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The precast segmental self-centering concrete-filled steel tube (PSCFST) bridge is not only the ideal choice for fast and environmentally friendly construction but also has good seismic and resilience properties. Our research group has carried out shaking table test research on the PSCFST bridge, but due to the limitation of test equipment and site, no damage test has been carried out. To further study the seismic performance of PSCFST bridges when subjected to larger ground motions, machine learning (ML) models are developed to predict the seismic performance of PSCFST. A novel combined prediction model based on Conv1D-LSTM was proposed to predict the PSCFST bridge acceleration response. Two other commonly used ML methods including XGBoost and Random forest regression (RFR) are also used for comparison purposes. A database of ML prediction models is established based on 116 sets of input ground motion (GM) and superstructure acceleration response from shaking table tests. Then, the data of RSN292 60% GM were selected as the prediction test data. Furthermore, based on the Opensees platform, the PSCFST fiber finite element (FFE) model was established and validated by the shaking table test results, then the dynamic time history analysis of the ground motion with larger amplitude (greater than the input ground motion assignment of the shaking table test) was carried out. The superstructure acceleration response of 70%–120% of the RSN 292 GM is obtained by the FFE model and used as the data set for the ML prediction model. After that, the superstructure acceleration response is obtained through three prediction models. Comparing the simulation and prediction results shows that all the Conv1D-LSTM, XGBoost, and RFR models can reliably predict the acceleration response of the PSCFST bridge. In all cases, the Conv1D-LSTM model performed outperforms the XGBoost and RFR models. The determination coefficients (R 2) of Conv1D-LSTM, XGBoost, and RFR model for the prediction of superstructure response are 0.9643, 0.8780, and 0.9623, respectively. • Proposed a novel combined prediction model based on Conv1D-LSTM to predict the PSCFST bridge acceleration response. • Established the fiber finite element analysis model of PSCFST single span bridge and validated by the shaking table test. • Three AM models are used to predict the acceleration response of the PSCFST bridge under large amplitude ground motions. [ABSTRACT FROM AUTHOR]

The wide application of metakaolin based geopolymer (MG) is highly limited by its brittleness. In this study, different contents of S823, S1213 and KH570 silane coupling agent (SCA) and waterborne epoxy resin (WR) were used to synthesize organic-geopolymer composites to improve the ductility of MG. The influence of the contents of these organic agents on the mechanical properties of MG was investigated with unconfined compression tests and three-point bending tests, and the organic-inorganic interaction was characterized with Scanning Electron Microscopy, Isothermal Calorimetry, solid-state Nuclear Magnetic Resonance and Nanoindentation. By adding 1% of SCA and 20% of WR, the 28-day compressive strength, flexural strength and flexural toughness of MG achieved the highest increase of 197.0%, 128.3% and 108.4%, respectively. The reaction degree of the MG-WR and MG-SCA composites were both higher than that of MG thanks to the polymerization between the organic agents and geopolymer gel, resulting in more compact microstructure. It was revealed that the organic-inorganic polymeric structure bridged by Si-O-Si and Si-O-Al bonds were formed between SCA and MG with higher content of Si O bonds, which enhanced the micro-mechanical homogeneity, and thus the strength and ductility of MG-SCA composites. In addition, the interlocked MG-WR network formed through the hydrogen bonds allowed the high-toughness WR to improve the ductility of MG. The better understanding of organic-geopolymer interaction in this study is beneficial for the synthesis of geopolymer composites with improved mechanical performance. • The ductility of geopolymer was improved by SCA and WR at appropriate contents. • The reaction rate and polymerization degree of MG were promoted by SCA and WR. • Interlocked network was formed via hydrogen bonds and improved ductility of MG-WR. • SCA and MG was polymerized via Si-O-Si bonds to improve micromechanical properties. [ABSTRACT FROM AUTHOR]

