The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational mach...This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.展开更多
The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyeffic...The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyefficient communication.This study explores the integration of Reconfigurable Intelligent Surfaces(RIS)into IoT networks to enhance communication performance.Unlike traditional passive reflector-based approaches,RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes,addressing critical IoT challenges such as energy efficiency,limited communication range,and double-fading effects in backscatter communication.We propose a novel computational framework that combines RIS functionality with Physical Layer Security(PLS)mechanisms,optimized through the algorithm known as Deep Deterministic Policy Gradient(DDPG).This framework adaptively adapts RIS configurations and transmitter beamforming to reduce key challenges,including imperfect channel state information(CSI)and hardware limitations like quantized RIS phase shifts.By optimizing both RIS settings and beamforming in real-time,our approach outperforms traditional methods by significantly increasing secrecy rates,improving spectral efficiency,and enhancing energy efficiency.Notably,this framework adapts more effectively to the dynamic nature of wireless channels compared to conventional optimization techniques,providing scalable solutions for large-scale RIS deployments.Our results demonstrate substantial improvements in communication performance setting a new benchmark for secure,efficient and scalable 6G communication.This work offers valuable insights for the future of IoT networks,with a focus on computational optimization,high spectral efficiency and energy-aware operations.展开更多
Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to ter...Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.展开更多
Presented herein is a methodology for the multi-objective optimization of damping and bending stiffness of cocoured composite laminates with embedded viscoelastic damping layer. The embedded viscoelastic damping layer...Presented herein is a methodology for the multi-objective optimization of damping and bending stiffness of cocoured composite laminates with embedded viscoelastic damping layer. The embedded viscoelastic damping layer is perforated with a series of small holes, and the ratio of the perforation area to the total damping area is the design variable of the methodology. The multi-objective optimization is converted into a single-objective problem by an evaluation function which is a liner weigh sum of the two sub-objective functions. The proposed methodology was carried out to determine the optimal perforation area ratios of two viscoelstic layers with different perforation distance embedded in two composite plates. Both the optimal perforation area ratios are approximate to 2.2%. However, the objective value of the plate with greater perforation distance in embedded viscoelatic layer is much greater.展开更多
Based on the productivity equation of coalbed methane(CBM) wells, three indexes, main production layer optimization index, main production layer expansion index and capacity contribution index are proposed, with which...Based on the productivity equation of coalbed methane(CBM) wells, three indexes, main production layer optimization index, main production layer expansion index and capacity contribution index are proposed, with which the three-step optimization method of production-layer combination is established. In selecting main production layer, the coal seam thickness, CBM content, coal seam permeability, coal seam reservoir pressure and coal structure are considered comprehensively to evaluate the potential of the production layer. In selecting expansion of the main production layer combination, on the premise of ensuring full and slow desorption of the main production layer and non-exposure of the main production layer out of liquid surface, the degree of mutual interference between the main and non-main production layers is comprehensively evaluated by coupling the critical desorption pressure, layer spacing and reservoir pressure gradient difference. In optimizing production layer combination, the main concern is the economic efficiency of the combined layers. Only when the contribution coefficient of the main production layer is greater than 30% and the contribution index of the other production layers is more than 10%, the economic benefit of a CBM well after being put into production can be ensured. Based on the comparative analysis of the development effect of the development test wells in Songhe of Guizhou province, it is proved that the "three-step method" for the optimization of production-layer combination is scientific and practical, and can be used to design the multi-layer commingling scheme of coalbed methane.展开更多
It is unpractical to learn the optimal structure of a big Bayesian network(BN)by exhausting the feasible structures,since the number of feasible structures is super exponential on the number of nodes.This paper propos...It is unpractical to learn the optimal structure of a big Bayesian network(BN)by exhausting the feasible structures,since the number of feasible structures is super exponential on the number of nodes.This paper proposes an approach to layer nodes of a BN by using the conditional independence testing.The parents of a node layer only belong to the layer,or layers who have priority over the layer.When a set of nodes has been layered,the number of feasible structures over the nodes can be remarkably reduced,which makes it possible to learn optimal BN structures for bigger sizes of nodes by accurate algorithms.Integrating the dynamic programming(DP)algorithm with the layering approach,we propose a hybrid algorithm—layered optimal learning(LOL)to learn BN structures.Benefitted by the layering approach,the complexity of the DP algorithm reduces to O(ρ2^n?1)from O(n2^n?1),whereρ<n.Meanwhile,the memory requirements for storing intermediate results are limited to O(C k#/k#^2 )from O(Cn/n^2 ),where k#<n.A case study on learning a standard BN with 50 nodes is conducted.The results demonstrate the superiority of the LOL algorithm,with respect to the Bayesian information criterion(BIC)score criterion,over the hill-climbing,max-min hill-climbing,PC,and three-phrase dependency analysis algorithms.展开更多
