The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstru...The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstructure,fracture surfaces,and crack growth paths were analyzed before and after CHT.Results indicate that in the stable crack growth region,the growth rates for the as-deposited and cyclic heat-treated specimens follow the relationships da/dN=1.8651×10^(−8)(ΔK)^(3.2271)and da/dN=1.4112×10^(−8)(ΔK)^(3.1125),respectively.Compared with that at the as-deposited state,the microstructure after CHT is transformed from a uniform basket-weave microstructure to a dual-phase microstructure consisting of near-sphericalαandβ-transformed matrix phases.The cyclic process also disrupts the continuity of the grain boundaryα(αGB)at the primaryβ-phase grain boundary.The coarsening of primaryαand the disruption ofαGB continuity are the primary factors to release stress concentration and promote crack deflection,thereby decreasing the fatigue crack growth rate.Additionally,the increased occurrence of crack branching,secondary cracking,and crack bridging in cyclic heat-treated specimens further reduces the crack driving force and slows the fatigue crack growth rate.展开更多
Acetolactate synthase(ALS)-targeting herbicides are among the most widely used weed-control chemicals globally.Mutations in the ALS gene can confer herbicide resistance in crops,thereby allowing selective elimination ...Acetolactate synthase(ALS)-targeting herbicides are among the most widely used weed-control chemicals globally.Mutations in the ALS gene can confer herbicide resistance in crops,thereby allowing selective elimination of weeds without harming crops.Herbicide-resistant ALS alleles were initially discovered in weeds and subsequently developed through artificial mutagenesis techniques.With the advancement of CRISPR/Cas technologies,various genome-editing tools are now available to introduce these resistant alleles,as well as novel variants,into diverse crop species.Moreover,emerging methodologies,such as directed evolution,enable the generation and screening of large populations of random ALS mutants.Consequently,ALS has become one of the most extensively targeted genes in plant gene evolution.This paper provides a comprehensive overview of both conventional and recently developed strategies for ALS evolution,with particular emphasis on CRISPR/Cas-based genome editing and directed evolution.Future perspectives on technological application are also discussed.By advancing our understanding of herbicide-resistant ALS allele development for crop improvement,these methodologies may also pave the way for their application to the evolution of other agronomically important genes.展开更多
The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a...The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a few hundred MeV/u up to 1 GeV/u.It aims to facilitate research on the quantum chromodynamics(QCD)phase structure in the high-baryondensity region.Collective flow is a fundamental observable in heavy-ion collision experiments,providing information on the bulk properties of the produced matter.Although the standard event plane method has been widely used to measure collective flow,it is still important to validate and optimize this method for the CEE spectrometer.In this paper,we study the experimental procedures for measuring directed flow in^(238)U+^(238)U collisions at 500 MeV/u,using event planes reconstructed by Multi-Wire Drift Chamber and Zero Degree Calorimeter,respectively.Jet AA Microscopic(JAM)transport generator is used to generate events,and the detector response is simulated by the CEE Fast Simulation(CFS)package.Finally,the optimal kinematic region for proton directed flow measurements is discussed for the future CEE experiment.展开更多
This work evaluates an architecture for decentralized authentication of Internet of Things(IoT)devices in Low Earth Orbit(LEO)satellite networks using IOTA Identity technology.To the best of our knowledge,it is the fi...This work evaluates an architecture for decentralized authentication of Internet of Things(IoT)devices in Low Earth Orbit(LEO)satellite networks using IOTA Identity technology.To the best of our knowledge,it is the first proposal to integrate IOTA’s Directed Acyclic Graph(DAG)-based identity framework into satellite IoT environments,enabling lightweight and distributed authentication under intermittent connectivity.The system leverages Decentralized Identifiers(DIDs)and Verifiable Credentials(VCs)over the Tangle,eliminating the need for mining and sequential blocks.An identity management workflow is implemented that supports the creation,validation,deactivation,and reactivation of IoT devices,and is experimentally validated on the Shimmer Testnet.Three metrics are defined and measured:resolution time,deactivation time,and reactivation time.To improve robustness,an algorithmic optimization is introduced that minimizes communication overhead and reduces latency during deactivation.The experimental results are compared with orbital simulations of satellite revisit times to assess operational feasibility.Unlike blockchain-based approaches,which typically suffer from high confirmation delays and scalability constraints,the proposed DAG architecture provides fast,cost-free operations suitable for resource-constrained IoT devices.The results show that authentication can be efficiently performed within satellite connectivity windows,positioning IOTA Identity as a viable solution for secure and scalable IoT authentication in LEO satellite networks.展开更多
To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional...To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional blockchains limit their application in large-scale FL tasks,and the synchronous traditional FL will also reduce the training efficiency.To address these issues,in this paper,we propose a Directed Acyclic Graph(DAG)blockchain-enabled generalized Federated Dropout(FD)learning strategy,which could improve the efficiency of FL while ensuring the model generalization.Specifically,the DAG maintained by multiple edge servers will guarantee the security and traceability of the data,and the Reputation-based Tips Selection Algorithm(RTSA)is proposed to reduce the blockchain consensus delay.Second,the semi-asynchronous training among Intelligent Devices(IDs)is adopted to improve the training efficiency,and a reputation-based FD technology is proposed to prevent overfitting of the model.In addition,a Hybrid Optimal Resource Allocation(HORA)algorithm is introduced to minimize the network delay.Finally,simulation results demonstrate the effectiveness and superiority of the proposed algorithms.展开更多
The layer-by-layer deposition strategy of additive manufacturing makes it ideal to fabricate dissimilar alloy components with varying functionality,which has promising application potential in a large number of indust...The layer-by-layer deposition strategy of additive manufacturing makes it ideal to fabricate dissimilar alloy components with varying functionality,which has promising application potential in a large number of industrial areas.In this study,two components composed of ERCuAl-A2 aluminum bronze(CuAl9)and Inconel 718 nickel-based superalloy were fabricated with different deposition orders by wire-arc directed energy deposition.Subject to changes in heat input and thermophysical properties of the substrate,the transition region of the deposited Cu-Ni component with the bottom half of CuAl9 and the top half of Inconel 718 is narrow and serrated.This region features a laminated intermetallic compound layer due to the convection and rapid cooling in the molten pool.In contrast,the Ni-Cu component deposited in the opposite order exhibits a 2 mm gradient transition zone.Within this region,a large number of diverse precipitates were found as well as regional variations in grain size due to the multi-layer partial remelting.Both two components show strong bonds and their tensile specimens tested along the vertical direction always fracture at the softer CuAl9 side.Excellent tensile properties along the horizontal direction were obtained for Cu-Ni(Ultimate tensile strength:573 MPa,yield stress:302 MPa,elongation:22%),while those of Ni-Cu are much lower due to the existence of the solidification cracks in the transition zone.The results from this study provide a reference for the additive manufacturing of Cu/Ni dissimilar alloy components,as well as their microstructure and mechanical properties control.展开更多
Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based me...Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.展开更多
Stainless steel parts with complex shape can be fabricated using additive manufacturing,which do not rely on molds and dies.However,coarse dendrites induced by repeated heating of additive manufacturing result in weak...Stainless steel parts with complex shape can be fabricated using additive manufacturing,which do not rely on molds and dies.However,coarse dendrites induced by repeated heating of additive manufacturing result in weak properties,which limits its application.In this study,an in-situ ultrasonic rolling(UR)device was developed to assist the laser directed energy deposition(LDED)process.The microstructural characteristics,as well as the microhardness and wear behavior,were studied for the 316L stainless steel manufactured by in-situ ultrasonic rolling assisted LDED.It is found that austenite,ferrite,and small Si oxides are the main constituents of both the LDED and LDED-UR alloy samples.Under the severe plastic deformation of ultrasonic rolling,the long-branched ferrites by LDED are transformed into the rod-like phases by LDED-UR.Meanwhile,the ferrite is more uniformly distributed in the LDED-UR alloy sample compared with that in LDED alloy sample.Columnar grains with the size of 97.85μm appear in the LDED alloy sample,which is larger than the fully equiaxed grains(22.35μm)of the LDED-UR alloy.The hardness of the LDED-UR alloy sample is about 266.13±13.62 HV_(0.2),which is larger than that of the LDED alloy sample(212.93±12.85 HV_(0.2)).Meanwhile,the wear resistance is also greatly enhanced by applying the assisted in-situ ultrasonic rolling.The achieved high wear resistance can be ascribed to the uniformly distributed hard matter(ferrites)and the impedance of dislocations by high fraction of grain boundaries.Abrasive wear and adhesive wear are identified as the primary wear mechanisms of the studied alloy.Gaining an in-depth understanding of the relationship between wear mechanisms and microstructures offers an effective approach in manufacturing high wear resistant alloys suitable for use in harsh working environments.展开更多
Under the laser directed energy deposition(LDED)process,the rapid melting and solidification usually lead to the emergence of pores and coarse columnar dendrites,which in turn compromise the properties of the deposite...Under the laser directed energy deposition(LDED)process,the rapid melting and solidification usually lead to the emergence of pores and coarse columnar dendrites,which in turn compromise the properties of the deposited alloys.This study introduced in-situ ultrasonic rolling(UR)as an innovative method to enhance the corrosion resistance of LDED specimens,and the microstructural characteristics and their correlation with corrosion resistance were deeply investigated.The findings reveal that the LDED-UR specimen exhibits a reduction in both the fraction and size of pores.Under the influence of severe plastic deformation generated by LDED-UR process,fully equiaxed grains appear with a reduced average size of 28.61μm(compared to63.98μm for the LDED specimen with columnar grains).The electrochemical corrosion resistance of the LDED-UR specimen is significantly enhanced compared to the LDED specimen.This enhanced corrosion resistance can be attributed to the low fraction of small-sized pores,the fine and uniformly distributed Cr-enriched ferrite phase,and the formation of a compact and thick passive film due to dense grain boundaries.The insight of the correlation between microstructure and corrosion behavior opens up a new pathway to enhance the corrosion resistance of LDED specimens.展开更多
Interface chemical modulation strategies are considered as promising method to prepare electrocatalysts for the urea oxidation reaction(UOR).However,conventional interface catalysts are generally limited by the inhere...Interface chemical modulation strategies are considered as promising method to prepare electrocatalysts for the urea oxidation reaction(UOR).However,conventional interface catalysts are generally limited by the inherent activity and incompatibility of the individual components themselves,and the irregular charge distribution and slow charge transfer ability between interfaces severely limit the activity of UOR.Therefore,we optimized and designed a Ni_(2)P/CoP interface with modulated surface charge distribution and directed charge transfer to promote UOR activity.Density functional theorycalculations first predict a regular charge transfer from CoP to Ni_(2)P,which creates a built-in electric field between Ni_(2)P and CoP interface.Optimization of the adsorption/desorption process of UOR/HER reaction intermediates leads to the improvement of catalytic activity.Electrochemical impedance spectroscopy and ex situ X-ray photoelectron spectroscopy characterization confirm the unique mechanism of facilitated reaction at the Ni_(2)P/CoP interface.Electrochemical tests further validated the prediction with excellent UOR/HER activities of 1.28 V and 19.7 mV vs.RHE,at 10 mA cm^(-2),respectively.Furthermore,Ni_(2)P/CoP achieves industrial-grade current densities(500 mA cm^(−2))at 1.75 V and 1.87 V in the overall urea electrolyzer(UOR||HER)and overall human urine electrolyzer(HUOR||HER),respectively,and demonstrates considerable durability.展开更多
Solution and aging treatment were conducted on the laser directed energy deposition(LDED)-prepared carbon nanotubes(CNTs)-reinforced WE43(CNTs/WE43)layers to optimize their microstructure and surface properties in thi...Solution and aging treatment were conducted on the laser directed energy deposition(LDED)-prepared carbon nanotubes(CNTs)-reinforced WE43(CNTs/WE43)layers to optimize their microstructure and surface properties in this study.The microstructure of the WE43 and CNTs/WE43 layers was systematically compared.The dissolution of divorced eutectics at the grain boundaries was retarded by CNTs during solution treatment.The spot segregation composed of Mg_(24)Y_(5),CNTs,and Zr cores in the solution treated CNTs/WE43 layer presented a slight decreasing in Y content.The grain growth of both types of layers underwent three stages:slow,rapid,and steady-state.The significant inhibitory effect of CNTs on the grain growth of the LDED WE43 matrix was more pronounced than the promoting effect of temperature,resulting in a 47%increase at 510℃ and a 35%increase at 540℃ in the grain growth exponent compared to the WE43 layers at 510℃.During the subsequent aging treatment at 225℃,the precipitation sequences from plate-shaped β″to plate-shaped and globular β′ were observed in both types of layers.CNTs can facilitate an increase in the nucleation rate of precipitates,but without accelerating precipitation hardening rate.The long and short diameters of the precipitates in peak-aged state were decreased by 48.5%and 43.1%by addition of CNTs,respectively.The wear resistance of both the WE43 and CNTs/WE43 layers can be significantly enhanced through solution and aging treatment.The enhancement in wear resistance for the CNTs/WE43 layers is considerably greater than that of the WE43 layers.展开更多
