Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in oper...Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.展开更多
Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pr...Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pressure attractive path of particle assembly can be constructed by the interference between two independent cylindrical Bessel beams,it remains challenging to create two-dimensional(2D)neighboring vortexes using a source array in practical applications.In this paper,a three-step phase-reversal strategy of 2D particle assembly based on the synchronized evolution of a centrosymmetric array of M off-axis acoustic vortexes(OA-AVs)with a preset radial offset is proposed based on a ring array of planar sources.By introducing initial vortex phase differences of-2π/M and+2π/M to the vortex array,low-pressure patterns of an M-sided regular polygon and M-branched star are formed by connecting the vortex cores and the field center before and after the tangent state of adjacent OA-AVs.Center-oriented particle assembly is finally realized by a central AV constructed by coincident in-phase OA-AVs.The capability of particle manipulation in the lateral and radial directions is demonstrated by low-pressure patterns with acoustic radiation forces pointing to the field center during a synchronized central approach.The field evolution is certified by experimental field measurements for OA-AVs with different vo rtex numbers,initial vortex phase differences,and radial offsets using a ring array of 16 planar sources.The feasibility of particle assembly in two dimensions is also verified by the accurate manipulation of four particles using the low-pressure patterns of a four-sided polygon,a four-branched star,and a central AV in experiments.The three-step strategy paves a new way for 2D particle assembly based on the synchronize d evolution of centrosymmetric OA-AVs using a simplified single-sided source array,exhibiting excellent potential for the precise navigation and manipulation of cells and particles in biomedical applications.展开更多
The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identif...The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identification,motion measurement,and assembly of two-species photoluminescence nanoparticles.A laser trapping array simultaneously levitates nitrogen-vacancy(NV)nanodiamonds and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticles.The species of each nanoparticle can be individually identified by measuring the photoluminescence spectrum.We choose the single NV nanodiamond and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle and assemble them into a Janus composite nanoparticle,which integrates the merits of the two components.This work demonstrates the potential advantages of a hybrid optically levitated system.It provides a practicable scheme for the study of macroscopic quantum phenomena and precision measurement,thanks to the spin manipulation or spin-mechanical coupling of an NV diamond and by simultaneously implementing laser refrigeration to the Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle in an optically levitated composite nanoparticle.展开更多
Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied p...Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied performance mainly due to the sluggish oxygen reduction reaction(ORR)kinetics even on state-of-the-art Pt catalyst.Octahedral PtNi nanoparticles(oct-PtNi NPs)with excellent ORR activity in a half-cell have been widely studied,while their performance in membrane electrode assembly(MEA)has much less reported.Herein,we investigated the MEA performance using the carbon supported oct-PtNi NPs(oct-PtNi/C)as the cathode catalyst.Under the mild acid washing condition,the surface Ni atoms of oct-PtNi/C were largely removed,and the performance of the MEA using the acid-leaching oct-PtNi/C(PNC-A)as the cathode catalyst was greatly improved.The maximum power density of the MEA reached 1.0 W·cm^(-2) with the cath-ode Pt loading of 0.2 mg·cm^(-2),which is 15%higher than that using Pt/C as the catalyst.After 30k cycles in the accelerated degradation test(ADT),the MEA using PNC-A as the catalyst showed a performance retention of 82%,higher than that of Pt/C(74%).The results reported here verify the possibility of using PNC-A as an advanced cathode catalyst in PEMFCs,thus enhancing the performance of PEMFCs while lowering the amount of expensive Pt.展开更多
Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of mi...Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of microorganisms in aquatic ecosystems.To understand the influences of ecological floating beds on size-fractionated microorganisms,we investigated the community assembly and nitrogen metabolic characteristics of three size-fractionated microorganism groups in the ecological floating bed area,using 18S rDNA,16S rDNA metabarcoding,and metagenomic sequencing techniques.Firstly,we discovered substantial differences between size-fractionated groups in the diversity and compositions of both microeukaryotic and bacterial communities,as well as the influences of floating beds on specific groups.The floating beds appeared to provide more habitats for heterotrophs and symbiotes while potentially inhibiting the growth of certain phytoplankton(cyanobacteria).Secondly,we observed that microeukaryotic and bacterial communities were predominantly influenced by stochastic and deterministic processes,respectively,and they both exhibited distinct patterns across different size-fractionated groups.Notably,microeukaryotic community assembly demonstrated a greater sensitivity to ecological floating beds,as indicated by an increase in dispersal limitation processes.Finally,the nitrogen metabolism functional genes revealed that microbes associated with large-sized particles played a crucial role in dissimilatory nitrate reduction to ammonium(DNRA)and denitrification processes within the floating bed area,thereby facilitating the removal of excess nitrogen nutrients from the water.In contrast,freeliving microorganisms from small-sized groups were linked mainly to the genes involved in nitrogen assimilation and assimilatory nitrate reduction to ammonium(ANRA)processes.These findings help understand the impact of ecological floating beds on the diversity and functional characteristics of microorganism communities in different size-fractionated groups.展开更多
Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativ...Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage...Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.展开更多
Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antago...Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antagonism between yield-related traits and disease resistance makes yield resistance coordination a major challenge in wheat breeding.The lack of genetic resources combining both disease resistance and high yield constrains the elucidation of underlying resistance-yield trade-off mechanisms,thereby hindering the development of high-yield and disease-resistant wheat cultivars.Remarkably,Yangmai 33(YM33),a notable wheat cultivar with resistance to both powdery mildew and FHB as well as high-yield performance,was recently developed.It offers a unique opportunity to dissect the genomic architecture underlying the coordination between disease resistance and yield.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usu...Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.展开更多
In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed thr...In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed through transient and static simulation.In this work,the theoretical deformation model for riveting assembly is established with round head rivet.The simulation analysis for riveting deformation is carried out with the riveting assembly piece including four rivets,which comparing with the measuring points experiment results of riveting test piece through dealing with the experimental data using the point coordinate transform method and the space line fitting method.Simultaneously,the deformation deviation of the overall thin-wall parts assembly structure is analyzed through finite element simulation;and its results are verified by the measuring experiment for riveting assembly with the deformation deviation of some key points on the thin-wall parts.Through the comparison analysis,it is shown that the simulation results agree well with the experimental results,which proves the correctness and effectiveness of the theoretical analysis,simulation results and the given experiment data processing method.Through the study on the riveting assembly for thin-wall parts,it will provide a theoretical foundation for improving thin-wall parts assembly quality of large antenna in future.展开更多
Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location ...Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout,which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms.At present,the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing.Based on the perception data of intelligent assembly unit of aircraft parts,a regression model of multi-input and multioutput support vector machine with Gauss kernel function as radial basis function is established,and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm(PSO-GA).GA-MSVR,PSO-MSVR and PSOGA-MSVR model are constructed respectively,and their results show that PSOGA-MSVR model has the best performance.Finally,the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method.展开更多
By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-swit...By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.展开更多
Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and dro...Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and drop-drying assembly. The obtained IrNPs and IrSMPs were characterized using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The IrSMPs (or IrNPs) with disc-like shape and irregular shapes were obtained on ITO substrate by direct surface growth method using polyvinylpyrrolidone (PVP) and sodium citrate as different stabilizers, respectively. The reaction time and the injection temperature of reducing agent are found to have great effect on the size and morphology of the surface-grown Ir particles. The disc-like, ellipsoidal, and spherical IrSMPs (or IrNPs) were also synthesized in homogeneous solution in the presence of H3BO3 and Na2B4O7 as assistant-stabilizer. These IrNPs and IrSMPs were used as building blocks to construct nanoparticle assemblies by using a simple drop-drying method. Uniform IrNP and IrSMP assemblies were successfully prepared on Si and ITO substrates, indicating that the drop-drying method is efficient for the preparation of not only nanoparticle assemblies but also submicroparticle assemblies.展开更多
In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found tha...In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found that the MDS not only quickly assesses the long-term reliability of solder joints within days,but can also mimic similar failure mechanisms in accelerated thermal cycling (ATC) tests. Based on the MDS and ATC reliability experiments,the acceleration factors (AF) were obtained for different reliability testing conditions.Furthermore,by using the creep constitutive relation and fatigue life model developed in part I,a numerical approach was established for the purpose of virtual life prediction of solder joints. The simulation results were found to be in good agreement with the test results from the MDS.As a result,a new reliability assessment methodology was established as an alternative to ATC for the evaluation of long-term reliability of plastic BGA assembly.展开更多
In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emp...In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.展开更多
The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The ...The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.展开更多
Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic a...Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic acid）（PSS） and poly（diallyl-dimethylammonium chloride）（PDADMAC） to improve the anchoring of the Ti O2 nanoparticle clusters. PDADMAC, which is positively charged, was then used as counter polyelectrolyte in tandem with anionic Ti O2 nanoparticles to construct Ti O2/PDADMAC bilayer in the Lb L fashion. The number of deposited Ti O2/PDADMAC layers was varied from 1 to 7 bilayer, and could be used to adjust Ti O2 loading. The Lb L technique showed higher Ti O2 loading efficiency than the impregnation approach. The modified fibers were tested for their photocatalytic activity against a model dye, Methylene Blue（MB）. Results showed that the Ti O2 modified fibers exhibited excellent photocatalytic activity efficiency similar to that of Ti O2 powder dispersed in solution. The deposition of Ti O23 bilayer on the PP substrate was sufficient to produce nanocomposite fibers that could bleach the MB solution in less than 4 hr.Ti O2-Lb L constructions also preserved Ti O2 adhesion on substrate surface after 1 cycle of photocatalytic test. Successive photocatalytic test showed decline in MB reduction rate with loss of Ti O2 particles from the substrate outer surface. However, even in the third cycle, the Ti O2 modified fibers are still moderately effective as it could remove more than 95% of MB after 8 hr of treatment.展开更多
Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional ph...Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional physical-master-gauge-based indirect tooth surface error measurement and circumferential assembly angle optimization methods have the disadvantages of high cost and weak generality.The unknown tooth surface fitting mechanism is a big barrier to assembly precision prediction and improvement.Therefore,this work puts forward a data-driven assembly simulation and optimization approach for aero-engine rotors connected by curvic couplings.The origin of curvic tooth surface error is deeply investigated.Using 5-axis sweep scan method,a large amount of high-precision curvic tooth surface data are acquired efficiently.Based on geometric models of parts,the fitting mechanism of curvic couplings is uncovered for assembly precision simulation and prediction.A circumferential assembly angle optimization model is developed to decrease axial and radial assembly runouts.Experimental results show that the assembly precision can be predicted accurately and improved dramatically.By uncovering the essential principle of the assembly precision formation and proposing circumferential assembly angle optimization model,this work is meaningful for assembly quality,efficiency and economy improvement of multistage aero-engine rotors connected by curvic couplings.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52475543)Natural Science Foundation of Henan(Grant No.252300421101)+1 种基金Henan Province University Science and Technology Innovation Talent Support Plan(Grant No.24HASTIT048)Science and Technology Innovation Team Project of Zhengzhou University of Light Industry(Grant No.23XNKJTD0101).
文摘Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.
