Two-dimensional double-layer honeycomb(DLHC)materials are known for their diverse physical properties,but superconductivity has been a notably absent characteristic in this structure.We address this gap by investigati...Two-dimensional double-layer honeycomb(DLHC)materials are known for their diverse physical properties,but superconductivity has been a notably absent characteristic in this structure.We address this gap by investigating M_(2)N_(2)(M=Nb,Ta)with DLHC structure using first-principles calculations.Our results show that M_(2)N_(2)are stable and metallic,exhibiting superconducting behavior.Specifically,Nb_(2)N_(2)and Ta_(2)N_(2)display superconducting transition temperatures of 6.8 K and 8.8 K,respectively.Their electron-phonon coupling is predominantly driven by the coupling between metal d-orbitals and low-frequency metal-dominated vibration modes.Interestingly,two compounds also exhibit non-trivial band topology.Thus,M_(2)N_(2)are promising platforms for studying the interplay between topology and superconductivity and fill the gap in superconductivity research for DLHC materials.展开更多
As healthcare systems increasingly embrace digitalization,effective management of electronic health records(EHRs)has emerged as a critical priority,particularly in inpatient settings where data sensitivity and realtim...As healthcare systems increasingly embrace digitalization,effective management of electronic health records(EHRs)has emerged as a critical priority,particularly in inpatient settings where data sensitivity and realtime access are paramount.Traditional EHR systems face significant challenges,including unauthorized access,data breaches,and inefficiencies in tracking follow-up appointments,which heighten the risk of misdiagnosis and medication errors.To address these issues,this research proposes a hybrid blockchain-based solution for securely managing EHRs,specifically designed as a framework for tracking inpatient follow-ups.By integrating QR codeenabled data access with a blockchain architecture,this innovative approach enhances privacy protection,data integrity,and auditing capabilities,while facilitating swift and real-time data retrieval.The architecture adheres to Role-Based Access Control(RBAC)principles and utilizes robust encryption techniques,including SHA-256 and AES-256-CBC,to secure sensitive information.A comprehensive threat model outlines trust boundaries and potential adversaries,complemented by a validated data transmission protocol.Experimental results demonstrate that the framework remains reliable in concurrent access scenarios,highlighting its efficiency and responsiveness in real-world applications.This study emphasizes the necessity for hybrid solutions in managing sensitive medical information and advocates for integrating blockchain technology and QR code innovations into contemporary healthcare systems.展开更多
With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,t...In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency,scalability,and energy consumption.This study proposes an innovative approach to Blockchain network optimization,drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms.Specifically,we explore the application of genetic algorithms,particle swarm optimization,and related evolutionary techniques to enhance the performance of blockchain networks.The proposed methodologies aim to optimize consensus mechanisms,improve transaction throughput,and reduce resource consumption.Through extensive simulations and real-world experiments,our findings demonstrate significant improvements in network efficiency,scalability,and stability.This research offers a thorough analysis of existing optimization techniques,introduces novel strategies,and assesses their efficacy based on empirical outputs.展开更多
With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes rely...With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes relying on untrusted third-party auditors suffer from both security and efficiency issues,while existing decentralized blockchain-based auditing solutions still face shortcomings in correctness and security.This paper proposes an improved blockchain-based cloud auditing scheme,with the following core contributions:Identifying critical logical contradictions in the original scheme,thereby establishing the foundation for the correctness of cloud auditing;Designing an enhanced mechanism that integrates multiple hashing with dynamic aggregate signatures,binding encrypted blocks through bilinear pairings and BLS signatures,and improving the scheme by setting parameters based on the Computational Diffie-Hellman(CDH)problem,significantly strengthening data integrity protection and anti-forgery capabilities;Introducing a random challenge mechanism and dynamic parameter adjustment strategy,effectively resisting various attacks such as forgery,tampering,and deletion,significantly improving the detection probability of malicious Cloud Service Providers(CSPs),and significantly reducing the proof generation overhead for CSPswhilemaintaining the same computational cost forDataOwners.Theoretical analysis and performance evaluation experiments demonstrate that the proposed scheme achieves significant improvements in both security and efficiency.Finally,the paper explores potential applications of the Enhanced Security Scheme in fields such as healthcare,drone swarms,and government office attendance systems,providing an effective approach for building secure,efficient,and decentralized cloud auditing systems.展开更多
Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic ...Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.展开更多
Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring ...Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.展开更多
With the development of sharded blockchains,high cross-shard rates and load imbalance have emerged as major challenges.Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates...With the development of sharded blockchains,high cross-shard rates and load imbalance have emerged as major challenges.Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates.Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads.Meanwhile,because of the coupling between consensus and execution,a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution.However,we observe that transaction partitioning and subsequent consensus do not require actual account data but only need to determine the relative partition order between shards.Therefore,we propose a novel sharded blockchain,called HATLedger,based on Hybrid Account and Transaction partitioning.First,HATLedger proposes building a future transaction graph to detect upcoming hotspot accounts and making more precise account partitioning to reduce transaction cross-shard rates.In the event of an impending overload,the source shard employs simulated partition transactions to specify the partition order across multiple target shards,thereby rapidly partitioning the pending transactions.The target shards can reach consensus on received transactions without waiting for account data.The source shard subsequently sends the account data to the corresponding target shards in the order specified by the previously simulated partition transactions.Based on real transaction history from Ethereum,we conducted extensive sharding scalability experiments.By maintaining low cross-shard rates and a relatively balanced load distribution,HATLedger achieves throughput improvements of 2.2x,1.9x,and 1.8x over SharPer,Shard Scheduler,and TxAllo,respectively,significantly enhancing efficiency and scalability.展开更多
In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic q...In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.展开更多
Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either re...Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.展开更多
The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significa...The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significant security challenges,including impersonation threats,data manipulation,distributed denial of service(DDoS)attacks,and privacy breaches.Traditional security measures are inadequate due to the decentralized and dynamic nature of next-generation networks.This survey provides a comprehensive review of how Federated Learning(FL),Blockchain,and Digital Twin(DT)technologies can collectively enhance the security of 5G and 6G systems.Blockchain offers decentralized,immutable,and transparent mechanisms for securing network transactions,while FL enables privacy-preserving collaborative learning without sharing raw data.Digital Twins create virtual replicas of network components,enabling real-time monitoring,anomaly detection,and predictive threat analysis.The survey examines major security issues in emerging wireless architectures and analyzes recent advancements that integrate FL,Blockchain,and DT to mitigate these threats.Additionally,it presents practical use cases,synthesizes key lessons learned,and identifies ongoing research challenges.Finally,the survey outlines future research directions to support the development of scalable,intelligent,and robust security frameworks for next-generation wireless networks.展开更多
Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work pr...Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.展开更多
The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)...The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)and artificial intelligence(AI)techniques,have become standard practice.The need for Federated Learning(FL)for ML model training in ORAN environments is heightened by the modularised structure of the ORAN architecture and the shortcomings of conventional ML techniques.However,the traditional plaintext model update sharing of FL in multi-BS contexts is susceptible to privacy violations such as deep-leakage gradient assaults and inference.Therefore,this research presents a novel blockchain-assisted improved cryptographic privacy-preserving federated learning(BICPPFL)model,with the help of ORAN,to safely carry out federated learning and protect privacy.This model improves on the conventional masking technique for sharing model parameters by adding new characteristics.These features include the choice of distributed aggregators,validation for final model aggregation,and individual validation for BSs.To manage the security and privacy of FL processes,a combined homomorphic proxy-reencryption(HPReE)and lattice-cryptographic method(HPReEL)has been used.The upgraded delegated proof of stake(Up-DPoS)consensus protocol,which will provide quick validation of model exchanges and protect against malicious attacks,is employed for effective consensus across blockchain nodes.Without sacrificing performance metrics,the BICPPFL model strengthens privacy and adds security layers while facilitating the transfer of sensitive data across several BSs.The framework is deployed on top of a Hyperledger Fabric blockchain to evaluate its effectiveness.The experimental findings prove the reliability and privacy-preserving capability of the BICPPFL model.展开更多
