With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach...With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach is proposed to rapidly construct full-scale meso-finite element models for Outer Reduction Yarn Woven Composites(ORYWC)and Inner Reduction Yarn Woven Composites(IRYWC).Then,six independent damage variables are identified:yarn fiber tension/compression,yarn matrix tension/compression,and resin matrix tension/compression.These variables are utilized to establish the constitutive equation of woven composites,considering the coupling effects of microscopic damage.Finally,combined with the Hashin failure criterion and von Mises failure criterion,the strength prediction model is implemented in ANSYS using APDL language to simulate the strength failure process of 2.5DWVTC.The results show that the predicted stiffness and strength values of various parts of ORYWC and IRYWC are in good agreement with the relevant test results.展开更多
An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of t...An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.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
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This...In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.展开更多
This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e....This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e.,covalent crosslinking and dynamic reversible crosslinking).The imprinting cavities are initially constructed using irreversible covalent crosslinking to specifically recognize BSA,and then the coumarin residues in the imprinting cavities are crosslinked under 365 nm UV light to further imprint Lyz,because Lyz has smaller size than BSA.Since the photo-crosslinking of coumarin is a reversible reaction,the imprinting cavities of Lyz can be de-crosslinked under 254 nm UV light and restore the imprinting cavities of BSA.Moreover,the N-isopropyl acrylamide(NIPAM)and pyrrolidine residues copolymerized in the polymeric surface of the nanospheres are temperature-and p H-responsive respectively.Therefore,the protein rebinding and release behaviors of the nanospheres are controlled by external temperature and p H.As a result,the materials can selectively separate BSA from real bovine whole blood and Lyz from egg white under different UV light.This study may provide a new strategy for construction of protein imprinted materials with tunable specificity for different proteins.展开更多
In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring m...In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring methods applied to PSP images often suffer from limited accuracy and require extensive computational resources.To address these issues,this study proposes a deep learning-based approach tailored for PSP image deblurring.Considering that PSP applications primarily involve the accurate pressure measurements of complex geometries,the images captured under such conditions exhibit distinctive non-uniform motion blur,presenting challenges for standard deep learning models utilizing convolutional or attention-based techniques.In this paper,we introduce a novel deblurring architecture featuring multiple DAAM(Deformable Ack Attention Module).These modules provide enhanced flexibility for end-to-end deblurring,leveraging irregular convolution operations for efficient feature extraction while employing attention mechanisms interpreted as multiple 1×1 convolutions,subsequently reassembled to enhance performance.Furthermore,we incorporate a RSC(Residual Shortcut Convolution)module for initial feature processing,aimed at reducing redundant computations and improving the learning capacity for representative shallow features.To preserve critical spatial information during upsampling and downsampling,we replace conventional convolutions with wt(Haar wavelet downsampling)and dysample(Upsampling by Dynamic Sampling).This modification significantly enhances high-precision image reconstruction.By integrating these advanced modules within an encoder-decoder framework,we present the DFDNet(Deformable Fusion Deblurring Network)for image blur removal,providing robust technical support for subsequent PSP data analysis.Experimental evaluations on the FY dataset demonstrate the superior performance of our model,achieving competitive results on the GOPRO and HIDE datasets.展开更多
This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorpo...This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorporated into the transport analysis.The Reiner-Rivlin nanofluid model includes variable thermal conductivity,mass diffusivity,and motile microorganism density to accurately reflect realistic biological conditions.Radiative heat transfer and internal heat generation are considered in the thermal energy equation,while the Cattaneo-Christov theory is employed to model non-Fourier heat and mass fluxes.The governing equations are non-dimensionalized to reduce complexity,and a numerical solution is obtained using a shooting method.Parametric studies are conducted to examine the influence of key dimensionless parameters on velocity,temperature,concentration,and motile microorganism profiles.The results are presented through a series of graphs,offering insight into the dynamic interplay between physical mechanisms affecting heat and mass transfer in non-Newtonian bioconvective nanofluid systems.展开更多