• Commercial implementation of an HPGR-tower mill comminution circuit. • Ore size transfer between HPGR and tower mill needs to be evaluated. • Reliable fine-screening technologies are crucial to the fine-crushing flowsheet. • The amenability of a comminution circuit relates to ore properties. • Scaling up HPGR-tower mill comminution circuit should consider size reduction ratio. This paper presents the commercial implementation of a novel comminution circuit with high pressure grinding rolls (HPGR) followed by tower mill in a copper–lead–zinc ore dressing plant. With a throughput of 650 t/d, the comminution circuit comprises three stages of crushing by a jaw crusher, cone crusher, and HPGR as primary, secondary, and tertiary crushers and one stage of grinding by tower mill. Closed with a flip-flow screen, the HPGR reduces the feed size from −12 to −1 mm, and the tower mill circuit produces a flotation feed with a fineness of 85 % passing 0.074 mm. This comminution circuit has HPGR for partial coarse grinding and uses tower mill to replace the energy-inefficient ball mill for primary grinding. The circuit has been operated for more than 7000 h without the replacement of rolls and is projected to reach its design service life of over 13,000 h. Compared with a conventional dressing plant handling similar ores using an SABC circuit, 20.16 % energy savings and improved separation are realised. Opportunities and considerations for this novel comminution configuration are discussed. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we present a new denoising method for the depth image of a time-of-flight (ToF) camera, based on weighted least squares (WLS) framework. The common method for ToF depth image denoising is to use bilateral filter. However, the ability of bilateral filter in edge preservation would be reduced while we attempt to smooth out larger spatial scale noise. In order to avoid this problem and preserve the edge information as much as possible, we introduce a new way to construct edge-preserving ToF depth image denoising based on WLS. We are to our knowledge the first to present a WLS-based method for ToF depth image denoising. Experimental results demonstrate that compared with bilateral filter, our proposed algorithm not only achieves better performance in edge preservation, but also improves the PSNR values of the denoised images by 0.5–2.6dB. [Copyright &y& Elsevier]

Abstract: Y2O3 films were deposited on both sides of biaxially textured Ni–5at.%W substrates by reel-to-reel DC. magnetron reactive sputtering, serving as a seed layer for high performance coated conductors. The deposition parameters, such as water vapor pressure, substrate temperature and sputtering power, were systematically studied. The YSZ layer and CeO2 layer were fabricated on Y2O3 buffered Ni–W tapes using the same deposition system. X-ray diffraction analysis confirmed that optimized double-sided CeO2/YSZ/Y2O3 buffer layers showed a significant improvement in in-plane and out-of-plane texture. Atomic force microscope revealed a smooth, dense and crack-free surface morphology. YBa2Cu3O7- δ films grown on double-sided CeO2/YSZ/Y2O3 buffered Ni–W tapes by D.C. sputtering exhibited a critical current density of 1.26MA/cm2 at 77K for each side. [Copyright &y& Elsevier]

• Applicability of the Witczak 1-40D model was evaluated. • Artificial intelligence model was employed to correct the inaccuracy of the Witczak 1-40D model. • Adaptive inertia weight and the Levy flight method were combined in BAS algorithm. The applicability of the widely used Witczak model was evaluated for the first time regarding the asphalt mixtures produced in the East part of China. 16 asphalt mixtures by 2 binders and 8 aggregate gradations were designed and the dynamic modulus testing was performed under various loading temperatures and frequencies. The results obtained are similar to previous studies from different countries (areas): the dynamic modulus of the asphalt mixture in the low-temperature region is overestimated. So then, a hybrid artificial intelligence algorithm to replace the traditional Witcazak model is implemented in this paper to correct the overestimation, using the same input parameters in the Witczak model. A modified beetle antennae search (BAS) algorithm was proposed in this study to improve the searching efficiency in the random forest (RF) model. The calculation process showed fast convergence and higher efficiency. The comparative results between the predicted and actual dynamic modulus showed higher prediction accuracy at all the temperature and frequency ranges, overcoming the weaknesses of the traditional Witczak model. The variable importance results showed that G* and phase angle of the binders have the greatest impact on the dynamic modulus. Volumetric properties also show certain influence ability, but the change of the variable controlling aggregate gradation has a weak influence on the dynamic modulus. [ABSTRACT FROM AUTHOR]

• Evaluation of the thickness effects on the pervious concrete. • Clogging behavior of pervious concrete. • Characterization of the pore size distribution in pervious concrete. • Modeling of clogging behavior considering the pore size distribution. Pervious concrete is an environmentally friendly material that improves water permeability, skid resistance, and sound absorption characteristics. However, due to a large number of pores and the absorption capacity, pervious concrete faces the problem of clogging caused by dust particles and solid contaminants entering the internal pores. In this study, both pore size distributions (PSD) of the pervious concrete and permeability reduction behavior are studied by laboratory tests. The extent of permeability reduction is addressed by designing the penetration test for 21 groups of pervious concrete mixes with varying aggregate gradations and specimen thickness. The PSD is determined by the two-dimensional (2D) sliced image scanned by the Computed Tomography (CT). An approach to represent the characteristic pore size of pervious concrete is proposed and verified. Results showed that: the effect of thickness on permeability is negligible while on clogging behavior is significant. The ratio between the clogging sand sizes and the characteristic pore size is an important parameter that affects the clogging behavior and can be used to predict the anti-clogging performance. [ABSTRACT FROM AUTHOR]