In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is p...In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is proposed. Measured frequencies are selected as the first-layer reference data, and the mass of the bridge deck, the grid density, the modulus of concrete and the ballast on the side span are modified by using a manual tuning technique. Measured global positioning system （GPS） data is selected as the second-layer reference data, and the degradation of the integral structure stiffness EI of the whole bridge is taken into account for the second-layer model updating by using the finite element iteration algorithm. The Nanpu Bridge in Shanghai is taken as a case to verify the applicability of the proposed model updating method. After the first-layer model updating, the standard deviation of modal frequencies is smaller than 7%. After the second-layer model updating, the error of the deflection of the mid-span is smaller than 10%. The integral structure stiffness of the whole bridge decreases about 20%. The research results show a good agreement between the calculated response and the measured response.展开更多
In order to increase the fatigue life (FL) of road wheels (RW), a kind of double layer rubber flange (DLRF) is put forward. It consists of two layers of rubber, where metal wires are laid in the inner layer and the ou...In order to increase the fatigue life (FL) of road wheels (RW), a kind of double layer rubber flange (DLRF) is put forward. It consists of two layers of rubber, where metal wires are laid in the inner layer and the outer layer has no inlaid metal wires. Stress, strain and temperature field of DLRF were calculated with ANSYS finite element analysis (FEA) software, FL of DLRF RW was also computed with fracture mechanics fatigue theory. The results of computation indicate that the heat generated in RW's rubber flange (RF) can be reduced by the use of DLRF, and the FL of RW can be increased without affecting the mechanical intensity of RW.展开更多
The aim of the study was to develop actarit double-layered osmotic pump tablets to overcome the weak points of actarit common tablets, such as short half-life and large plasma concentration fluctuations. Single factor...The aim of the study was to develop actarit double-layered osmotic pump tablets to overcome the weak points of actarit common tablets, such as short half-life and large plasma concentration fluctuations. Single factor experiment and orthogonal test were applied to optimize the formulation;the pharmacokinetic study was performed in beagle dogs adopting actarit common tablets as reference tablets. The optimal formulation was as follows: drug layer: 150 mg actarit, 240 mg PEO-N80, 50 mg NaCl;push layer: 140 mg PEO-WSR303, 20 mg NaCl;coating solution: 30 g cellulose acetate and 6 g PEG 4000 in 1000 ml 94% acetone solution, 60 mg coating weight gain. The pharmacokinetic study showed that T max was prolonged by the contrast of commercial common tablets with constant drug release rate, but the bioavailability was equivalent. And a good in vivo –in vitro correlation of the actarit osmotic pump tablets was also established. The designed actarit osmotic pump tablets can be applied for rheumatoid arthritis, proposing a promising replacement for the marked common products.展开更多
AIM To investigate the efficacy of double-layered covered stent in the treatment of malignant oesophageal obstructions.METHODS A systematic review and meta-analysis was performed following the PRISMA process. Pub Med(...AIM To investigate the efficacy of double-layered covered stent in the treatment of malignant oesophageal obstructions.METHODS A systematic review and meta-analysis was performed following the PRISMA process. Pub Med(Medline),EMBASE(Excerpta Medical Database),AMED(Allied and Complementary medicine Database),Scopus and online content,were searched for studies reporting on the Ni Ti-S polyurethane-covered double oesophageal stent for the treatment of malignant dysphagia. Weighted pooled outcomes were synthesized with a random effects model to account for clinical heterogeneity. All studies reporting the outcome of palliative management of dysphagia due to histologically confirmed malignant oesophageal obstruction using double-layered covered nitinol stent were included. The level of statistical significance was set at α = 0.05.RESULTS Six clinical studies comprising 250 patients in total were identified. Pooled technical success of stent insertion was 97.2%(95%CI: 94.8%-98.9%; I2 = 5.8%). Pooled complication rate was 27.6%(95%CI: 20.7%-35.2%; I2 = 41.9%). Weighted improvement of dysphagia on a scale of 0-5 scoring system was-2.00 [95%CI:-2.29%-(-1.72%); I2 = 87%]. Distal stent migration was documented in 10 out of the 250 cases examined.Pooled stent migration rate was 4.7%(95%CI: 2.5%-7.7%; I2 = 0%). Finally,tumour overgrowth was reported in 34 out of the 250 cases with pooled rate of tumour overgrowth of 11.2%(95%CI: 3.7%-22.1%; I2 = 82.2%). No funnel plot asymmetry to suggest publication bias(bias = 0.39,P = 0.78). In the sensitivity analysis all results were largely similar between the fixed and random effects models.CONCLUSION The double-layered nitinol stent provides immediate relief of malignant dysphagia with low rates of stent migration and tumour展开更多