We present a design method for calculating and optimizing sound absorption coefficient of multi-layered porous fibrous metals （PFM） in the low frequency range. PFM is simplified as an equivalent idealized sheet with...We present a design method for calculating and optimizing sound absorption coefficient of multi-layered porous fibrous metals （PFM） in the low frequency range. PFM is simplified as an equivalent idealized sheet with all metallic fibers aligned in one direction and distributed in periodic hexagonal patterns. We use a phenomenological model in the literature to investigate the effects of pore geometrical parameters （fiber diameter and gap） on sound absorption performance. The sound absorption coefficient of multi- layered PFMs is calculated using impedance translation theorem, To demonstrate the validity of the present model, we compare the predicted results with the experimental data. With the average sound absorption （low frequency range） as the objective function and the fiber gaps as the design variables, an optimization method for multi-layered fibrous metals is proposed. A new fibrous layout with given porosity of multi-layered fibrous metals is suggested to achieve optimal low frequency sound absorption. The sound absorption coefficient of the optimal multi-layered fibrous metal is higher than the single- layered fibrous metal, and a significant effect of the fibrous material on sound absorption is found due to the surface Dorosity of the multi-layered fibrous.展开更多
Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer...Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer hierarchical constraint method is proposed by coupling principal component analysis(PCA) dimensionality reduction and e-constraint method to translate the original high-dimensional problem into a bi-objective problem. This paper selects the main design objectives by conducting PCA to the preliminary solution of original problem with consideration of the priority of design objectives. According to the e-constraint method, the design model is established by treating the two top-ranking design goals as objective and others as variable constraints. A series of bi-objective Pareto curves will be obtained by changing the variable constraints, and the favorable solution can be obtained by analyzing Pareto curve spectrum. This method is applied to the rotor airfoil design and makes great improvement in aerodynamic performance. It is shown that the method is convenient and efficient, beyond which, it facilitates decision-making of the highdimensional multi-objective engineering problem.展开更多
The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of...The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy.But the power generated by wind turbine changes rapidly because of the continuous fluctuation of wind speed and direction.At the same time,wind energy conversion systems are of high order,time delays and strong nonlinear characteristics because of many uncertain factors.Based on analyzing the all dynamic processes of wind turbine,a kind of layered multi-mode optimal control strategy is presented which is that three control strategies:bang-bang,fuzzy and adaptive proportional integral derivative(PID)are adopted according to different stages and expected performance of wind turbine to capture optimum wind power,compensate the nonlinearity and improve the wind turbine performance at low,rated and high wind speed.展开更多
Microstructure and misfit dislocation behavior in In_xGa_(1-x)As/InP heteroepitaxial materials grown by low pressure metal organic chemical vapor deposition(LP-MOCVD) were analyzed by high resolution transmission elec...Microstructure and misfit dislocation behavior in In_xGa_(1-x)As/InP heteroepitaxial materials grown by low pressure metal organic chemical vapor deposition(LP-MOCVD) were analyzed by high resolution transmission electron microscopy(HRTEM), scanning electron microscopy(SEM), atomic force microscopy(AFM), Raman spectroscopy and Hall effect measurements. To optimize the structure of In_(0.82)Ga_(0.18)As/InP heterostructure, the In_xGa_(1-x)As buffer layer was grown. The residual strain of the In_(0.82)Ga_(0.18)As epitaxial layer was calculated. Further, the periodic growth pattern of the misfit dislocation at the interface was discovered and verified. Then the effects of misfit dislocation on the surface morphology and microstructure of the material were studied. It is found that the misfit dislocation of high indium(In) content In_(0.82)Ga_(0.18)As epitaxial layer has significant influence on the carrier concentration.展开更多
Rayleigh wave exploration is based on an elastic layered half-space model. If practical formations contain porous layers, these layers need to be simplified as an elastic medium. We studied the effects of this simplif...Rayleigh wave exploration is based on an elastic layered half-space model. If practical formations contain porous layers, these layers need to be simplified as an elastic medium. We studied the effects of this simplification on the results of Rayleigh wave exploration. Using a half-space model with coexisting porous and elastic layers, we derived the dispersion functions of Rayleigh waves in a porous layered half-space system with porous layers at different depths, and the problem of transferring variables to matrices of different orders is solved. To solve the significant digit overflow in the multiplication of transfer matrices, we propose a simple, effective method. Results suggest that dispersion curves differ in a low- frequency region when a porous layer is at the surface; otherwise, the difference is small.展开更多