To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical s...To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical simulation was proposed to predict the temperature during LDED.A finite element(FE)thermal analysis model was established.The model's accuracy was verified through in-situ monitoring experiments,and a basic database for the predictive model was obtained based on FE simulations.Temperature prediction was performed using a generalized regression neural network(GRNN).To reduce dependence on human experience during GRNN parameter tuning and to enhance model prediction performance,an improved adaptive step-size fruit fly optimization algorithm(ASSFOA)was introduced.Finally,the prediction performance of ASSFOA-GRNN model was compared with that of back-propagation neural network model,GRNN model,and fruit fly optimization algorithm(FOA)-GRNN model.The evaluation metrics included the root mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R^(2)),training time,and prediction time.Results show that the ASSFOA-GRNN model exhibits optimal performance regarding RMSE,MAE,and R^(2) indexes.Although its prediction efficiency is slightly lower than that of the FOA-GRNN model,its prediction accuracy is significantly better than that of the other models.This proposed method can be used for temperature prediction in LDED process and also provide a reference for similar methods.展开更多
The ultra-high speed,ultra-low latency,and massive connectivity of the 6 th Generation Mobile Network(6G)present unprecedented challenges to network security.In addition,the deep integration of Artificial Intelligence...The ultra-high speed,ultra-low latency,and massive connectivity of the 6 th Generation Mobile Network(6G)present unprecedented challenges to network security.In addition,the deep integration of Artificial Intelligence(AI)into 6G networks introduces AI-native features that further complicate the design and implementation of secure network architectures.To meet the security demands posed by the massive number of devices and edge nodes in 6G networks,a decentralized security architecture is essential,as it effectively mitigates the performance bottlenecks typically associated with centralized systems.Blockchain technology offers a promising trust mechanism among devices in 6G networks.However,conventional blockchain systems suffer from limited scalability under high-load conditions,making them inadequate for supporting a large volume of nodes and frequent data exchanges.To overcome these limitations,We propose Shard-DAG,a scalable architecture that structurally integrates Directed Acyclic Graphs(DAG)and sharding.Each shard adopts a Block-DAG structure for parallel block processing,effectively overcoming the performance bottlenecks of traditional chain-based blockchains.Furthermore,we introduce a DAG-based transaction ordering mechanism within each shard to defend against double-spending attacks.To ensure inter-shard security,Block-DAG adopts a black-box interaction approach to prevent cross-shard double-spending.Theoretical analysis and experimental evaluations demonstrate that Shard-DAG achieves near-linear scalability.In a network of 1,200 nodes with 8 shards,Shard-DAG achieves peak throughput improvements of 14.64 times over traditional blockchains,8.61 times over standalone BlockDAG,and 2.05 times over conventional sharded blockchains.The results validate Shard-DAG's ability to scale efficiently while maintaining robust security properties.展开更多
The issue of privacy leakage in distributed consensus has garnered significant attention over the years,but existing studies often overlook the challenges posed by limited communication in algorithm design.This paper ...The issue of privacy leakage in distributed consensus has garnered significant attention over the years,but existing studies often overlook the challenges posed by limited communication in algorithm design.This paper addresses the issue of privacy preservation in distributed weighted average consensus under limited communication scenarios.Specifically targeting directed and unbalanced topologies,we propose a privacy-preserving implementation protocol that incorporates the Paillier homomorphic encryption scheme.The protocol encrypts only the 1-bit quantized messages exchanged between agents,thus ensuring both the correctness of the consensus result and the confidentiality of each agent's initial state.To demonstrate the practicality of the proposed method,we carry out numerical simulations that illustrate its ability to reach consensus effectively while ensuring the protection of private information.展开更多
The development of the Internet of Things(IoT)has brought convenience to people’s lives,but it also introduces significant security risks.Due to the limitations of IoT devices themselves and the challenges of re-host...The development of the Internet of Things(IoT)has brought convenience to people’s lives,but it also introduces significant security risks.Due to the limitations of IoT devices themselves and the challenges of re-hosting technology,existing fuzzing for IoT devices is mainly conducted through black-box methods,which lack effective execution feedback and are blind.Meanwhile,the existing static methods mainly rely on taint analysis,which has high overhead and high false alarm rates.We propose a new directed fuzz testing method for detecting bugs in web service programs of IoT devices,which can test IoT devices more quickly and efficiently.Specifically,we identify external input entry points using multiple features.Then we quickly find sensitive targets and paths affected by external input sources based on sensitive data flow analysis of decompiled code,treating them as testing objects.Finally,we performa directed fuzzing test.We use debugging interfaces to collect execution feedback and guide the programto reach sensitive targets based on programpruning techniques.We have implemented a prototype system,AntDFuzz,and evaluated it on firmware fromten devices across five well-known manufacturers.We discovered twelve potential vulnerabilities,seven of which were confirmed and assigned bug id by China National Vulnerability Database(CNVD).The results show that our approach has the ability to find unknown bugs in real devices and is more efficient compared to existing tools.展开更多
The enzymatic depolymerization of polyethylene terephthalate(PET)offers a sustainable approach for the recycling of PET waste.Great efforts have been devoted to engineering PET depolymerases on the substrate binding c...The enzymatic depolymerization of polyethylene terephthalate(PET)offers a sustainable approach for the recycling of PET waste.Great efforts have been devoted to engineering PET depolymerases on the substrate binding cleft and the surrounding loops/α-helices on the surface.Here,we report the systematic engineering of whole β-sheet regions in the core of IsPETase(a PETase from Ideonella sakaiensis)via a fluorescent high-throughput screening assay.Twenty-one beneficial substitutions were obtained and iteratively recombined.The best variant,DepoPETase β,with an increase in the melting temperatures(T_(m))of 22.9℃,exhibited superior depolymerization performance and enabled complete depolymerization of100.5 g of untreated post-consumer PET(pc-PET;0.26% W_(enzyme)/W_(PET) enzyme loading)in liter-scale bioreactor at 50℃within 4 d.Crystallization and molecular dynamics simulations revealed that the improved activity and thermostability of DepoPETase β were due to enhanced hydrogen bonds and salt bridges in the β-sheet region,a more tightly packed structure of the core sheets and the surrounding helix,and improved binding of PET to the active sites.This study not only demonstrates the importance of engineering strategy in theβ-sheet region of PET hydrolases but also provides a potential PET depolymerase for large-scale PET recycling.展开更多
