In this paper,we propose a systematic approach for accelerating finite element-type methods by machine learning for the numerical solution of partial differential equations(PDEs).The main idea is to use a neural netwo...In this paper,we propose a systematic approach for accelerating finite element-type methods by machine learning for the numerical solution of partial differential equations(PDEs).The main idea is to use a neural network to learn the solution map of the PDEs and to do so in an element-wise fashion.This map takes input of the element geometry and the PDE’s parameters on that element,and gives output of two operators:(1)the in2out operator for inter-element communication,and(2)the in2sol operator(Green’s function)for element-wise solution recovery.A significant advantage of this approach is that,once trained,this network can be used for the numerical solution of the PDE for any domain geometry and any parameter distribution without retraining.Also,the training is significantly simpler since it is done on the element level instead on the entire domain.We call this approach element learning.This method is closely related to hybridizable discontinuous Galerkin(HDG)methods in the sense that the local solvers of HDG are replaced by machine learning approaches.Numerical tests are presented for an example PDE,the radiative transfer or radiation transport equation,in a variety of scenarios with idealized or realistic cloud fields,with smooth or sharp gradient in the cloud boundary transition.Under a fixed accuracy level of 10^(−3) in the relative L^(2) error,and polynomial degree p=6 in each element,we observe an approximately 5 to 10 times speed-up by element learning compared to a classical finite element-type method.展开更多
The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic fi...The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic field.These microorganisms produce density gradients by swimming,which induces macroscopic convection flows in the fluid.This procedure improves the mass and heat transfer,illustrating the interaction between biological activity and fluid dynamics.Furthermore,instead of considering traditional Fourier's and Fick's law the energy and concentration equations are developed by incorporating Cattaneo-Christov double diffusion theory.Moreover,to examine the influence of thermophoresis and Brownian diffusions in the fluid we have adopted the Buongiorno nanofluid model.Due to the oscillation of the surface of the channel,the mathematical development of the considered flow problem is obtained in the form of partial differential equations via the curvilinear coordinate system.The convergent series solution of the governing flow equations is obtained after applying the homotopy analysis method(HAM).The effects of different pertinent flow parameters on velocity,motile microorganism density distribution,concentration,pressure,temperature,and skin friction coefficient are examined and discussed in detail with the help of graphs and tables.It is observed during the current study that the density of microorganisms is enhanced for higher values of Reynolds number,Peclet number,radius of curvature variable,and Lewis number.展开更多
It is well known that the inhomogeneous Calderón-Zygmund convolution operators are bounded on the local Hardy spaces.In this paper,we prove that these operators are bounded on the local product Hardy spaces and t...It is well known that the inhomogeneous Calderón-Zygmund convolution operators are bounded on the local Hardy spaces.In this paper,we prove that these operators are bounded on the local product Hardy spaces and the Lipschitz spaces.The key ideas used here are the discrete local Calderón identity and a density argument for the inhomogeneous product Lipschitz spaces in the weak sense.展开更多
A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order ...A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order time derivatives.The proposed scheme attains third-order temporal accuracy and is rigorously validated through stability and convergence analyses for both scalar and coupled systems.Its effectiveness is demonstrated by simulating unsteady Eyring-Prandtl non-Newtonian nanofluid flow over a Riga plate with coupled heat and mass transfer under electromagnetic actuation.The physical model accounts for Brownian motion and thermophoresis,and the nanofluid considered is a Prandtl-type non-Newtonian base fluid containing suspended nanoparticles,with heat and mass transport governed by coupled momentum,energy,and concentration equations.Numerical simulations are performed over practically relevant parameter ranges,with the Reynolds number fixed at Re=5 and the Prandtl number set to Pr=3 to represent moderate inertial and thermal diffusion effects typical of nanofluid transport systems.To enhance computational efficiency,an artificial neural network(ANN)-based surrogate model is developed to predict the skin friction coefficient and local Sherwood number as functions of Reynolds number,Prandtl number,Schmidt number,Brownian motion,and thermophoresis parameters.The training dataset is generated entirely from high-fidelity numerical simulations produced by the proposed hybrid scheme.The data are systematically partitioned into 70%for training,15%for validation,and 15%for testing,ensuring reliable generalization.Regression analysis yields a near-unity correlation coefficient(R≈0.99),while error histograms exhibit tightly clustered residuals around zero,confirming high predictive accuracy.Furthermore,a benchmark convergence study using Stokes’first problem demonstrates that the proposed scheme consistently achieves lower global error norms than the classical Runge–Kutta method for identical spatial and temporal resolutions.Overall,this study introduces a novel computational intelligence framework that integrates high-order numerical solvers with machine learning,offering a robust and time-efficient tool for advanced modeling and real-time prediction of non-Newtonian nanofluid transport phenomena under electromagnetic flow control.展开更多