The thermal nanofluids have garnered widespread attention for their use in multiple thermal systems,including heating processes,sustainable energy,and nuclear reactions.Research on nanofluids has revealed that the the...The thermal nanofluids have garnered widespread attention for their use in multiple thermal systems,including heating processes,sustainable energy,and nuclear reactions.Research on nanofluids has revealed that the thermal efficiencies of such materials are adversely affected by various thermal features.The purpose of the current work is to demonstrate the thermal analysis of Jeffrey nanofluids with the suspension of microorganisms in the presence of variable thermal sources.The variable effects of thermal conductivity,Brownian diffusivity,and motile density are utilized.The investigated model also reveals the contributions of radiation phenomena and chemical reactions.A porous,saturated,moving surface with a suction phenomenon promotes flow.The modeling of the problem is based on the implementation of the Cattaneo-Christov approach.The convective thermal constraints are used to promote the heat transfer features.A simplified form of the governing model is treated with the assistance of a shooting technique.The physical effects of different parameters for the problem are presented.The current problem justifies its applications in heat transfer,coating processes,heat exchangers,cooling systems in microelectronics,solar systems,chemical processes,etc.展开更多
This article analyzes the design of a variable-height simply supported steel truss bridge based on an actual project.It includes its basic situation,introduction to variable-height simply supported steel truss bridges...This article analyzes the design of a variable-height simply supported steel truss bridge based on an actual project.It includes its basic situation,introduction to variable-height simply supported steel truss bridges,key design points of such bridges,and finite element analysis of the design effect.The analysis shows that for such bridges,reasonable main structure design and node design are the keys to determining the overall design idea,and through the reasonable application of the finite element analysis method,the design effect can be scientifically determined,providing a reference for the subsequent structural design of such projects.展开更多
Difficulty in extracting nonlinear sparse impulse features due to variable speed conditions and redundant noise interference leads to challenges in diagnosing variable speed faults.Therefore,an improved spectral amplit...Difficulty in extracting nonlinear sparse impulse features due to variable speed conditions and redundant noise interference leads to challenges in diagnosing variable speed faults.Therefore,an improved spectral amplitude modulation(ISAM)based on sparse feature adaptive convolution(SFAC)is proposed to enhance the fault features under variable speed conditions.First,an optimal bi-damped wavelet construction method is proposed to learn signal impulse features,which selects the optimal bi-damped wavelet parameters with correlation criterion and particle swarm optimization.Second,a convolutional basis pursuit denoising model based on an optimal bi-damped wavelet is proposed for resolving sparse impulses.A model regularization parameter selection method based on weighted fault characteristic amplitude ratio assistance is proposed.Then,an ISAM method based on kurtosis threshold is proposed to further enhance the fault information of sparse signal.Finally,the type of variable speed faults is determined by order spectrum analysis.Various experimental results,such as spectral amplitude modulation and Morlet wavelet matching,verify the effectiveness and advantages of the ISAM-SFAC method.展开更多
Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked dec...Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.展开更多
This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its stre...This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its strength.The design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical spring.The tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and extensibility.This paper presents a new design for extensible manipulator and analyzes its stiffness and motion characteristics.Experimental results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum manipulator.The impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.展开更多
The work comparing the Yamada-Ota and Xue models for nanoparticle flow across a stretching surface has benefits in nanotechnology,medicinal treatments,environmental engineering,renewable energy,and heat exchangers.Mos...The work comparing the Yamada-Ota and Xue models for nanoparticle flow across a stretching surface has benefits in nanotechnology,medicinal treatments,environmental engineering,renewable energy,and heat exchangers.Most published nanofluid flow models assumed constant thermal conductivity and viscosity.With such great physiognomies in mind,the novelty of this work focuses on comparing the performance of the nanofluid models,Xue,and Yamada-Ota models on a stretched sheet with variable thickness under the influence of a magnetic field and quadratic thermal radiation.The altered boundary layer equations for momentum and temperature,subject to adequate boundary conditions,are numerically solved using an optimized,efficient,and extensive bvp-4c approach.The effects of non-dimensional constraints such as magnetic field,power index of velocity,wall thickness parameter,and quadratic radiation parameter on momentum and temperature profile in the boundary layer area are analyzed thoroughly and outcomes were illustrated graphically.Additionally,the consequences of certain distinctive parameters over engineering factors are also examined and results were presented in tabular form.From the outcomes,it is seen that fluid velocity slows down in the presence of a magnetic field but the opposite nature is observed in the case of temperature profile.With a higher index of velocity,the velocity profile decreases and the temperature field elevates.It has been found that the presence of quadratic convection improves the temperature field.The outcomes of the two models are compared.The Yamada-Ota model performed far better than the Xue model in the heat transfer analysis.展开更多
