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For near-field acoustic holography, sparse array measurement for cost reduction can result in inaccuracy due to aliasing error. To attenuate it, there are data-driven methods based on artificial intelligence theories. Among these, the JTCSA-NAH method has not adopted measures for robustness enhancement despite its high accuracy in practice. In this work, the influence of measuring noise on JTCSA-NAH is analyzed followed by the principle of adding Gaussian noise for robustness improvement. Based on the relevant prior conditions, the ICCSA-NAH method, which relies on self-identity constraint data working as the Kalman gain is proposed. Subsequently, numerical example and experiment are carried out, and the results show that compared with JTCSA-NAH method, the mean errors of near-field vibration velocity reconstruction are theoretically and experimentally reduced from 15.19% and 23.64% to 6.03% and 12.45%, respectively, by the ICCSA-NAH method, which verifies the feasibility and superiority of the proposed method.

Support structures are widely used in laser powder bed fusion (LPBF) for overhanging features. However, the majority of works carried out on support modeling were to obtain the best trade-off between production time, cost, and accuracy. A notable absence in the existing literature pertains to investigate support structure modeling for optimizing heat dissipation and residual stresses for improving the support structure, thus, enhancing the final part quality. In this study, the effects of the support structure on residual stress were investigated systematically. The influences of the support on residual stress in LPBF sample were categorized into the effect of the constraints and heat conduction area. The rigidity and area of the support structure are used to describe the effect of the support structure on the residual stress. The results showed that the constrain of LPBF samples mainly depends on their inherent characteristics, with limited impact from external constraints. The residual stress in the samples increased as the support area increased. Therefore, when designing the support, priority should be given to reduce its thermal conductivity area. In addition, the hardness of the support added sample were lower than that of the sample without the support, but the hardness distribution is uniform along the deposition height regardless of whether the support is added or not. Therefore, the introduction of support does not result in performance irregularities along the sample height direction.

The rational design and green synthesis of low-cost, robust, and efficient catalysts for the selective oxidation of various alcohols are highly challenging. Herein, we report a fast and solvent-free arc-melting (AM) method to controllably synthesize a semimetallic CoSi alloy catalyst (denoted as AM-CoSi) that is efficient in the base- and solvent-free oxidation of six types of aromatic alcohols. X-ray absorption fine structure analysis, electron paramagnetic resonance spectroscopy, and aberration-corrected high angle annular dark field scanning transmission electron microscopy confirmed the successful synthesis of AM-CoSi with abundant Si vacancies (Siv). The as-prepared CoSi alloy catalysts exhibit an order of magnitude greater activity in the oxidation of a model reactant, benzyl alcohol (BAL) to benzyl benzoate (BBE), compared with their mono-counterparts, and provide 70% yield of BBE, the highest yield reported to date. Experimental results and density functional theory calculations suggest that the CoSi alloy structure improves the BAL conversion and that Si vacancy is the main contributor to the generation of BBE, based on which a potential reaction pathway is rationally proposed. Furthermore, the CoSi alloy maintains high stability and also exhibits high activity in the selective oxidation of various alcohols with different functional groups. This work demonstrates for the first time that semimetallic CoSi alloys can be robust catalysts for the green oxidation of various alcohols and proviedes a vast opportunity for the rational design and application of other semimetal alloy catalysts.

Urban road facilities are typically shared by heterogeneous traffic, such as cars, buses, and bicycles. This paper investigates the car and bicycle traffic at the network level by extending the 3D-MFD model to the car-bicycle network. Statistical 3D-MFDs for the car-bicycle traffic are proposed and empirically estimated for three selected networks in Shanghai. Simulation-based 3D-MFDs are used to determine the network bicycle capacity and validate statistical 3D-MFDs. Estimation results quantify negative marginal effects of car and bicycle density on network car speeds, and confirm the negative effect of bi-modal speed difference on bicycle traffic. When looking into the predicted results of 3D-MFDs, the maximum bi-modal production changes with the accumulation of bicycles, indicating car-bicycle interactions within the network. Few empirical observations are in the optimum operation regime, which indicate the potential of improving the multi-modal networks. Findings of this study can benefit network designs and traffic operations, such as adjusting separation types, implementing stricter bicycle management, and extending bicycle priority in certain areas.

Vehicle restriction has been one of the most popular policies in alleviating traffic congestion and air pollution in mega cities. This paper evaluates the effect of the vehicle restriction policy on urban networks in Shanghai based on multi-source traffic data. First, before–after comparisons are conducted to investigate the impact of the restriction policy on travelers’ adaptation behaviors. A macroscopic fundamental diagram (MFD)-based approach is then applied to analyze the network performance under different levels of restrictions that have been implemented over the years. A spatial regression method is used to account for the spatial and temporal reasons of network performance under different restriction policy stages. Following the first increase of the vehicle restriction time in Shanghai (2015), the network-wide traffic performance significantly improved in the short term (within one month), but the effect was not substantial in the long term (one year). Affected drivers tended to shift either their travel routes or departure time. No significant increase of travelers on the public transport system was found after the extension of the vehicle restriction time. Both urban expressways and surface road networks became less efficient after a further extension of restricted time in 2016. Population distribution, interactions among different modes, distribution of parking facilities, and locations of ramps can account for the increase of congested links at the neighborhood level, which in turn aggravated the imbalance of the entire network after the extension of vehicle restriction time.

