This study aims to formulate a steady-state mathematical model for a three-dimensional permeable enclosure(cavity)to determine the oil extraction rate using three distinct nanoparticles,SiO_(2),Al_(2)O_(3),and Fe_(2)O...This study aims to formulate a steady-state mathematical model for a three-dimensional permeable enclosure(cavity)to determine the oil extraction rate using three distinct nanoparticles,SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),in unconventional oil reservoirs.The simulation is conducted for different parameters of volume fractions,porosities,and mass flow rates to determine the optimal oil recovery.The impact of nanoparticles on relative permeability(kr)and water is also investigated.The simulation process utilizes the finite volume ANSYS Fluent.The study results showed that when the mass flow rate at the inlet is low,oil recovery goes up.In addition,they indicated that silicon nanoparticles are better at getting oil out of the ground(i.e.,oil reservoir)than Al_(2)O_(3)and Fe_(2)O_(3).Most oil can be extracted from SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3)at a rate of 97.8%,96.5%,and 88%,respectively.展开更多
In this paper,we establish a stability estimate for the isoperimetric inequality of horospherically convex domains in hyperbolic plane.This estimate involves a relationship between the Hausdorff distance to a geodesic...In this paper,we establish a stability estimate for the isoperimetric inequality of horospherically convex domains in hyperbolic plane.This estimate involves a relationship between the Hausdorff distance to a geodesic ball and the deficit in the isoperimetric inequality,where the coefficient of the deficit is a universal constant.展开更多
We prove that for a smooth convex body K⊂ℝ^(d),d≥2,with positive Gauss curvature,its homothety with a certain associated convex body implies that K is either a ball or an ellipsoid,depending on the associated body co...We prove that for a smooth convex body K⊂ℝ^(d),d≥2,with positive Gauss curvature,its homothety with a certain associated convex body implies that K is either a ball or an ellipsoid,depending on the associated body considered.展开更多
In this paper we work with the ordinary diffential equation u′′ u3 = 0 and obtain some interesting phenomena concerning blow-up, blow-up rate, life-spann, zeros and critical points of solutions to this equation.
In this paper, we work with the ordinary differential equation n^2u （n）＂ = u（n）^p and obtain some interesting phenomena concerning, boundedness, blow-up, blow-up rate, life-span of solutions to those equations.
In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer...In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer phenomenon is involved.Fourier’s law of heat conduction has been used as the foundation for predicting the heat transfer behavior in a variety of real-world contexts.This model’s production of a parabolic energy expression,which means that an initial disturbance would immediately affect the system under investigation,is one of its main drawbacks.Therefore,numerous researchers worked on such problem to resolve this issue.At last,this problem was resolved by Cattaneo by adding relaxation time for heat flux in Fourier’s law,which was defined as the time required to establish steady heat conduction once a temperature gradient is imposed.Christov offered a material invariant version of Cattaneo’s model by taking into account the upper-connected derivative of the Oldroyd model.Nowadays,both models are combinedly known as the Cattaneo-Christov(CC)model.In this attempt,the mixed convective MHD Falkner-Skan Sutterby nanofluid flow is addressed towards a wedge surface in the presence of the variable external magnetic field.The CC model is incorporated instead of Fourier’s law for the examination of heat transfer features in the energy expression.A two-phase nanofluid model is utilized for the implementation of nano-concept.The nonlinear system of equations is tackled through the bvp4c technique in the MATLAB software 2016.The influence of pertinent flow parameters is discussed and displayed through different sketches.Major and important results are summarized in the conclusion section.Furthermore,in both cases of wall-through flow(i.e.,suction and injection effects),the porosity parameters increase the flow speed,and decrease the heat transport and the influence of drag forces.展开更多
In this paper,we present a mathematical model of the cerebrospinal fluid(CSF)formation based on fluid mechanics concepts.Maintenance of intracranial pressure(IP)in the cases of patients with head injury has been a pro...In this paper,we present a mathematical model of the cerebrospinal fluid(CSF)formation based on fluid mechanics concepts.Maintenance of intracranial pressure(IP)in the cases of patients with head injury has been a problem for some time now.Cerebrospinal fluid is one of the cranial vault content that influences the normality of the IP.It was assumed that cerebrospinal fluid(CSF)formation begins as plasma,展开更多
In this paper we work with the ordinary equation u＇＇ - u2 （u ＋ ） = 0 and ob- tain some interesting phenomena concerning, blow-up, blow-up rate, life-span of solutions to those equations.