To elucidate the relationship between pipeline erosion and wear during slurry transportation,this study considers three key influencing parameters,namely,the ratio of inlet to outlet pipe diameter,the length of the va...To elucidate the relationship between pipeline erosion and wear during slurry transportation,this study considers three key influencing parameters,namely,the ratio of inlet to outlet pipe diameter,the length of the variable diameter section,and the roughness of the pipe wall.The impact of these factors on pipeline erosion and wear is analyzed using a single-factor analysis approach.In particular,the Fluent software is employed to conduct the required numerical simulations for variable diameter elbows of varying morphologies.The results indicate that as the inlet to outlet diameter ratio increases,the wear on the pipe inlet and the outer wall of the elbow becomes increasingly pronounced.Notably,when the diameter ratio exceeds 0.8,there is a significant escalation in wear on both the inner and outer elbow walls.Initially,the maximum erosion rate decreases sharply with increasing diameter ratio before a stable condition is attained.Erosion wear in the variable diameter section exhibits a distinct layered distribution pattern.In this region,the wear range for a 40 mm length of the pipe body is relatively small;however,once this length exceeds 40 mm,the wear range expands,ultimately covering the entire pipe section.The length of the variable diameter section significantly influences the maximum erosion rate of the pipeline,with sections shorter than 80 mm experiencing the most severe effects,and showing an exponential decline in erosion rate.As the wall roughness gradually increases,the wear area on both cheeks of the bend section rapidly expands and tends to deepen further.When the roughness reaches 4 mm,the pipeline wear experiences a dramatic shift,resulting in extensive“spot-like”wear patterns emerging at the bottom and sides of the horizontal flow section,which previously exhibited no wear.展开更多
The adaptive filtering algorithm with a fixed projection order is unable to adjust its performance in response to changes in the external environment of airborne radars.To overcome this limitation,a new approach is in...The adaptive filtering algorithm with a fixed projection order is unable to adjust its performance in response to changes in the external environment of airborne radars.To overcome this limitation,a new approach is introduced,which is the variable projection order Ekblom norm-promoted adaptive algorithm(VPO-EPAA).The method begins by examining the mean squared deviation(MSD)of the EPAA,deriving a formula for its MSD.Next,it compares the MSD of EPAA at two different projection orders and selects the one that minimizes the MSD as the parameter for the current iteration.Furthermore,the algorithm’s computational complexity is analyzed theoretically.Simulation results from system identification and self-interference cancellation show that the proposed algorithm performs exceptionally well in airborne radar signal self-interference cancellation,even under various noise intensities and types of interference.展开更多
The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) metho...The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) method to address these limitations. In the vLEC method, the waverider is directly designed from the preassigned leading edge and the variable shock angle distribution based on the Leading-Edge Cone (LEC) concept. Since the vLEC method is an approximate method, two test waveriders are designed and evaluated using numerical simulations to validate the shock design accuracy and the effectiveness of the vLEC method. The results show that the shocks of the test waveriders coincide well with the preassigned positions. Furthermore, four specifically designed application cases are conducted to analyze the performance benefits of the vLEC waveriders. The results of these cases indicate that, due to their variable shock angle distributions, the vLEC waveriders exhibit higher lift-to-drag ratios and better longitudinal static stability than conventional waveriders. Additionally, the vLEC waveriders demonstrate superior volumetric capacities near the symmetry plane, albeit with a minor decrease in volumetric efficiency.展开更多
基金supported by National Science and Technology Major Project,China(No.2017-IV-0007-0044)National Natural Science Foundation of China(No.52175142),National Natural Science Foundation of China(No.52305170)Natural Science Foundation of Sichuan Province,China(No.2022NSFSC1885)。
文摘With the application of 2.5D Woven Variable Thickness Composites(2.5DWVTC)in aviation and other fields,the issue of strength failure in this composite type has become a focal point.First,a three-step modeling approach is proposed to rapidly construct full-scale meso-finite element models for Outer Reduction Yarn Woven Composites(ORYWC)and Inner Reduction Yarn Woven Composites(IRYWC).Then,six independent damage variables are identified:yarn fiber tension/compression,yarn matrix tension/compression,and resin matrix tension/compression.These variables are utilized to establish the constitutive equation of woven composites,considering the coupling effects of microscopic damage.Finally,combined with the Hashin failure criterion and von Mises failure criterion,the strength prediction model is implemented in ANSYS using APDL language to simulate the strength failure process of 2.5DWVTC.The results show that the predicted stiffness and strength values of various parts of ORYWC and IRYWC are in good agreement with the relevant test results.