Based on non-Darcian flow law described by exponent and threshold gradient within a double-layered soil, the classic theory of one-dimensional consolidation of double-layered soil was modified to consider the change o...Based on non-Darcian flow law described by exponent and threshold gradient within a double-layered soil, the classic theory of one-dimensional consolidation of double-layered soil was modified to consider the change of vertical total stress with depth and time together. Because of the complexity of governing equations, the numerical solutions were obtained in detail by finite difference method. Then, the numerical solutions were compared with the analytical solutions in condition that non-Darcian flow law was degenerated to Dary's law, and the comparison results show that numerical solutions are reliable. Finally, consolidation behavior of double-layered soil with different parameters was analyzed, and the results show that the consolidation rate of double-layered soil decreases with increasing the value of exponent and threshold of non-Darcian flow, and the exponent and threshold gradient of the first soil layer greatly influence the consolidation rate of double-layered soil. The larger the ratio of the equivalent water head of external load to the total thickness of double-layered soil, the larger the rate of the consolidation, and the similitude relationship in classical consolidation theory of double-layered soil is not satisfied. The other consolidation behavior of double-layered soil with non-Darcian flow is the same as that with Darcy's law.展开更多
The velocity structures of flow through vertically double-layered vegetation(VDLV)as well as single-layered rigid vegetation(SLV)were investigated computationally with a three-dimensional(3D)Reynolds stress turbulence...The velocity structures of flow through vertically double-layered vegetation(VDLV)as well as single-layered rigid vegetation(SLV)were investigated computationally with a three-dimensional(3D)Reynolds stress turbulence model,using the computational fluid dynamics(CFD)code FLUENT.The detailed velocity distribution was explored with a varying initial Froude number(Fr),with consideration of the steady subcritical flow conditions of an inland tsunami.In VDLV flows,the numerical model successfully captured the inflection point in the profiles of mean streamwise velocities in the mixing-layer region around the top of short submerged vegetation.An upward and downward movement of flow occurred at the positions located just behind the tall and short vegetation,respectively.Overall,higher streamwise velocities were observed in the upper vegetation layer due to high porosity,with Pr=98%(sparse vegetation,where Pr is the porosity),as compared to those in the lower vegetation layer,which had comparatively low porosity,with Pr=91%(dense vegetation).A rising trend of velocities was found as the flow passed through the vegetation region,followed by a clear sawtooth distribution,as compared to the regions just upstream and downstream of vegetation where the flow was almost uniform.In VDLV flows,a rising trend in the flow resistance was observed with the increase in the initial Froude number,i.e.,Fr?0.67,0.70,and 0.73.However,the flow resistance in the case of SLV was relatively very low.The numerical results also show the flow structures within the vicinity of short and tall vegetation,which are difficult to attain through experimental measurements.展开更多
To further investigate the one-dimensional(1D)rheological consolidation mechanism of double-layered soil,the fractional derivative Merchant model(FDMM)and the non-Darcian flow model with the non-Newtonian index are re...To further investigate the one-dimensional(1D)rheological consolidation mechanism of double-layered soil,the fractional derivative Merchant model(FDMM)and the non-Darcian flow model with the non-Newtonian index are respectively introduced to describe the deformation of viscoelastic soil and the flow of pore water in the process of consolidation.Accordingly,an 1D rheological consolidation equation of double-layered soil is obtained,and its numerical analysis is performed by the implicit finite difference method.In order to verify its validity,the numerical solutions by the present method for some simplified cases are compared with the results in the related literature.Then,the influence of the revelent parameters on the rheological consolidation of double-layered soil are investigated.Numerical results indicate that the parameters of non-Darcian flow and FDMM of the first soil layer greatly influence the consolidation rate of double-layered soil.As the decrease of relative compressibility or the increase of relative permeability between the lower soil and the upper soil,the dissipation rate of excess pore water pressure and the settlement rate of the ground will be accelerated.Increasing the relative thickness of soil layer with high permeability or low compressibility will also accelerate the consolidation rate of double-layered soil.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12074213 and 11574108)the National Key R&D Program of China(Grant No.2022YFA1403103)+2 种基金the Major Basic Program of Natural Science Foundation of Shandong Province(Grant No.ZR2021ZD01)the Natural Science Foundation of Shandong Province(Grant No.ZR2023MA082)the Project of Introduction and Cultivation for Young Innovative Talents in Colleges and Universities of Shandong Province。
文摘Two-dimensional double-layer honeycomb(DLHC)materials are known for their diverse physical properties,but superconductivity has been a notably absent characteristic in this structure.We address this gap by investigating M_(2)N_(2)(M=Nb,Ta)with DLHC structure using first-principles calculations.Our results show that M_(2)N_(2)are stable and metallic,exhibiting superconducting behavior.Specifically,Nb_(2)N_(2)and Ta_(2)N_(2)display superconducting transition temperatures of 6.8 K and 8.8 K,respectively.Their electron-phonon coupling is predominantly driven by the coupling between metal d-orbitals and low-frequency metal-dominated vibration modes.Interestingly,two compounds also exhibit non-trivial band topology.Thus,M_(2)N_(2)are promising platforms for studying the interplay between topology and superconductivity and fill the gap in superconductivity research for DLHC materials.
基金funded by Multimedia University,Cyberjaya,Selangor,Malaysia(Grant Number:PostDoc(MMUI/240029)).