Causality,the science of cause and effect,has made it possible to create a new family of models.Such models are often referred to as causal models.Unlike those of mathematical,numerical,empirical,or machine learning(M...Causality,the science of cause and effect,has made it possible to create a new family of models.Such models are often referred to as causal models.Unlike those of mathematical,numerical,empirical,or machine learning(ML)nature,causal models hope to tie the cause(s)to the effect(s)pertaining to a phenomenon(i.e.,data generating process)through causal principles.This paper presents one of the first works at creating causal models in the area of structural and construction engineering.To this end,this paper starts with a brief review of the principles of causality and then adopts four causal discovery algorithms,namely,PC(Peter-Clark),FCI(fast causal inference),GES(greedy equivalence search),and GRa SP(greedy relaxation of the sparsest permutation),have been used to examine four phenomena,including predicting the load-bearing capacity of axially loaded members,fire resistance of structural members,shear strength of beams,and resistance of walls against impulsive(blast)loading.Findings from this study reveal the possibility and merit of discovering complete and partial causal models.Finally,this study also proposes two simple metrics that can help assess the performance of causal discovery algorithms.展开更多
The colored noise disrupts the detailed balance,enabling directed transport in ratchet systems without additional driving forces.Despite a well-established understanding of the conditions for Brownian motors,quantific...The colored noise disrupts the detailed balance,enabling directed transport in ratchet systems without additional driving forces.Despite a well-established understanding of the conditions for Brownian motors,quantification of the driving effect of colored noise and its connection to deviations from equilibrium remains unexplored.In this study,we examined the directed motion of an overdamped Brownian motor within an asymmetric traveling potential subjected to Ornstein–Uhlenbeck colored noise.We propose a scheme to quantify the driving effect of colored noise by defining an effective force based on the stopping velocity of the traveling potential where directed transport halts.Our results revealed a nonmonotonic dependence of the effective force on the noise correlation time and a monotonic dependence on the noise strength,corresponding to double and single current reversals,respectively.The nonmonotonicity of the current is attributed to the interplay between the fluctuating characteristics and the driving effects of colored noise.展开更多
The fabrication of Invar/MnCu functionally graded material(FGM)through directed energy deposition(DED)can satisfy the demands for precision devices in aerospace,providing lightweight properties and integrating thermal...The fabrication of Invar/MnCu functionally graded material(FGM)through directed energy deposition(DED)can satisfy the demands for precision devices in aerospace,providing lightweight properties and integrating thermal stability and vibration damping capabilities.However,basic research on Invar/MnCu FGM is still lacking,hindering its potential applications.To address this gap,this study was conducted using mixed powders and consistent process parameters to print experiments for Invar/MnCu FGM and homogeneous samples.Phases,microstructures,compositions,and thermal expansion properties were thoroughly examined.Three types of defects were detected in the Invar/MnCu FGM sample:unmelted Invar 36 powders,cracks,and pores.The mechanism of unmelted powders was deeply discussed,attributing it to material properties influencing laser absorptivity,the required time for melting powder,and effects on solidus temperature.The mechanism of cracks was also discussed,attributing it to theγ-Fe dendritic structure causing low melting point metal to form an intergranular liquid film,harmful secondary phases mismatched with the terminal alloy,and obvious tensile stresses during the DED process.Additionally,an effective strategy was proposed to reduce defects in Invar/MnCu FGM.After optimization,the specimens exhibited excellent tensile properties,with a yield strength of 262±5 MPa,an ultimate tensile strength of 316±7 MPa,and an elongation of 3%±1%.This research provides valuable references and insights for subsequent work,offering robust support for better understanding and designing other FGM.展开更多
Laser-directed energy deposition(LDED)technology has demonstrated great potential for the rapid and integrated fabrication of nickel-based superalloy components.The plastic deformation-assisted method is crucial for a...Laser-directed energy deposition(LDED)technology has demonstrated great potential for the rapid and integrated fabrication of nickel-based superalloy components.The plastic deformation-assisted method is crucial for achieving grain refinement and microstructural homogeneity in LDED-fabricated superalloys.However,existing methods suffer from uniformity constraints owing to their high deformation resistance,which significantly limits their application in load-bearing components.To address these issues,a synchronous-hot-forging-assisted(SHFA)LDED additive manufacturing method was proposed,and its effects on the macroscopic morphology,microstructure,and mechanical properties of GH4169 nickel-based alloy specimens were systematically compared.The results demonstrated up to 30.1%average plastic deformation in hot-forging components while maintaining good surface flatness.The synergistic effect of dislocation accumulation and dynamic recrystallization during hot forging enables dramatic grain refinement,reducing the average grain size by 89.1%(from 168.5μm to 18.4μm)while weakening texture intensity from 15.31 to 2.15,ultimately promoting equiaxed grain formation.The pores of hot-forging components changed from fine round to flat,the porosity decreased from 0.264%to 0.089%,and the densification level was significantly improved.With the increase in the synchronous hot-forging force,the average ultimate tensile strength of hot-forging components can reach 1175.1 MPa,while the anisotropy difference is gradually weakened.The SHFA-LDED process not only achieves excellent grain refinement and microstructure homogenization but also enhances mechanical properties,providing a new technical path for the additive manufacturing of high-performance nickel-based superalloy components.展开更多
基金National Key Research and Development Program of China(2024YFB4610803)。
文摘The fatigue crack growth rate of a novel Ti-6Al-4V-1Mo titanium alloy,which is developed for laser directed energy deposition technique,was investigated before and after cyclic heat treatment(CHT).Changes in microstructure,fracture surfaces,and crack growth paths were analyzed before and after CHT.Results indicate that in the stable crack growth region,the growth rates for the as-deposited and cyclic heat-treated specimens follow the relationships da/dN=1.8651×10^(−8)(ΔK)^(3.2271)and da/dN=1.4112×10^(−8)(ΔK)^(3.1125),respectively.Compared with that at the as-deposited state,the microstructure after CHT is transformed from a uniform basket-weave microstructure to a dual-phase microstructure consisting of near-sphericalαandβ-transformed matrix phases.The cyclic process also disrupts the continuity of the grain boundaryα(αGB)at the primaryβ-phase grain boundary.The coarsening of primaryαand the disruption ofαGB continuity are the primary factors to release stress concentration and promote crack deflection,thereby decreasing the fatigue crack growth rate.Additionally,the increased occurrence of crack branching,secondary cracking,and crack bridging in cyclic heat-treated specimens further reduces the crack driving force and slows the fatigue crack growth rate.
