed. Firstly, the effectiveness of the finite-element analysis software ABAQUS 6.14-4 is proved by the test results of the PSCFSTBP and the corresponding finite-element model analysis results. Secondly, ABAQUS 6.14-4 was used to establish four-segment PSCFSTBP models with four different structural forms (non-energy dissipation device, external arch steel plate, external vertical steel plate, and external AEDD), and the seismic performance of each model was compared and analyzed under reciprocating displacement loading. The results show that compared with the PSCFSTBP with an external AEDD, the lateral bearing capacity of the PSCFSTBP with an external vertical steel plate is increased by about 11.9%, and the initial stiffness is increased by about 2.5%. Compared with the PSCFSTBP with an external arch steel plate, the lateral bearing capacity, initial stiffness, and energy dissipation capacity are increased by 28.8%, 4.6%, and 13 times, respectively. Compared with the PSCFSTBP without an energy dissipation device, its lateral bearing capacity, initial stiffness, and energy dissipation capacity are increased by 39.4%, 10.4%, and 18 times, respectively. The residual displacement of the PSCFSTBP with an external AEDD is kept within 1 mm in the whole displacement loading stage, the offset rate is less than 1%, and the pier damage is controllable, which can realize rapid repair after an earthquake. Finally, the multi-level energy consumption and local replacement of the AEDD are also explored.

Yttria-stabilized zirconia (YSZ) nanospheres were synthesized by calcination at 900 °C after the adsorption of Y3+ ions into the pores of a zirconium-based metal–organic framework (MOF). The synthesized 3YSZ (zirconia doped with 3 mol% Y2O3), 8YSZ (8 mol% Y2O3), and 30YSZ (30 mol% Y2O3) nanospheres were found to exhibit uniform sizes and shapes. Complex permittivity and complex permeability were carried out in K-band (i.e., 18–26.5 GHz) to determine their suitability for use as low-k materials in 5G communications. The real and imaginary parts of the permittivity of the sintered 3YSZ were determined to be 21.24 and 0.12, respectively, while those of 8YSZ were 22.80 and 0.16, and those of 30YSZ were 7.16 and 0.38. Control of the real part of the permittivity in the sintered YSZ was facilitated by modifying the Y2O3 content, thereby rendering this material an electronic ceramic with potential for use in high-frequency 5G communications due to its excellent mechanical properties, high chemical resistance, and good thermal stability. In particular, it could be employed as an exterior material for electronic communication products requiring the minimization of information loss.

This paper proposes a novel type of steel angle-corrugated steel plate-confined concrete column (SA-CS column). The axial compression behavior of the SA-CS column was investigated by load experiments and finite element (FE) simulation. The study also compared the load–displacement curves, core concrete strength index, and specimens’ ductility indices between the SA-CS columns and concrete-filled steel tube (CFST) columns. The results indicated that the mechanical properties of the SA-CS column were better than those of the CFST column with a similar steel ratio. The rationality and reliability of the finite element model were confirmed by comparing the experimental results’ load–displacement curves and failure modes. Based on the FE model, a supplementary parametric analysis of the effects of the compressive strength of core concrete, thickness, yield strength, and wave height of the corrugated steel plate, thickness, and yield strength of the steel angles was conducted. Moreover, some existing design codes were assessed based on the numerical results available in this study. A new calculating model for the SA-CS column was proposed, which is capable of reasonably predicting the numerical results.

Hashing has been widely used for large-scale remote sensing image retrieval due to its outstanding advantages in storage and search speed. Recently, deep hashing methods, which produce discriminative hash codes by building end-to-end deep convolutional networks, have shown promising results. However, training these networks requires numerous labeled images, which are scarce and expensive in remote sensing datasets. In order to solve this problem, we propose a deep unsupervised hashing method, namely deep contrastive self-supervised hashing (DCSH), which uses only unlabeled images to learn accurate hash codes. It eliminates the need for label annotation by maximizing the consistency of different views generated from the same image. More specifically, we assume that the hash codes generated from different views of the same image are similar, and those generated from different images are dissimilar. On the basis of the hypothesis, we can develop a novel loss function containing the temperature-scaled cross-entropy loss and the quantization loss to train the developed deep network end-to-end, resulting in hash codes with semantic similarity preserved. Our proposed network contains four parts. First, each image is transformed into two different views using data augmentation. After that, they are fed into an encoder with the same shared parameters to obtain deep discriminate features. Following this, a hash layer converts the high-dimensional image representations into compact binary codes. Lastly, a novel hash function is introduced to train the proposed network end-to-end and thus guide generated hash codes with semantic similarity. Extensive experiments on two popular benchmark datasets of the UC Merced Land Use Database and the Aerial Image Dataset have demonstrated that our DCSH has significant superiority in remote sensing image retrieval compared with state-of-the-art unsupervised hashing methods.