基金supported by the National Natural Science Foundation of China(No.51905123)Major Scientific and Technological Innovation Program of Shandong Province,China(Nos.2020CXGC010303,2022ZLGX04)Key R&D Programme of Shandong Province,China(No.2022JMRH0308).
文摘An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.
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supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
基金Supported by the Natural Science Foundation of Fujian Province(2022J011177,2024J01903)the Key Project of Fujian Provincial Education Department(JZ230054)。
文摘In clinical research,subgroup analysis can help identify patient groups that respond better or worse to specific treatments,improve therapeutic effect and safety,and is of great significance in precision medicine.This article considers subgroup analysis methods for longitudinal data containing multiple covariates and biomarkers.We divide subgroups based on whether a linear combination of these biomarkers exceeds a predetermined threshold,and assess the heterogeneity of treatment effects across subgroups using the interaction between subgroups and exposure variables.Quantile regression is used to better characterize the global distribution of the response variable and sparsity penalties are imposed to achieve variable selection of covariates and biomarkers.The effectiveness of our proposed methodology for both variable selection and parameter estimation is verified through random simulations.Finally,we demonstrate the application of this method by analyzing data from the PA.3 trial,further illustrating the practicality of the method proposed in this paper.
基金financial support from the National Natural Science Foundation of China(No.22275148)National Key R&D Program of China(No.2018YFB1900201)for Qiuyu Zhang+2 种基金the National Natural Science Foundation of China(No.22271232)Fundamental Research Funds for the Central Universities(No.D5000230114)for Shixin Fathe Fundamental Research Funds for the Central Universities(No.D5000220339)for Qing Liu。
文摘This work develops a protein imprinted nanosphere with varied recognition specificity for bovine serum albumin(BSA)and lysozyme(Lyz)under different UV light through a gradient dual crosslinked imprinting strategy(i.e.,covalent crosslinking and dynamic reversible crosslinking).The imprinting cavities are initially constructed using irreversible covalent crosslinking to specifically recognize BSA,and then the coumarin residues in the imprinting cavities are crosslinked under 365 nm UV light to further imprint Lyz,because Lyz has smaller size than BSA.Since the photo-crosslinking of coumarin is a reversible reaction,the imprinting cavities of Lyz can be de-crosslinked under 254 nm UV light and restore the imprinting cavities of BSA.Moreover,the N-isopropyl acrylamide(NIPAM)and pyrrolidine residues copolymerized in the polymeric surface of the nanospheres are temperature-and p H-responsive respectively.Therefore,the protein rebinding and release behaviors of the nanospheres are controlled by external temperature and p H.As a result,the materials can selectively separate BSA from real bovine whole blood and Lyz from egg white under different UV light.This study may provide a new strategy for construction of protein imprinted materials with tunable specificity for different proteins.
基金supported by the National Natural Science Foundation of China(No.12202476).
文摘In the PSP(Pressure-Sensitive Paint),image deblurring is essential due to factors such as prolonged camera exposure times and highmodel velocities,which can lead to significant image blurring.Conventional deblurring methods applied to PSP images often suffer from limited accuracy and require extensive computational resources.To address these issues,this study proposes a deep learning-based approach tailored for PSP image deblurring.Considering that PSP applications primarily involve the accurate pressure measurements of complex geometries,the images captured under such conditions exhibit distinctive non-uniform motion blur,presenting challenges for standard deep learning models utilizing convolutional or attention-based techniques.In this paper,we introduce a novel deblurring architecture featuring multiple DAAM(Deformable Ack Attention Module).These modules provide enhanced flexibility for end-to-end deblurring,leveraging irregular convolution operations for efficient feature extraction while employing attention mechanisms interpreted as multiple 1×1 convolutions,subsequently reassembled to enhance performance.Furthermore,we incorporate a RSC(Residual Shortcut Convolution)module for initial feature processing,aimed at reducing redundant computations and improving the learning capacity for representative shallow features.To preserve critical spatial information during upsampling and downsampling,we replace conventional convolutions with wt(Haar wavelet downsampling)and dysample(Upsampling by Dynamic Sampling).This modification significantly enhances high-precision image reconstruction.By integrating these advanced modules within an encoder-decoder framework,we present the DFDNet(Deformable Fusion Deblurring Network)for image blur removal,providing robust technical support for subsequent PSP data analysis.Experimental evaluations on the FY dataset demonstrate the superior performance of our model,achieving competitive results on the GOPRO and HIDE datasets.