The purpose of the present investigation is to explore the implications of Cross fluid in a Darcy-Forchheimer porousmediumdue to the tri-hybrid nanofluid past a porous cylinder.Thermal radiation,heat generation,therma...The purpose of the present investigation is to explore the implications of Cross fluid in a Darcy-Forchheimer porousmediumdue to the tri-hybrid nanofluid past a porous cylinder.Thermal radiation,heat generation,thermal convection,solutal convective and chemical reaction have been encountered in this analysis.Entropy generation has been accounted for under the fluidic friction,heat rate analysis,and porosity analysis.Three different nanoparticles of multiwall carbon nanotube(MWCNT),aluminum oxide(Al_(2)O_(3)),and silver(Ag)are utilized to illustrate the tri-hybrid nanofluid flow with Ethlene Glycol(EG)as the base fluid.The governance model,consisting of linked inadequate differential conditions,is transformed into an ordinary configuration of nonlinear coupled differential conditions by acceptable adjustments.The obtained outcomes in combination with the bvp4c approach are then used to resolve the generated ODEs.For discussion purposes,the impacts of the physical limitations on temperature profile,velocity,and concentration have also been illustrated.Numerical results have been obtained for the diffusion rate,heat transfer rate,drag force,and other factors.While the Forchheimer parameter and the inclination angle reduce the fluid flow’s velocity,the Biot number of heat and mass transfer influences the fluid’s temperature.According to the findings,hybrid nanofluid is the most effective way to improve heat transmission and may also be utilized for cooling.Three different kinds of nanofluids were used in a comparative examination to clarify the study’s conclusions.Changes in viscosity and porousness caused the nanofluids’velocity to drop by 13.12%and 15.8%,respectively;however,trihybrid nanofluids with improved convection showed a 13.12%rise.展开更多
In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→...In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.展开更多
Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analy...Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analysis of ternary hybrid nanofluids,TiO_(2)-CdTe-MoS_(2) dispersed in water,flowing over a vertical stretching or shrinking surface in a Darcy-Brinkman porous medium.The investigation accounts for the combined effects of magnetohydrodynamics,thermal radiation,viscous dissipation,and internal heat generation.In contrast to previous studies that predominantly focused on single or binary nanofluids,the present work systematically examines the thermal and hydrodynamic performance of ternary hybrid nanofluids,highlighting their enhanced heat transport capabilities in porous structures.The governing momentum and energy equations are formulated in nondimensional form and solved numerically using the shifted Legendre collocation method.The results show that increasing the magnetic parameter,M=0-4,suppresses the fluid velocity by up to 28%,while stronger thermal radiation,R=0-5,raises the near-surface temperature by approximately 32%.Viscous dissipation and internal heat generation further enhance the Nusselt number,indicating improved heat transfer performance.Overall,the findings demonstrate the synergistic influence of the three nanoparticles in optimizing flow behavior and thermal characteristics,offering valuable insights for the design of high-performance thermal management systems in energy and aerospace applications.展开更多
Thiswork explores aMagnetohydrodynamic(MHD)flowin a triangular cavitywith a thermally insulated baffle.Enclosure’s inclined wall is hotter,whereas the vertical border is adiabatic and the bottom is cooler.The study a...Thiswork explores aMagnetohydrodynamic(MHD)flowin a triangular cavitywith a thermally insulated baffle.Enclosure’s inclined wall is hotter,whereas the vertical border is adiabatic and the bottom is cooler.The study aims to clarify how geometric changes affect thermal performance and offers new perspectives on how to improve heat dissipation mechanisms.A COMSOL Multiphysics version 6.2 has been used to solve numerical solutions.Streamlines and thermal distributions are examined systematically in order to understand how the unique geometry and baffle size of triangular cavities can influence the fluid flow.This influence can result in optimized flow patterns,promoting efficient heat transfer by directing the fluid to specific areas that require more cooling.In comparison with conventional designs,this optimization results in more efficient convective heat transfer,which raises cooling efficiency and lowers thermal resistance.Furthermore,by strengthening heat transfer characteristics in heat transfer systems,these geometries increase thermal efficiency,which helps several sectors,including the production of electricity,HVAC,and the automobile industry.展开更多
In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regiona...In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regional controllability is more adapted to systems described by dynamic systems.Regional controllability results in a strategic area were established for vibrating plates by the Hilbertian Uniqueness Method.展开更多