In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for reco...In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.展开更多
We develop a uniaxial optimal perfectly matched layer （opt PML） method for solving the time-harmonic scattering problems by choosing a particular absorbing function with unbounded integral in a rectangular domain. W...We develop a uniaxial optimal perfectly matched layer （opt PML） method for solving the time-harmonic scattering problems by choosing a particular absorbing function with unbounded integral in a rectangular domain. With this choice, the solution of the optimal PML problem not only converges exponentially to the solution of the original scatting problem, but also is insensitive to the thickness of the PML layer for sufficiently small parameter ε0. Numerical experiments are included to illustrate the competitive behavior of the proposed optimal method.展开更多
In this study,an environment-friendly layered double hydroxide(LDH)film has been deposited on Mg Ca alloy by a two-step technique.To improve the chemical conversion technique and control the film properties,batch stud...In this study,an environment-friendly layered double hydroxide(LDH)film has been deposited on Mg Ca alloy by a two-step technique.To improve the chemical conversion technique and control the film properties,batch studies have been carried out to address various process parameters such as pH value,treatment temperature and immersion time.The chemical composition was determined by X-ray diffractometry and energy dispersive X-ray spectroscopy.The morphology was characterized by scanning electron microscopy.The corrosion resistance of the samples with various films was compared by polarization curves and immersion test.It is found that the transformation duration of Mg-Fe LDH is long.Too high pH value and temperature has harmful effect on the purity of the film composition.The corrosion resistance of the films formed at low value of pH or high temperature or short treatment time is deteriorative.The optimum process is as follows:the sample is first immersed in the solution containing Fe^(3+)/HCO_(3)^-/CO_(3)^(2-)with a pH value of 5 at a temperature of 55℃for 1 h to form a precursor film,and then this precursor film is immersed into the solution containing Fe^(3+)/HCO_(3)^-/CO_(3)^(2-)with a pH of 11 at 55℃for 24 h to obtain the Mg-Fe LDH conversion film.展开更多
This study develops a method for the full-size structural design of blade,involving the optimal layer thickness configuration of the blade to maximize its bending stiffness using a genetic algorithm.Numerical differen...This study develops a method for the full-size structural design of blade,involving the optimal layer thickness configuration of the blade to maximize its bending stiffness using a genetic algorithm.Numerical differentiation is employed to solve the sensitivity of blade modal frequency to the layer thickness of each part of blade.The natural frequencies of first-order flapwise and edgewise modes are selected as the optimal objectives.Based on the modal sensitivity analysis of all design variables,the effect of discretized layer thickness on bending stiffness of the blade is explored,and 14 significant design variables are filtered to drive the structural optimization.The best solution predicts an increase in natural frequencies of first-order flapwise and edgewise blade modes by up to 12%and 10.4%,respectively.The results show that the structural optimization method based on modal sensitivity is more effective to improve the structural performance.展开更多
In this article, the model of a non-Newtonian fluid (Thixotropic) flow past a vertical surface in the presence of exponential space and temperature dependent heat source in a thermally stratified medium is studied. It...In this article, the model of a non-Newtonian fluid (Thixotropic) flow past a vertical surface in the presence of exponential space and temperature dependent heat source in a thermally stratified medium is studied. It is assumed that free convection is induced by buoyancy and exponentially decaying internal heat source across the space. The dynamic viscosity is taken to be constant and thermal conductivity of this particular fluid model is assumed to vary linearly with temperature. Thermal stratification has been properly incorporated into the governing equation so that its effect can be revealed and properly reported. The governing partial differential equations describing the model are transformed and parameterized to a system of non-linear ordinary differential equation using similarity transformations. Approximate analytic solutions were obtained by adopting Optimal Homotopy Analysis Method (OHAM). The results show that for both cases of non-Newtonian parameters (Thixotropic) (K1=K2=0?& K1=K2=1.0), increasing stratification parameters, relate to decreasing in the heat energy entering into the fluid region and thus reducing the temperature of the Thixotropic fluid as it flows.展开更多