Addiction is a societal issue with many negative effects. Substances that cause addictive reactions are easily ingested and interact with some part of the neural pathway. This paper describes a mathematical model for ...Addiction is a societal issue with many negative effects. Substances that cause addictive reactions are easily ingested and interact with some part of the neural pathway. This paper describes a mathematical model for the systemic level of a substance subject to degradation (via metabolism) and reversible binding to psychoactive sites. The model allows the determination of bound substance levels during the processing of a dose, and how the maximum level depends on system parameters. The model also allows the study of a particular periodic repetitive dosing described by a rapid ingestion if a dose is at constant intervals.展开更多
We present a first-order finite difference scheme for approximating solutions of a mathematical model of cervical cancer induced by the human papillomavirus (HPV), which consists of four nonlinear partial differential...We present a first-order finite difference scheme for approximating solutions of a mathematical model of cervical cancer induced by the human papillomavirus (HPV), which consists of four nonlinear partial differential equations and a nonlinear first-order ordinary differential equation. The scheme is analyzed and used to provide an existence-uniqueness result. Numerical simulations are performed in order to demonstrate the first-order rate of convergence. A sensitivity analysis was done in order to compare the effects of two drug types, those that increase the death rate of HPV-infected cells, and those that increase the death rate of the precancerous cell population. The model predicts that treatments that affect the precancerous cell population by directly increasing the corresponding death rate are far more effective than those that increase the death rate of HPV-infected cells.展开更多
Let H denote the class of complex-valued harmonic functions f defined in the open unit disc D and normalized by f(0)=fz(0)-1=0.In this paper,we define a new generalized subclass of H associated with the(p,q)-Ruschewey...Let H denote the class of complex-valued harmonic functions f defined in the open unit disc D and normalized by f(0)=fz(0)-1=0.In this paper,we define a new generalized subclass of H associated with the(p,q)-Ruscheweyh-type harmonic differential operator in D.We first obtain a sufficient coefficient condition that guarantees that a function f in H is sense-preserving harmonic univalent in D and belongs to the aforementioned class.Using this coefficient condition,we then examine ratios of partial sums of f in H.In all cases the results are sharp.In addition,the results so obtained generalize the related works of some authors,and many other new results are obtained.展开更多
State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging pro...State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based SOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(SVR)were applied to estimate SOH,and root mean square error(RMSE)was used to evaluate and compare the estimation performance.The results showed that the feature selection pipeline can improve SOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and SVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on SOH estimation performance and tries to fill the gap of effective SOH estimation between theoretical study and real dynamic application.展开更多
The presence of the debris in the Earth’s orbit poses a significant risk to human activity in outer space.This debris population continues to grow due to ground launches,the loss of external parts from space ships,an...The presence of the debris in the Earth’s orbit poses a significant risk to human activity in outer space.This debris population continues to grow due to ground launches,the loss of external parts from space ships,and uncontrollable collisions between objects.A computationally feasible continuum model for the growth of the debris population and its spatial distribution is therefore critical.Here we propose a diffusion-collision model for the evolution of the debris density in the low-Earth orbit and its dependence on the ground-launch policy.We parametrize this model and test it against data from publicly available object catalogs to examine timescales for the uncontrolled growth.Finally,we consider sensible launch policies and cleanup strategies and how they reduce the future risk of collisions with active satellites or space ships.展开更多
A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a compar...A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently used.From this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG distribution.From a classical point of view,the likelihood and product of spacing estimation methods are considered.Observed Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the suggestedmodel.In the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown subjects.Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’findings.Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy.Further,using several optimality criteria,the optimumprogressive censoring design is suggested.To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.展开更多
A new one-parameter Chris-Jerry distribution,created by mixing exponential and gamma distributions,is discussed in this article in the presence of incomplete lifetime data.We examine a novel generalized progressively ...A new one-parameter Chris-Jerry distribution,created by mixing exponential and gamma distributions,is discussed in this article in the presence of incomplete lifetime data.We examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry(CJ)distribution.When the indicated censored data is present,Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices,including the hazard rate and reliability functions.We acquire the estimated asymptotic and credible confidence intervals of each unknown quantity.Additionally,via the squared-error loss,the Bayes’estimators are obtained using gamma prior.The Bayes estimators cannot be expressed theoretically since the likelihood density is created in a complex manner;nonetheless,Markov-chain Monte Carlo techniques can be used to evaluate them.The effectiveness of the investigated estimations is assessed,and some recommendations are given using Monte Carlo results.Ultimately,an analysis of two engineering applications,such as mechanical equipment and ball bearing data sets,shows the applicability of the proposed approaches that may be used in real-world settings.展开更多