Deconstructing Fe-contaminated biomass waste to obtain FeSAC containing FeN4active sites as a photocatalyst to remove antibiotics, which embodies the concept of sustainable development and pollutants control.

Interactions between bicycles and cars have attracted increasing attention during recent years. This paper aims to investigate the impact of bicycle traffic on the macroscopic fundamental diagrams (MFDs) for urban car traffic. A Bicycle Congestion Index (BCI)-based MFD relating network bicycle flow and car flow reductions was constructed. A link-based method was proposed to estimate the MFD, considering the spilling behaviors of bicycles at the link level. The results indicate that the effect of bicycle traffic on car MFD varies with different traffic conditions and network features. Compared with car-only roads, it is more efficient to increase network car flow by installing physically separated facilities and reducing the spilling bicycles. To this end, various traffic management strategies may be applied in Shanghai, such as lifting the ban of cyclists on the central city area, building physically connected facilities, and enforcing stricter operational regulations and management on bicycle traffic.

Quinolones are widely used in the pharmaceutical industry; however, the high residue of these antibiotics has caused serious water quality issues, and their effective removal is still a great challenge. In this work, bimetallic magnetic FexMnycatalysts are prepared by a facile impregnation method and are efficient for photocatalytic removal of five typical quinolone pollutants without oxidant under simulated light irradiation. The fabricated bimetallic magnetic FexMnycatalyst with the Fe3+/Mn2+ratio of 1 : 1 exhibits a large surface area of 122.5 m2g−1, highly porous structure, rich defects and a covalent metal environment. These fabricated semiconductor catalysts can degrade 98.3% of ciprofloxacin (CIP), 96.0% of ofloxacin (OFL), 91.0% of enrofloxacin (ENR), 92.2% of levofloxacin (LEV), and 93.5% of norfloxacin (NOR) in 30 min without using any oxidant. The magnetic FexMnycatalysts can be simply recycled using a magnet and maintain high stability, avoiding complex recycling procedures. Even after five cycles, the degradation rate of CIP was still over 92.0%. The degradation performance is far superior to that of most previously reported candidates. The bimetallic FexMnycatalyst improves the ability to capture sunlight, increases the interface charge transfer rate, and inhibits the recombination of photogenerated electron–hole pairs. In addition, the mechanism and the main intermediates in the photocatalytic degradation of CIP are explored by quenching experiments, electron paramagnetic resonance (EPR) and liquid chromatography-mass spectrometry (LC-MS) analysis. These noble-metal free magnetic FexMnycatalysts provide a promising opportunity for advanced photocatalytic oxidation technology to treat wastewater.

Petroleum and its refined products enter the marine environment during the extraction process, causing serious pollution. Herein, a bifunctional Fe–N2single-atom embedded in nitrogen-doped porous carbon photocatalyst (FC) was fabricated for the efficient removal of marine petroleum pollutants. The combination of highly dispersed Fe–N2active sites, large surface area, high porosity, and good conductivity results in excellent photocatalytic activities. The FC catalyst exhibited a 96.7% degradation rate in the oxidative removal of bisphenol A (BPA) and a 63.4% reduction of Cr(VI) within 1 ​h, whereas the reaction equilibrium rate constants of 0.0132 ​min−1and 0.0505 ​min−1were reached, respectively. FC with good stability and reusability could reach 88.3% and 53.5% removal rate of BPA and Cr(VI) after 5 cycles. Radical quenching experiments and electron spin resonance (ESR) confirmed that ‧OH and e−were the most driving active species for photo-oxidation and reduction, respectively. Besides, the FC catalyst was applied to an actual seawater system and the simulation results showed a good removal rate (82.7% of BPA and 50.9% of Cr(VI) within 1 ​h). The BPA oxidation pathway in the system was proposed and the toxicity of each intermediate was accessed. This work offers a new way to construct single-atom functionalized carbon-based catalysts for marine pollution control.

Detailed heat transfer coefficient distributions are presented for a two-pass square channel with a 180° turn. One wall of the channel has periodically placed rib turbulators and bleed holes. Four different configurations of 90° parallel, 60° parallel, 60° V ribs, and 60° inverted V ribs are studied in conjunction with the effect of bleed holes on the same wall. The surface is coated with a thin layer of thermochromic liquid crystals and a transient test is run to obtain the detailed heat transfer distributions. Detailed distributions show distinctive peaks in heat transfer levels around bleed holes and on rib turbulator tips. The 60° parallel, 60° V, and 60° inverted V ribbed channels produce similar levels of heat transfer enhancement in the first pass. However, the 60° inverted V ribbed channel produces higher enhancement in the second pass. Regional-averaged heat transfer results indicate that a surface with bleed holes provides similar heat transfer enhancement as that for a surface without bleed holes although 20–25% of the inlet mass flow exits through the bleed holes.

Nonlinear dynamic responses of functionally graded graphene-reinforced nanocomposite (FG-GRC) plates in thermal environment are studied in the present work. A modified Halpin-Tsai micromechanics model is applied to evaluate the equivalent material properties of the nanocomposite. Based on von Karman nonlinear strains displacement relationship and the first-order shear deformation plate theory (FSDT), the nonlinear governing equations are derived by Hamilton principle. Galerkin and Runge-Kutta numerical method are employed to obtain the dynamic responses of the FG-GRC plate. Results show the GPLs distribution and temperature have remarkable effects on dynamic responses of a FG-GRC plate.