Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerge...This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.展开更多
Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class at...Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.展开更多
BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To ...BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.展开更多
In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapi...In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.展开更多
Clarify the mechanical properties of different laminations and the fracture mechanism of continental shale under in-situ stress can provide theoretical basis for more comprehensive evaluation of the fracability of con...Clarify the mechanical properties of different laminations and the fracture mechanism of continental shale under in-situ stress can provide theoretical basis for more comprehensive evaluation of the fracability of continental shale oil reservoir.The Chang 72continental shale was used to investigate the mechanical properties of laminations and the effect of natural structure on the crack propagation of the shale.The XRD and thin section tests show that the laminations contain two types:bright sandy lamination with void structure and dark muddy lamination with layer structure.The real-time CT uniaxial compression tests were conducted to investigate the differences of mechanical properties between the muddy lamination and sandy lamination.It found that the uniaxial compression strength and elastic modulus of the sandy lamination are higher,forming a simple crack with large opening,and the Poisson's ratio of the muddy lamination is large,forming obvious lateral deformation and more secondary cracks.On this basis,the cuboid-shaped continental shale specimens were tested under true triaxial compression conditions to study the effect of laminations and interface cracks on crack propagation combining AE and CT techniques.It found that nascent cracks connected laminations and interface cracks to form fracture network under appropriate loading condition,tensile cracks developed in sandy lamination and shear cracks occurred in muddy lamination because of deformation dissonance and brittleness index differences,and more secondary cracks formed in muddy lamination with smaller fracture toughness.Moreover,the combination relationships between nascent and natural cracks mainly conclude direct penetration and deflection,which is affected by the filling degree and morphology of interface cracks and the relationship of lamination types.These conclusions show that laminar continental shale is conducive to forming complex fracture network,which can provide a theoretical basis for the proposal of indicators and methods for fracability evaluation.展开更多
This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fib...This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fiber surface subjected to the blast load.Each of the two layers that make up the double-curved shell structure is made up of an auxetic honeycomb core and two laminated sheets of three-phase polymer/GNP/fiber.The exterior is supported by a Kerr elastic foundation with three characteristics.The key innovation of the proposed theory is that the transverse shear stresses are zero at two free surfaces of each layer.In contrast to previous first-order shear deformation theories,no shear correction factor is required.Navier's exact solution was used to treat the double-curved shell problem with a single title boundary,while the finite element technique and an eight-node quadrilateral were used to address the other boundary requirements.To ensure the accuracy of these results,a thorough comparison technique is employed in conjunction with credible statements.The problem model's edge cases allow for this kind of analysis.The study's findings may be used in the post-construction evaluation of military and civil works structures for their ability to sustain explosive loads.In addition,this is also an important basis for the calculation and design of shell structures made of smart materials when subjected to shock waves or explosive loads.展开更多
Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero....Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.展开更多
This study attempts to develop a reproducible thin-film formation technique called vacuum-free(VF)lamination,which transfers thin films using elastomeric polymer-based laminating mediators.Precisely,by controlling the...This study attempts to develop a reproducible thin-film formation technique called vacuum-free(VF)lamination,which transfers thin films using elastomeric polymer-based laminating mediators.Precisely,by controlling the interface characteristics of the mediator based on the work of adhesion,VF lamination is successfully performed for various thicknesses(from 20 to 240 nm)of a conjugated photoactive material composed of poly[(2,6-(4,8-bis(5-(2-ethylhexyl-3-fluoro)thiophen-2-yl)-benzo[1,2-b:4,5-bʹ]dithiophene))-alt-(5,5-(1ʹ,3ʹ-di-2-thienyl-5ʹ,7ʹ-bis(2-ethylhexyl)benzo[1ʹ,2ʹ-c:4ʹ,5ʹ-cʹ]dithiophene-4,8-dione)](a polymer donor)and 2,2ʹ-((2Z,2ʹZ)-((12,13-bis(2-butyloctyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2ʹʹ,3ʹʹ:4ʹ,5ʹ]thieno[2ʹ,3ʹ:4,5]pyrrolo[3,2-g]thieno[2ʹ,3ʹ:4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile(a nonfullerene acceptor).Interestingly,the organic photovoltaic and photodetecting applications,prepared by the VF lamination process,showed superior performance compared to those of devices prepared by conventional spin-coating.This is due to the overturned surface morphology,which led to enhanced charge transport ability and blocking of the externally injected charge.Thus,the reproducible VF lamination process,exploiting an adhesion-based elastomeric polymer mediator,is a promising thin-film formation technique for developing efficient next-generation organic optoelectronic materials consistent with the solution process.展开更多
Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain les...Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.展开更多
In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the oper...In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.展开更多
Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design o...Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.展开更多
Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4...Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4/TB8 titanium(Ti)laminates,inspired by theheterostructures of natural biological shells,were fabricated using a hybrid diffusion bonding-hot rolling process followed by an aging treatment,resulting in an architected micro structure.The laminate achieves an ultra-high yield stress of 1020 MPa and proper uniform elongation of 4.2%at 500℃.The TB8 layers with high-density nano-precipitates and dislocations act as hard zone,contributing to high strength.The TC4 layers,with their bimodal structure consisting of coarse and fine grains characterized by equiaxed and lamellar structures,experience more plastic strain than the TB8 layers.The hetero deformation associated with the detwinning ofαgrains in the TC4 layer induces toughening at high temperatures.展开更多
Plasma electrolytic oxidation(PEO)coatings were prepared on Al−Mg laminated macro composites(LMCs)using both unipolar and bipolar waveforms in an appropriate electrolyte for both aluminum and magnesium alloys.The tech...Plasma electrolytic oxidation(PEO)coatings were prepared on Al−Mg laminated macro composites(LMCs)using both unipolar and bipolar waveforms in an appropriate electrolyte for both aluminum and magnesium alloys.The techniques of FESEM/EDS,grazing incident beam X-ray diffraction(GIXRD),and electrochemical methods of potentiodynamic polarization and electrochemical impedance spectroscopy(EIS)were used to characterize the coatings.The results revealed that the coatings produced using the bipolar waveform exhibited lower porosity and higher thickness than those produced using the unipolar one.The corrosion performance of the specimens’cut edge was investigated using EIS after 1,8,and 12 h of immersion in a 3.5 wt.%NaCl solution.It was observed that the coating produced using the bipolar waveform demonstrated the highest corrosion resistance after 12 h of immersion,with an estimated corrosion resistance of 5.64 kΩ·cm^(2),which was approximately 3 times higher than that of the unipolar coating.Notably,no signs of galvanic corrosion were observed in the LMCs,and only minor corrosion attacks were observed on the magnesium layer in some areas.展开更多
A flexible copper clad laminate(FCCL) was fabricated using electroless-and electro-Cu plating processes and the effects of pre-treatment time on the adhesion strength of the FCCL were evaluated based on interfacial mo...A flexible copper clad laminate(FCCL) was fabricated using electroless-and electro-Cu plating processes and the effects of pre-treatment time on the adhesion strength of the FCCL were evaluated based on interfacial morphology.The neutralization and catalyst time were varied in the range of 0-20 min and 0.1-10 min,respectively,and the interfacial condition of the FCCL was characterized by atomic force microscopy(AFM) and X-ray photoelectron spectroscopy(XPS).It is observed that the peel strength increases significantly as the neutralization and catalyst time increase.Peel strength as high as 7.2-7.3 N/cm is obtained as the neutralization and catalyst time increase up to 20 min and 10 min,respectively,which is comparable to the strength achieved by the conventional laminating and sputtering processes.These improvements are probably due to an increase in the surface roughness of polyimide(PI),the activated surface condition,and the adsorption of palladium ions/atoms(Pd) on the PI surface which act as nucleation sites for Cu.展开更多
This study aims to investigate the propagation of harmonic waves in nonlocal magneto-electro-elastic(MEE)laminated composites with interface stress imperfections using an analytical approach.The pseudo-Stroh formulati...This study aims to investigate the propagation of harmonic waves in nonlocal magneto-electro-elastic(MEE)laminated composites with interface stress imperfections using an analytical approach.The pseudo-Stroh formulation and nonlocal theory proposed by Eringen were adopted to derive the propagator matrix for each layer.Both the propagator and interface matrices were formulated to determine the recursive fields.Subsequently,the dispersion equation was obtained by imposing traction-free and magneto-electric circuit open boundary conditions on the top and bottom surfaces of the plate.Dispersion curves,mode shapes,and natural frequencies were calculated for sandwich plates composed of BaTiO3 and CoFe2O4.Numerical simulations revealed that both interface stress and the nonlocal effect influenced the tuning of the dispersion curve and mode shape for the given layup.The nonlocal effect caused a significant decrease in the dispersion curves,particularly in the high-frequency regions.Additionally,compared to the nonlocal effect,the interface stress exerted a greater influence on the mode shapes.The generalized analytical framework developed in this study provides an effective tool for both the theoretical analysis and practical design of MEE composite laminates.展开更多