In this paper, we firstly introduce the definition of the fuzzy metric of sets, and discuss the properties of fuzzy metric induced by the Hausdorff metric. Then we prove the limit theorems for set-valued random variables in fuzzy metric space; the convergence is about fuzzy metric induced by the Hausdorff metric. The work is an extension from the classical results for set-valued random variables to fuzzy metric space. [ABSTRACT FROM AUTHOR]

• A new program evaluating the impact of graphite and slag, and curing time. • Optimized slag and graphite to achieve balanced electrical and mechanical properties. • A microstructural interpretation to reveal distributions of conductive filler and C-S-H gel. Electrically conductive cementitious composites (ECCCs) have become a significant research interest in structural health monitoring. The use of graphite in ECCCs can significantly improve their electrical performance, however, with unsatisfactory friction resistance because of the graphite's smooth micro-surfaces. Slag can be incorporated with graphites into ECCCs to achieve good performance in both of mechanical resistance and electrical conductivity. This study investigated the impact of graphite and slag on the electrical and mechanical behaviors of ECCCs. Two hundred and eighty ECCC specimens were prepared with two different types of slags and with various conductivity ingredient fractions and curing times. The specimens were tested for compressive strength, flexural strength, and electrical resistance. It was concluded the 4% graphite content in ECCCs can significantly enhance electrical conductivity with moderate decrease in compressive and flexural strengths. Slags were found to improve both electrical conductivity and mechanical properties of ECCCs. The best results could be obtained with optimized contents of steel slag, blast furnace slag, and graphite. Finally, the microstructural mechanisms of the ECCC specimens were analyzed using scanning electron microscope (SEM) for graphite and slag. Variable sensitivity analysis was performed to allow for optimization of ingredient contents. [ABSTRACT FROM AUTHOR]

• Potential anti-vibration pavements with damping layer. • Vibration evaluation based on FE analysis. • Novel characterization method for damping property. • Parametrical analysis for anti-vibration pavements. Vibrations induced by traffic are of concern for road authorities due to disturbance on the population, and the damage of buildings and structures. In the field of pavement engineering, the anti-vibration paving technologies by the so-called damping layer are under investigation to avoid the generation of excessive vibration and contains propagation. To more fully examine the effectiveness and potential of such a damping layer in the application of anti-vibration pavement, numerical simulations based on a two-dimensional (2D) finite element (FE) model is conducted. The method of determining Rayleigh damping parameters is proposed to more accurately characterize the attenuation of vibration in the road pavements. Sensitivity analysis of varying monitored points and varying loads are performed. Several important parameters such as the damping layer position and thickness, damping ratio are evaluated as well. By the use of this FE simulation to model the vibration response induced by traffic, the costly construction mistakes and field experimentation can be avoided. [ABSTRACT FROM AUTHOR]

• Instant correlation between super-early age stiffness of 3D printable composite and EMI signatures was established. • An optimization method for printing process based on EMI detection is proposed. • PZT transducers were implemented to monitor the damage evolution of printed samples exposed to orthogonal loadings. This study is a pilot exploration to develop rigorous, green, intellectualized approach for optimal controlling the 3D concrete printing. The mechanical performances of 3D printed samples during super-early age, early age, and hardened state are tested and monitored using piezoelectric zirconate titanate (PZT) patches. EMI sensing technique is applied to quantify stiffness gain of printed concrete to evaluate the structural build-up behaviour by establishing the instant correlation between the stiffness of concrete and the EMI signatures. An optimization method for printing process based on EMI detection is proposed. In this way, the PZT signals can be feedback to the digital control system of printer in real time to adjust the printing setting. Instant intellectualization for the 3D printing technique is then realized and the buildability of the printed concrete is expected to be improved. The different early age properties of both printed and casted composites are elaborated. Thereafter, changes of frequency and amplitude in the conductance spectrum acquired by mounted PZT patches are employed to characterize and quantify the mechanical behaviours of the 3D printed samples exposed to orthogonal loadings, which contribute to the understanding of damage accumulation and failure process of concrete materials. [ABSTRACT FROM AUTHOR]