基金Guangdong Basic and Applied Basic Research Foundation(2023B1515120050,2023A1515110529 and 2024A1515012454)Shenzhen Science and Technology Program(JCYJ20230807145759008 and KJZD20240903100206009).
文摘Acetolactate synthase(ALS)-targeting herbicides are among the most widely used weed-control chemicals globally.Mutations in the ALS gene can confer herbicide resistance in crops,thereby allowing selective elimination of weeds without harming crops.Herbicide-resistant ALS alleles were initially discovered in weeds and subsequently developed through artificial mutagenesis techniques.With the advancement of CRISPR/Cas technologies,various genome-editing tools are now available to introduce these resistant alleles,as well as novel variants,into diverse crop species.Moreover,emerging methodologies,such as directed evolution,enable the generation and screening of large populations of random ALS mutants.Consequently,ALS has become one of the most extensively targeted genes in plant gene evolution.This paper provides a comprehensive overview of both conventional and recently developed strategies for ALS evolution,with particular emphasis on CRISPR/Cas-based genome editing and directed evolution.Future perspectives on technological application are also discussed.By advancing our understanding of herbicide-resistant ALS allele development for crop improvement,these methodologies may also pave the way for their application to the evolution of other agronomically important genes.
基金supported in part by the National Key R&D Program of China(No.2024YFA1610700)the National Natural Science Foundation of China(No.12475147)。
文摘The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a few hundred MeV/u up to 1 GeV/u.It aims to facilitate research on the quantum chromodynamics(QCD)phase structure in the high-baryondensity region.Collective flow is a fundamental observable in heavy-ion collision experiments,providing information on the bulk properties of the produced matter.Although the standard event plane method has been widely used to measure collective flow,it is still important to validate and optimize this method for the CEE spectrometer.In this paper,we study the experimental procedures for measuring directed flow in^(238)U+^(238)U collisions at 500 MeV/u,using event planes reconstructed by Multi-Wire Drift Chamber and Zero Degree Calorimeter,respectively.Jet AA Microscopic(JAM)transport generator is used to generate events,and the detector response is simulated by the CEE Fast Simulation(CFS)package.Finally,the optimal kinematic region for proton directed flow measurements is discussed for the future CEE experiment.
基金This work is part of the‘Intelligent and Cyber-Secure Platform for Adaptive Optimization in the Simultaneous Operation of Heterogeneous Autonomous Robots(PICRAH4.0)’with reference MIG-20232082,funded by MCIN/AEI/10.13039/501100011033supported by the Universidad Internacional de La Rioja(UNIR)through the Precompetitive Research Project entitled“Nuevos Horizontes en Internet de las Cosas y NewSpace(NEWIOT)”,reference PP-2024-13,funded under the 2024 Call for Research Projects.
文摘This work evaluates an architecture for decentralized authentication of Internet of Things(IoT)devices in Low Earth Orbit(LEO)satellite networks using IOTA Identity technology.To the best of our knowledge,it is the first proposal to integrate IOTA’s Directed Acyclic Graph(DAG)-based identity framework into satellite IoT environments,enabling lightweight and distributed authentication under intermittent connectivity.The system leverages Decentralized Identifiers(DIDs)and Verifiable Credentials(VCs)over the Tangle,eliminating the need for mining and sequential blocks.An identity management workflow is implemented that supports the creation,validation,deactivation,and reactivation of IoT devices,and is experimentally validated on the Shimmer Testnet.Three metrics are defined and measured:resolution time,deactivation time,and reactivation time.To improve robustness,an algorithmic optimization is introduced that minimizes communication overhead and reduces latency during deactivation.The experimental results are compared with orbital simulations of satellite revisit times to assess operational feasibility.Unlike blockchain-based approaches,which typically suffer from high confirmation delays and scalability constraints,the proposed DAG architecture provides fast,cost-free operations suitable for resource-constrained IoT devices.The results show that authentication can be efficiently performed within satellite connectivity windows,positioning IOTA Identity as a viable solution for secure and scalable IoT authentication in LEO satellite networks.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB1714100in part by the National Natural Science Foundation of China(NSFC)under Grant 62371082 and 62001076in part by the Natural Science Foundation of Chongqing under Grant CSTB2023NSCQ-MSX0726 and cstc2020jcyjmsxmX0878.
文摘To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional blockchains limit their application in large-scale FL tasks,and the synchronous traditional FL will also reduce the training efficiency.To address these issues,in this paper,we propose a Directed Acyclic Graph(DAG)blockchain-enabled generalized Federated Dropout(FD)learning strategy,which could improve the efficiency of FL while ensuring the model generalization.Specifically,the DAG maintained by multiple edge servers will guarantee the security and traceability of the data,and the Reputation-based Tips Selection Algorithm(RTSA)is proposed to reduce the blockchain consensus delay.Second,the semi-asynchronous training among Intelligent Devices(IDs)is adopted to improve the training efficiency,and a reputation-based FD technology is proposed to prevent overfitting of the model.In addition,a Hybrid Optimal Resource Allocation(HORA)algorithm is introduced to minimize the network delay.Finally,simulation results demonstrate the effectiveness and superiority of the proposed algorithms.
基金supported by the Key Research and Development Program of Shaanxi Province(2023-YBGY361)the National Natural Science Foundation of China(52275374 and 52205414)+1 种基金the Postdoctoral Fellowship Program of CPSF(GZC20232098)as well as the Xiaomi Foundation through Xiaomi Young Scholar Program。
文摘The layer-by-layer deposition strategy of additive manufacturing makes it ideal to fabricate dissimilar alloy components with varying functionality,which has promising application potential in a large number of industrial areas.In this study,two components composed of ERCuAl-A2 aluminum bronze(CuAl9)and Inconel 718 nickel-based superalloy were fabricated with different deposition orders by wire-arc directed energy deposition.Subject to changes in heat input and thermophysical properties of the substrate,the transition region of the deposited Cu-Ni component with the bottom half of CuAl9 and the top half of Inconel 718 is narrow and serrated.This region features a laminated intermetallic compound layer due to the convection and rapid cooling in the molten pool.In contrast,the Ni-Cu component deposited in the opposite order exhibits a 2 mm gradient transition zone.Within this region,a large number of diverse precipitates were found as well as regional variations in grain size due to the multi-layer partial remelting.Both two components show strong bonds and their tensile specimens tested along the vertical direction always fracture at the softer CuAl9 side.Excellent tensile properties along the horizontal direction were obtained for Cu-Ni(Ultimate tensile strength:573 MPa,yield stress:302 MPa,elongation:22%),while those of Ni-Cu are much lower due to the existence of the solidification cracks in the transition zone.The results from this study provide a reference for the additive manufacturing of Cu/Ni dissimilar alloy components,as well as their microstructure and mechanical properties control.