A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free b...A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free boundary condition in other directions.In the present study,partial-periodic model for composite laminate beam structures is particularly studied.Three-point bending experiments for laminate beam specimens with different laying parameters are firstly used to verify the present partial-periodic model.In addition,a detailed finite element method(FEM)model is also used to further quantitatively compare with the present partial-periodic model for composite laminate beams with different laying parameters.The results indicate that the proposed partial-periodic model is capable of providing accurate predictions in most cases.The computational time cost of the proposed partial-periodic model is much lower than that of the detailed FEM model as well.Convergence studies are also conducted for the present partial-periodic model with different model sizes and element sizes.It is suggested that the proposed partial-periodic model has the potential to be used as an accurate and time-saving tool for predicting the structural properties of composite laminate beam structures.展开更多
The remarkable mechanical properties exhibited by laminated structures have generated significant in-terest in the realm of additively manufactured laminated high-entropy alloys(HEAs).Despite this bur-geoning interest...The remarkable mechanical properties exhibited by laminated structures have generated significant in-terest in the realm of additively manufactured laminated high-entropy alloys(HEAs).Despite this bur-geoning interest,the nexus between process,structure,and properties within laminated HEAs remains largely uncharted.There is a vast space for investigating the effect of the typical heterogeneous interface on the macroscopic mechanical properties.This study focuses on the influence of the characteristic het-erogeneous interface on macroscopic mechanical properties of laminated HEAs,particularly anisotropy.Using the 3D-printed Fe_(50)Mn_(30)Co_(10)Cr_(10)-CoCrNi HEA as a model,we investigate the impact of interface geometry on mechanical characteristics.Tensile tests show that the reduced interface spacing increases yield strength.This laminated HEA displays significant anisotropy in strength and ductility,depending on the loading direction relative to the interface.Electron microscopic observations suggest that finer layer spacing enhances interface and dislocation strengthening,increasing yield strength.Anisotropic behaviors are confirmed to be mediated by interface orientation,explained in terms of deformation compatibility and crack development at the interface.This research offers fundamental insights into the relationship between heterogeneous interfaces and the mechanical properties in laminated HEAs.The knowledge is vital for designing,fabricating,and optimizing laminated HEAs through additive manufacturing,advancing their engineering applications.展开更多
Three types of Al/Al−27%Si laminated composites,each containing 22%Si,were fabricated via hot pressing and hot rolling.The microstructures,mechanical properties and thermo-physical properties of these composites were ...Three types of Al/Al−27%Si laminated composites,each containing 22%Si,were fabricated via hot pressing and hot rolling.The microstructures,mechanical properties and thermo-physical properties of these composites were investigated.The results demonstrated that the three laminated composites exhibited similar microstructural features,characterized by well-bonded interfaces between the Al layer and the Al−27%Si alloy layer.The tensile and flexural strengths of the composites were significantly higher than those of both Al−22%Si and Al−27%Si alloys.These strengths increased gradually with decreasing the layer thickness,reaching peak values of 222.5 and 407.4 MPa,respectively.Crack deflection was observed in the cross-sections of the bending fracture surfaces,which contributed to the enhanced strength and toughness.In terms of thermo-physical properties,the thermal conductivity of the composites was lower than that of Al−22%Si and Al−27%Si alloys.The minimum reductions in thermal conductivity were 6.8%and 0.9%for the T3 laminated composite,respectively.Additionally,the coefficient of thermal expansion of the composites was improved,exhibiting varying temperature-dependent behaviors.展开更多