In this paper,we review computational approaches to optimization problems of inhomogeneous rods and plates.We consider both the optimization of eigenvalues and the localization of eigenfunctions.These problems are mot...In this paper,we review computational approaches to optimization problems of inhomogeneous rods and plates.We consider both the optimization of eigenvalues and the localization of eigenfunctions.These problems are motivated by physical problems including the determination of the extremum of the fundamental vibration frequency and the localization of the vibration displacement.We demonstrate how an iterative rearrangement approach and a gradient descent approach with projection can successfully solve these optimization problems under different boundary conditions with different densities given.展开更多
A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied...A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied.In this research, using a progressive Type-II censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.展开更多
In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic ...In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.展开更多
The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver(Ag)−Magnesium oxide(MgO)hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone,...The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver(Ag)−Magnesium oxide(MgO)hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone,with the influence of transverse magnetic field and thermal radiation.The physical flow problem has been modeled with coupled partial differential equations.We apply similarity transformations to the nondimensionalized equations,and the resulting nonlinear differential equations are solved using overlapping grid multidomain spectral quasilinearization method.The flow behavior for the fluid is scrutinized under the impact of diverse physical constraints,which are illustrated graphically.The results of the skin friction coefficient and Nusselt number varying different flow parameters are presented in the form of a table.It is observed that the main flow of the hybrid nanofluid,nano particle fraction of silver and Magnesium/water,enhances compared to the mono-nano fluid MgO as the coupling number increases.The application of studies like this can be found in the atomization process of liquids such as centrifugal pumps,viscometers,rotors,fans.展开更多
The research examines fluid behavior in a porous box-shaped enclosure.The fluid contains nanoscale particles and swimming microbes and is subject to magnetic forces at an angle.Natural circulation driven by biological...The research examines fluid behavior in a porous box-shaped enclosure.The fluid contains nanoscale particles and swimming microbes and is subject to magnetic forces at an angle.Natural circulation driven by biological factors is investigated.The analysis combines a traditional numerical approach with machine learning techniques.Mathematical equations describing the system are transformed into a dimensionless form and then solved using computational methods.The artificial neural network(ANN)model,trained with the Levenberg-Marquardt method,accurately predicts(Nu)values,showing high correlation(R=1),low mean squared error(MSE),and minimal error clustering.Parametric analysis reveals significant effects of parameters,length and location of source(B),(D),heat generation/absorption coefficient(Q),and porosity parameter(ε).Increasing the cooling area length(B)reduces streamline intensity and local Nusselt and Sherwood numbers,while decreasing isotherms,isoconcentrations,and micro-rotation.The Bejan number(Be+)decreases with increasing(B),whereas(Be+++),and global entropy(e+++)increase.Variations in(Q)slightly affect streamlines but reduce isotherm intensity and average Nusselt numbers.Higher(D)significantly impacts isotherms,iso-concentrations,andmicro-rotation,altering streamline contours and local Bejan number distribution.Increased(ε)enhances streamline strength and local Nusselt number profiles but has mixed effects on average Nusselt numbers.These findings highlight the complex interactions between cooling area length,fluid flow,and heat transfer properties.By combining finite volume method(FVM)with machine learning technique,this study provides valuable insights into the complex interactions between key parameters and heat transfer,contributing to the development of more efficient designs in applications such as cooling systems,energy storage,and bioengineering.展开更多
基金The APC of this article is covered by Research Grant YUTP 015LCO-526。
文摘This study aims to formulate a steady-state mathematical model for a three-dimensional permeable enclosure(cavity)to determine the oil extraction rate using three distinct nanoparticles,SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3),in unconventional oil reservoirs.The simulation is conducted for different parameters of volume fractions,porosities,and mass flow rates to determine the optimal oil recovery.The impact of nanoparticles on relative permeability(kr)and water is also investigated.The simulation process utilizes the finite volume ANSYS Fluent.The study results showed that when the mass flow rate at the inlet is low,oil recovery goes up.In addition,they indicated that silicon nanoparticles are better at getting oil out of the ground(i.e.,oil reservoir)than Al_(2)O_(3)and Fe_(2)O_(3).Most oil can be extracted from SiO_(2),Al_(2)O_(3),and Fe_(2)O_(3)at a rate of 97.8%,96.5%,and 88%,respectively.
