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Offshore wind power has been an important force to promote energy transformation. To build an advanced offshore wind farm, wind turbine selection requires the decision maker to explore new relevant criteria and evaluate alternatives with respect to decision criteria with assigning importance weightings to the criteria. In this paper, we devise a novel hybrid multi-criteria decision-making (MCDM) approach for offshore wind turbine selection by reconstructing analytic network process (ANP) and entropy-weight method (EWM). Based on the assigned weightings for ANP and EWM, the best alternative can be selected. For the decision-making model, five main criteria are specifically subdivided into 22 sub-criteria. The method is then applied to deal with the quantitative and qualitative inputs and the interrelation of criteria as arising from decision-making process. The results show that the proposed method can effectively select the optimal one from four different types of alternative offshore wind turbines.

A series of new halogen-free dicationic ionic liquids (ILs) with different alkyl chain lengths were prepared, and the relationship between the alkyl chain length, physicochemical and tribological properties of ILs, and their role as neat lubricant for steel-steel friction pairs, was investigated. Evaluation of stability during hydrolysis and copper strip corrosion test results show that synthetic ILs are stable and not corrosive to metal contacts, due to the halogen-free anions. The friction and wear test results indicate that ILs with long alkyl chains have excellent friction-reducing and anti-wear properties, especially at high temperatures. Based on the surface three-dimensional (3D) profiles, electrical contact resistance, scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and the X-ray photoelectron spectrometry (XPS) analysis of the worn surfaces of steel discs, we can conclude that the efficiency of ILs is due to the formation of high quality tribofilms that consist of both tribochemical reaction and ordered absorption films.

Multimode fiber (MMF) based endoscopy could reach high resolution and is fine enough for vivo imaging. However, the received images are speckles due to the mode crosstalk and sensitivity to environment of MMF, which makes image reconstruction the main challenge. We propose to use pre-trained autoencoder for image reconstruction from speckles to original images, which shows high performance and fast convergence speed. The network architecture includes two parts, i.e ., encoder and decoder. In the first step, we pre-train the network to initialize the parameters of the decoder. In the second step, the network can learn the mapping relation between speckle patterns and original images. We conduct experiment of transmitting over one-meter MMF with 50- $\mu \text{m}$ -core to verify this method. Structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and mean square error (MSE) are measured to evaluate the performance. Compared with U-net, the SSIM increases by 11% with pre-trained autoencoder. Moreover, the training of pre-trained autoencoder is both fast and steady.

The Internet of Things (IoT) is a new technology rapidly developed in various fields in recent years. With the continuous application of the IoT technology in production and life, the network security problem of IoT is increasingly prominent. In order to meet the challenges brought by the development of IoT technology, this paper focuses on network security situational awareness. The network security situation awareness is basic of IoT network security. Situation prediction of network security is a kind of time series forecasting problem in essence. So it is necessary to construct a modification function that is suitable for time series data to revise the kernel function of traditional support vector machine (SVM). An improved network security situation awareness model for IoT is proposed in this paper. The sequence kernel support vector machine is obtained and the particle swarm optimization (PSO) method is used to optimize related parameters. It proves that the method is feasible by collecting the boundary data of a university campus IoT network. Finally, a comparison with the PSO-SVM is made to prove the effectiveness of this method in improving the accuracy of network security situation prediction of IoT. The experimental results show that PSO-time series kernel support vector machine is better than the PSO-Gauss kernel support vector machine in network security situation prediction. The application of the Hadoop platform also enhances the efficiency of data processing.

This paper focuses on the effect of repeated loading and unloading conditions on cement sheaths during staged fracturing. Triaxial compression and cyclic loading/unloading tests were designed for cement at room temperature and elevated temperatures of 95 °C and 130 °C. Based on the mechanical characteristics of cyclic loading and unloading, in the staged fracturing simulation process, numerical simulation of the cement sheath in both shallow and deep formations was performed. The following observations were made. (1) The elastic modulus of the cement was high at room temperature but lower under 95 °C and 130 °C. However, the deformation performance was greatly improved at higher temperatures, showing significant mechanical properties of an elastoplastic material. (2) In the cyclic loading test, the residual strain of the cement increased as the number of cycles at room temperature increased, and the unloading secant modulus was larger than that of the initial loading segment. The cement cumulative residual strain was larger under a higher temperature, and there was a significant “rebound hysteresis” in the unloading curve; the unloading secant modulus value also increased. The numerical simulation of staged fracturing produced the following conclusions. (1) The cement sheath in the shallow formation undergoing fracturing was at risk of circumferential tensile failure, and the severity of tensile failure increased with an increasing number of fracturing stages. (2) The cement sheath in the deep formation was at risk of plastic failure under compression, and the cement sheath gradually entered the plastic yield state as the number of fracturing stages increased.