文摘As healthcare systems increasingly embrace digitalization,effective management of electronic health records(EHRs)has emerged as a critical priority,particularly in inpatient settings where data sensitivity and realtime access are paramount.Traditional EHR systems face significant challenges,including unauthorized access,data breaches,and inefficiencies in tracking follow-up appointments,which heighten the risk of misdiagnosis and medication errors.To address these issues,this research proposes a hybrid blockchain-based solution for securely managing EHRs,specifically designed as a framework for tracking inpatient follow-ups.By integrating QR codeenabled data access with a blockchain architecture,this innovative approach enhances privacy protection,data integrity,and auditing capabilities,while facilitating swift and real-time data retrieval.The architecture adheres to Role-Based Access Control(RBAC)principles and utilizes robust encryption techniques,including SHA-256 and AES-256-CBC,to secure sensitive information.A comprehensive threat model outlines trust boundaries and potential adversaries,complemented by a validated data transmission protocol.Experimental results demonstrate that the framework remains reliable in concurrent access scenarios,highlighting its efficiency and responsiveness in real-world applications.This study emphasizes the necessity for hybrid solutions in managing sensitive medical information and advocates for integrating blockchain technology and QR code innovations into contemporary healthcare systems.
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
文摘In recent years,Blockchain Technology has become a paradigm shift,providing Transparent,Secure,and Decentralized platforms for diverse applications,ranging from Cryptocurrency to supply chain management.Nevertheless,the optimization of blockchain networks remains a critical challenge due to persistent issues such as latency,scalability,and energy consumption.This study proposes an innovative approach to Blockchain network optimization,drawing inspiration from principles of biological evolution and natural selection through evolutionary algorithms.Specifically,we explore the application of genetic algorithms,particle swarm optimization,and related evolutionary techniques to enhance the performance of blockchain networks.The proposed methodologies aim to optimize consensus mechanisms,improve transaction throughput,and reduce resource consumption.Through extensive simulations and real-world experiments,our findings demonstrate significant improvements in network efficiency,scalability,and stability.This research offers a thorough analysis of existing optimization techniques,introduces novel strategies,and assesses their efficacy based on empirical outputs.
基金funded by the National Natural Science Foundation of China(New Design and Analysis of Fully Homomorphic Signatures,Grant No.62172436).
文摘With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes relying on untrusted third-party auditors suffer from both security and efficiency issues,while existing decentralized blockchain-based auditing solutions still face shortcomings in correctness and security.This paper proposes an improved blockchain-based cloud auditing scheme,with the following core contributions:Identifying critical logical contradictions in the original scheme,thereby establishing the foundation for the correctness of cloud auditing;Designing an enhanced mechanism that integrates multiple hashing with dynamic aggregate signatures,binding encrypted blocks through bilinear pairings and BLS signatures,and improving the scheme by setting parameters based on the Computational Diffie-Hellman(CDH)problem,significantly strengthening data integrity protection and anti-forgery capabilities;Introducing a random challenge mechanism and dynamic parameter adjustment strategy,effectively resisting various attacks such as forgery,tampering,and deletion,significantly improving the detection probability of malicious Cloud Service Providers(CSPs),and significantly reducing the proof generation overhead for CSPswhilemaintaining the same computational cost forDataOwners.Theoretical analysis and performance evaluation experiments demonstrate that the proposed scheme achieves significant improvements in both security and efficiency.Finally,the paper explores potential applications of the Enhanced Security Scheme in fields such as healthcare,drone swarms,and government office attendance systems,providing an effective approach for building secure,efficient,and decentralized cloud auditing systems.
基金funded in part by the Supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China under Grants 2024QN06022 and 2023QN06008in part by the First-Class Discipline Research Special Project under Grant YLXKZX-NGD-015in part by the Inner Mongolia University of Technology Scientific Research Start-Up Project under Grant BS2024067.
文摘Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.
文摘Industrial Cyber-Physical Systems(ICPSs)play a vital role in modern industries by providing an intellectual foundation for automated operations.With the increasing integration of information-driven processes,ensuring the security of Industrial Control Production Systems(ICPSs)has become a critical challenge.These systems are highly vulnerable to attacks such as denial-of-service(DoS),eclipse,and Sybil attacks,which can significantly disrupt industrial operations.This work proposes an effective protection strategy using an Artificial Intelligence(AI)-enabled Smart Contract(SC)framework combined with the Heterogeneous Barzilai-Borwein Support Vector(HBBSV)method for industrial-based CPS environments.The approach reduces run time and minimizes the probability of attacks.Initially,secured ICPSs are achieved through a comprehensive exchange of views on production plant strategies for condition monitoring using SC and blockchain(BC)integrated within a BC network.The SC executes the HBBSV strategy to verify the security consensus.The Barzilai-Borwein Support Vectorized algorithm computes abnormal attack occurrence probabilities to ensure that components operate within acceptable production line conditions.When a component remains within these conditions,no security breach occurs.Conversely,if a component does not satisfy the condition boundaries,a security lapse is detected,and those components are isolated.The HBBSV method thus strengthens protection against DoS,eclipse,and Sybil attacks.Experimental results demonstrate that the proposed HBBSV approach significantly improves security by enhancing authentication accuracy while reducing run time and authentication time compared to existing techniques.