基金supported by Macao Science and Technology Development Fund,Macao SAR,China(Grant No.:0043/2023/AFJ)the National Natural Science Foundation of China(Grant No.:22173038)Macao Polytechnic University,Macao SAR,China(Grant No.:RP/FCA-01/2022).
文摘Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.
基金supports from the National Natural Science Foundation of China(No.52305440)the Natural Science Foundation of Changsha City(Nos.kq2208272,kq2208274)+1 种基金the Tribology Science Fund of the State Key Laboratory of Tribology in Advanced Equipment(No.SKLTKF22B09)the National Key Research and Development Program of China(No.2022YFB3706902)were acknowledged.
文摘Stainless steel parts with complex shape can be fabricated using additive manufacturing,which do not rely on molds and dies.However,coarse dendrites induced by repeated heating of additive manufacturing result in weak properties,which limits its application.In this study,an in-situ ultrasonic rolling(UR)device was developed to assist the laser directed energy deposition(LDED)process.The microstructural characteristics,as well as the microhardness and wear behavior,were studied for the 316L stainless steel manufactured by in-situ ultrasonic rolling assisted LDED.It is found that austenite,ferrite,and small Si oxides are the main constituents of both the LDED and LDED-UR alloy samples.Under the severe plastic deformation of ultrasonic rolling,the long-branched ferrites by LDED are transformed into the rod-like phases by LDED-UR.Meanwhile,the ferrite is more uniformly distributed in the LDED-UR alloy sample compared with that in LDED alloy sample.Columnar grains with the size of 97.85μm appear in the LDED alloy sample,which is larger than the fully equiaxed grains(22.35μm)of the LDED-UR alloy.The hardness of the LDED-UR alloy sample is about 266.13±13.62 HV_(0.2),which is larger than that of the LDED alloy sample(212.93±12.85 HV_(0.2)).Meanwhile,the wear resistance is also greatly enhanced by applying the assisted in-situ ultrasonic rolling.The achieved high wear resistance can be ascribed to the uniformly distributed hard matter(ferrites)and the impedance of dislocations by high fraction of grain boundaries.Abrasive wear and adhesive wear are identified as the primary wear mechanisms of the studied alloy.Gaining an in-depth understanding of the relationship between wear mechanisms and microstructures offers an effective approach in manufacturing high wear resistant alloys suitable for use in harsh working environments.
基金financial supports from the National Natural Science Foundation of China (No.52305440)the Natural Science Foundation of Changsha City (Nos.kq2208272,kq2208274)+1 种基金the Tribology Science Fund of the State Key Laboratory of Tribology in Advanced Equipment (SKLTKF22B09)the National Key Research and Development Program of China (2022YFB3706902)。
文摘Under the laser directed energy deposition(LDED)process,the rapid melting and solidification usually lead to the emergence of pores and coarse columnar dendrites,which in turn compromise the properties of the deposited alloys.This study introduced in-situ ultrasonic rolling(UR)as an innovative method to enhance the corrosion resistance of LDED specimens,and the microstructural characteristics and their correlation with corrosion resistance were deeply investigated.The findings reveal that the LDED-UR specimen exhibits a reduction in both the fraction and size of pores.Under the influence of severe plastic deformation generated by LDED-UR process,fully equiaxed grains appear with a reduced average size of 28.61μm(compared to63.98μm for the LDED specimen with columnar grains).The electrochemical corrosion resistance of the LDED-UR specimen is significantly enhanced compared to the LDED specimen.This enhanced corrosion resistance can be attributed to the low fraction of small-sized pores,the fine and uniformly distributed Cr-enriched ferrite phase,and the formation of a compact and thick passive film due to dense grain boundaries.The insight of the correlation between microstructure and corrosion behavior opens up a new pathway to enhance the corrosion resistance of LDED specimens.
文摘Interface chemical modulation strategies are considered as promising method to prepare electrocatalysts for the urea oxidation reaction(UOR).However,conventional interface catalysts are generally limited by the inherent activity and incompatibility of the individual components themselves,and the irregular charge distribution and slow charge transfer ability between interfaces severely limit the activity of UOR.Therefore,we optimized and designed a Ni_(2)P/CoP interface with modulated surface charge distribution and directed charge transfer to promote UOR activity.Density functional theorycalculations first predict a regular charge transfer from CoP to Ni_(2)P,which creates a built-in electric field between Ni_(2)P and CoP interface.Optimization of the adsorption/desorption process of UOR/HER reaction intermediates leads to the improvement of catalytic activity.Electrochemical impedance spectroscopy and ex situ X-ray photoelectron spectroscopy characterization confirm the unique mechanism of facilitated reaction at the Ni_(2)P/CoP interface.Electrochemical tests further validated the prediction with excellent UOR/HER activities of 1.28 V and 19.7 mV vs.RHE,at 10 mA cm^(-2),respectively.Furthermore,Ni_(2)P/CoP achieves industrial-grade current densities(500 mA cm^(−2))at 1.75 V and 1.87 V in the overall urea electrolyzer(UOR||HER)and overall human urine electrolyzer(HUOR||HER),respectively,and demonstrates considerable durability.
基金supported by the National Natural Science Foundation of China(52005264).