Pavement construction in permafrost regions is complicated by the fact that the permafrost properties are influenced by the temperature and are extremely unstable.The numerical model for runway structures in permafros...Pavement construction in permafrost regions is complicated by the fact that the permafrost properties are influenced by the temperature and are extremely unstable.The numerical model for runway structures in permafrost regions is applied to analyze the time–space characteristics of the temperature field and the depth of the frozen layer.The influence of the installation layer is studied to enable structural optimization of the runway.Numerical results show that the temperature stabilization depth,low-and high-temperature interlayer response ranges,and maximum depth of the frozen layer are greater in runway engineering than in highway and railway engineering.The time history curves for the pavement and natural surface are similar,and the development of freezing and thawing is approximately linear.The pavement and natural surface have similar thawing rates,but the freezing rate of the natural surface is faster than that of the pavement.The depth of the frozen layer and the time of the frozen are greater for the natural surface than for the pavement.The installation layer helps to stabilize the temperature of the subgrade and reduces the freezing and thawing rates.This study provides technical support for the design and maintenance of runways in permafrost regions.展开更多
To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.Th...To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.展开更多
Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selecti...Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network usability.Further,choosing the optimal number of hidden nodes for a network usually requires intensive human intervention,which may lead to an ill-conditioned situation.In this context,chemical reaction optimization(CRO)is a meta-heuristic paradigm with increased success in a large number of application areas.It is characterized by faster convergence capability and requires fewer tunable parameters.This study develops a learning framework combining the advantages of ELM and CRO,called extreme learning with chemical reaction optimization(ELCRO).ELCRO simultaneously optimizes the weight and bias vector and number of hidden neurons of a single layer feed-forward neural network without compromising prediction accuracy.We evaluate its performance by predicting the daily volatility and closing prices of BSE indices.Additionally,its performance is compared with three other similarly developed models—ELM based on particle swarm optimization,genetic algorithm,and gradient descent—and find the performance of the proposed algorithm superior.Wilcoxon signed-rank and Diebold–Mariano tests are then conducted to verify the statistical significance of the proposed model.Hence,this model can be used as a promising tool for financial forecasting.展开更多
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
基金supported by the National Natural Science Foundation of China under Grant 52325402,52274057,and 52074340the National Key R&D Program of China under Grant 2023YFB4104200+2 种基金the Major Scientific and Technological Projects of CNOOC under Grant CCL2022RCPS0397RSN111 Project under Grant B08028China Scholarship Council under Grant 202306450108.
文摘This study introduces a novel approach to addressing the challenges of high-dimensional variables and strong nonlinearity in reservoir production and layer configuration optimization.For the first time,relational machine learning models are applied in reservoir development optimization.Traditional regression-based models often struggle in complex scenarios,but the proposed relational and regression-based composite differential evolution(RRCODE)method combines a Gaussian naive Bayes relational model with a radial basis function network regression model.This integration effectively captures complex relationships in the optimization process,improving both accuracy and convergence speed.Experimental tests on a multi-layer multi-channel reservoir model,the Egg reservoir model,and a real-field reservoir model(the S reservoir)demonstrate that RRCODE significantly reduces water injection and production volumes while increasing economic returns and cumulative oil recovery.Moreover,the surrogate models employed in RRCODE exhibit lightweight characteristics with low computational overhead.These results highlight RRCODE's superior performance in the integrated optimization of reservoir production and layer configurations,offering more efficient and economically viable solutions for oilfield development.
基金funded by the deanship of scientific research(DSR),King Abdukaziz University,Jeddah,under grant No.(G-1436-611-225)。
文摘The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet ofThings(IoT)applications,particularly in terms of ultra-reliable,secure,and energyefficient communication.This study explores the integration of Reconfigurable Intelligent Surfaces(RIS)into IoT networks to enhance communication performance.Unlike traditional passive reflector-based approaches,RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes,addressing critical IoT challenges such as energy efficiency,limited communication range,and double-fading effects in backscatter communication.We propose a novel computational framework that combines RIS functionality with Physical Layer Security(PLS)mechanisms,optimized through the algorithm known as Deep Deterministic Policy Gradient(DDPG).This framework adaptively adapts RIS configurations and transmitter beamforming to reduce key challenges,including imperfect channel state information(CSI)and hardware limitations like quantized RIS phase shifts.By optimizing both RIS settings and beamforming in real-time,our approach outperforms traditional methods by significantly increasing secrecy rates,improving spectral efficiency,and enhancing energy efficiency.Notably,this framework adapts more effectively to the dynamic nature of wireless channels compared to conventional optimization techniques,providing scalable solutions for large-scale RIS deployments.Our results demonstrate substantial improvements in communication performance setting a new benchmark for secure,efficient and scalable 6G communication.This work offers valuable insights for the future of IoT networks,with a focus on computational optimization,high spectral efficiency and energy-aware operations.