基金funded by the National Nature Science Foundation of China(11934009,12174198,and 12227808)the Natural Science Foundation of Jiangsu Province,China(BE2022814)+2 种基金the Universal Technology for Primary and Secondary Schoolsthe National Research Institute for Teaching Materialsthe Qing Lan Project of Jiangsu Province,China。
文摘Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pressure attractive path of particle assembly can be constructed by the interference between two independent cylindrical Bessel beams,it remains challenging to create two-dimensional(2D)neighboring vortexes using a source array in practical applications.In this paper,a three-step phase-reversal strategy of 2D particle assembly based on the synchronized evolution of a centrosymmetric array of M off-axis acoustic vortexes(OA-AVs)with a preset radial offset is proposed based on a ring array of planar sources.By introducing initial vortex phase differences of-2π/M and+2π/M to the vortex array,low-pressure patterns of an M-sided regular polygon and M-branched star are formed by connecting the vortex cores and the field center before and after the tangent state of adjacent OA-AVs.Center-oriented particle assembly is finally realized by a central AV constructed by coincident in-phase OA-AVs.The capability of particle manipulation in the lateral and radial directions is demonstrated by low-pressure patterns with acoustic radiation forces pointing to the field center during a synchronized central approach.The field evolution is certified by experimental field measurements for OA-AVs with different vo rtex numbers,initial vortex phase differences,and radial offsets using a ring array of 16 planar sources.The feasibility of particle assembly in two dimensions is also verified by the accurate manipulation of four particles using the low-pressure patterns of a four-sided polygon,a four-branched star,and a central AV in experiments.The three-step strategy paves a new way for 2D particle assembly based on the synchronize d evolution of centrosymmetric OA-AVs using a simplified single-sided source array,exhibiting excellent potential for the precise navigation and manipulation of cells and particles in biomedical applications.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.61975101,11234008,11361161002,and 6157-1276)。
文摘The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identification,motion measurement,and assembly of two-species photoluminescence nanoparticles.A laser trapping array simultaneously levitates nitrogen-vacancy(NV)nanodiamonds and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticles.The species of each nanoparticle can be individually identified by measuring the photoluminescence spectrum.We choose the single NV nanodiamond and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle and assemble them into a Janus composite nanoparticle,which integrates the merits of the two components.This work demonstrates the potential advantages of a hybrid optically levitated system.It provides a practicable scheme for the study of macroscopic quantum phenomena and precision measurement,thanks to the spin manipulation or spin-mechanical coupling of an NV diamond and by simultaneously implementing laser refrigeration to the Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle in an optically levitated composite nanoparticle.
基金supported by grants from the Natural Science Foundation of China(22362031 and 21805121)the Science and Technology Project of Yunnan Province(2019FD137)。
文摘Proton exchange membrane fuel cells(PEMFCs)are considered as a promising renewable power source.However,the massive commercial application of PEMFCs has been greatly hindered by their high expense and less-satisfied performance mainly due to the sluggish oxygen reduction reaction(ORR)kinetics even on state-of-the-art Pt catalyst.Octahedral PtNi nanoparticles(oct-PtNi NPs)with excellent ORR activity in a half-cell have been widely studied,while their performance in membrane electrode assembly(MEA)has much less reported.Herein,we investigated the MEA performance using the carbon supported oct-PtNi NPs(oct-PtNi/C)as the cathode catalyst.Under the mild acid washing condition,the surface Ni atoms of oct-PtNi/C were largely removed,and the performance of the MEA using the acid-leaching oct-PtNi/C(PNC-A)as the cathode catalyst was greatly improved.The maximum power density of the MEA reached 1.0 W·cm^(-2) with the cath-ode Pt loading of 0.2 mg·cm^(-2),which is 15%higher than that using Pt/C as the catalyst.After 30k cycles in the accelerated degradation test(ADT),the MEA using PNC-A as the catalyst showed a performance retention of 82%,higher than that of Pt/C(74%).The results reported here verify the possibility of using PNC-A as an advanced cathode catalyst in PEMFCs,thus enhancing the performance of PEMFCs while lowering the amount of expensive Pt.
基金Supported by the National Natural Science Foundation of China(Nos.42141003,42176147)the National Key Research and Development Program of China(No.2022YFF0802204)the Xiamen Key Laboratory of Urban Sea Ecological Conservation and Restoration(USER)(Nos.USER2021-1,USER2021-5)。
文摘Ecological floating bed is an important biological remediation method for water pollution control.During the removal of excess nutrients and pollutants,changes in environmental factors affect the characteristics of microorganisms in aquatic ecosystems.To understand the influences of ecological floating beds on size-fractionated microorganisms,we investigated the community assembly and nitrogen metabolic characteristics of three size-fractionated microorganism groups in the ecological floating bed area,using 18S rDNA,16S rDNA metabarcoding,and metagenomic sequencing techniques.Firstly,we discovered substantial differences between size-fractionated groups in the diversity and compositions of both microeukaryotic and bacterial communities,as well as the influences of floating beds on specific groups.The floating beds appeared to provide more habitats for heterotrophs and symbiotes while potentially inhibiting the growth of certain phytoplankton(cyanobacteria).Secondly,we observed that microeukaryotic and bacterial communities were predominantly influenced by stochastic and deterministic processes,respectively,and they both exhibited distinct patterns across different size-fractionated groups.Notably,microeukaryotic community assembly demonstrated a greater sensitivity to ecological floating beds,as indicated by an increase in dispersal limitation processes.Finally,the nitrogen metabolism functional genes revealed that microbes associated with large-sized particles played a crucial role in dissimilatory nitrate reduction to ammonium(DNRA)and denitrification processes within the floating bed area,thereby facilitating the removal of excess nitrogen nutrients from the water.In contrast,freeliving microorganisms from small-sized groups were linked mainly to the genes involved in nitrogen assimilation and assimilatory nitrate reduction to ammonium(ANRA)processes.These findings help understand the impact of ecological floating beds on the diversity and functional characteristics of microorganism communities in different size-fractionated groups.