文摘Solution and aging treatment were conducted on the laser directed energy deposition(LDED)-prepared carbon nanotubes(CNTs)-reinforced WE43(CNTs/WE43)layers to optimize their microstructure and surface properties in this study.The microstructure of the WE43 and CNTs/WE43 layers was systematically compared.The dissolution of divorced eutectics at the grain boundaries was retarded by CNTs during solution treatment.The spot segregation composed of Mg_(24)Y_(5),CNTs,and Zr cores in the solution treated CNTs/WE43 layer presented a slight decreasing in Y content.The grain growth of both types of layers underwent three stages:slow,rapid,and steady-state.The significant inhibitory effect of CNTs on the grain growth of the LDED WE43 matrix was more pronounced than the promoting effect of temperature,resulting in a 47%increase at 510℃ and a 35%increase at 540℃ in the grain growth exponent compared to the WE43 layers at 510℃.During the subsequent aging treatment at 225℃,the precipitation sequences from plate-shaped β″to plate-shaped and globular β′ were observed in both types of layers.CNTs can facilitate an increase in the nucleation rate of precipitates,but without accelerating precipitation hardening rate.The long and short diameters of the precipitates in peak-aged state were decreased by 48.5%and 43.1%by addition of CNTs,respectively.The wear resistance of both the WE43 and CNTs/WE43 layers can be significantly enhanced through solution and aging treatment.The enhancement in wear resistance for the CNTs/WE43 layers is considerably greater than that of the WE43 layers.
基金National Key Research and Development Program of China(2022YFB4602200)。
文摘To address the issues of low accuracy,long time consumption,and high cost of the traditional temperature prediction methods for laser directed energy deposition(LDED),a machine learning model combined with numerical simulation was proposed to predict the temperature during LDED.A finite element(FE)thermal analysis model was established.The model's accuracy was verified through in-situ monitoring experiments,and a basic database for the predictive model was obtained based on FE simulations.Temperature prediction was performed using a generalized regression neural network(GRNN).To reduce dependence on human experience during GRNN parameter tuning and to enhance model prediction performance,an improved adaptive step-size fruit fly optimization algorithm(ASSFOA)was introduced.Finally,the prediction performance of ASSFOA-GRNN model was compared with that of back-propagation neural network model,GRNN model,and fruit fly optimization algorithm(FOA)-GRNN model.The evaluation metrics included the root mean square error(RMSE),mean absolute error(MAE),coefficient of determination(R^(2)),training time,and prediction time.Results show that the ASSFOA-GRNN model exhibits optimal performance regarding RMSE,MAE,and R^(2) indexes.Although its prediction efficiency is slightly lower than that of the FOA-GRNN model,its prediction accuracy is significantly better than that of the other models.This proposed method can be used for temperature prediction in LDED process and also provide a reference for similar methods.
基金supported by National Natural Science Foundation of China:Education Big Data Analysis based on Software Defined Networking Architecture(No.62177019,F0701)。
文摘The ultra-high speed,ultra-low latency,and massive connectivity of the 6 th Generation Mobile Network(6G)present unprecedented challenges to network security.In addition,the deep integration of Artificial Intelligence(AI)into 6G networks introduces AI-native features that further complicate the design and implementation of secure network architectures.To meet the security demands posed by the massive number of devices and edge nodes in 6G networks,a decentralized security architecture is essential,as it effectively mitigates the performance bottlenecks typically associated with centralized systems.Blockchain technology offers a promising trust mechanism among devices in 6G networks.However,conventional blockchain systems suffer from limited scalability under high-load conditions,making them inadequate for supporting a large volume of nodes and frequent data exchanges.To overcome these limitations,We propose Shard-DAG,a scalable architecture that structurally integrates Directed Acyclic Graphs(DAG)and sharding.Each shard adopts a Block-DAG structure for parallel block processing,effectively overcoming the performance bottlenecks of traditional chain-based blockchains.Furthermore,we introduce a DAG-based transaction ordering mechanism within each shard to defend against double-spending attacks.To ensure inter-shard security,Block-DAG adopts a black-box interaction approach to prevent cross-shard double-spending.Theoretical analysis and experimental evaluations demonstrate that Shard-DAG achieves near-linear scalability.In a network of 1,200 nodes with 8 shards,Shard-DAG achieves peak throughput improvements of 14.64 times over traditional blockchains,8.61 times over standalone BlockDAG,and 2.05 times over conventional sharded blockchains.The results validate Shard-DAG's ability to scale efficiently while maintaining robust security properties.
基金supported by National Natural Science Foundation of China under Grants 62203045,62433020 and T2293770。
文摘The issue of privacy leakage in distributed consensus has garnered significant attention over the years,but existing studies often overlook the challenges posed by limited communication in algorithm design.This paper addresses the issue of privacy preservation in distributed weighted average consensus under limited communication scenarios.Specifically targeting directed and unbalanced topologies,we propose a privacy-preserving implementation protocol that incorporates the Paillier homomorphic encryption scheme.The protocol encrypts only the 1-bit quantized messages exchanged between agents,thus ensuring both the correctness of the consensus result and the confidentiality of each agent's initial state.To demonstrate the practicality of the proposed method,we carry out numerical simulations that illustrate its ability to reach consensus effectively while ensuring the protection of private information.
文摘The development of the Internet of Things(IoT)has brought convenience to people’s lives,but it also introduces significant security risks.Due to the limitations of IoT devices themselves and the challenges of re-hosting technology,existing fuzzing for IoT devices is mainly conducted through black-box methods,which lack effective execution feedback and are blind.Meanwhile,the existing static methods mainly rely on taint analysis,which has high overhead and high false alarm rates.We propose a new directed fuzz testing method for detecting bugs in web service programs of IoT devices,which can test IoT devices more quickly and efficiently.Specifically,we identify external input entry points using multiple features.Then we quickly find sensitive targets and paths affected by external input sources based on sensitive data flow analysis of decompiled code,treating them as testing objects.Finally,we performa directed fuzzing test.We use debugging interfaces to collect execution feedback and guide the programto reach sensitive targets based on programpruning techniques.We have implemented a prototype system,AntDFuzz,and evaluated it on firmware fromten devices across five well-known manufacturers.We discovered twelve potential vulnerabilities,seven of which were confirmed and assigned bug id by China National Vulnerability Database(CNVD).The results show that our approach has the ability to find unknown bugs in real devices and is more efficient compared to existing tools.
基金funded by the National Key Research and Development Program of China(2023YFC3903300)the Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project(TSBICIPIJCP-003,TSBICIP-KJGG-009-0203,and TSBICIP-BRFI-005)the Innovation Fund of Haihe Laboratory of Synthetic Biology(22HHSWSS00018)。
文摘The enzymatic depolymerization of polyethylene terephthalate(PET)offers a sustainable approach for the recycling of PET waste.Great efforts have been devoted to engineering PET depolymerases on the substrate binding cleft and the surrounding loops/α-helices on the surface.Here,we report the systematic engineering of whole β-sheet regions in the core of IsPETase(a PETase from Ideonella sakaiensis)via a fluorescent high-throughput screening assay.Twenty-one beneficial substitutions were obtained and iteratively recombined.The best variant,DepoPETase β,with an increase in the melting temperatures(T_(m))of 22.9℃,exhibited superior depolymerization performance and enabled complete depolymerization of100.5 g of untreated post-consumer PET(pc-PET;0.26% W_(enzyme)/W_(PET) enzyme loading)in liter-scale bioreactor at 50℃within 4 d.Crystallization and molecular dynamics simulations revealed that the improved activity and thermostability of DepoPETase β were due to enhanced hydrogen bonds and salt bridges in the β-sheet region,a more tightly packed structure of the core sheets and the surrounding helix,and improved binding of PET to the active sites.This study not only demonstrates the importance of engineering strategy in theβ-sheet region of PET hydrolases but also provides a potential PET depolymerase for large-scale PET recycling.