Heterogeneous laminated structure(HLS)design offers new opportunities to enhance the mechanical performance of high-entropy alloys(HEAs)through synergistic effects from heterogeneity.However,it remains challenging to ...Heterogeneous laminated structure(HLS)design offers new opportunities to enhance the mechanical performance of high-entropy alloys(HEAs)through synergistic effects from heterogeneity.However,it remains challenging to introduce the HLS into HEAs via severe plastic deformation due to their strong work-hardening capacity.In this study,a specially designed multi-level HLS,characterized by alterna-tively stacked micro-grained soft CoCrFeNi layers and nanostructured ultra-hard Al_(0.3)CoCrFeNi layers con-taining a three-phase microstructure(composed of nanograined face-centered cubic matrix,(Al,Ni)-rich B2 precipitates,and Cr-richσprecipitates),is controllably introduced into FCC HEAs via a conventional thermo-mechanical processing involving hot-pressing,cold-rolling,and annealing.Meanwhile,thermo-mechanical processing induces Al element diffusion across the layer interface,resulting in the formation of an interfacial transition layer and the establishment of a strong interface bonding between the neigh-boring CoCrFeNi and Al_(0.3)CoCrFeNi layers.As a result,the multi-level HLSed CoCrFeNi/Al_(0.3)CoCrFeNi com-posite exhibits a yield strength as high as 1127±25.4 MPa while maintaining a large fracture elongation(up to(26.3±2.4)%).Such an excellent strength-ductility synergy surpasses that of most previously reported high-performance monolithic bulk CoCrFeNi and Al_(0.3)CoCrFeNi HEAs prepared through care-ful chemical composition optimization and/or thermo-mechanical processing.Strong hetero-deformation induced strengthening benefited from the apparent microstructural/microhardness difference and the strong interface bonding between the neighbouring CoCrFeNi and Al03CoCrFeNi layers,together with si-multaneous activation of multiple strain hardening mechanisms containing mechanical twinning,stack-ing faults and precipitation strengthening,is responsible for the excellent strength-ductility combination.This multi-level HLS and its fabrication strategy provide an enlightening way to develop strong and duc-tile HEAs and can also be applied to high-performance designs of other metallic materials.展开更多
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
基金supported by MHRD as researcher C.K.Neog received the MHRD Institute GATE scholarship from Govt.of India.
文摘This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)—Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156334)in part by Liaoning Province Nature Fund Project(2024-BSLH-214).
文摘Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
基金Supported by Talent Scientific Research Start-up Foundation of Wannan Medical College,No.WYRCQD2023045.
文摘BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.
基金supported by the Basic Scientific Research Business Fund Project of Higher Education Institutions in Heilongjiang Province(145409601)the First Batch of Experimental Teaching and Teaching Laboratory Construction Research Projects in Heilongjiang Province(SJGZ20240038).
文摘In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.
基金funded by the National Natural Science Foundation of China(42102309 and 42007243)the Natural Science Foundation of Liaoning Province(2023-MSBA-120)the National Key Research and Development Program(2022YFB3304705)。
文摘Clarify the mechanical properties of different laminations and the fracture mechanism of continental shale under in-situ stress can provide theoretical basis for more comprehensive evaluation of the fracability of continental shale oil reservoir.The Chang 72continental shale was used to investigate the mechanical properties of laminations and the effect of natural structure on the crack propagation of the shale.The XRD and thin section tests show that the laminations contain two types:bright sandy lamination with void structure and dark muddy lamination with layer structure.The real-time CT uniaxial compression tests were conducted to investigate the differences of mechanical properties between the muddy lamination and sandy lamination.It found that the uniaxial compression strength and elastic modulus of the sandy lamination are higher,forming a simple crack with large opening,and the Poisson's ratio of the muddy lamination is large,forming obvious lateral deformation and more secondary cracks.On this basis,the cuboid-shaped continental shale specimens were tested under true triaxial compression conditions to study the effect of laminations and interface cracks on crack propagation combining AE and CT techniques.It found that nascent cracks connected laminations and interface cracks to form fracture network under appropriate loading condition,tensile cracks developed in sandy lamination and shear cracks occurred in muddy lamination because of deformation dissonance and brittleness index differences,and more secondary cracks formed in muddy lamination with smaller fracture toughness.Moreover,the combination relationships between nascent and natural cracks mainly conclude direct penetration and deflection,which is affected by the filling degree and morphology of interface cracks and the relationship of lamination types.These conclusions show that laminar continental shale is conducive to forming complex fracture network,which can provide a theoretical basis for the proposal of indicators and methods for fracability evaluation.