文摘This study explores the bioconvective behavior of a Reiner-Rivlin nanofluid,accounting for spatially varying thermal properties.The flow is considered over a porous,stretching surface with mass suction effects incorporated into the transport analysis.The Reiner-Rivlin nanofluid model includes variable thermal conductivity,mass diffusivity,and motile microorganism density to accurately reflect realistic biological conditions.Radiative heat transfer and internal heat generation are considered in the thermal energy equation,while the Cattaneo-Christov theory is employed to model non-Fourier heat and mass fluxes.The governing equations are non-dimensionalized to reduce complexity,and a numerical solution is obtained using a shooting method.Parametric studies are conducted to examine the influence of key dimensionless parameters on velocity,temperature,concentration,and motile microorganism profiles.The results are presented through a series of graphs,offering insight into the dynamic interplay between physical mechanisms affecting heat and mass transfer in non-Newtonian bioconvective nanofluid systems.
基金appreciation to King Saud University for funding this work through researchers supporting project(No.RSPD2025R1056).
文摘The thermal nanofluids have garnered widespread attention for their use in multiple thermal systems,including heating processes,sustainable energy,and nuclear reactions.Research on nanofluids has revealed that the thermal efficiencies of such materials are adversely affected by various thermal features.The purpose of the current work is to demonstrate the thermal analysis of Jeffrey nanofluids with the suspension of microorganisms in the presence of variable thermal sources.The variable effects of thermal conductivity,Brownian diffusivity,and motile density are utilized.The investigated model also reveals the contributions of radiation phenomena and chemical reactions.A porous,saturated,moving surface with a suction phenomenon promotes flow.The modeling of the problem is based on the implementation of the Cattaneo-Christov approach.The convective thermal constraints are used to promote the heat transfer features.A simplified form of the governing model is treated with the assistance of a shooting technique.The physical effects of different parameters for the problem are presented.The current problem justifies its applications in heat transfer,coating processes,heat exchangers,cooling systems in microelectronics,solar systems,chemical processes,etc.
文摘This article analyzes the design of a variable-height simply supported steel truss bridge based on an actual project.It includes its basic situation,introduction to variable-height simply supported steel truss bridges,key design points of such bridges,and finite element analysis of the design effect.The analysis shows that for such bridges,reasonable main structure design and node design are the keys to determining the overall design idea,and through the reasonable application of the finite element analysis method,the design effect can be scientifically determined,providing a reference for the subsequent structural design of such projects.
基金funded by the National Natural Science Foundation of China(grant nos.52475084 and 52375076)the Postdoctoral Fellowship Program of CPSF(grant no.GZC20230202).
文摘Difficulty in extracting nonlinear sparse impulse features due to variable speed conditions and redundant noise interference leads to challenges in diagnosing variable speed faults.Therefore,an improved spectral amplitude modulation(ISAM)based on sparse feature adaptive convolution(SFAC)is proposed to enhance the fault features under variable speed conditions.First,an optimal bi-damped wavelet construction method is proposed to learn signal impulse features,which selects the optimal bi-damped wavelet parameters with correlation criterion and particle swarm optimization.Second,a convolutional basis pursuit denoising model based on an optimal bi-damped wavelet is proposed for resolving sparse impulses.A model regularization parameter selection method based on weighted fault characteristic amplitude ratio assistance is proposed.Then,an ISAM method based on kurtosis threshold is proposed to further enhance the fault information of sparse signal.Finally,the type of variable speed faults is determined by order spectrum analysis.Various experimental results,such as spectral amplitude modulation and Morlet wavelet matching,verify the effectiveness and advantages of the ISAM-SFAC method.