文摘In this paper,we establish a stability estimate for the isoperimetric inequality of horospherically convex domains in hyperbolic plane.This estimate involves a relationship between the Hausdorff distance to a geodesic ball and the deficit in the isoperimetric inequality,where the coefficient of the deficit is a universal constant.
文摘We prove that for a smooth convex body K⊂ℝ^(d),d≥2,with positive Gauss curvature,its homothety with a certain associated convex body implies that K is either a ball or an ellipsoid,depending on the associated body considered.
基金financed by NSC, Metta Education, Grand Hall Company and Auria Solar Company
文摘In this paper we work with the ordinary diffential equation u′′ u3 = 0 and obtain some interesting phenomena concerning blow-up, blow-up rate, life-spann, zeros and critical points of solutions to this equation.
基金financed by NSC,Metta Education,Grand Hall Company and Auria Solar Company
文摘In this paper, we work with the ordinary differential equation n^2u （n）＂ = u（n）^p and obtain some interesting phenomena concerning, boundedness, blow-up, blow-up rate, life-span of solutions to those equations.
基金Deanship of Scientific Research at King Khalid University for funding this work through Large Group Research Project(No.RGP2/19/44)。
文摘In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer phenomenon is involved.Fourier’s law of heat conduction has been used as the foundation for predicting the heat transfer behavior in a variety of real-world contexts.This model’s production of a parabolic energy expression,which means that an initial disturbance would immediately affect the system under investigation,is one of its main drawbacks.Therefore,numerous researchers worked on such problem to resolve this issue.At last,this problem was resolved by Cattaneo by adding relaxation time for heat flux in Fourier’s law,which was defined as the time required to establish steady heat conduction once a temperature gradient is imposed.Christov offered a material invariant version of Cattaneo’s model by taking into account the upper-connected derivative of the Oldroyd model.Nowadays,both models are combinedly known as the Cattaneo-Christov(CC)model.In this attempt,the mixed convective MHD Falkner-Skan Sutterby nanofluid flow is addressed towards a wedge surface in the presence of the variable external magnetic field.The CC model is incorporated instead of Fourier’s law for the examination of heat transfer features in the energy expression.A two-phase nanofluid model is utilized for the implementation of nano-concept.The nonlinear system of equations is tackled through the bvp4c technique in the MATLAB software 2016.The influence of pertinent flow parameters is discussed and displayed through different sketches.Major and important results are summarized in the conclusion section.Furthermore,in both cases of wall-through flow(i.e.,suction and injection effects),the porosity parameters increase the flow speed,and decrease the heat transport and the influence of drag forces.
文摘In this paper,we present a mathematical model of the cerebrospinal fluid(CSF)formation based on fluid mechanics concepts.Maintenance of intracranial pressure(IP)in the cases of patients with head injury has been a problem for some time now.Cerebrospinal fluid is one of the cranial vault content that influences the normality of the IP.It was assumed that cerebrospinal fluid(CSF)formation begins as plasma,
基金financed by NSC,Metta Education,Grand Hall Company and Auria Solar Company
文摘In this paper we work with the ordinary equation u＇＇ - u2 （u ＋ ） = 0 and ob- tain some interesting phenomena concerning, blow-up, blow-up rate, life-span of solutions to those equations.
文摘Addiction is a societal issue with many negative effects. Substances that cause addictive reactions are easily ingested and interact with some part of the neural pathway. This paper describes a mathematical model for the systemic level of a substance subject to degradation (via metabolism) and reversible binding to psychoactive sites. The model allows the determination of bound substance levels during the processing of a dose, and how the maximum level depends on system parameters. The model also allows the study of a particular periodic repetitive dosing described by a rapid ingestion if a dose is at constant intervals.
文摘We present a first-order finite difference scheme for approximating solutions of a mathematical model of cervical cancer induced by the human papillomavirus (HPV), which consists of four nonlinear partial differential equations and a nonlinear first-order ordinary differential equation. The scheme is analyzed and used to provide an existence-uniqueness result. Numerical simulations are performed in order to demonstrate the first-order rate of convergence. A sensitivity analysis was done in order to compare the effects of two drug types, those that increase the death rate of HPV-infected cells, and those that increase the death rate of the precancerous cell population. The model predicts that treatments that affect the precancerous cell population by directly increasing the corresponding death rate are far more effective than those that increase the death rate of HPV-infected cells.