A new strategy for preparing Raney nickel catalyst was proposed, which could significantly improve the catalytic activity of the catalyst in the methanation of syngas to substitute natural gas in a continuous flow microreactor. The new preparation strategy includes a hydrochloric acid solution quenching process interpolated between two alkali leaching steps. Raney Ni III catalyst showed the best activity with a CO conversion of almost 100% and a CH4 selectivity of 98% at 548 K under 1.0 MPa with the molar ratio of 3H2:1CO and a gas hourly space velocity of 10000 h−1. The catalysts were characterized by N2 adsorption–desorption, scanning electron microscopy, X-ray powder diffraction, high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy and temperature-programmed desorption of hydrogen. The results of systematic characterization and catalytic activity evaluation show that the formation of 3Ni(OH)2·2H2O in the catalyst is beneficial to the adsorption and activation of hydrogen and the C=O bond, which greatly improves the activity of Raney nickel III in methanation of syngas. Meanwhile, high specific surface area leads to more active sites on the catalyst surface, which is also conducive to the improvement in catalyst activity.

The density functional theory method is employed to systematically explore the mechanism of syngas methanation on the Ni4/MCM-41 catalyst surface. The calculation results show that the optimal pathway of CH4 formation is CO + H → CHO + H → CH2O + H → CH3O → CH3 + H → CH4 with the rate-determining step of CH3O direct dissociation. Because the activation energy for the direct dissociation of CH3O species is much lower than that for the CH3OH formation (198.6 vs 264.8 kJ mol−1), there is almost no by-product CH3OH that appeared in the products of the syngas methanation over the Ni4/MCM-41 catalyst. Compared with other conventional nickel-based methanation catalysts, Ni4/MCM-41 catalyst is an excellent methanation catalyst with high selectivity of CH4.

Two oil-soluble ionic liquids N, N-trimethyl-N-hexadecyl ammonium bis(2-ethylhexyl) phosphate (NP-16))and 1,2-bis-N, N-dimethyl-N-cetylammonium bis (2-ethylhexyl) phosphate (NP-16-2-16) have been synthesized and investigated as a potential friction reduction and anti-wear lubricant additive with anti-corrosion properties. The results indicate that the addition of 1.0 wt % NP-16 into PAO10 can significantly reduce friction coefficient and improve its anti-wear performance under RT and 100 °C. The performance is obviously better than that of traditional additives ZDDP and tricresyl phosphate. PAO10 + 1.0 wt % NP-16 even outperformed the PAO10 with about 40% lower friction and 2 orders of magnitude less wear. The analysis results of SEM, EDS and XPS show that an FePO4 or nitrogen-containing tribofilm is formed on the friction interface when NP-16 and NP-16-2-16 are selected as additives, which play a key role in reducing friction and wear.

Both magnetic flux leakage (MFL) and magnetic field distortion (MFD) techniques are promising methods for surface defect detection in ferromagnetic components. The two techniques are based on different physical principles. However, their defect sizing and shape reconstruction abilities are seldom comparatively explored. In this study, finite element simulations and experiments were performed to achieve magnetic scanning imaging of a defective plate with both MFD and MFL techniques. First, the curves of voltage extracted from the lines crossing the center of cylindrical-hole defect (CHD) were used to evaluate the performance of several feature parameters in sizing the diameter and the depth of CHD. Second, the profiles of the normalized magnetic scanning imaging results were analyzed with a threshold plane to evaluate the abilities of MFD and MFL on reconstructing the shape of 8-shaped and cross-type through wall defects. Under the condition that the Hall device for measuring both the normal component of MFL and MFD has same lift-off distance as 1 mm, the MFD technique showed the advantages in defect shape reconstruction at the cost of available detection depth as compared with MFL techniques.

Morphing aircraft structures usually introduce greater compliance into aerodynamic sections, and therefore will affect the aeroelasticity with the potential risk of increased flutter. A low-fidelity model of an active camber morphing wing and its aeroelastic model are developed in order to investigate the potential critical speed by exploiting its chord-wise dimension and flexibility. Such a model may be used for conceptual design, where low fidelity models are used to explore and optimise a wide range of configurations. The morphing camber concept is implemented using a continuous representation of a two-segment structure with a rigid segment and a deformable part. The aeroelastic model is developed based on both steady and unsteady aerodynamic models, so that different parameters can be easily modified to examine changes in the flutter solutions. Of particular interest are the ratio of the morphing segment length to the chord, and its relative stiffness, as such morphing camber is potential operated using the deformable part as a flap. By comparing the results of the quasi-steady and unsteady aerodynamic models, it is shown that the quasi-steady aerodynamic model gives a more conservative prediction of the flutter speed. In addition, responses in phase space are simulated to show the fundamental aeroelastic behaviour of the morphing camber wing. It is also shown that the active compliant segment can be used to stabilise the morphing aircraft by using feedback control. This paper provides a system-level insight through mathematical modelling, parameter analysis and feedback control into dynamics applications of morphing camber.