Elliptic curve(EC)based cryptosystems gained more attention due to enhanced security than the existing public key cryptosystems.A substitution box(S-box)plays a vital role in securing modern symmetric key cryptosystem...Elliptic curve(EC)based cryptosystems gained more attention due to enhanced security than the existing public key cryptosystems.A substitution box(S-box)plays a vital role in securing modern symmetric key cryptosystems.However,the recently developed EC based algorithms usually trade off between computational efficiency and security,necessitating the design of a new algorithm with the desired cryptographic strength.To address these shortcomings,this paper proposes a new scheme based onMordell elliptic curve(MEC)over the complex field for generating distinct,dynamic,and highly uncorrelated S-boxes.Furthermore,we count the exact number of the obtained S-boxes,and demonstrate that the permuted version of the presented S-box is statistically optimal.The nonsingularity of the presented algorithm and the injectivity of the resultant output are explored.Rigorous theoretical analysis and experimental results demonstrate that the proposedmethod is highly effective in generating a large number of dynamic S-boxes with adequate cryptographic properties,surpassing current state-of-the-art S-box generation algorithms in terms of security.Apart fromthis,the generated S-box is benchmarked using side-channel attacks,and its performance is compared with highly nonlinear S-boxes,demonstrating comparable results.In addition,we present an application of our proposed S-box generator by incorporating it into an image encryption technique.The encrypted and decrypted images are tested by employing extensive standard security metrics,including the Number of Pixel Change Rate,the Unified Average Changing Intensity,information entropy,correlation coefficient,and histogram analysis.Moreover,the analysis is extended beyond conventional metrics to validate the new method using advanced tests,such as the NIST statistical test suite,robustness analysis,and noise and cropping attacks.Experimental outcomes show that the presented algorithm strengthens the existing encryption scheme against various well-known cryptographic attacks.展开更多
The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearitie...The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearities.To discretize the continuous problem in space,we utilize a spectral Galerkin method.Subsequently,we introduce a nonlinear-tamed exponential integrator scheme,resulting in a fully discrete scheme.Within the framework of semigroup theory,this study provides precise estimations of the Sobolev regularity,L^(∞) regularity in space,and Hölder continuity in time for the mild solution,as well as for its semi-discrete and full-discrete approximations.Building upon these results,we establish moment boundedness for the numerical solution and obtain strong convergence rates in both spatial and temporal dimensions.A numerical example is presented to validate the theoretical findings.展开更多
The flow of a tetra-hybrid Casson nanofluid(Al_(2)O_(3)-CuO-TiO_(2)-Ag/H_(2)O)over a nonlinear stretching sheet is investigated.The Buongiorno model is used to account for thermophoresis and Brownian motion,while ther...The flow of a tetra-hybrid Casson nanofluid(Al_(2)O_(3)-CuO-TiO_(2)-Ag/H_(2)O)over a nonlinear stretching sheet is investigated.The Buongiorno model is used to account for thermophoresis and Brownian motion,while thermal radiation is incorporated to examine its influence on the thermal boundary layer.The governing partial differential equations(PDEs)are reduced to a system of nonlinear ordinary differential equations(ODEs)with fully non-dimensional similarity transformations involving all independent variables.To solve the obtained highly nonlinear system of differential equations,a novel Clique polynomial collocation method is applied.The analysis focuses on the effects of the Casson parameter,power index,radiation parameter,thermophoresis parameter,Brownian motion parameter,and Lewis number.The key findings show that thermal radiation intensifies the thermal boundary layer,the Casson parameter reduces the velocity,and the Lewis number suppresses the concentration with direct relevance to polymer processing,coating flows,electronic cooling,and biomedical applications.展开更多
Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigat...Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.展开更多
In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling...The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.展开更多
Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study...Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.展开更多
Lassa Fever(LF)is a viral hemorrhagic illness transmitted via rodents and is endemic in West Africa,causing thousands of deaths annually.This study develops a dynamic model of Lassa virus transmission,capturing the pr...Lassa Fever(LF)is a viral hemorrhagic illness transmitted via rodents and is endemic in West Africa,causing thousands of deaths annually.This study develops a dynamic model of Lassa virus transmission,capturing the progression of the disease through susceptible,exposed,infected,and recovered populations.The focus is on simulating this model using the fractional Caputo derivative,allowing both qualitative and quantitative analyses of boundedness,positivity,and solution uniqueness.Fixed-point theory and Lipschitz conditions are employed to confirm the existence and uniqueness of solutions,while Lyapunov functions establish the global stability of both disease-free and endemic equilibria.The study further examines the role of the Caputo operator by solving the generalized power-law kernel via a two-step Lagrange polynomial method.This approach offers practical advantages in handling additional data points in integral forms,though Newton polynomial-based schemes are generally more accurate and can outperform Lagrange-based Adams-Bashforth methods.Graphical simulations validate the proposed numerical approach for different fractional orders(ν)and illustrate the influence of model parameters on disease dynamics.Results indicate that increasing the fractional order accelerates the decline of Lassa fever in both human and rodent populations.Moreover,fractional-order modeling provides more nuanced insights than traditional integer-order models,suggesting potential improvements for medical intervention strategies.The study demonstrates that carefully chosen fractional orders can optimize convergence and enhance the predictive capacity of Lassa fever models,offering a promising direction for future research in epidemiological modeling.展开更多