文摘This work uses refined first-order shear theory to analyze the free vibration and transient responses of double-curved sandwich two-layer shells made of auxetic honeycomb core and laminated three-phase polymer/GNP/fiber surface subjected to the blast load.Each of the two layers that make up the double-curved shell structure is made up of an auxetic honeycomb core and two laminated sheets of three-phase polymer/GNP/fiber.The exterior is supported by a Kerr elastic foundation with three characteristics.The key innovation of the proposed theory is that the transverse shear stresses are zero at two free surfaces of each layer.In contrast to previous first-order shear deformation theories,no shear correction factor is required.Navier's exact solution was used to treat the double-curved shell problem with a single title boundary,while the finite element technique and an eight-node quadrilateral were used to address the other boundary requirements.To ensure the accuracy of these results,a thorough comparison technique is employed in conjunction with credible statements.The problem model's edge cases allow for this kind of analysis.The study's findings may be used in the post-construction evaluation of military and civil works structures for their ability to sustain explosive loads.In addition,this is also an important basis for the calculation and design of shell structures made of smart materials when subjected to shock waves or explosive loads.
基金supported by the Scientific Research Project of Xiang Jiang Lab(22XJ02003)the University Fundamental Research Fund(23-ZZCX-JDZ-28)+5 种基金the National Science Fund for Outstanding Young Scholars(62122093)the National Natural Science Foundation of China(72071205)the Hunan Graduate Research Innovation Project(ZC23112101-10)the Hunan Natural Science Foundation Regional Joint Project(2023JJ50490)the Science and Technology Project for Young and Middle-aged Talents of Hunan(2023TJ-Z03)the Science and Technology Innovation Program of Humnan Province(2023RC1002)。
文摘Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF)funded by the Ministry of Science,ICT (MSIT) (Grant Nos.2023R1A2C2008021 and RS-2023-00217270)supported by the Technology Innovation Program (Grant No.20017439,“Development of manufacturing process technique on high-speed signal transmission line for 6G device,”and Grant No.20021915,“Development on Nanocomposite Material of Optical Film[GPa]for Foldable Devices”)funded by the Ministry of Trade,Industry&Energy (MOTIE,Korea).
文摘This study attempts to develop a reproducible thin-film formation technique called vacuum-free(VF)lamination,which transfers thin films using elastomeric polymer-based laminating mediators.Precisely,by controlling the interface characteristics of the mediator based on the work of adhesion,VF lamination is successfully performed for various thicknesses(from 20 to 240 nm)of a conjugated photoactive material composed of poly[(2,6-(4,8-bis(5-(2-ethylhexyl-3-fluoro)thiophen-2-yl)-benzo[1,2-b:4,5-bʹ]dithiophene))-alt-(5,5-(1ʹ,3ʹ-di-2-thienyl-5ʹ,7ʹ-bis(2-ethylhexyl)benzo[1ʹ,2ʹ-c:4ʹ,5ʹ-cʹ]dithiophene-4,8-dione)](a polymer donor)and 2,2ʹ-((2Z,2ʹZ)-((12,13-bis(2-butyloctyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2ʹʹ,3ʹʹ:4ʹ,5ʹ]thieno[2ʹ,3ʹ:4,5]pyrrolo[3,2-g]thieno[2ʹ,3ʹ:4,5]thieno[3,2-b]indole-2,10-diyl)bis(methanylylidene))bis(5,6-difluoro-3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile(a nonfullerene acceptor).Interestingly,the organic photovoltaic and photodetecting applications,prepared by the VF lamination process,showed superior performance compared to those of devices prepared by conventional spin-coating.This is due to the overturned surface morphology,which led to enhanced charge transport ability and blocking of the externally injected charge.Thus,the reproducible VF lamination process,exploiting an adhesion-based elastomeric polymer mediator,is a promising thin-film formation technique for developing efficient next-generation organic optoelectronic materials consistent with the solution process.