文摘Existing systems use key performance indicators(KPIs)as metrics for physical layer(PHY)optimization,which suffers from the problem of overoptimization,because some unnecessary PHY enhancements are imperceptible to terminal users and thus induce additional cost and energy waste.Therefore,it is necessary to utilize directly the quality of experience(QoE)of user as a metric of optimization,which can achieve the global optimum of QoE under cost and energy constraints.However,QoE is still a metric of application layer that cannot be easily used to design and optimize the PHY.To address this problem,we in this paper propose a novel end-to-end QoE(E2E-QoE)based optimization architecture at the user-side for the first time.Specifically,a cross-layer parameterized model is proposed to establish the relationship between PHY and E2E-QoE.Based on this,an E2E-QoE oriented PHY anomaly diagnosis method is further designed to locate the time and root cause of anomalies.Finally,we investigate to optimize the PHY algorithm directly based on the E2E-QoE.The proposed frameworks and algorithms are all validated using the data from real fifth-generation(5G)mobile system,which show that using E2E-QoE as the metric of PHY optimization is feasible and can outperform existing schemes.
文摘Presented herein is a methodology for the multi-objective optimization of damping and bending stiffness of cocoured composite laminates with embedded viscoelastic damping layer. The embedded viscoelastic damping layer is perforated with a series of small holes, and the ratio of the perforation area to the total damping area is the design variable of the methodology. The multi-objective optimization is converted into a single-objective problem by an evaluation function which is a liner weigh sum of the two sub-objective functions. The proposed methodology was carried out to determine the optimal perforation area ratios of two viscoelstic layers with different perforation distance embedded in two composite plates. Both the optimal perforation area ratios are approximate to 2.2%. However, the objective value of the plate with greater perforation distance in embedded viscoelatic layer is much greater.
基金Supported by the China National Science and Technology Major Project(2016ZX05044-002)the National Natural Science Foundation of China(41772155)the Fundamental Research Funds for the Central Universities of China(No.2015XKZD07)
文摘Based on the productivity equation of coalbed methane(CBM) wells, three indexes, main production layer optimization index, main production layer expansion index and capacity contribution index are proposed, with which the three-step optimization method of production-layer combination is established. In selecting main production layer, the coal seam thickness, CBM content, coal seam permeability, coal seam reservoir pressure and coal structure are considered comprehensively to evaluate the potential of the production layer. In selecting expansion of the main production layer combination, on the premise of ensuring full and slow desorption of the main production layer and non-exposure of the main production layer out of liquid surface, the degree of mutual interference between the main and non-main production layers is comprehensively evaluated by coupling the critical desorption pressure, layer spacing and reservoir pressure gradient difference. In optimizing production layer combination, the main concern is the economic efficiency of the combined layers. Only when the contribution coefficient of the main production layer is greater than 30% and the contribution index of the other production layers is more than 10%, the economic benefit of a CBM well after being put into production can be ensured. Based on the comparative analysis of the development effect of the development test wells in Songhe of Guizhou province, it is proved that the "three-step method" for the optimization of production-layer combination is scientific and practical, and can be used to design the multi-layer commingling scheme of coalbed methane.
基金supported by the National Natural Science Foundation of China(61573285)
文摘It is unpractical to learn the optimal structure of a big Bayesian network(BN)by exhausting the feasible structures,since the number of feasible structures is super exponential on the number of nodes.This paper proposes an approach to layer nodes of a BN by using the conditional independence testing.The parents of a node layer only belong to the layer,or layers who have priority over the layer.When a set of nodes has been layered,the number of feasible structures over the nodes can be remarkably reduced,which makes it possible to learn optimal BN structures for bigger sizes of nodes by accurate algorithms.Integrating the dynamic programming(DP)algorithm with the layering approach,we propose a hybrid algorithm—layered optimal learning(LOL)to learn BN structures.Benefitted by the layering approach,the complexity of the DP algorithm reduces to O(ρ2^n?1)from O(n2^n?1),whereρ<n.Meanwhile,the memory requirements for storing intermediate results are limited to O(C k#/k#^2 )from O(Cn/n^2 ),where k#<n.A case study on learning a standard BN with 50 nodes is conducted.The results demonstrate the superiority of the LOL algorithm,with respect to the Bayesian information criterion(BIC)score criterion,over the hill-climbing,max-min hill-climbing,PC,and three-phrase dependency analysis algorithms.