Coronavirus disease 2019 (COVID-19) is a highly contagious infectious disease. Similar to H7N9 infection, pneumonia and cytokine storm are typical clinical manifestations of COVID-19. Our previous studies found that H7N9 patients had intestinal dysbiosis. However, the relationship between the gut microbiome and COVID-19 has not been determined. This study recruited a cohort of 57 patients with either general (n = 20), severe (n = 19), or critical (n = 18) disease. The objective of this study was to investigate changes in the abundance of ten predominant intestinal bacterial groups in COVID-19 patients using quantitative polymerase chain reaction (q-PCR), and to establish a correlation between these bacterial groups and clinical indicators of pneumonia in these patients. The results indicated that dysbiosis occurred in COVID-19 patients and changes in the gut microbial community were associated with disease severity and hematological parameters. The abundance of butyrate-producing bacteria, such as Faecalibacterium prausnitzii, Clostridium butyricum, Clostridium leptum, and Eubacterium rectale, decreased significantly, and this shift in bacterial community may help discriminate critical patients from general and severe patients. Moreover, the number of common opportunistic pathogens Enterococcus (Ec) and Enterobacteriaceae (E) increased, especially in critically ill patients with poor prognosis. The results suggest that these bacterial groups can serve as diagnostic biomarkers for COVID-19, and that the Ec/E ratio can be used to predict death in critically ill patients.

In this paper we study a plane wave generator (PWG) under various excitation methods. By optimizing the amplitude and phase of the weighting coefficient of each array element, the plane wave generator superimposes the spherical waves radiated by all the array elements onto each other to synthesize the plane wave. The weighting coefficients of the array elements are calculated using three methods, i.e., the least square (LS), singular value decomposition (SVD) and sparse optimization algorithms, that are most suitable for the application. The maximum phase error and amplitude error generated by the considered algorithms in the test plane are compared by simulations and their performance are analyzed.

In the synthesis of metal nanoclusters (NCs), small molecules are widely used as capping ligands and reducing agents. However, metal NCs are usually sensitive to solvents and aerobic atmosphere and are also prone to oxidation; thus, their photonic properties deteriorate. In this work, 4-aminothiophenol (PATP) was used as a ligand to prepare Cu NCs and their fluorescence, morphology, and electronic states were characterized. The as-prepared Cu NCs could be dispersed in aqueous media and their fluorescence was sensitive to Hg2+. It was found that after mixing Cu NCs with 2,3-dialdehyde cellulose (DAC) prepared via oxidation by NaIO4, the fluorescence stability of Cu NCs could be enhanced from overnight to 7 days. This might be due to the reaction of the amine group of PATP with the aldehyde group of DAC to form Schiff bases, which are then reduced to form more stable C–N bonds via reduction by NaBH4. Therefore, Cu NCs were attached to a rigid skeleton and their stability increased. Furthermore, the composite of Cu NCs mixed with DAC could be used to prepare colorimetric cards for the rapid detection of Hg2+ with high sensitivity.

As pure lubricants, ILs performed very well by forming the classical self-assembly bilayer at the sliding interface. The interface mechanism is still not clear in a very polar, e.g., water-based lubricating system. In this work, the interfacial absorption and tribological behavior of carboxylic alkanolamine ionic liquids (CAILs) serving as aqueous lubricating additives were studied by applying positive and negative potentials on the friction pair, accompanied by the comprehensive discussion of data from critical micelle concentration, quartz crystal microbalance, ECR, and MD results. The results reveal that the adsorption behavior, unexpectedly, was affected by the high polarity of H2O, where a less dense double-layer structure is observed at the interface by model imitation. Conversely, the monomolecular adsorption layer constructed electrostatically between the polar head (-COO-) and the positive base dominates the tribofilm. Meanwhile, the cations are partially accumulating around anions in the presence of static electricity, which does not form a neat and dense one-to-one corresponding cation-anion pair. In the solution, the IL maintains a state of dissociation and minor agglomeration. Furthermore, an increase in alkyl chains contributes to the thickness of the protective film generated by CAILs on the sliding asperity. Eventually, the synergistic effect from physical adsorption and the tribochemical reaction is responsible for excellent lubricity and antiwear performance of CAILs.

In recent years, the popularity of depth sensors and 3D scanners has led to a rapid development of 3D point clouds. Semantic segmentation of point cloud, as a key step in understanding 3D scenes, has attracted extensive attention of researchers. Recent advances in this topic are dominantly led by deep learning-based methods. In this paper, we provide a survey covering various aspects ranging from indirect segmentation to direct segmentation. Firstly, we review methods of indirect segmentation based on multi-views and voxel grids, as well as direct segmentation methods from different perspectives including point ordering, multi-scale, feature fusion and fusion of graph convolutional neural network (GCNN). Then, the common datasets for point cloud segmentation are exposed to help researchers choose which one is the most suitable for their tasks. Following that, we devote a part of the paper to analyze the quantitative results of these methods. Finally, the development trend of point cloud semantic segmentation technology is prospected.