基金funded by the National Key Research and Development Program of China(Grant No.2024YFE0209000)the NSFC(Grant No.U23B2019)。
文摘With the development of sharded blockchains,high cross-shard rates and load imbalance have emerged as major challenges.Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates.Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads.Meanwhile,because of the coupling between consensus and execution,a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution.However,we observe that transaction partitioning and subsequent consensus do not require actual account data but only need to determine the relative partition order between shards.Therefore,we propose a novel sharded blockchain,called HATLedger,based on Hybrid Account and Transaction partitioning.First,HATLedger proposes building a future transaction graph to detect upcoming hotspot accounts and making more precise account partitioning to reduce transaction cross-shard rates.In the event of an impending overload,the source shard employs simulated partition transactions to specify the partition order across multiple target shards,thereby rapidly partitioning the pending transactions.The target shards can reach consensus on received transactions without waiting for account data.The source shard subsequently sends the account data to the corresponding target shards in the order specified by the previously simulated partition transactions.Based on real transaction history from Ethereum,we conducted extensive sharding scalability experiments.By maintaining low cross-shard rates and a relatively balanced load distribution,HATLedger achieves throughput improvements of 2.2x,1.9x,and 1.8x over SharPer,Shard Scheduler,and TxAllo,respectively,significantly enhancing efficiency and scalability.
基金supported in part by the National Natural Science Foundation of China under Grant 62262073in part by the Yunnan Provincial Ten Thousand People Program for Young Top Talents under Grant YNWR-QNBJ-2019-237in part by the Yunnan Provincial Major Science and Technology Special Program under Grant 202402AD080002.
文摘In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.
基金supported in part by the Research Fund of Key Lab of Education Blockchain and Intelligent Technology,Ministry of Education(EBME25-F-08).
文摘Lightweight nodes are crucial for blockchain scalability,but verifying the availability of complete block data puts significant strain on bandwidth and latency.Existing data availability sampling(DAS)schemes either require trusted setups or suffer from high communication overhead and low verification efficiency.This paper presents ISTIRDA,a DAS scheme that lets light clients certify availability by sampling small random codeword symbols.Built on ISTIR,an improved Reed–Solomon interactive oracle proof of proximity,ISTIRDA combines adaptive folding with dynamic code rate adjustment to preserve soundness while lowering communication.This paper formalizes opening consistency and prove security with bounded error in the random oracle model,giving polylogarithmic verifier queries and no trusted setup.In a prototype compared with FRIDA under equal soundness,ISTIRDA reduces communication by 40.65%to 80%.For data larger than 16 MB,ISTIRDA verifies faster and the advantage widens;at 128 MB,proofs are about 60%smaller and verification time is roughly 25%shorter,while prover overhead remains modest.In peer-to-peer emulation under injected latency and loss,ISTIRDA reaches confidence more quickly and is less sensitive to packet loss and load.These results indicate that ISTIRDA is a scalable and provably secure DAS scheme suitable for high-throughput,large-block public blockchains,substantially easing bandwidth and latency pressure on lightweight nodes.
基金derived from a research grant“Cybersecurity Research and Innovation Pioneers Grants Initiative”funded by The National Program for RDI in Cybersecurity(National Cybersecurity Authority)-Kingdom of Saudi Arabia-with grant number(CRPG-25-3168)supported by EIAS Data Science and Blockchain Lab,CCIS,Prince Sultan University.
文摘The growing developments in 5G and 6G wireless communications have revolutionized communications technologies,providing faster speeds with reduced latency and improved connectivity to users.However,it raises significant security challenges,including impersonation threats,data manipulation,distributed denial of service(DDoS)attacks,and privacy breaches.Traditional security measures are inadequate due to the decentralized and dynamic nature of next-generation networks.This survey provides a comprehensive review of how Federated Learning(FL),Blockchain,and Digital Twin(DT)technologies can collectively enhance the security of 5G and 6G systems.Blockchain offers decentralized,immutable,and transparent mechanisms for securing network transactions,while FL enables privacy-preserving collaborative learning without sharing raw data.Digital Twins create virtual replicas of network components,enabling real-time monitoring,anomaly detection,and predictive threat analysis.The survey examines major security issues in emerging wireless architectures and analyzes recent advancements that integrate FL,Blockchain,and DT to mitigate these threats.Additionally,it presents practical use cases,synthesizes key lessons learned,and identifies ongoing research challenges.Finally,the survey outlines future research directions to support the development of scalable,intelligent,and robust security frameworks for next-generation wireless networks.