In order to develop a new type of prefabricated bridge structure system with green, efficient and recoverable function, which complies with the new requirements of rapid repair of pier function after earthquake, and improves the applicable performance of prefabricated assembled pier in medium and high-intensity seismic areas, a precast segmental concrete-filled steel tubular (PSCFST) pier with an external energy dissipation ring is proposed. Based on ABAQUS analysis software, a four-segment PSCFST pier model is established, and the pseudo-static comparative analysis is carried out between the traditional PSCFST pier and the PSCFST pier with the external energy dissipation ring. The results show that compared with the traditional PSCFST pier, the lateral bearing capacity of the PSCFST pier with an external energy dissipation ring is increased by 60%, the energy dissipation capacity is increased by about 20 times, and the damage is concentrated in the energy dissipation ring, the damage is controllable, and the rapid repair after the earthquake can be realized by replacing energy dissipation devices and other measures. At the same time, the seismic performance of pier models with three different control parameters (initial prestress, material strength of energy dissipation ring and section width of energy dissipation ring) under reciprocating loading is analyzed. The results show that the initial prestress does not affect the cumulative energy consumption of the pier; the increase in the material strength of the energy dissipation ring improves the overall stiffness and improves the energy dissipation capacity of the PSCFST pier; the reduction in section width will affect the overall equivalent stiffness and unloading stiffness of the segmental pier, and the energy dissipation capacity will be significantly reduced.

Ultrasonic nanocrystal surface modification (UNSM) was applied to hot-rolled Mg-Li alloys (LAE361 and LA106). The microstructure, mechanical properties, deformation mechanisms, and corrosion resistance properties of these alloys after UNSM treatment were systematically studied. Significant improvement in surface hardness and decrease in surface roughness were achieved by UNSM treatment. Meanwhile, the basal texture intensity of the Mg-Li alloys reduced significantly, and several deformation twins appeared on the surface layer. The α phase of the surface layer underwent twin deformation and basal plane slip. The fibre textures in the β phase of LA106 Mg-Li alloy changed from γ and η to α and ε, which mainly resulted in the dislocation slip. More importantly, UNSM treatment exhibited enhanced strength and improved plasticity of LAE361 and LA106 Mg-Li alloys. The corrosion current density of LAE361 Mg-Li alloy reduced approximately 29.3% by UNSM treatment, while it increased the corrosion current density of LA106 Mg-Li alloy by 189.7%. These studies show that the application of UNSM to improve the corrosion resistance of duplex phases of LA106 Mg-Li alloy needs further investigation.

Coffee, one of the most popular beverages in the world, attracts consumers by its rich aroma and the stimulating effect of caffeine. Increasing consumers prefer decaffeinated coffee to regular coffee due to health concerns. There are some main decaffeination methods commonly used by commercial coffee producers for decades. However, a certain amount of the aroma precursors can be removed together with caffeine, which could cause a thin taste of decaffeinated coffee. To understand the difference between regular and decaffeinated coffee from the volatile composition point of view, headspace solid-phase microextraction two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS) was employed to examine the headspace volatiles of eight pairs of regular and decaffeinated coffees in this study. Using the key aroma-related volatiles, decaffeinated coffee was significantly separated from regular coffee by principal component analysis (PCA). Using feature-selection tools (univariate analysis: t-test and multivariate analysis: partial least squares-discriminant analysis (PLS-DA)), a group of pyrazines was observed to be significantly different between regular coffee and decaffeinated coffee. Pyrazines were more enriched in the regular coffee, which was due to the reduction of sucrose during the decaffeination process. The reduction of pyrazines led to a lack of nutty, roasted, chocolate, earthy, and musty aroma in the decaffeinated coffee. For the non-targeted analysis, the random forest (RF) classification algorithm was used to select the most important features that could enable a distinct classification between the two coffee types. In total, 20 discriminatory features were identified. The results suggested that pyrazine-derived compounds were a strong marker for the regular coffee group whereas furan-derived compounds were a strong marker for the decaffeinated coffee samples.

In this study, two innovative surface severe plastic deformation (SSPD) methods, namely abrasive waterjet peening (AWJP) and ultrasonic nanocrystal surface modification (UNSM), were applied to a 304 stainless steel to improve the mechanical behavior. The surface roughness, microstructure, residual stress, hardness, and tensile mechanical properties of the alloy after the two SSPD treatments were studied systematically. The results show that both the AWJP and UNSM treatments have greatly positive effects on the mechanical-properties improvements by successfully introducing a hardening layer. Especially the UNSM-processed specimen possesses the most outstanding comprehensive mechanical properties (high strength with the comparable ductility). The yield strength with the UNSM treatment is 443 MPa, corresponding to the 109% and 19% improvements, as compared to that of the base (212 MPa) and AWJP-treated specimens (372 MPa). The results can be attributed to a much thicker hardening layer (about 500 μm) and a better surface integrity with lower roughness (Ra: 0.10 μm) formed by the UNSM technique.