文摘Effective small object detection is crucial in various applications including urban intelligent transportation and pedestrian detection.However,small objects are difficult to detect accurately because they contain less information.Many current methods,particularly those based on Feature Pyramid Network(FPN),address this challenge by leveraging multi-scale feature fusion.However,existing FPN-based methods often suffer from inadequate feature fusion due to varying resolutions across different layers,leading to suboptimal small object detection.To address this problem,we propose the Two-layerAttention Feature Pyramid Network(TA-FPN),featuring two key modules:the Two-layer Attention Module(TAM)and the Small Object Detail Enhancement Module(SODEM).TAM uses the attention module to make the network more focused on the semantic information of the object and fuse it to the lower layer,so that each layer contains similar semantic information,to alleviate the problem of small object information being submerged due to semantic gaps between different layers.At the same time,SODEM is introduced to strengthen the local features of the object,suppress background noise,enhance the information details of the small object,and fuse the enhanced features to other feature layers to ensure that each layer is rich in small object information,to improve small object detection accuracy.Our extensive experiments on challenging datasets such as Microsoft Common Objects inContext(MSCOCO)and Pattern Analysis Statistical Modelling and Computational Learning,Visual Object Classes(PASCAL VOC)demonstrate the validity of the proposedmethod.Experimental results show a significant improvement in small object detection accuracy compared to state-of-theart detectors.
文摘In the context of China’s“double carbon”goals and rural revitalization strategy,the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids.Considering the operational characteristics of rural microgrids and their impact on users,this paper establishes a two-layer scheduling model incorporating flexible loads.The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid,while the lower-layer aims to minimize the total electricity cost for rural users.An Improved Adaptive Genetic Algorithm(IAGA)is proposed to solve the model.Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations,enhance microgrid stability,increase clean energy consumption,and balance microgrid operating costs with user benefits.
基金supports for this research were provided by the National Natural Science Foundation of China(No.12272301,12002278,U1906233)the Guangdong Basic and Applied Basic Research Foundation,China(Nos.2023A1515011970,2024A1515010256)+1 种基金the Dalian City Supports Innovation and Entrepreneurship Projects for High-Level Talents,China(2021RD16)the Key R&D Project of CSCEC,China(No.CSCEC-2020-Z-4).
文摘Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consider the variable stiffness design optimization of typical non-perforated and perforated composite laminates with circular, square, and irregular holes, and systematically discuss the number of candidate discrete fiber laying angles, discrete fiber continuous filtering strategies, and filter radius on structural compliance, continuity, and manufacturability. The optimized discrete fiber angles of variable stiffness laminates are converted into continuous fiber laying paths using a streamlined process for continuous fiber additive manufacturing. Meanwhile, the optimized non-perforated and perforated MBB beams after discrete fiber continuous treatment, are manufactured using continuous fiber co-extrusion additive manufacturing technology to verify the effectiveness of the variable stiffness fiber optimization framework proposed in this paper.
基金financially supported by the Natural Science Foundation of Changsha,China(No.kq2402015)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIP)(Nos.NRF-2021R1A2C3006662 and NRF-2022R1A5A1030054)supported by Brain Pool Program through the NRF of Korea,funded by the Ministry of Science and ICT(No.NRF-RS_(2)02300263999)
文摘Lightweight,high-strength,and heat-resistant protective structures have consistently been crucial for applications in extreme environments,such as aerospace,semiconductors,and nuclear power industries.Multilayered TC4/TB8 titanium(Ti)laminates,inspired by theheterostructures of natural biological shells,were fabricated using a hybrid diffusion bonding-hot rolling process followed by an aging treatment,resulting in an architected micro structure.The laminate achieves an ultra-high yield stress of 1020 MPa and proper uniform elongation of 4.2%at 500℃.The TB8 layers with high-density nano-precipitates and dislocations act as hard zone,contributing to high strength.The TC4 layers,with their bimodal structure consisting of coarse and fine grains characterized by equiaxed and lamellar structures,experience more plastic strain than the TB8 layers.The hetero deformation associated with the detwinning ofαgrains in the TC4 layer induces toughening at high temperatures.
文摘Plasma electrolytic oxidation(PEO)coatings were prepared on Al−Mg laminated macro composites(LMCs)using both unipolar and bipolar waveforms in an appropriate electrolyte for both aluminum and magnesium alloys.The techniques of FESEM/EDS,grazing incident beam X-ray diffraction(GIXRD),and electrochemical methods of potentiodynamic polarization and electrochemical impedance spectroscopy(EIS)were used to characterize the coatings.The results revealed that the coatings produced using the bipolar waveform exhibited lower porosity and higher thickness than those produced using the unipolar one.The corrosion performance of the specimens’cut edge was investigated using EIS after 1,8,and 12 h of immersion in a 3.5 wt.%NaCl solution.It was observed that the coating produced using the bipolar waveform demonstrated the highest corrosion resistance after 12 h of immersion,with an estimated corrosion resistance of 5.64 kΩ·cm^(2),which was approximately 3 times higher than that of the unipolar coating.Notably,no signs of galvanic corrosion were observed in the LMCs,and only minor corrosion attacks were observed on the magnesium layer in some areas.