Carbon nanotubes (CNTs) have been the focus of much research due to their excellent lubricity and anti-wear properties. However, when they are used as lubricating oil additives, they tend to agglomerate and precipitate, because of which achieving good dispersion stability is a significant problem. This manuscript reports a new strategy to successfully resolve the problem of poor dispersion stability of CNTs in the lubricating material 12-hydroxystearic acid (12-HSA) supramolecular gel. On the one hand, the carbon nanotubes are trapped in the network of the supramolecular gel which greatly reduces its reaggregation in the 500SN base oil. On the other hand, the carbon nanotubes significantly improved the thermal, mechanical and tribological properties of the supramolecular gel. For example, the decomposition temperature is increased by 30 °C as the 500SN base oil molecules are trapped in the 3-D network of supramolecules. The viscoelasticity of the supramolecular gel is improved when the carbon nanotubes are used as additives. The results also show that a small quantity of modified carbon nanotubes as additives can significantly reduce friction and wear. And the CNTs and acidified carbon nanotubes (CNTHs) can provide the same friction coefficient as both of them are trapped in the 3-D network of the quasi-solid state 12-HSA soft-nanocomposite. In addition, we performed experiments and molecular dynamics simulations to explore the microstructure and self-assembly mechanism of the soft-nanocomposite lubricant. The soft-nanocomposite lubricant not only prolonged the useful life of machinery, but also reduced the waste of resources, which is significant in sustainable development.

A new core-shell structured nanomaterial based on Fe3O4 nanoparticles and 2,3-dialdehyde nanocrystalline cellulose (DAC) coating and its high efficiency in the preconcentration of glycoproteins were described in this work. DAC was obtained after the periodate oxidation of nanocrystalline cellulose to form aldehyde groups; then, Fe3O4 nanoparticles were coated with DAC, which were further attached to 4-aminophenylboronic acid (PBA) to form PBA-functionalized magnetic core-shell structured materials (Fe3O4@DAC-PBA). The oxidation of cellulose and the production of sufficient amounts of aldehyde group sites were essential for the preparation of Fe3O4@DAC-PBA used for the affinity adsorption of glycoproteins because the aldehyde groups on DAC allowed DAC to attach to the Fe3O4 nanoparticles and bind with PBA, which was active in forming a complex with the glyco sites in glycoproteins. Moreover, the preconcentration properties of Fe3O4@DAC-PBA through PBA adsorption can be pH-triggered without the disassembly of the structures; thus, the developed Fe3O4@DAC-PBA can be efficiently prepared to provide a promising affinity material for the affinity adsorption and purification of glycoproteins.

Hydrological applications rely on the availability and quality of precipitation products, especially model- and satellite-based products for use in areas without ground measurements. It is known that the quality of model- and satellite-based precipitation products is complementary: model-based products exhibit high quality during cold seasons while satellite-based products are better during warm seasons. To explore the complementary behavior of the quality of the precipitation products, this study uses 2-m air temperature as auxiliary information to evaluate high-resolution (0.1°/hourly) precipitation estimates from the Weather Research and Forecasting (WRF) Model and from the version 5 Integrated Multisatellite Retrievals for GPM (IMERG) algorithm (i.e., early and final runs). The products are evaluated relative to the reference NCEP Stage IV precipitation estimates over the central United States during August 2015–July 2017. Results show that the IMERG final-run estimates are nearly unbiased, while the IMERG early-run and the WRF estimates are positively biased. The WRF estimates exhibit high correlations with the reference data when the temperature falls below 280 K. The IMERG estimates, both early and final runs, do so when the temperature exceeds 280 K. Moreover, the complementary behavior of the WRF and the IMERG products conditioned on air temperature does not vary with either season or location.

A method of effervescent-assisted dispersive liquid–liquid microextraction based on the solidification of a floating organic droplet is reported. This approach was used to measure the fungicides myclobutanil, tebuconazole and epoxiconazole in vinegar and juice. Acidic vinegar and juice reacted with the carbonate to produce effervescence in situ, which then promoted contact of the sample with the extraction solvent. The 1-dodecanol extraction solvent helped solidify the floating organic droplets and could be fully dispersed by effervescence. The extraction solvent, salt, carbonate, and extraction time were optimised. The optimal conditions were 200 μL of 1-dodecanol, 100 mg of sodium chloride, 50 mg of sodium bicarbonate, and 30 s of extraction time. The proposed method has good linearity between 10 and 1000 ng mL−1. Recoveries were between 70.4% and 103.1% in different vinegar and juice samples. This method was successfully used to measure fungicides in vinegar and juice. This system is simple, fast and environmentally friendly.

Linear-chirp-Golay (LCG)-coded excitation combined with pulse compression is proposed in this paper to improve the time resolution and suppress sidelobe in ultrasonic testing. The LCG-coded excitation is binary complementary pair Golay signal with linear-chirp signal applied on every sub pulse. Compared with conventional excitation which is a common ultrasonic testing method using a brief narrow pulse as exciting signal, the performances of LCG-coded excitation, in terms of time resolution improvement and sidelobe suppression, are studied via numerical and experimental investigations. The numerical simulations are implemented using Matlab K-wave toolbox. It is seen from the simulation results that time resolution of LCG excitation is 35.5% higher and peak sidelobe level (PSL) is 57.6 dB lower than linear-chirp excitation with 2.4 MHz chirp bandwidth and 3 μs time duration. In the B-scan experiment, time resolution of LCG excitation is higher and PSL is lower than conventional brief pulse excitatio...