Abrasive waterjet peening (AWJP) as an important surface strengthening method can effectively improve surface properties. In this study, after multiple AWJP, the distribution of compressive residual stress and roughness on the surface of 18CrNiMo7-6 steel has been evaluated by an X-ray diffraction (XRD) method and a 3D surface topography system, respectively. Compared with the single AWJP, multiple AWJP can obviously increase the surface residual stresses (−1024 MPa to −1455 MPa) and the depth of maximum compressive residual stress (100 μm to 120 μm), as well as make the stress distribution more uniform. In terms of the surface roughness, multiple AWJP influences its uniform distribution and reduces the surface roughness (Sa = 0.69 μm), compared with a single AWJP (Sa = 2.96 μm), due to the smaller shot balls and a uniform deformation during multiple AWJP. In addition, we have studied the effects of multiple AWJP on the hardness of the surface layer. The results show that multiple AWJP increases the hardness by up to 15.9%, compared to the single AWJP. These studies provide useful insight into improving the surface properties of 18CrNiMo7-6 steel by multiple AWJP.

Because of the slow dynamic behavior of the large-inertia wind turbine rotor, variable-speed wind turbines (VSWTs) are actually unable to keep operating at the design tip speed ratio (TSR) during the maximum power point tracking (MPPT) process. Moreover, it has been pointed out that although a larger design TSR can increase the maximum power coefficient, it also greatly prolongs the MPPT process of VSWTs. Consequently, turbines spend more time operating at the off-design TSRs and the wind energy capture efficiency is decreased. Therefore, in the inverse aerodynamic design of VSWTs, the static aerodynamic performance (i.e., the maximum power coefficient) and the dynamic process of MPPT should be comprehensively modeled for determining an appropriate design TSR. In this paper, based on the inverse design method, an aerodynamic optimization method for VSWTs, fully considering the impacts of the design TSR on the static and dynamic behavior of wind turbines is proposed. In this method, to achieve higher wind energy production, the design TSR, chord length and twist angle are jointly optimized, which is structurally different from the conventional separated design procedure. Finally, the effectiveness of the proposed method is validated by simulation results based on the Bladed software.

Due to the dynamic process of maximum power point tracking (MPPT) caused by turbulence and large rotor inertia, variable-speed wind turbines (VSWTs) cannot maintain the optimal tip speed ratio (TSR) from cut-in wind speed up to the rated speed. Therefore, in order to increase the total captured wind energy, the existing aerodynamic design for VSWT blades, which only focuses on performance improvement at a single TSR, needs to be improved to a multi-point design. In this paper, based on a closed-loop system of VSWTs, including turbulent wind, rotor, drive train and MPPT controller, the distribution of operational TSR and its description based on inflow wind energy are investigated. Moreover, a multi-point method considering the MPPT dynamic process for the aerodynamic optimization of VSWT blades is proposed. In the proposed method, the distribution of operational TSR is obtained through a dynamic simulation of the closed-loop system under a specific turbulent wind, and accordingly the multiple design TSRs and the corresponding weighting coefficients in the objective function are determined. Finally, using the blade of a National Renewable Energy Laboratory (NREL) 1.5 MW wind turbine as the baseline, the proposed method is compared with the conventional single-point optimization method using the commercial software Bladed. Simulation results verify the effectiveness of the proposed method.

As one possible alternative to the finite element method, the interpolation characteristic is a key property that meshless shape functions aspire to. Meanwhile, the interpolation meshless method can directly impose essential boundary conditions, which is undoubtedly an advantage over other meshless methods. In this paper, the establishment, implementation, and horizontal comparison of interpolative meshless analyses of orthotropic elasticity were studied. In addition, the radial point interpolation method, the improved interpolative element-free Galerkin method and the interpolative element-free Galerkin method based on the non-singular weight function were applied to solve orthotropic beams and ring problems. Meanwhile, the direct method is used to apply the displacement boundary conditions for orthotropic elastic problems. Finally, a detailed convergence study of the numerical parameters and horizontal comparison of numerical accuracy and efficiency were carried out. The results indicate that the three kinds of interpolative meshless methods showed good numerical accuracy in modelling orthotropic elastic problems, and the accuracy of the radial point interpolation method is the highest.