The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a wat...The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.展开更多
With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on pre...With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on predetermined refueling duration;however,the precise mission scheduling solution will be difficult to apply due to uncertain refueling duration caused by orbital transfer deviations and stochastic actuator faults during actual on-orbit service.Therefore,this paper proposes a robust mission scheduling strategy for geosynchronous orbit spacecraft on-orbit refueling missions with uncertain refueling duration.Firstly,a robust mission scheduling model is constructed by introducing the budget uncertainty set to describe the uncertain refueling duration.Secondly,a hybrid harris hawks optimization algorithm is designed to explore the optimal mission allocation and refueling sequences,which combines cubic chaotic mapping to initialize the population,and the crossover in the genetic algorithm is introduced to enhance global convergence.Finally,the typical simulation examples are constructed with real-mission scenarios in three aspects to analyze:performance comparisons with various algorithms;robustness analyses via comparisons of different on-orbit refueling durations;investigations into the impacts of different initial population strategies on algorithm performance,demonstrating the proposed mission scheduling framework's robustness and effectiveness by comparing it with the exact mission scheduling.展开更多
There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reac...There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reactive coating processes,but existing work is not uncharacteristically remiss regarding viscoelasticity,radiative heating,viscous dissipation,and homogeneous–heterogeneous reactions within a single scheme that is calibrated.This research investigates the flow of Williamson nanofluid across a dynamically wedged surface under conditions that include viscous dissipation,thermal radiation,and homogeneous-heterogeneous reactions.The paper develops a detailed mathematical approach that utilizes boundary layers to transform partial differential equations into ordinary differential equations using similarity transformations.RK4 is the technique for gaining numerical solutions,but with the addition of ANNs,there is an improvement in prediction accuracy and computational efficiency.The study investigates the influence of wedge angle parameter,along with Weissenberg number,thermal radiation parameter and Brownian motion parameter,and Schmidt number,on velocity distribution,temperature distribution,and concentra-tion distribution.Enhanced Weissenberg numbers enhance viscoelastic responses that modify velocity patterns,but radiation parameters and thermophoresis have key impacts on thermal transfer phenomena.This research develops findings that are of enormous application in aerospace,biomedical(artificial hearts and drug delivery),and industrial cooling technology applications.New findings on non-Newtonian nanofluids under full flow systems are included in this work to enhance heat transfer methods in novel fluid-based systems.展开更多
基金partially supported by the NSF(Grant No.DMS 2324368)by the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison with funding from the Wisconsin Alumni Research Foundation.
文摘In this paper,we propose a systematic approach for accelerating finite element-type methods by machine learning for the numerical solution of partial differential equations(PDEs).The main idea is to use a neural network to learn the solution map of the PDEs and to do so in an element-wise fashion.This map takes input of the element geometry and the PDE’s parameters on that element,and gives output of two operators:(1)the in2out operator for inter-element communication,and(2)the in2sol operator(Green’s function)for element-wise solution recovery.A significant advantage of this approach is that,once trained,this network can be used for the numerical solution of the PDE for any domain geometry and any parameter distribution without retraining.Also,the training is significantly simpler since it is done on the element level instead on the entire domain.We call this approach element learning.This method is closely related to hybridizable discontinuous Galerkin(HDG)methods in the sense that the local solvers of HDG are replaced by machine learning approaches.Numerical tests are presented for an example PDE,the radiative transfer or radiation transport equation,in a variety of scenarios with idealized or realistic cloud fields,with smooth or sharp gradient in the cloud boundary transition.Under a fixed accuracy level of 10^(−3) in the relative L^(2) error,and polynomial degree p=6 in each element,we observe an approximately 5 to 10 times speed-up by element learning compared to a classical finite element-type method.