基金supported by the National Key Research and Development Program of China(2022YFC3204401)the National Natural Science Foundation of China(U23A2001,U2243234)+2 种基金the Major Science and Technology Projects of Inner Mongolia Autonomous Region(KCX2024013-1,2022EEDSKJXM005)the Inner Mongolia Autonomous Region Science and Technology Leading Talent Team(2022LJRC0007)the Inner Mongolia Agricultural University Basic Research Business Expenses Project(BR221012,BR221204).
文摘Climate change and human activities are primary drivers of runoff variations,significantly impacting the hydrological balance of river basins.In recent decades,the Yellow River Basin,China has experienced a marked decline in runoff,posing challenges to the sustainable development of regional water resources and ecosystem stability.To enhance the understanding of runoff dynamics in the basin,we selected the Dahei River Basin,a representative tributary in the upper reaches of the Yellow River Basin as the study area.A comprehensive analysis of runoff trends and contributing factors was conducted using the data on hydrology,meteorology,and water resource development and utilization.Abrupt change years of runoff series in the Dahei River Basin was identified by the Mann-Kendall and Pettitt tests:1999 at Dianshang,Qixiaying,and Meidai hydrological stations and 1995 at Sanliang hydrological station.Through hydrological simulations based on the Variable Infiltration Capacity(VIC)model,we quantified the factors driving runoff evolution in the Dahei River Basin,with climate change contributing 9.92%–22.91%and human activities contributing 77.09%–90.08%.The Budyko hypothesis method provided similar results,with climate change contributing 13.06%–20.89%and human activities contributing 79.11%–86.94%.Both methods indicated that human activities,particularly water consumption,were dominant factors in the runoff variations of the Dahei River Basin.The integration of hydrological modeling with attribution analysis offers valuable insights into runoff evolution,facilitating adaptive strategies to mitigate water scarcity in arid and semi-arid areas.
基金supported by the National Key R&D Program of China(No.2018YFB1305400)the Major Research Plan of the National Natural Science Foundation of China(No.92048301)+1 种基金the National Natural Science Foundation of China(No.52025054)the Joint Research Fund between the National Natural Science Foundation of China(NSFC)and Shen Zhen(No.U1713201).
文摘This paper presents a continuum manipulator inspired by the anatomical characteristics of the elephant trunk.Specifically,the manipulator mimics the conoid profile of the elephant trunk,which helps to enhance its strength.The design features two concentric parts:inner pneumatically actuated bellows and an outer tendon-driven helical spring.The tendons control the omnidirectional bending of the manipulator,while the fusion of the pneumatic bellows with the tendon-driven spring results in an antagonistic actuation mechanism that provides the manipulator with variable stiffness and extensibility.This paper presents a new design for extensible manipulator and analyzes its stiffness and motion characteristics.Experimental results are consistent with theoretical analysis,thereby demonstrating the validity of the theoretical approach and the versatile practical mechanical properties of the continuum manipulator.The impressive extensibility and variable stiffness of the manipulator were further demonstrated by performing a pin-hole assembly task.
基金supported by the National Research Foundation,Korea(Grant No.NRF2022-R1A2C2002799)support provided by the German Jordanian University,Amman,Jordan,is greatly acknowledged by the authors.Ulavathi Shettar Mahabaleshwar wishes to thank Sang Woo Joo,School of Mechanical Engineering,Yeungnam University,Gyeongsan,Korea,for his hospitality.
文摘The work comparing the Yamada-Ota and Xue models for nanoparticle flow across a stretching surface has benefits in nanotechnology,medicinal treatments,environmental engineering,renewable energy,and heat exchangers.Most published nanofluid flow models assumed constant thermal conductivity and viscosity.With such great physiognomies in mind,the novelty of this work focuses on comparing the performance of the nanofluid models,Xue,and Yamada-Ota models on a stretched sheet with variable thickness under the influence of a magnetic field and quadratic thermal radiation.The altered boundary layer equations for momentum and temperature,subject to adequate boundary conditions,are numerically solved using an optimized,efficient,and extensive bvp-4c approach.The effects of non-dimensional constraints such as magnetic field,power index of velocity,wall thickness parameter,and quadratic radiation parameter on momentum and temperature profile in the boundary layer area are analyzed thoroughly and outcomes were illustrated graphically.Additionally,the consequences of certain distinctive parameters over engineering factors are also examined and results were presented in tabular form.From the outcomes,it is seen that fluid velocity slows down in the presence of a magnetic field but the opposite nature is observed in the case of temperature profile.With a higher index of velocity,the velocity profile decreases and the temperature field elevates.It has been found that the presence of quadratic convection improves the temperature field.The outcomes of the two models are compared.The Yamada-Ota model performed far better than the Xue model in the heat transfer analysis.