文摘Causality,the science of cause and effect,has made it possible to create a new family of models.Such models are often referred to as causal models.Unlike those of mathematical,numerical,empirical,or machine learning(ML)nature,causal models hope to tie the cause(s)to the effect(s)pertaining to a phenomenon(i.e.,data generating process)through causal principles.This paper presents one of the first works at creating causal models in the area of structural and construction engineering.To this end,this paper starts with a brief review of the principles of causality and then adopts four causal discovery algorithms,namely,PC(Peter-Clark),FCI(fast causal inference),GES(greedy equivalence search),and GRa SP(greedy relaxation of the sparsest permutation),have been used to examine four phenomena,including predicting the load-bearing capacity of axially loaded members,fire resistance of structural members,shear strength of beams,and resistance of walls against impulsive(blast)loading.Findings from this study reveal the possibility and merit of discovering complete and partial causal models.Finally,this study also proposes two simple metrics that can help assess the performance of causal discovery algorithms.
基金supported by the National Natural Science Foundation of China(Grant Nos.12075199 and 12247172)the Natural Science Foundation of Fujian Province,China(Grant No.2021J01006)the Natural Science Foundation of Jiangxi Province,China(Grant No.20212BAB201024)。
文摘The colored noise disrupts the detailed balance,enabling directed transport in ratchet systems without additional driving forces.Despite a well-established understanding of the conditions for Brownian motors,quantification of the driving effect of colored noise and its connection to deviations from equilibrium remains unexplored.In this study,we examined the directed motion of an overdamped Brownian motor within an asymmetric traveling potential subjected to Ornstein–Uhlenbeck colored noise.We propose a scheme to quantify the driving effect of colored noise by defining an effective force based on the stopping velocity of the traveling potential where directed transport halts.Our results revealed a nonmonotonic dependence of the effective force on the noise correlation time and a monotonic dependence on the noise strength,corresponding to double and single current reversals,respectively.The nonmonotonicity of the current is attributed to the interplay between the fluctuating characteristics and the driving effects of colored noise.
基金supported by the National Key Research and Development Program of China(Nos.2022YFB4600300 and 2022YFB4600301)the National Natural Science Foundation of China(No.52175364)+1 种基金the ND Basic Research Funds of NPU(G2022WD)the Research Fund of the State Key Laboratory of Solidification Processing(NPU),China(No.2023-QZ-04).
文摘The fabrication of Invar/MnCu functionally graded material(FGM)through directed energy deposition(DED)can satisfy the demands for precision devices in aerospace,providing lightweight properties and integrating thermal stability and vibration damping capabilities.However,basic research on Invar/MnCu FGM is still lacking,hindering its potential applications.To address this gap,this study was conducted using mixed powders and consistent process parameters to print experiments for Invar/MnCu FGM and homogeneous samples.Phases,microstructures,compositions,and thermal expansion properties were thoroughly examined.Three types of defects were detected in the Invar/MnCu FGM sample:unmelted Invar 36 powders,cracks,and pores.The mechanism of unmelted powders was deeply discussed,attributing it to material properties influencing laser absorptivity,the required time for melting powder,and effects on solidus temperature.The mechanism of cracks was also discussed,attributing it to theγ-Fe dendritic structure causing low melting point metal to form an intergranular liquid film,harmful secondary phases mismatched with the terminal alloy,and obvious tensile stresses during the DED process.Additionally,an effective strategy was proposed to reduce defects in Invar/MnCu FGM.After optimization,the specimens exhibited excellent tensile properties,with a yield strength of 262±5 MPa,an ultimate tensile strength of 316±7 MPa,and an elongation of 3%±1%.This research provides valuable references and insights for subsequent work,offering robust support for better understanding and designing other FGM.
基金supported by National Natural Science Foundation of China(Grant No.52375312)National Key Research and Development Program of China(Grant No.2023YFB4605900)+3 种基金Liaoning Province Science and Technology Plan Joint Program(Grant No.2023JH2/101700299)Open Research Fund of Key Laboratory of Precision Special Machining and Micromanufacturing Technology of Ministry of Education for Dalian University of Technology(Grant No.B202305)Shenzhen National Major Science and Technology Projects(Grant No.CJGJZD20240729113704006)Shenzhen Key Technology R&D Programs(Grant No.JSGG20210420091802007).
文摘Laser-directed energy deposition(LDED)technology has demonstrated great potential for the rapid and integrated fabrication of nickel-based superalloy components.The plastic deformation-assisted method is crucial for achieving grain refinement and microstructural homogeneity in LDED-fabricated superalloys.However,existing methods suffer from uniformity constraints owing to their high deformation resistance,which significantly limits their application in load-bearing components.To address these issues,a synchronous-hot-forging-assisted(SHFA)LDED additive manufacturing method was proposed,and its effects on the macroscopic morphology,microstructure,and mechanical properties of GH4169 nickel-based alloy specimens were systematically compared.The results demonstrated up to 30.1%average plastic deformation in hot-forging components while maintaining good surface flatness.The synergistic effect of dislocation accumulation and dynamic recrystallization during hot forging enables dramatic grain refinement,reducing the average grain size by 89.1%(from 168.5μm to 18.4μm)while weakening texture intensity from 15.31 to 2.15,ultimately promoting equiaxed grain formation.The pores of hot-forging components changed from fine round to flat,the porosity decreased from 0.264%to 0.089%,and the densification level was significantly improved.With the increase in the synchronous hot-forging force,the average ultimate tensile strength of hot-forging components can reach 1175.1 MPa,while the anisotropy difference is gradually weakened.The SHFA-LDED process not only achieves excellent grain refinement and microstructure homogenization but also enhances mechanical properties,providing a new technical path for the additive manufacturing of high-performance nickel-based superalloy components.