文摘The present study investigates the flow,heat,and mass transfer analysis in the bioconvection of nanofluid containing motile gyrotactic microorganisms through a semi-porous curved oscillatory channel with a magnetic field.These microorganisms produce density gradients by swimming,which induces macroscopic convection flows in the fluid.This procedure improves the mass and heat transfer,illustrating the interaction between biological activity and fluid dynamics.Furthermore,instead of considering traditional Fourier's and Fick's law the energy and concentration equations are developed by incorporating Cattaneo-Christov double diffusion theory.Moreover,to examine the influence of thermophoresis and Brownian diffusions in the fluid we have adopted the Buongiorno nanofluid model.Due to the oscillation of the surface of the channel,the mathematical development of the considered flow problem is obtained in the form of partial differential equations via the curvilinear coordinate system.The convergent series solution of the governing flow equations is obtained after applying the homotopy analysis method(HAM).The effects of different pertinent flow parameters on velocity,motile microorganism density distribution,concentration,pressure,temperature,and skin friction coefficient are examined and discussed in detail with the help of graphs and tables.It is observed during the current study that the density of microorganisms is enhanced for higher values of Reynolds number,Peclet number,radius of curvature variable,and Lewis number.
基金supported by the NSFC(12301115)the Natural Science Foundation of Huzhou(2023YZ11,2024YZ37)the second author was supported by the NSFC(12071437).
文摘It is well known that the inhomogeneous Calderón-Zygmund convolution operators are bounded on the local Hardy spaces.In this paper,we prove that these operators are bounded on the local product Hardy spaces and the Lipschitz spaces.The key ideas used here are the discrete local Calderón identity and a density argument for the inhomogeneous product Lipschitz spaces in the weak sense.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2603).
文摘A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order time derivatives.The proposed scheme attains third-order temporal accuracy and is rigorously validated through stability and convergence analyses for both scalar and coupled systems.Its effectiveness is demonstrated by simulating unsteady Eyring-Prandtl non-Newtonian nanofluid flow over a Riga plate with coupled heat and mass transfer under electromagnetic actuation.The physical model accounts for Brownian motion and thermophoresis,and the nanofluid considered is a Prandtl-type non-Newtonian base fluid containing suspended nanoparticles,with heat and mass transport governed by coupled momentum,energy,and concentration equations.Numerical simulations are performed over practically relevant parameter ranges,with the Reynolds number fixed at Re=5 and the Prandtl number set to Pr=3 to represent moderate inertial and thermal diffusion effects typical of nanofluid transport systems.To enhance computational efficiency,an artificial neural network(ANN)-based surrogate model is developed to predict the skin friction coefficient and local Sherwood number as functions of Reynolds number,Prandtl number,Schmidt number,Brownian motion,and thermophoresis parameters.The training dataset is generated entirely from high-fidelity numerical simulations produced by the proposed hybrid scheme.The data are systematically partitioned into 70%for training,15%for validation,and 15%for testing,ensuring reliable generalization.Regression analysis yields a near-unity correlation coefficient(R≈0.99),while error histograms exhibit tightly clustered residuals around zero,confirming high predictive accuracy.Furthermore,a benchmark convergence study using Stokes’first problem demonstrates that the proposed scheme consistently achieves lower global error norms than the classical Runge–Kutta method for identical spatial and temporal resolutions.Overall,this study introduces a novel computational intelligence framework that integrates high-order numerical solvers with machine learning,offering a robust and time-efficient tool for advanced modeling and real-time prediction of non-Newtonian nanofluid transport phenomena under electromagnetic flow control.
基金the research support through grants ANTARABANGSA(IRMG)-TEL-U/2025/FTKM/A00086.
文摘The purpose of the present investigation is to explore the implications of Cross fluid in a Darcy-Forchheimer porousmediumdue to the tri-hybrid nanofluid past a porous cylinder.Thermal radiation,heat generation,thermal convection,solutal convective and chemical reaction have been encountered in this analysis.Entropy generation has been accounted for under the fluidic friction,heat rate analysis,and porosity analysis.Three different nanoparticles of multiwall carbon nanotube(MWCNT),aluminum oxide(Al_(2)O_(3)),and silver(Ag)are utilized to illustrate the tri-hybrid nanofluid flow with Ethlene Glycol(EG)as the base fluid.The governance model,consisting of linked inadequate differential conditions,is transformed into an ordinary configuration of nonlinear coupled differential conditions by acceptable adjustments.The obtained outcomes in combination with the bvp4c approach are then used to resolve the generated ODEs.For discussion purposes,the impacts of the physical limitations on temperature profile,velocity,and concentration have also been illustrated.Numerical results have been obtained for the diffusion rate,heat transfer rate,drag force,and other factors.While the Forchheimer parameter and the inclination angle reduce the fluid flow’s velocity,the Biot number of heat and mass transfer influences the fluid’s temperature.According to the findings,hybrid nanofluid is the most effective way to improve heat transmission and may also be utilized for cooling.Three different kinds of nanofluids were used in a comparative examination to clarify the study’s conclusions.Changes in viscosity and porousness caused the nanofluids’velocity to drop by 13.12%and 15.8%,respectively;however,trihybrid nanofluids with improved convection showed a 13.12%rise.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12361040,12061064)the National Science Foundation of Gansu Province(Grant No.22JR5RA264)State Scholarship Fund(Grant No.20230862021).