Multistable phenomenon have long been used in mechanism design. In this paper a subset\ud of unstable configurations of a smart structure model will be used to develop energyefficient\ud schemes to reconfigure the structure. This new concept for reconfiguration uses\ud heteroclinic connections to transition the structure between different unstable equalenergy\ud states. In an ideal structure model zero net energy input is required for the recon-\ud figuration, compared to transitions between stable equilibria across a potential barrier. A\ud simple smart structure model is firstly used to identify sets of equal-energy unstable con-\ud figurations using dynamical systems theory. Dissipation is then added to be more representative\ud of a practical structure. A range of strategies are then used to reconfigure the\ud smart structure using heteroclinic connections with different approaches to handle\ud dissipation.

A passive energy balancing concept for linear actuation is investigated in the current work by adopting a negative stiffness mechanism. The proposed negative stiffness mechanism uses a pre-tensioned spring to produce a passive torque and therefore to transfer the passive torque through a crankshaft for linear motion. The proposed passive energy balancing design is supposed to be applied in a morphing wingtip, of which the shape change comes from the elastic deformation of the morphing structure. A significant amount of linear actuation force can be required to deform the structure, and therefore it is important to reduce the required force and the consumed energy by adopting the passive energy balancing design. The kinematics of the negative stiffness mechanism is developed to satisfy the required linear motion and its geometry is then optimised to reduce the energy requirements. The performance of the optimised negative stiffness mechanism is evaluated through the net force and the total required energy, which shows the potential of the design in the morphing wingtip application.

A novel meta-material has been designed and implemented into a rotor blade to enhance aerodynamic efficiency by achieving a passive twist during rotation. The twist is induced by bend-twist coupling exhibited in the meta-material, which is created to possess anisotropic elastic properties at the bulk level. A concept design of a rectangular blade spar is proposed where the metamaterial is used as the core material to induce twist. Using finite element analysis(FEA) we demonstrate how the bend-twist property of the blade spar is governed by cell geometries of the core material. The twist is activated by a lagwise bending moment generated from a movable mass at the blade tip due to off-centre centrifugal forces. The relationship between the twist, mass location and rotational speed has been explored. Moreover, it was found that the bend-twist property achieved by the proposed blade spar is more effective compared to that of an anisotropic thin-walled composite beam.

Extensive use of organophosphorus pesticides (OPs) in crop protection has aroused worldwidely great concern about safety and the detection of OPs is of great significance to food safety and human health. In this work, peptides attached with tetraphenylethylene (TPE) molecule were synthesized to from an aggregation-induced emission fluorescent probe (TPE-Peptide) for the determination of OPs. The working mechanism was as follows: in presence of OPs, OPs would react with active site serine in the peptide sequence via covalent bond and adducts were formed between OPs and the peptides; once formed, the adducts accelerated the aggregation of peptides, thus inducing strong emission of TPE-Peptide probe. So the adducts formation and the enhanced emission of the TPE-Peptide probe were the key factors for the OPs' sensing. Herein, the adducts formed between OPs and TPE-Peptide probe, the aggregated peptide fibrils were characterized by fluorescence, mass spectrometry, transmission electron microscopy, dynamic light scattering, atomic force microscopy, circular dichroism spectra and confocal fluorescence microscopy etc. This TPE-Peptide probe displayed highly sensitive fluorescence response where OPs' concentrations ranged from 1 to 100 μM with the limit of detection 0.6 μM and also showed selectivity.

Three-dimensional (3D) printing is a promising method to prepare scaffolds for tissue regeneration. Collagen and chitosan composites are superior materials for tissue engineering scaffold but rarely printed due to their poor printability. Here, we prepared a series of tunable hybrid collagen/chitosan bioinks with significantly improved printability through hydrogen bond interaction and printed them into scaffolds by carefully controlling the temperature. Rheological tests proved the printable bioinks had sound shear thinning behavior, dramatical viscosity variation with temperature, and the gelation temperature from 7 to 10 °C. Chitosan could decrease the swelling ratio of the printed scaffolds, while their degradation rate increased with collagen proportion and the values of Young's modulus and tensile strength increased with chitosan proportion. Moreover, the scaffolds containing 2% (m/v) collagen and 2% (m/v) chitosan had a homogeneous and compact honeycomb-like structure, demonstrating the strengthening effect of chitosan. Cell viability assay presented vigorous cell growth on the surface of scaffolds, meanwhile, live cells were also found inside and at the bottom of the scaffolds, indicating the migration of cells. Therefore, chitosan can improve the printability of collagen and the hybrid collagen/chitosan bioinks can be printed into scaffolds with regulated properties, thus can fit different applications in tissue engineering.