基金the support of the National Basic Research Program(973 Program)of China(Grant No.2011CB610304)the National Natural Science Foundation of China(Grant Nos.11332004 and 11402046)+2 种基金China Postdoctoral Science Foundation(No.2015M571296)the 111 Project(B14013)the CATIC Industrial Production Projects(Grant No.CXY2013DLLG32)
文摘We present a design method for calculating and optimizing sound absorption coefficient of multi-layered porous fibrous metals （PFM） in the low frequency range. PFM is simplified as an equivalent idealized sheet with all metallic fibers aligned in one direction and distributed in periodic hexagonal patterns. We use a phenomenological model in the literature to investigate the effects of pore geometrical parameters （fiber diameter and gap） on sound absorption performance. The sound absorption coefficient of multi- layered PFMs is calculated using impedance translation theorem, To demonstrate the validity of the present model, we compare the predicted results with the experimental data. With the average sound absorption （low frequency range） as the objective function and the fiber gaps as the design variables, an optimization method for multi-layered fibrous metals is proposed. A new fibrous layout with given porosity of multi-layered fibrous metals is suggested to achieve optimal low frequency sound absorption. The sound absorption coefficient of the optimal multi-layered fibrous metal is higher than the single- layered fibrous metal, and a significant effect of the fibrous material on sound absorption is found due to the surface Dorosity of the multi-layered fibrous.
基金supported by the National Natural Science Foundation of China (No. 11402288 and 11372254)the National Basic Research Program of China (No. 2014CB744804)
文摘Rotor airfoil design is investigated in this paper. There are many difficulties for this highdimensional multi-objective problem when traditional multi-objective optimization methods are used. Therefore, a multi-layer hierarchical constraint method is proposed by coupling principal component analysis(PCA) dimensionality reduction and e-constraint method to translate the original high-dimensional problem into a bi-objective problem. This paper selects the main design objectives by conducting PCA to the preliminary solution of original problem with consideration of the priority of design objectives. According to the e-constraint method, the design model is established by treating the two top-ranking design goals as objective and others as variable constraints. A series of bi-objective Pareto curves will be obtained by changing the variable constraints, and the favorable solution can be obtained by analyzing Pareto curve spectrum. This method is applied to the rotor airfoil design and makes great improvement in aerodynamic performance. It is shown that the method is convenient and efficient, beyond which, it facilitates decision-making of the highdimensional multi-objective engineering problem.
基金Science & Technology Development Foundation of Shanghai,China(No.062158017)Postdoctoral Foundation of Shanghai,China(No.05R214133)Postdoctoral Foundation of China(No.2005038435)
文摘The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy.But the power generated by wind turbine changes rapidly because of the continuous fluctuation of wind speed and direction.At the same time,wind energy conversion systems are of high order,time delays and strong nonlinear characteristics because of many uncertain factors.Based on analyzing the all dynamic processes of wind turbine,a kind of layered multi-mode optimal control strategy is presented which is that three control strategies:bang-bang,fuzzy and adaptive proportional integral derivative(PID)are adopted according to different stages and expected performance of wind turbine to capture optimum wind power,compensate the nonlinearity and improve the wind turbine performance at low,rated and high wind speed.
基金supported by the National Key Basic Research Program of China(No.2012CB619200)the National Natural Science Foundation of China(No.61474053)+1 种基金the State Key Laboratory for Mechanical Behavior of Materials of Xi'an Jiaotong University(No.20161806)the Natural Science Basic Research Open Foundation of the Key Lab of Automobile Materials,Ministry of Education,Jilin University(No.1018320144001)
文摘Microstructure and misfit dislocation behavior in In_xGa_(1-x)As/InP heteroepitaxial materials grown by low pressure metal organic chemical vapor deposition(LP-MOCVD) were analyzed by high resolution transmission electron microscopy(HRTEM), scanning electron microscopy(SEM), atomic force microscopy(AFM), Raman spectroscopy and Hall effect measurements. To optimize the structure of In_(0.82)Ga_(0.18)As/InP heterostructure, the In_xGa_(1-x)As buffer layer was grown. The residual strain of the In_(0.82)Ga_(0.18)As epitaxial layer was calculated. Further, the periodic growth pattern of the misfit dislocation at the interface was discovered and verified. Then the effects of misfit dislocation on the surface morphology and microstructure of the material were studied. It is found that the misfit dislocation of high indium(In) content In_(0.82)Ga_(0.18)As epitaxial layer has significant influence on the carrier concentration.