基金financial y supported by the National Key Research and Development Program of China (2023YFD1900902)the Joint Funds of the Zhejiang Provincial Natural Science Foundation of China (LLSSZ24C030001)+1 种基金the Earmarked Fund for China Agriculture Research System (CARS-08-G-09)sponsored by the K.C.Wong Magna Fund of Ningbo University,China。
文摘Fungi play crucial roles in nutrient acquisition,plant growth promotion,and the enhancement of resistance to both abiotic and biotic stresses.However,studies on the fungal communities associated with peas (Pisum sativum L.) remain limited.In this study,we systematically investigated the ecological effects of host niches (soil,root,stem,leaf,and pod) and genotypes on the diversity and composition of fungal communities in peas using a multi-level approach that encompassed pattern recognition (β-diversity decomposition),mechanism validation (neutral community model testing),and dynamic tracking methods (migration pathway source-tracking).The results revealed that the dominant fungal phyla across niches and genotypes were Ascomycota,Basidiomycota,and Mortierellomycota,and the community structures of the soil–plant continuum were primarily determined by the pea niches rather than genotypes.β-diversity decomposition was largely attributed to species replacement rather than richness differences,indicating strong niche specificity and microbial replacement across microhabitats.Neutral model analysis revealed that stochastic processes influenced genotypeassociated communities,while deterministic processes played a dominant role in niche-based community assembly.Source-tracking analysis identified niche-to-niche fungal migration,with Erysiphe,Fusarium,Cephaliophora,Ascobolus,Alternaria,and Aspergillus as the key genera.Migration rates from exogenous to endogenous niches were low (1.3–61.5%),whereas those within exogenous (64.4–83.7%) or endogenous (73.9–96.4%) compartments were much higher,suggesting that the pea epidermis acts as a selective barrier that filters and enriches microbial communities prior to internal colonization.This study provides comprehensive insights into the mechanisms of host filtering,enrichment and microbial sourcing,which increases our understanding of the assembly rules of the pea-associated fungal microbiome.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金supported by the National Key R&D Project of China(Nos.2022YFC2304205,2022YFC2304202)Key scientific research project of universities in Guangdong Province(No.2023KCXTD026)the Major Project of Guangzhou National Laboratory(No.GZNL2023A03002).
文摘Adjuvants enhance and prolong the immune response to therapeutic agents,such as drugs and vaccines.However,conventional adjuvants have limitations in terms of immune specificity and duration.Nanoadjuvants can leverage their nanoscale size to increase the capture efficacy of antigens by antigen-presenting cells and improve immunogen presentation for targeted delivery.Furthermore,noninvasive visualization of bifunctional nanoadjuvants with integrated efficacy and imaging postdelivery can provide insights into in vivo distribution and performance,aiding in the optimization and design of new dosage forms.This review systematically summarizes the structure,assembly,and function of nanoadjuvants alongside contrast agents.It delves into the impact of complex structures formed by nanoadjuvant-contrast agent interactions on antigen presentation,migration,imaging tracking,and visualization of immune cell recruitment.It also discusses how imaging can determine optimal immune intervals,vaccine safety,and toxicity while enabling diagnostic and therapeutic integration.Moreover,this paper discusses potential applications of novel adjuvants and promising imaging technologies that could have implications for future vaccine and drug development endeavors.