文摘Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.
文摘The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)and artificial intelligence(AI)techniques,have become standard practice.The need for Federated Learning(FL)for ML model training in ORAN environments is heightened by the modularised structure of the ORAN architecture and the shortcomings of conventional ML techniques.However,the traditional plaintext model update sharing of FL in multi-BS contexts is susceptible to privacy violations such as deep-leakage gradient assaults and inference.Therefore,this research presents a novel blockchain-assisted improved cryptographic privacy-preserving federated learning(BICPPFL)model,with the help of ORAN,to safely carry out federated learning and protect privacy.This model improves on the conventional masking technique for sharing model parameters by adding new characteristics.These features include the choice of distributed aggregators,validation for final model aggregation,and individual validation for BSs.To manage the security and privacy of FL processes,a combined homomorphic proxy-reencryption(HPReE)and lattice-cryptographic method(HPReEL)has been used.The upgraded delegated proof of stake(Up-DPoS)consensus protocol,which will provide quick validation of model exchanges and protect against malicious attacks,is employed for effective consensus across blockchain nodes.Without sacrificing performance metrics,the BICPPFL model strengthens privacy and adds security layers while facilitating the transfer of sensitive data across several BSs.The framework is deployed on top of a Hyperledger Fabric blockchain to evaluate its effectiveness.The experimental findings prove the reliability and privacy-preserving capability of the BICPPFL model.
基金The Special Project of the Ministry of Construction ofChina (No.20060909).
文摘In order to establish the relationship between the measured dynamic response and the health status of long-span bridges, a double-layer model updating method for steel-concrete composite beam cable-stayed bridges is proposed. Measured frequencies are selected as the first-layer reference data, and the mass of the bridge deck, the grid density, the modulus of concrete and the ballast on the side span are modified by using a manual tuning technique. Measured global positioning system （GPS） data is selected as the second-layer reference data, and the degradation of the integral structure stiffness EI of the whole bridge is taken into account for the second-layer model updating by using the finite element iteration algorithm. The Nanpu Bridge in Shanghai is taken as a case to verify the applicability of the proposed model updating method. After the first-layer model updating, the standard deviation of modal frequencies is smaller than 7%. After the second-layer model updating, the error of the deflection of the mid-span is smaller than 10%. The integral structure stiffness of the whole bridge decreases about 20%. The research results show a good agreement between the calculated response and the measured response.
文摘In order to increase the fatigue life (FL) of road wheels (RW), a kind of double layer rubber flange (DLRF) is put forward. It consists of two layers of rubber, where metal wires are laid in the inner layer and the outer layer has no inlaid metal wires. Stress, strain and temperature field of DLRF were calculated with ANSYS finite element analysis (FEA) software, FL of DLRF RW was also computed with fracture mechanics fatigue theory. The results of computation indicate that the heat generated in RW's rubber flange (RF) can be reduced by the use of DLRF, and the FL of RW can be increased without affecting the mechanical intensity of RW.
文摘The aim of the study was to develop actarit double-layered osmotic pump tablets to overcome the weak points of actarit common tablets, such as short half-life and large plasma concentration fluctuations. Single factor experiment and orthogonal test were applied to optimize the formulation;the pharmacokinetic study was performed in beagle dogs adopting actarit common tablets as reference tablets. The optimal formulation was as follows: drug layer: 150 mg actarit, 240 mg PEO-N80, 50 mg NaCl;push layer: 140 mg PEO-WSR303, 20 mg NaCl;coating solution: 30 g cellulose acetate and 6 g PEG 4000 in 1000 ml 94% acetone solution, 60 mg coating weight gain. The pharmacokinetic study showed that T max was prolonged by the contrast of commercial common tablets with constant drug release rate, but the bioavailability was equivalent. And a good in vivo –in vitro correlation of the actarit osmotic pump tablets was also established. The designed actarit osmotic pump tablets can be applied for rheumatoid arthritis, proposing a promising replacement for the marked common products.