Perfluoropolyether (PFPE) remains a highly desirable synthetic fluid for industries like aerospace and special machinery lubricants owing to its excellent chemical constancy, radiation and corrosion resistance, lubricating properties. However, like most phenomenal substances, even PFPE exhibits some shortcomings like low surface tension, which produces creeping and leakage from friction interface while in use. This manuscript reports a new method to rectify the creeping demonstrated by the PFPE lubricant, which is deemed to utilize the confinement effect of the supramolecular gel. A novel fluorine-functionalized gelator (BHD) which can gelatinize PFPE, was successfully synthesized. The results of molecular dynamics and experiment reveal that BHD compound self-assembles into spherical by interactions among the gelators and PFPE. The event of thermocapillary migration and creep behavior of the PFPE gel lubricants acting on the steel, while employing temperature gradients and exposure to the irradiation of Atomic Oxygen (AO) and Ultraviolet (UV) for 4 h was thoroughly investigated. The results reveal that the gelation of PFPE oils minimizes the thermocapillary migration of PFPE and averts the creeping from occurring at the sliding interface. The tribological representations of supramolecular gels ensure excellent lubricity and anti-wear performances under some critical environments, including ranging from high to low temperatures and irradiation in vacuum conditions. Furthermore, the supramolecular gels register that the PFPE oils are slow-release lubricants enabled by their complicated reassembling network, manifesting stronger anti-irradiation properties. These deductions make a strong case for this gel lubricant to replace PFPE lubricants administered for the lubrication of aerospace machinery components.

In this paper, the effect of various parameters of a specific rotor blade cross-section on the effectiveness of a twist morphing concept is investigated. Then, by considering different constraints, a cross-section consistent with this morphing concept with high lag-twist coupling and low extension-twist, is developed. This lag bending-torsion coupling is used to change the twist of the blade during the flight, while the high values of extension-twist coupling is avoided. To this end, a concentrated mass is added to the blade, where its chordwise location varies in flight. When the mass moves in the chordwise direction, a local lag bending is introduced into the blade. This in-plane bending moment then changes the blade twist distribution through lag-twist coupling induced through stiffness tailoring in the blade cross-section. Therefore, this coupling plays an important role in this morphing concept. The one-dimensional dynamics of the blade is modelled by using the geometrically exact fully intrinsic bean equations while the 2D cross-sectional stiffness values are determined by using the VABS software. First, a blade which resembles the BO-105 main rotor blade in the fundamental frequencies is designed. Then, the effect of various parameters of the cross-section on the fundamental frequencies, the lag-twist coupling, and the extension-twist coupling are determined. It is found that the skin of the spar has the highest contribution to both the extension-twist and the lag-twist coupling. Finally, a cross-section compatible with the proposed morphing concept is designed and it is demonstrated that the twist of the blade may be changed significantly.

In this paper, a new concept for morphing composite blades is proposed, and how this concept changes the twist distribution of the blade is explained. A change in the blade twist is obtained by add...

The energy balancing concept seeks to reduce actuation requirements for a morphing structure by strategically locating negative stiffness devices to tailor the required deployment forces and moments. One such device is the spiral pulley negative stiffness mechanism. This uses a cable connected with a pre-tension spring to convert the decreasing spring force into the increasing balanced torque. The kinematics of the spiral pulley is first developed for bidirectional actuation, and its geometry is then optimized by employing an energy conversion efficiency function. The performance of the optimized bidirectional spiral pulley is then evaluated through the net torque, the total required energy, and energy conversion efficiency. Then, an additional test rig tests the bidirectional negative stiffness property and compares the characteristics with the corresponding analytical result. Exploiting the negative stiffness mechanism is of significant interest not only in the field of morphing aircraft but also in many other energy and power reduction applications.

A new concept of an integrated bidirectional torsional negative stiffness mechanism is introduced which allows for passive energy balancing of mechanical systems by reducing actuation requirements and improving energy efficiency. This novel design is a modular device, is bidirectional and is easily integrated and customised for different applications. The energy balance concept is achieved by employing a negative stiffness system to couple with a positive stiffness system of the mechanical system to create a zero stiffness system which can be driven with lower energy requirements. The bidirectional torsional negative stiffness mechanism proposed here uses a series of pre-compressed springs around a bidirectional torque shaft to convert decreasing force in the springs into increasing torque output through geometric reconfiguration to generate the negative stiffness characteristic. The kinematics of the negative stiffness mechanism were derived and a physical model was assembled from LEGO® components for validation. An analytical model was developed for prediction and the numerical results showed that a satisfactory performance can be generated to match the torque requirements. An experimental demonstrator was then built and tested to verify the predictions from the analysis. To show the impact of the energy balancing concept on actuator efficiency, a representative case study is made of a tendon-driven morphing active camber mechanism. The performance of the optimised bidirectional negative stiffness device is investigated to shows an improvement by the kinematics tailoring.

Inkjet printing technology is widely used in the manufacture of conformal structures, such as load-bearing antennas or frequency-selective surface radomes. It is particularly promising for preparing conductive patterns on non-developable surfaces. Existing printing technologies employ a single nozzle and a five-axis linkage technique for printing, which is time-consuming. In this study, a conformal plane printing technology based on the arrayed nozzle was developed to prepare conductive patterns on a non-developable surface. The technique actualizes fast printing of passive circuits on a conformal surface, such as a microstrip antenna. Compared to printing techniques employing a single nozzle, the proposed method greatly improves the printing efficiency on conformal surfaces. Specifically, we first developed a model for the driver waveforms and the printing injection parameters via simulation. Subsequently, the accuracy of the computational fluid dynamic simulation results was validated by comparing them with the experimental measurements of droplet trajectory captured using a camera. Next, a droplet spreading model was established, considering energy conservation principles. Finally, a conformal surface printing technology using arrayed nozzles was developed based on the injection parameter and droplet spreading models. The effectiveness and feasibility of the proposed printing method were further validated via simulation and experimental tests of return loss.