基金supported by Grant No.RTI04-03-04 from the Regional Technology Innovation Program of the Ministry of Commerce,Industry and Energy (MOCIE),Korea
文摘A flexible copper clad laminate(FCCL) was fabricated using electroless-and electro-Cu plating processes and the effects of pre-treatment time on the adhesion strength of the FCCL were evaluated based on interfacial morphology.The neutralization and catalyst time were varied in the range of 0-20 min and 0.1-10 min,respectively,and the interfacial condition of the FCCL was characterized by atomic force microscopy(AFM) and X-ray photoelectron spectroscopy(XPS).It is observed that the peel strength increases significantly as the neutralization and catalyst time increase.Peel strength as high as 7.2-7.3 N/cm is obtained as the neutralization and catalyst time increase up to 20 min and 10 min,respectively,which is comparable to the strength achieved by the conventional laminating and sputtering processes.These improvements are probably due to an increase in the surface roughness of polyimide(PI),the activated surface condition,and the adsorption of palladium ions/atoms(Pd) on the PI surface which act as nucleation sites for Cu.
基金supported by the Ministry of Science and Technology Taiwan under Grant No.MOST 109-2628-E-009-002-MY3.
文摘This study aims to investigate the propagation of harmonic waves in nonlocal magneto-electro-elastic(MEE)laminated composites with interface stress imperfections using an analytical approach.The pseudo-Stroh formulation and nonlocal theory proposed by Eringen were adopted to derive the propagator matrix for each layer.Both the propagator and interface matrices were formulated to determine the recursive fields.Subsequently,the dispersion equation was obtained by imposing traction-free and magneto-electric circuit open boundary conditions on the top and bottom surfaces of the plate.Dispersion curves,mode shapes,and natural frequencies were calculated for sandwich plates composed of BaTiO3 and CoFe2O4.Numerical simulations revealed that both interface stress and the nonlocal effect influenced the tuning of the dispersion curve and mode shape for the given layup.The nonlocal effect caused a significant decrease in the dispersion curves,particularly in the high-frequency regions.Additionally,compared to the nonlocal effect,the interface stress exerted a greater influence on the mode shapes.The generalized analytical framework developed in this study provides an effective tool for both the theoretical analysis and practical design of MEE composite laminates.
基金financial support from the National Key Research and Development Plan(2022YFB3707700)the National Natural Science Foundation of China(11872138 and 12172074)+1 种基金the Liaoning Revitalization Talents Program(XLYC2001003)the Dalian Excellent Young Science and Technology Talent Program(2023RY025).
文摘A partial-periodic model is proposed for predicting structural properties of composite laminate structures.The partial-periodic model contains periodic boundary conditions in one direction or two directions,and free boundary condition in other directions.In the present study,partial-periodic model for composite laminate beam structures is particularly studied.Three-point bending experiments for laminate beam specimens with different laying parameters are firstly used to verify the present partial-periodic model.In addition,a detailed finite element method(FEM)model is also used to further quantitatively compare with the present partial-periodic model for composite laminate beams with different laying parameters.The results indicate that the proposed partial-periodic model is capable of providing accurate predictions in most cases.The computational time cost of the proposed partial-periodic model is much lower than that of the detailed FEM model as well.Convergence studies are also conducted for the present partial-periodic model with different model sizes and element sizes.It is suggested that the proposed partial-periodic model has the potential to be used as an accurate and time-saving tool for predicting the structural properties of composite laminate beam structures.
基金supported by the National Natural Science Foundation of China(No.12272392 and 11790292)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB22040303)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(No.2022020).