基金supported by the National Key R&D Program of China(2024YFD1201100)the research program from the Zhongshan Biological Breeding Laboratory(ZSBBL-KY2023-02)the National Natural Science Foundation of China(32341037).
文摘Wheat(Triticum aestivum)faces significant threats from diseases such as powdery mildew(Blumeria graminis)and Fusarium head blight(FHB;caused by Fusarium graminearum),which cause severe yield losses.Moreover,the antagonism between yield-related traits and disease resistance makes yield resistance coordination a major challenge in wheat breeding.The lack of genetic resources combining both disease resistance and high yield constrains the elucidation of underlying resistance-yield trade-off mechanisms,thereby hindering the development of high-yield and disease-resistant wheat cultivars.Remarkably,Yangmai 33(YM33),a notable wheat cultivar with resistance to both powdery mildew and FHB as well as high-yield performance,was recently developed.It offers a unique opportunity to dissect the genomic architecture underlying the coordination between disease resistance and yield.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
基金financially supported by the National Natural Science Foundation of China(Nos.22475057 and No.52373262).
文摘Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.
基金Project(51675100)supported by the National Natural Science Foundation of ChinaProject(2016ZX04004008)supported by the National Numerical Control Equipment Major Project of ChinaProject(6902002116)supported by the Foundation of Certain Ministry of China
文摘In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed through transient and static simulation.In this work,the theoretical deformation model for riveting assembly is established with round head rivet.The simulation analysis for riveting deformation is carried out with the riveting assembly piece including four rivets,which comparing with the measuring points experiment results of riveting test piece through dealing with the experimental data using the point coordinate transform method and the space line fitting method.Simultaneously,the deformation deviation of the overall thin-wall parts assembly structure is analyzed through finite element simulation;and its results are verified by the measuring experiment for riveting assembly with the deformation deviation of some key points on the thin-wall parts.Through the comparison analysis,it is shown that the simulation results agree well with the experimental results,which proves the correctness and effectiveness of the theoretical analysis,simulation results and the given experiment data processing method.Through the study on the riveting assembly for thin-wall parts,it will provide a theoretical foundation for improving thin-wall parts assembly quality of large antenna in future.
基金supported by the Equipment Pre-research Project of China (No. 41423010202)
文摘Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout,which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms.At present,the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing.Based on the perception data of intelligent assembly unit of aircraft parts,a regression model of multi-input and multioutput support vector machine with Gauss kernel function as radial basis function is established,and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm(PSO-GA).GA-MSVR,PSO-MSVR and PSOGA-MSVR model are constructed respectively,and their results show that PSOGA-MSVR model has the best performance.Finally,the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method.
基金supported by the Inner Mongolia Power(Group) Co., Ltd.,Technology Project (No. 2016-20)
文摘By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.
基金financially supported by the National Natural Science Foundation of China (Nos.20973020 and21173016)Doctoral Fund of Ministry of Education of China (No. 20101102110002)+1 种基金Program for New Century Excellent Talents in University (No.NCET-08-0034)Program for Changjiang Scholars and Innovative Research Team in University (No.IRT0805)
文摘Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and drop-drying assembly. The obtained IrNPs and IrSMPs were characterized using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The IrSMPs (or IrNPs) with disc-like shape and irregular shapes were obtained on ITO substrate by direct surface growth method using polyvinylpyrrolidone (PVP) and sodium citrate as different stabilizers, respectively. The reaction time and the injection temperature of reducing agent are found to have great effect on the size and morphology of the surface-grown Ir particles. The disc-like, ellipsoidal, and spherical IrSMPs (or IrNPs) were also synthesized in homogeneous solution in the presence of H3BO3 and Na2B4O7 as assistant-stabilizer. These IrNPs and IrSMPs were used as building blocks to construct nanoparticle assemblies by using a simple drop-drying method. Uniform IrNP and IrSMP assemblies were successfully prepared on Si and ITO substrates, indicating that the drop-drying method is efficient for the preparation of not only nanoparticle assemblies but also submicroparticle assemblies.