With the increasingly serious environmental pollution and energy issues, water-based lubricating materials will gradually replace oil-based lubricating materials in some specific applications, which has become a trend. As a water-soluble lubricating additive, the synthesized proton-type ionic liquids (PILs) have the advantages of simple synthesis, good solubility stability, and excellent corrosion resistance properties, providing a method to better solve the problems of traditional water-based additives. The physical-chemical properties and lubrication functions of additives were characterized by foam corrosion test and tribological trials, with the detailed exploration of their lubricating mechanism obtained from QCM, TEM, TOF-SIMS, XPS and MD analysis. The results show that PILs display excellent friction-reducing and anti-wear performances, and improve the carrying capacity for water, which is mainly attributed to the formed tribofilm on the friction surface. The tribofilm is probably triggered by ions pair adsorption on the substrate surfaces, equipping with a typical bilayer structure self-assembly between two convexs. When it worked on the interface, a double layer structure is formed by the way of self-assembly, resulting in the formation of a continuous boundary protective film induced by tribochemical reaction, which can effectively reduce the shear damping during friction. Torque testing system results show that PILs have the smaller torque values, indicating their better lubricating performance in the small-scale platform test, which can make it to be used as a potential additive with excellent properties in water-based cutting fluids.

Action recognition is one significant yet challenging task in computer vision. Recent methods mainly model an end-to-end one-stage non-deep or deep learning networks to distinguish different action categories. In this paper we introduce one novel hierarchical action classification framework: Unlike existing one-stage recognition models, the proposed work improves the recognition accuracy by: 1) developing a hierarchical coarse-to-fine action classification framework by dividing the recognition processing into two stages: coarse- grained classification and fine-grained classification, and 2) representing actions in different stages with different granularity features representation: global features are utilized for coarse classifiers while more body parts patterns for fine-grained classifiers are aggregated. Experiments on two widely-tested benchmark datasets show that our method can achieve state-of-the-art or competitive performance compared with existing results using one-stage models, with advantages regarding the recognition accuracy and robustness.

Using in thermal load dominant mode will restrict the flexible output of the micro-combustion engine for the combined heat and power supply system (CCHP), this paper established a joint model of multi-energy flow micro-grid for intelligent community combined with the time-sharing price response and compression chiller. The mathematical model of the maximum integrated operating income of the system, which is based on the installation of the compression chiller to decouple the system cooling and consider the influence of the time-sharing price on user's electrical habits. And the Shuffled Frog Leaping Algorithm (SFLA) is used to optimize the cooling load model after the user load response. The results show that the SFLA algorithm can obtain the faster global optimal solution and the better fitness value of the model.

The energy balancing concept seeks to reduce actuation requirements for a morphing structure by strategically locating negative stiffness devices to tailor the required deployment forces and moments. One such device is the spiral pulley negative stiffness mechanism. This uses a cable connected with a pre-tension spring to covert decreasing spring force into increasing balanced torque. The kinematics of the spiral pulley are firstly developed and its geometry is then optimised by employing an energy conversion efficiency function. The performance of the optimised spiral pulley is then evaluated through the net torque, the total required energy and energy conversion efficiency. An experiment demonstrates the negative stiffness property of the mechanism and compares its characteristics with the analytical result. Exploiting the negative stiffness mechanism has a significant interest in not only the field of morphing aircraft but many other power reduction applications.an increasing output torque. The kinematics of the spiral pulley are firstly developed and its geometry is then optimised by employing an energy conversion efficiency function. The performance of the optimised spiral pulley is then evaluated through the net torque, the total required energy and energy conversion efficiency. An experiment demonstrates the negative stiffness property of the mechanism and compares its characteristics with the analytical result. Exploiting the negative stiffness mechanism has a significant interest in not only the field of morphing aircraft but also many other energy and power reduction applications.

In order to improve the measurement accuracy of the laser displacement sensor, the laser triangulation displacement measuring system is established. The spot subdivision location algorithms of the system are studied, such as the Gaussian curve fitting, traditional gray weighted centroid and gray square weighted centroid. First, according to the principle of laser triangulation, the displacement measuring system is built. Then, objects are moved by the high-precision motorized stage, obtaining multiple sets of image data. Next, these data respectively are processed by the above several algorithms to obtain the corresponding coordinates of the laser spot, the system is calibrated respectively. Finally, comparing the displacement of calibration results calculating with the actual displacement. The results show that: those data that are processed by the gray square weighted centroid are used to calibrate , calculating the minimum error, and is 71.1 μm. It concludes that gray square weighted centroid is an ideal location segmentation method, which is not only simple and easy to implement, but also has a higher positioning accuracy.