文摘In this article,we show the existence,uniqueness and stability of bounded solutions to the following quasilinear problems with mean curvature operator(φ'(x′(t)))′=f(t,x),t≥t_(0),lim_(t→∞)x(t)=ψ_(0),lim_(t→∞)x′(t)e^(t)=0,where t_(0) and ψ_(0) are real constants,φ(s)=s/√1−s^(2),s∈R with s∈(−1,1),f:[t_(0),∞)×R→R satisfies the Lipschitz or Osgood-type conditions.
文摘Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analysis of ternary hybrid nanofluids,TiO_(2)-CdTe-MoS_(2) dispersed in water,flowing over a vertical stretching or shrinking surface in a Darcy-Brinkman porous medium.The investigation accounts for the combined effects of magnetohydrodynamics,thermal radiation,viscous dissipation,and internal heat generation.In contrast to previous studies that predominantly focused on single or binary nanofluids,the present work systematically examines the thermal and hydrodynamic performance of ternary hybrid nanofluids,highlighting their enhanced heat transport capabilities in porous structures.The governing momentum and energy equations are formulated in nondimensional form and solved numerically using the shifted Legendre collocation method.The results show that increasing the magnetic parameter,M=0-4,suppresses the fluid velocity by up to 28%,while stronger thermal radiation,R=0-5,raises the near-surface temperature by approximately 32%.Viscous dissipation and internal heat generation further enhance the Nusselt number,indicating improved heat transfer performance.Overall,the findings demonstrate the synergistic influence of the three nanoparticles in optimizing flow behavior and thermal characteristics,offering valuable insights for the design of high-performance thermal management systems in energy and aerospace applications.
文摘Thiswork explores aMagnetohydrodynamic(MHD)flowin a triangular cavitywith a thermally insulated baffle.Enclosure’s inclined wall is hotter,whereas the vertical border is adiabatic and the bottom is cooler.The study aims to clarify how geometric changes affect thermal performance and offers new perspectives on how to improve heat dissipation mechanisms.A COMSOL Multiphysics version 6.2 has been used to solve numerical solutions.Streamlines and thermal distributions are examined systematically in order to understand how the unique geometry and baffle size of triangular cavities can influence the fluid flow.This influence can result in optimized flow patterns,promoting efficient heat transfer by directing the fluid to specific areas that require more cooling.In comparison with conventional designs,this optimization results in more efficient convective heat transfer,which raises cooling efficiency and lowers thermal resistance.Furthermore,by strengthening heat transfer characteristics in heat transfer systems,these geometries increase thermal efficiency,which helps several sectors,including the production of electricity,HVAC,and the automobile industry.
文摘In this paper,we define for the trace operator,the solution of certain models of vibrating plates standards with initial data in a strategic region spaces of weak regularities.Indeed,we know that the notion of regional controllability is more adapted to systems described by dynamic systems.Regional controllability results in a strategic area were established for vibrating plates by the Hilbertian Uniqueness Method.
文摘Elliptic curve(EC)based cryptosystems gained more attention due to enhanced security than the existing public key cryptosystems.A substitution box(S-box)plays a vital role in securing modern symmetric key cryptosystems.However,the recently developed EC based algorithms usually trade off between computational efficiency and security,necessitating the design of a new algorithm with the desired cryptographic strength.To address these shortcomings,this paper proposes a new scheme based onMordell elliptic curve(MEC)over the complex field for generating distinct,dynamic,and highly uncorrelated S-boxes.Furthermore,we count the exact number of the obtained S-boxes,and demonstrate that the permuted version of the presented S-box is statistically optimal.The nonsingularity of the presented algorithm and the injectivity of the resultant output are explored.Rigorous theoretical analysis and experimental results demonstrate that the proposedmethod is highly effective in generating a large number of dynamic S-boxes with adequate cryptographic properties,surpassing current state-of-the-art S-box generation algorithms in terms of security.Apart fromthis,the generated S-box is benchmarked using side-channel attacks,and its performance is compared with highly nonlinear S-boxes,demonstrating comparable results.In addition,we present an application of our proposed S-box generator by incorporating it into an image encryption technique.The encrypted and decrypted images are tested by employing extensive standard security metrics,including the Number of Pixel Change Rate,the Unified Average Changing Intensity,information entropy,correlation coefficient,and histogram analysis.Moreover,the analysis is extended beyond conventional metrics to validate the new method using advanced tests,such as the NIST statistical test suite,robustness analysis,and noise and cropping attacks.Experimental outcomes show that the presented algorithm strengthens the existing encryption scheme against various well-known cryptographic attacks.