基金supported by the project of the Educational Department of Liaoning Province(No.LJKMZ20220825)the National Natural Science Foundation of China(51774199).
文摘To elucidate the relationship between pipeline erosion and wear during slurry transportation,this study considers three key influencing parameters,namely,the ratio of inlet to outlet pipe diameter,the length of the variable diameter section,and the roughness of the pipe wall.The impact of these factors on pipeline erosion and wear is analyzed using a single-factor analysis approach.In particular,the Fluent software is employed to conduct the required numerical simulations for variable diameter elbows of varying morphologies.The results indicate that as the inlet to outlet diameter ratio increases,the wear on the pipe inlet and the outer wall of the elbow becomes increasingly pronounced.Notably,when the diameter ratio exceeds 0.8,there is a significant escalation in wear on both the inner and outer elbow walls.Initially,the maximum erosion rate decreases sharply with increasing diameter ratio before a stable condition is attained.Erosion wear in the variable diameter section exhibits a distinct layered distribution pattern.In this region,the wear range for a 40 mm length of the pipe body is relatively small;however,once this length exceeds 40 mm,the wear range expands,ultimately covering the entire pipe section.The length of the variable diameter section significantly influences the maximum erosion rate of the pipeline,with sections shorter than 80 mm experiencing the most severe effects,and showing an exponential decline in erosion rate.As the wall roughness gradually increases,the wear area on both cheeks of the bend section rapidly expands and tends to deepen further.When the roughness reaches 4 mm,the pipeline wear experiences a dramatic shift,resulting in extensive“spot-like”wear patterns emerging at the bottom and sides of the horizontal flow section,which previously exhibited no wear.
基金supported by the Shan⁃dong Provincial Natural Science Foundation(No.ZR2022MF314).
文摘The adaptive filtering algorithm with a fixed projection order is unable to adjust its performance in response to changes in the external environment of airborne radars.To overcome this limitation,a new approach is introduced,which is the variable projection order Ekblom norm-promoted adaptive algorithm(VPO-EPAA).The method begins by examining the mean squared deviation(MSD)of the EPAA,deriving a formula for its MSD.Next,it compares the MSD of EPAA at two different projection orders and selects the one that minimizes the MSD as the parameter for the current iteration.Furthermore,the algorithm’s computational complexity is analyzed theoretically.Simulation results from system identification and self-interference cancellation show that the proposed algorithm performs exceptionally well in airborne radar signal self-interference cancellation,even under various noise intensities and types of interference.
基金supported by grants from the National Natural Science Foundation of China(No.U20B2006)the Guangdong Basic and Applied Basic Research Foundation(No.2022A1515110145)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2022QNRC001).
文摘The optimization of the waverider is constrained by the reversely designed leading edge and the constant shock angle distribution. This paper proposes a design method called the variable Leading-Edge Cone (vLEC) method to address these limitations. In the vLEC method, the waverider is directly designed from the preassigned leading edge and the variable shock angle distribution based on the Leading-Edge Cone (LEC) concept. Since the vLEC method is an approximate method, two test waveriders are designed and evaluated using numerical simulations to validate the shock design accuracy and the effectiveness of the vLEC method. The results show that the shocks of the test waveriders coincide well with the preassigned positions. Furthermore, four specifically designed application cases are conducted to analyze the performance benefits of the vLEC waveriders. The results of these cases indicate that, due to their variable shock angle distributions, the vLEC waveriders exhibit higher lift-to-drag ratios and better longitudinal static stability than conventional waveriders. Additionally, the vLEC waveriders demonstrate superior volumetric capacities near the symmetry plane, albeit with a minor decrease in volumetric efficiency.