基金supported by National Sciences Foundation(No.11174321,11174322,and 11574343)
文摘Rayleigh wave exploration is based on an elastic layered half-space model. If practical formations contain porous layers, these layers need to be simplified as an elastic medium. We studied the effects of this simplification on the results of Rayleigh wave exploration. Using a half-space model with coexisting porous and elastic layers, we derived the dispersion functions of Rayleigh waves in a porous layered half-space system with porous layers at different depths, and the problem of transferring variables to matrices of different orders is solved. To solve the significant digit overflow in the multiplication of transfer matrices, we propose a simple, effective method. Results suggest that dispersion curves differ in a low- frequency region when a porous layer is at the surface; otherwise, the difference is small.
基金supported by the National Defense Pre-research Project in 13th Five-Year(41404050502)the National Defense Science and Technology Fund of the Central Military Commission(2101140)
文摘In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.
基金The Major State Research Development Program (2005CB321701) of Chinathe NSF(10801063) of China
文摘We develop a uniaxial optimal perfectly matched layer （opt PML） method for solving the time-harmonic scattering problems by choosing a particular absorbing function with unbounded integral in a rectangular domain. With this choice, the solution of the optimal PML problem not only converges exponentially to the solution of the original scatting problem, but also is insensitive to the thickness of the PML layer for sufficiently small parameter ε0. Numerical experiments are included to illustrate the competitive behavior of the proposed optimal method.
基金financial support by the Sichuan Science and Technology Program(No.2020YFG0165)the Projects in Sichuan Province Education Office(No.18ZA0453)+1 种基金the National Natural Science Foundation of China(No.51501156)the Sichuan Science and Technology Program(No.2019JDTD0024&No.2019ZHCG0048)。
文摘In this study,an environment-friendly layered double hydroxide(LDH)film has been deposited on Mg Ca alloy by a two-step technique.To improve the chemical conversion technique and control the film properties,batch studies have been carried out to address various process parameters such as pH value,treatment temperature and immersion time.The chemical composition was determined by X-ray diffractometry and energy dispersive X-ray spectroscopy.The morphology was characterized by scanning electron microscopy.The corrosion resistance of the samples with various films was compared by polarization curves and immersion test.It is found that the transformation duration of Mg-Fe LDH is long.Too high pH value and temperature has harmful effect on the purity of the film composition.The corrosion resistance of the films formed at low value of pH or high temperature or short treatment time is deteriorative.The optimum process is as follows:the sample is first immersed in the solution containing Fe^(3+)/HCO_(3)^-/CO_(3)^(2-)with a pH value of 5 at a temperature of 55℃for 1 h to form a precursor film,and then this precursor film is immersed into the solution containing Fe^(3+)/HCO_(3)^-/CO_(3)^(2-)with a pH of 11 at 55℃for 24 h to obtain the Mg-Fe LDH conversion film.
基金supported by the National Natural Science Foundation of China(Nos.51965034,51565028)the Lanzhou City Innovation and Entrepreneurship Project(No.2018-RC-25)。
文摘This study develops a method for the full-size structural design of blade,involving the optimal layer thickness configuration of the blade to maximize its bending stiffness using a genetic algorithm.Numerical differentiation is employed to solve the sensitivity of blade modal frequency to the layer thickness of each part of blade.The natural frequencies of first-order flapwise and edgewise modes are selected as the optimal objectives.Based on the modal sensitivity analysis of all design variables,the effect of discretized layer thickness on bending stiffness of the blade is explored,and 14 significant design variables are filtered to drive the structural optimization.The best solution predicts an increase in natural frequencies of first-order flapwise and edgewise blade modes by up to 12%and 10.4%,respectively.The results show that the structural optimization method based on modal sensitivity is more effective to improve the structural performance.