基金partially supported by the National Natural Science Foundation of China(Grant No.12071073)financial support by the Jiangsu Provincial Scientific Research Center of Applied Mathematics(Grant No.BK20233002).
文摘The strong convergence of an explicit full-discrete scheme is investigated for the stochastic Burgers-Huxley equation driven by additive space-time white noise,which possesses both Burgers-type and cubic nonlinearities.To discretize the continuous problem in space,we utilize a spectral Galerkin method.Subsequently,we introduce a nonlinear-tamed exponential integrator scheme,resulting in a fully discrete scheme.Within the framework of semigroup theory,this study provides precise estimations of the Sobolev regularity,L^(∞) regularity in space,and Hölder continuity in time for the mild solution,as well as for its semi-discrete and full-discrete approximations.Building upon these results,we establish moment boundedness for the numerical solution and obtain strong convergence rates in both spatial and temporal dimensions.A numerical example is presented to validate the theoretical findings.
基金the UGC,New Delhi,India for financial assistance via the UGC-Junior Research Fellowship(CSIR-UGC NET JULY 2024)(Student ID:241610090610)。
文摘The flow of a tetra-hybrid Casson nanofluid(Al_(2)O_(3)-CuO-TiO_(2)-Ag/H_(2)O)over a nonlinear stretching sheet is investigated.The Buongiorno model is used to account for thermophoresis and Brownian motion,while thermal radiation is incorporated to examine its influence on the thermal boundary layer.The governing partial differential equations(PDEs)are reduced to a system of nonlinear ordinary differential equations(ODEs)with fully non-dimensional similarity transformations involving all independent variables.To solve the obtained highly nonlinear system of differential equations,a novel Clique polynomial collocation method is applied.The analysis focuses on the effects of the Casson parameter,power index,radiation parameter,thermophoresis parameter,Brownian motion parameter,and Lewis number.The key findings show that thermal radiation intensifies the thermal boundary layer,the Casson parameter reduces the velocity,and the Lewis number suppresses the concentration with direct relevance to polymer processing,coating flows,electronic cooling,and biomedical applications.
文摘Hepatitis B Virus(HBV)infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis.In this paper,we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients,respectively.The intricate interactions between liver cirrhosis,recovery,and treatment dynamics are captured by the model.This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces it.We proved that a unique solution of the proposed model exists,which is positive and bounded.Using the next-generation matrix approach,two basic reproductive numbers R_(A_(0))and R_(A_(max))are calculated to identify future recurrence.The equilibrium points are calculated,and both equilibria are proved locally and globally asymptotically stable when R_(0)is below and above one,respectively.It is shown that bifurcation exists at R_(0)=1 and a detailed proof for forward bifurcation is given.Furthermore,we performed the sensitivity analysis of the model parameters on R_(0).For the confirmation of analytical work,we performed numerical simulations,and the results indicate that the treatment and the inhibitory effects reduce the risk of developing liver cirrhosis in individuals,while heavy alcohol consumption accelerates markedly the liver cirrhosis progression in patients with chronic hepatitis B.
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
文摘The increasing occurrence of corrosion-related damage in steel pipelines has led to the growing use of composite-based repair techniques as an efficient alternative to traditional replacement methods.Computer modeling and structural analysis were performed for the repair reinforcement of a steel pipeline with a composite bandage.A preliminary analysis of possible contact interaction schemes was implemented based on the theory of cylindrical shells,taking into account transverse shear deformations.The finite element method was used for a detailed study of the stress state of the composite bandage and the reinforced section of the pipeline.The limit state of the reinforced section was assessed based on the von Mises criterion for steel and the Tsai-Wu criterion for composites.The effectiveness of the repair was demonstrated on a pipeline whose wall thickness had decreased by 20%as a result of corrosion damage.At a nominal pressure of P=6 MPa,the maximum normal stress in the weakened area reached 381 MPa.The installation of a composite bandage reduced this stress to 312 MPa,making the repaired section virtually as strong as the undamaged pipeline.Due to the linearity of the problem,the results obtained can be easily used to find critical internal pressure values.