文摘AIM To investigate the efficacy of double-layered covered stent in the treatment of malignant oesophageal obstructions.METHODS A systematic review and meta-analysis was performed following the PRISMA process. Pub Med(Medline),EMBASE(Excerpta Medical Database),AMED(Allied and Complementary medicine Database),Scopus and online content,were searched for studies reporting on the Ni Ti-S polyurethane-covered double oesophageal stent for the treatment of malignant dysphagia. Weighted pooled outcomes were synthesized with a random effects model to account for clinical heterogeneity. All studies reporting the outcome of palliative management of dysphagia due to histologically confirmed malignant oesophageal obstruction using double-layered covered nitinol stent were included. The level of statistical significance was set at α = 0.05.RESULTS Six clinical studies comprising 250 patients in total were identified. Pooled technical success of stent insertion was 97.2%(95%CI: 94.8%-98.9%; I2 = 5.8%). Pooled complication rate was 27.6%(95%CI: 20.7%-35.2%; I2 = 41.9%). Weighted improvement of dysphagia on a scale of 0-5 scoring system was-2.00 [95%CI:-2.29%-(-1.72%); I2 = 87%]. Distal stent migration was documented in 10 out of the 250 cases examined.Pooled stent migration rate was 4.7%(95%CI: 2.5%-7.7%; I2 = 0%). Finally,tumour overgrowth was reported in 34 out of the 250 cases with pooled rate of tumour overgrowth of 11.2%(95%CI: 3.7%-22.1%; I2 = 82.2%). No funnel plot asymmetry to suggest publication bias(bias = 0.39,P = 0.78). In the sensitivity analysis all results were largely similar between the fixed and random effects models.CONCLUSION The double-layered nitinol stent provides immediate relief of malignant dysphagia with low rates of stent migration and tumour
基金Projects(50878191,51109092)supported by the National Natural Science Foundation of China
文摘Based on non-Darcian flow law described by exponent and threshold gradient within a double-layered soil, the classic theory of one-dimensional consolidation of double-layered soil was modified to consider the change of vertical total stress with depth and time together. Because of the complexity of governing equations, the numerical solutions were obtained in detail by finite difference method. Then, the numerical solutions were compared with the analytical solutions in condition that non-Darcian flow law was degenerated to Dary's law, and the comparison results show that numerical solutions are reliable. Finally, consolidation behavior of double-layered soil with different parameters was analyzed, and the results show that the consolidation rate of double-layered soil decreases with increasing the value of exponent and threshold of non-Darcian flow, and the exponent and threshold gradient of the first soil layer greatly influence the consolidation rate of double-layered soil. The larger the ratio of the equivalent water head of external load to the total thickness of double-layered soil, the larger the rate of the consolidation, and the similitude relationship in classical consolidation theory of double-layered soil is not satisfied. The other consolidation behavior of double-layered soil with non-Darcian flow is the same as that with Darcy's law.
文摘The velocity structures of flow through vertically double-layered vegetation(VDLV)as well as single-layered rigid vegetation(SLV)were investigated computationally with a three-dimensional(3D)Reynolds stress turbulence model,using the computational fluid dynamics(CFD)code FLUENT.The detailed velocity distribution was explored with a varying initial Froude number(Fr),with consideration of the steady subcritical flow conditions of an inland tsunami.In VDLV flows,the numerical model successfully captured the inflection point in the profiles of mean streamwise velocities in the mixing-layer region around the top of short submerged vegetation.An upward and downward movement of flow occurred at the positions located just behind the tall and short vegetation,respectively.Overall,higher streamwise velocities were observed in the upper vegetation layer due to high porosity,with Pr=98%(sparse vegetation,where Pr is the porosity),as compared to those in the lower vegetation layer,which had comparatively low porosity,with Pr=91%(dense vegetation).A rising trend of velocities was found as the flow passed through the vegetation region,followed by a clear sawtooth distribution,as compared to the regions just upstream and downstream of vegetation where the flow was almost uniform.In VDLV flows,a rising trend in the flow resistance was observed with the increase in the initial Froude number,i.e.,Fr?0.67,0.70,and 0.73.However,the flow resistance in the case of SLV was relatively very low.The numerical results also show the flow structures within the vicinity of short and tall vegetation,which are difficult to attain through experimental measurements.
基金Project(51578511)supported by the National Natural Science Foundation of China。
文摘To further investigate the one-dimensional(1D)rheological consolidation mechanism of double-layered soil,the fractional derivative Merchant model(FDMM)and the non-Darcian flow model with the non-Newtonian index are respectively introduced to describe the deformation of viscoelastic soil and the flow of pore water in the process of consolidation.Accordingly,an 1D rheological consolidation equation of double-layered soil is obtained,and its numerical analysis is performed by the implicit finite difference method.In order to verify its validity,the numerical solutions by the present method for some simplified cases are compared with the results in the related literature.Then,the influence of the revelent parameters on the rheological consolidation of double-layered soil are investigated.Numerical results indicate that the parameters of non-Darcian flow and FDMM of the first soil layer greatly influence the consolidation rate of double-layered soil.As the decrease of relative compressibility or the increase of relative permeability between the lower soil and the upper soil,the dissipation rate of excess pore water pressure and the settlement rate of the ground will be accelerated.Increasing the relative thickness of soil layer with high permeability or low compressibility will also accelerate the consolidation rate of double-layered soil.