基金The project supported by the National Natural Science Foundation of China (59705008)
文摘In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found that the MDS not only quickly assesses the long-term reliability of solder joints within days,but can also mimic similar failure mechanisms in accelerated thermal cycling (ATC) tests. Based on the MDS and ATC reliability experiments,the acceleration factors (AF) were obtained for different reliability testing conditions.Furthermore,by using the creep constitutive relation and fatigue life model developed in part I,a numerical approach was established for the purpose of virtual life prediction of solder joints. The simulation results were found to be in good agreement with the test results from the MDS.As a result,a new reliability assessment methodology was established as an alternative to ATC for the evaluation of long-term reliability of plastic BGA assembly.
基金The National Natural Science Foundation of China(No.51675100)the National Numerical Control Equipment Major Project of China(o.2016ZX04004008)
文摘In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.
基金The Natural Science Foundation of Jiangsu Province,China(No.BK20200470)China Postdoctoral Science Foundation(No.2021M691595)Innovation and Entrepreneurship Plan Talent Program of Jiangsu Province(No.AD99002).
文摘The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.
基金supported by Rachadapisek Sompote Fund for Postdoctoral Fellowship, Chulalongkorn University, Thailandthe Nanotechnology Center (NANOTEC), NSTDA Ministry of Science and Technology, Thailand, through its program of Center of Excellence Network+1 种基金National Research University Project of CHEthe Rachadapisek Sompote Endowment Fund (No. AM1041A)
文摘Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic acid）（PSS） and poly（diallyl-dimethylammonium chloride）（PDADMAC） to improve the anchoring of the Ti O2 nanoparticle clusters. PDADMAC, which is positively charged, was then used as counter polyelectrolyte in tandem with anionic Ti O2 nanoparticles to construct Ti O2/PDADMAC bilayer in the Lb L fashion. The number of deposited Ti O2/PDADMAC layers was varied from 1 to 7 bilayer, and could be used to adjust Ti O2 loading. The Lb L technique showed higher Ti O2 loading efficiency than the impregnation approach. The modified fibers were tested for their photocatalytic activity against a model dye, Methylene Blue（MB）. Results showed that the Ti O2 modified fibers exhibited excellent photocatalytic activity efficiency similar to that of Ti O2 powder dispersed in solution. The deposition of Ti O23 bilayer on the PP substrate was sufficient to produce nanocomposite fibers that could bleach the MB solution in less than 4 hr.Ti O2-Lb L constructions also preserved Ti O2 adhesion on substrate surface after 1 cycle of photocatalytic test. Successive photocatalytic test showed decline in MB reduction rate with loss of Ti O2 particles from the substrate outer surface. However, even in the third cycle, the Ti O2 modified fibers are still moderately effective as it could remove more than 95% of MB after 8 hr of treatment.
基金co-supported by the National Basic Research Project(Nos.J2022-VII-0001-0043 and 2017-VII-0010-0104)the Fundamental Research Funds for the Central Universities,and the National Natural Science Foundation of China(No.72231008)。
文摘Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional physical-master-gauge-based indirect tooth surface error measurement and circumferential assembly angle optimization methods have the disadvantages of high cost and weak generality.The unknown tooth surface fitting mechanism is a big barrier to assembly precision prediction and improvement.Therefore,this work puts forward a data-driven assembly simulation and optimization approach for aero-engine rotors connected by curvic couplings.The origin of curvic tooth surface error is deeply investigated.Using 5-axis sweep scan method,a large amount of high-precision curvic tooth surface data are acquired efficiently.Based on geometric models of parts,the fitting mechanism of curvic couplings is uncovered for assembly precision simulation and prediction.A circumferential assembly angle optimization model is developed to decrease axial and radial assembly runouts.Experimental results show that the assembly precision can be predicted accurately and improved dramatically.By uncovering the essential principle of the assembly precision formation and proposing circumferential assembly angle optimization model,this work is meaningful for assembly quality,efficiency and economy improvement of multistage aero-engine rotors connected by curvic couplings.