文摘In this article, the model of a non-Newtonian fluid (Thixotropic) flow past a vertical surface in the presence of exponential space and temperature dependent heat source in a thermally stratified medium is studied. It is assumed that free convection is induced by buoyancy and exponentially decaying internal heat source across the space. The dynamic viscosity is taken to be constant and thermal conductivity of this particular fluid model is assumed to vary linearly with temperature. Thermal stratification has been properly incorporated into the governing equation so that its effect can be revealed and properly reported. The governing partial differential equations describing the model are transformed and parameterized to a system of non-linear ordinary differential equation using similarity transformations. Approximate analytic solutions were obtained by adopting Optimal Homotopy Analysis Method (OHAM). The results show that for both cases of non-Newtonian parameters (Thixotropic) (K1=K2=0?& K1=K2=1.0), increasing stratification parameters, relate to decreasing in the heat energy entering into the fluid region and thus reducing the temperature of the Thixotropic fluid as it flows.
基金the National Natural Science Foundation of China(Grant No.52108333)the Natural Science Foundation of Tianjin(Grant Nos.18JCQNJC08300,18JCYBJC90800,20JCQNJC01320)the Key Laboratory of Road Structure and Materials Transportation Industry(Grant No.310821171114)for providing the funding that made this study possible.
文摘Pavement construction in permafrost regions is complicated by the fact that the permafrost properties are influenced by the temperature and are extremely unstable.The numerical model for runway structures in permafrost regions is applied to analyze the time–space characteristics of the temperature field and the depth of the frozen layer.The influence of the installation layer is studied to enable structural optimization of the runway.Numerical results show that the temperature stabilization depth,low-and high-temperature interlayer response ranges,and maximum depth of the frozen layer are greater in runway engineering than in highway and railway engineering.The time history curves for the pavement and natural surface are similar,and the development of freezing and thawing is approximately linear.The pavement and natural surface have similar thawing rates,but the freezing rate of the natural surface is faster than that of the pavement.The depth of the frozen layer and the time of the frozen are greater for the natural surface than for the pavement.The installation layer helps to stabilize the temperature of the subgrade and reduces the freezing and thawing rates.This study provides technical support for the design and maintenance of runways in permafrost regions.
基金supported by the National Natural Science Foundation of China(Grant No.61961024)the Top Double 1000 Talent Programme of Jiangxi Province(Grant No.JXSQ2019201055)+1 种基金the Natural Science Foundation of Jiangxi Province(Grant No.20181BAB202001)the Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security(Grant No.AGK201602)。
文摘To further improve the secrecy rate,a joint optimization scheme for the reconfigurable intelligent surface(RIS)phase shift and the power allocation is proposed in the untrusted relay(UR)networks assisted by the RIS.The eavesdropping on the UR is interfered by a source-based jamming strategy.Under the constraints of unit modulus and total power,the RIS phase shift,the power allocation between the confidential signal and the jamming signal,and the power allocation between the source node and the UR are jointly optimized to maximize the secrecy rate.The complex multivariable coupling problem is decomposed into three sub-problems,and the non-convexity of the objective function and the constraints is solved with semi-definite relaxation.Simulation results indicate that the secrecy rate is remarkably enhanced with the proposed scheme compared with the equal power allocation scheme,the random phase shift scheme,and the no-RIS scheme.
文摘Extreme learning machine(ELM)allows for fast learning and better generalization performance than conventional gradient-based learning.However,the possible inclusion of non-optimal weight and bias due to random selection and the need for more hidden neurons adversely influence network usability.Further,choosing the optimal number of hidden nodes for a network usually requires intensive human intervention,which may lead to an ill-conditioned situation.In this context,chemical reaction optimization(CRO)is a meta-heuristic paradigm with increased success in a large number of application areas.It is characterized by faster convergence capability and requires fewer tunable parameters.This study develops a learning framework combining the advantages of ELM and CRO,called extreme learning with chemical reaction optimization(ELCRO).ELCRO simultaneously optimizes the weight and bias vector and number of hidden neurons of a single layer feed-forward neural network without compromising prediction accuracy.We evaluate its performance by predicting the daily volatility and closing prices of BSE indices.Additionally,its performance is compared with three other similarly developed models—ELM based on particle swarm optimization,genetic algorithm,and gradient descent—and find the performance of the proposed algorithm superior.Wilcoxon signed-rank and Diebold–Mariano tests are then conducted to verify the statistical significance of the proposed model.Hence,this model can be used as a promising tool for financial forecasting.