Since the coherent noise affected the quality of the Fizeau’s interferograms in the large aperture, the coherence of the beam was changed by rotated diffuser to reduce the noise of the interfering system. The relationships between the frequency of the rotated diffuser, the contrast of the fringes and the SNR of the system were simulated. Then, the control parameters of rotated diffuser would be required in the optimum interference fringe. The interference images were obtained under different control parameters, and the fringe contrast and system SNR of each image were analyzed. The results showed that the contrast can be reduced by choosing the proper frequency of the rotated diffuser in a certain extent, but the SNR can be improved effectively and it was convenient to process the interference image later.

The phenomenon of bi-stable behaviour has been widely used in the structural design, as it can provide large deformation by switching between two stable equilibrium positions. This paper aims to investigate the intrinsic nonlinear dynamic characteristics of an actively controlled bistable beam using a simplified spring-mass model. The dynamic model for an active (heated) SMA wire driven bistable beam is established based on a polynomial constitutive equation to describe the thermomechanical behaviour of the shape memory alloy. The actively controlled bistable beams are designed, fabricated and experimentally tested to achieve the morphing behaviour snapping-through form one position to another. The results obtained from the experimental testing and the theoretical simulation are compared to validate the proposed model. Dynamic behavior of the proposed SMA wires actuated bistable beam under varying external excitation is investigated to show the influence of the thermomechanical loadings. Analysis of the experimental data and simulation results shows that the SMA wires actuated bistable structure can be well-performed for the bistable switching. It also approved that the different behaviours of the system, including periodic responses, complex responses and chaos can be accurately predicted using the proposed simplified model.

Aiming to verify the concept of using heteroclinic connections to reconfigure smart structures, a multistable buckled beam with integrated Shape Memory Alloy (SMA) wires is utilized as a high fidelity model. The Shape Memory Alloy (SMA) wires are resistively heated to provide the actuation force to stabilize the unstable configuration and the transition of the beam from one unstable equilibrium condition to the other. This concept provides a means of reducing the energy requirement for transitions between configurations of the structure, which is an energy-efficient reconfiguration scheme between equal-energy unstable (but actively controlled) equilibria. This letter presents a detailed design of the system, and how the active (heated) SMA wires control the structure stay in unstable configuration and drive the structure to achieve reconfiguration. Exploiting the instability of the smart structure has significant interests in many power reduction applications, including active flow control, reconfiguration of large deployable aerospace structures, and MEMS devices.

A reconfigurable smart surface with multiple equilibria is presented, modelled using discrete point masses and linear springs with geometric nonlinearity. An energy-efficient reconfiguration scheme is then investigated to connect equal-energy unstable (but actively controlled) equilibria. In principle, zero net energy input is required to transition the surface between these unstable states, compared to transitions between stable equilibria across a potential barrier. These transitions between equal-energy unstable states, therefore, form heteroclinic connections in the phase space of the problem. Moreover, the smart surface model developed can be considered as a unit module for a range of applications, including modules which can aggregate together to form larger distributed smart surface systems.

In this paper, the aeroelastic stability of a composite hingeless rotor blade with a chordwise movable mass is investigated. The point mass is located near the tip of the blade and its chordwise location is variable with respect to the elastic axis and can be moved during the flight. This movable mass is added to the blade to actuate the blade twist during flight. By actuating the mass in the chord direction of the blade during the flight, a bending moment which is the result of the centrifugal force of the mass and its offset is induced on the blade. This bending moment induces twist in the blade, due to bend-twist coupling in the composite lamination. The blade is modelled by using the geometrically exact fully intrinsic beam equations along with the variational asymptotic beam sectional analysis. The aerodynamic loads are simulated by using the two-dimensional strip theory combined with a uniform inflow. The nonlinear partial differential aeroelastic equations are discretized by a time-space scheme, and the converged results are compared with those reported in the literature and a very good match is observed. The results show that by positioning the mass near the tip of the blade, and also by using the ply angle of about 30 degree in this configuration, the highest possible twist change is achieved when the mass moves from the leading edge to the trailing edge of the blade. Moreover, the spanwise location of the mass slightly changes the stability boundaries, while the chordwise movement significantly affects the aeroelastic instability.

Since 2008, a regional medical health platform has been built for managing electronic health records of top public hospitals in Shanghai. However, public hospitals often use different names to present a same laboratory examination item (or lab indicator) in this regional platform, which seriously hinders the interconnection and sharing of medical information among hospitals. In this paper, we propose an effective method to standardize the lab indicators using n-gram features and Stacking mechanism. Our proposed method sequentially combines a clustering model and a binary classification model. More specifically, we first cluster the lab indicators based on character uni-gram similarity distances to reduce the alignment scale, and then leverage a binary classification algorithm through Stacking mechanism based on character n-gram similarity features to generate candidate-standard indicator pairs iteratively. Experimental studies on the clinical data collected from eight top public hospitals in Shanghai show that our proposed method achieves a good performance 88.43% in terms of F 1 -score in the final binary classification, which is highly competitive performance compared to baseline methods.