基金supported by the Iran National Science Foundation(INSF)the University of Birjand under grant number 4034771.
文摘Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.
文摘Lassa Fever(LF)is a viral hemorrhagic illness transmitted via rodents and is endemic in West Africa,causing thousands of deaths annually.This study develops a dynamic model of Lassa virus transmission,capturing the progression of the disease through susceptible,exposed,infected,and recovered populations.The focus is on simulating this model using the fractional Caputo derivative,allowing both qualitative and quantitative analyses of boundedness,positivity,and solution uniqueness.Fixed-point theory and Lipschitz conditions are employed to confirm the existence and uniqueness of solutions,while Lyapunov functions establish the global stability of both disease-free and endemic equilibria.The study further examines the role of the Caputo operator by solving the generalized power-law kernel via a two-step Lagrange polynomial method.This approach offers practical advantages in handling additional data points in integral forms,though Newton polynomial-based schemes are generally more accurate and can outperform Lagrange-based Adams-Bashforth methods.Graphical simulations validate the proposed numerical approach for different fractional orders(ν)and illustrate the influence of model parameters on disease dynamics.Results indicate that increasing the fractional order accelerates the decline of Lassa fever in both human and rodent populations.Moreover,fractional-order modeling provides more nuanced insights than traditional integer-order models,suggesting potential improvements for medical intervention strategies.The study demonstrates that carefully chosen fractional orders can optimize convergence and enhance the predictive capacity of Lassa fever models,offering a promising direction for future research in epidemiological modeling.
基金funded by King Saud University,Riyadh,Saudi Arabia,through the Ongo-ing Research Funding program—Research Chairs(ORF-RC-2025-0127)funded via Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R443).
文摘The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.
基金co-supported by the National Natural Science Foundation of China(Nos.62473110,62403166)the Fundamental Research Funds for the Central Universities,China(No.2023FRFK02043)+1 种基金the Natural Science Foundation of Heilongjiang Province,China(No.LH2022F023)the National Key Laboratory of Space Intelligent Control Foundation,China(No.2023-JCJQ-LB-006-19)。
文摘With the increasing number of geosynchronous orbit satellites with expiring lifetime,spacecraft refueling is crucial in enhancing the economic benefits of on-orbit services.The existing studies tend to be based on predetermined refueling duration;however,the precise mission scheduling solution will be difficult to apply due to uncertain refueling duration caused by orbital transfer deviations and stochastic actuator faults during actual on-orbit service.Therefore,this paper proposes a robust mission scheduling strategy for geosynchronous orbit spacecraft on-orbit refueling missions with uncertain refueling duration.Firstly,a robust mission scheduling model is constructed by introducing the budget uncertainty set to describe the uncertain refueling duration.Secondly,a hybrid harris hawks optimization algorithm is designed to explore the optimal mission allocation and refueling sequences,which combines cubic chaotic mapping to initialize the population,and the crossover in the genetic algorithm is introduced to enhance global convergence.Finally,the typical simulation examples are constructed with real-mission scenarios in three aspects to analyze:performance comparisons with various algorithms;robustness analyses via comparisons of different on-orbit refueling durations;investigations into the impacts of different initial population strategies on algorithm performance,demonstrating the proposed mission scheduling framework's robustness and effectiveness by comparing it with the exact mission scheduling.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)and the Ministry of Trade,Industry&Energy(MOTIE)of the Republic of Korea(No.RS-2025-02315209).
文摘There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reactive coating processes,but existing work is not uncharacteristically remiss regarding viscoelasticity,radiative heating,viscous dissipation,and homogeneous–heterogeneous reactions within a single scheme that is calibrated.This research investigates the flow of Williamson nanofluid across a dynamically wedged surface under conditions that include viscous dissipation,thermal radiation,and homogeneous-heterogeneous reactions.The paper develops a detailed mathematical approach that utilizes boundary layers to transform partial differential equations into ordinary differential equations using similarity transformations.RK4 is the technique for gaining numerical solutions,but with the addition of ANNs,there is an improvement in prediction accuracy and computational efficiency.The study investigates the influence of wedge angle parameter,along with Weissenberg number,thermal radiation parameter and Brownian motion parameter,and Schmidt number,on velocity distribution,temperature distribution,and concentra-tion distribution.Enhanced Weissenberg numbers enhance viscoelastic responses that modify velocity patterns,but radiation parameters and thermophoresis have key impacts on thermal transfer phenomena.This research develops findings that are of enormous application in aerospace,biomedical(artificial hearts and drug delivery),and industrial cooling technology applications.New findings on non-Newtonian nanofluids under full flow systems are included in this work to enhance heat transfer methods in novel fluid-based systems.