文摘The remarkable mechanical properties exhibited by laminated structures have generated significant in-terest in the realm of additively manufactured laminated high-entropy alloys(HEAs).Despite this bur-geoning interest,the nexus between process,structure,and properties within laminated HEAs remains largely uncharted.There is a vast space for investigating the effect of the typical heterogeneous interface on the macroscopic mechanical properties.This study focuses on the influence of the characteristic het-erogeneous interface on macroscopic mechanical properties of laminated HEAs,particularly anisotropy.Using the 3D-printed Fe_(50)Mn_(30)Co_(10)Cr_(10)-CoCrNi HEA as a model,we investigate the impact of interface geometry on mechanical characteristics.Tensile tests show that the reduced interface spacing increases yield strength.This laminated HEA displays significant anisotropy in strength and ductility,depending on the loading direction relative to the interface.Electron microscopic observations suggest that finer layer spacing enhances interface and dislocation strengthening,increasing yield strength.Anisotropic behaviors are confirmed to be mediated by interface orientation,explained in terms of deformation compatibility and crack development at the interface.This research offers fundamental insights into the relationship between heterogeneous interfaces and the mechanical properties in laminated HEAs.The knowledge is vital for designing,fabricating,and optimizing laminated HEAs through additive manufacturing,advancing their engineering applications.
基金supported by the National Natural Science Foundation of China(No.52274369)the National Key Laboratory of Science and Technology on High-strength Structural Materials,China(No.623020034).
文摘Three types of Al/Al−27%Si laminated composites,each containing 22%Si,were fabricated via hot pressing and hot rolling.The microstructures,mechanical properties and thermo-physical properties of these composites were investigated.The results demonstrated that the three laminated composites exhibited similar microstructural features,characterized by well-bonded interfaces between the Al layer and the Al−27%Si alloy layer.The tensile and flexural strengths of the composites were significantly higher than those of both Al−22%Si and Al−27%Si alloys.These strengths increased gradually with decreasing the layer thickness,reaching peak values of 222.5 and 407.4 MPa,respectively.Crack deflection was observed in the cross-sections of the bending fracture surfaces,which contributed to the enhanced strength and toughness.In terms of thermo-physical properties,the thermal conductivity of the composites was lower than that of Al−22%Si and Al−27%Si alloys.The minimum reductions in thermal conductivity were 6.8%and 0.9%for the T3 laminated composite,respectively.Additionally,the coefficient of thermal expansion of the composites was improved,exhibiting varying temperature-dependent behaviors.
基金supported by the National Natural Science Foundation of China(No.52361021)the Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province(No.20232BCJ23001)+1 种基金the Jiangxi Provincial Natural Science Foundation(No.20232ACB214003)the Jiangxi Province Major Science&Technology Research&Development Project(No.20223AAG01009).
文摘Heterogeneous laminated structure(HLS)design offers new opportunities to enhance the mechanical performance of high-entropy alloys(HEAs)through synergistic effects from heterogeneity.However,it remains challenging to introduce the HLS into HEAs via severe plastic deformation due to their strong work-hardening capacity.In this study,a specially designed multi-level HLS,characterized by alterna-tively stacked micro-grained soft CoCrFeNi layers and nanostructured ultra-hard Al_(0.3)CoCrFeNi layers con-taining a three-phase microstructure(composed of nanograined face-centered cubic matrix,(Al,Ni)-rich B2 precipitates,and Cr-richσprecipitates),is controllably introduced into FCC HEAs via a conventional thermo-mechanical processing involving hot-pressing,cold-rolling,and annealing.Meanwhile,thermo-mechanical processing induces Al element diffusion across the layer interface,resulting in the formation of an interfacial transition layer and the establishment of a strong interface bonding between the neigh-boring CoCrFeNi and Al_(0.3)CoCrFeNi layers.As a result,the multi-level HLSed CoCrFeNi/Al_(0.3)CoCrFeNi com-posite exhibits a yield strength as high as 1127±25.4 MPa while maintaining a large fracture elongation(up to(26.3±2.4)%).Such an excellent strength-ductility synergy surpasses that of most previously reported high-performance monolithic bulk CoCrFeNi and Al_(0.3)CoCrFeNi HEAs prepared through care-ful chemical composition optimization and/or thermo-mechanical processing.Strong hetero-deformation induced strengthening benefited from the apparent microstructural/microhardness difference and the strong interface bonding between the neighbouring CoCrFeNi and Al03CoCrFeNi layers,together with si-multaneous activation of multiple strain hardening mechanisms containing mechanical twinning,stack-ing faults and precipitation strengthening,is responsible for the excellent strength-ductility combination.This multi-level HLS and its fabrication strategy provide an enlightening way to develop strong and duc-tile HEAs and can also be applied to high-performance designs of other metallic materials.