文摘Let H denote the class of complex-valued harmonic functions f defined in the open unit disc D and normalized by f(0)=fz(0)-1=0.In this paper,we define a new generalized subclass of H associated with the(p,q)-Ruscheweyh-type harmonic differential operator in D.We first obtain a sufficient coefficient condition that guarantees that a function f in H is sense-preserving harmonic univalent in D and belongs to the aforementioned class.Using this coefficient condition,we then examine ratios of partial sums of f in H.In all cases the results are sharp.In addition,the results so obtained generalize the related works of some authors,and many other new results are obtained.
基金funded by China Scholarship Council.The fund number is 202108320111 and 202208320055。
文摘State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based SOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(SVR)were applied to estimate SOH,and root mean square error(RMSE)was used to evaluate and compare the estimation performance.The results showed that the feature selection pipeline can improve SOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and SVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on SOH estimation performance and tries to fill the gap of effective SOH estimation between theoretical study and real dynamic application.
基金supported by a graduate fellowship from the Department of Mathematical Sciences at the University of Wisconsin-Milwaukee.
文摘The presence of the debris in the Earth’s orbit poses a significant risk to human activity in outer space.This debris population continues to grow due to ground launches,the loss of external parts from space ships,and uncontrollable collisions between objects.A computationally feasible continuum model for the growth of the debris population and its spatial distribution is therefore critical.Here we propose a diffusion-collision model for the evolution of the debris density in the low-Earth orbit and its dependence on the ground-launch policy.We parametrize this model and test it against data from publicly available object catalogs to examine timescales for the uncontrolled growth.Finally,we consider sensible launch policies and cleanup strategies and how they reduce the future risk of collisions with active satellites or space ships.
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding after Publication,Grant No.(RPFAP-34-1445).
文摘A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is considered.In many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently used.From this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG distribution.From a classical point of view,the likelihood and product of spacing estimation methods are considered.Observed Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the suggestedmodel.In the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown subjects.Markov-Chain with Monte-Carlo steps are considered to approximate all Bayes’findings.Extensive numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of accuracy.Further,using several optimality criteria,the optimumprogressive censoring design is suggested.To highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.
基金This research was funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R50)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘A new one-parameter Chris-Jerry distribution,created by mixing exponential and gamma distributions,is discussed in this article in the presence of incomplete lifetime data.We examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry(CJ)distribution.When the indicated censored data is present,Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices,including the hazard rate and reliability functions.We acquire the estimated asymptotic and credible confidence intervals of each unknown quantity.Additionally,via the squared-error loss,the Bayes’estimators are obtained using gamma prior.The Bayes estimators cannot be expressed theoretically since the likelihood density is created in a complex manner;nonetheless,Markov-chain Monte Carlo techniques can be used to evaluate them.The effectiveness of the investigated estimations is assessed,and some recommendations are given using Monte Carlo results.Ultimately,an analysis of two engineering applications,such as mechanical equipment and ball bearing data sets,shows the applicability of the proposed approaches that may be used in real-world settings.
基金supported by the DMS-1853701supported in part by the DMS-2208373.
文摘In this paper,we review computational approaches to optimization problems of inhomogeneous rods and plates.We consider both the optimization of eigenvalues and the localization of eigenfunctions.These problems are motivated by physical problems including the determination of the extremum of the fundamental vibration frequency and the localization of the vibration displacement.We demonstrate how an iterative rearrangement approach and a gradient descent approach with projection can successfully solve these optimization problems under different boundary conditions with different densities given.
文摘A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied.In this research, using a progressive Type-II censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.
基金supported by China Postdoctoral Science Foundation grant 2020TQ0344the NSFC grants 11871139 and 12101597the NSF grants DMS-1720116,DMS-2012882,DMS-2011838,DMS-1719942,DMS-1913072.
文摘In this work,we develop energy stable numerical methods to simulate electromagnetic waves propagating in optical media where the media responses include the linear Lorentz dispersion,the instantaneous nonlinear cubic Kerr response,and the nonlinear delayed Raman molecular vibrational response.Unlike the first-order PDE-ODE governing equations considered previously in Bokil et al.(J Comput Phys 350:420–452,2017)and Lyu et al.(J Sci Comput 89:1–42,2021),a model of mixed-order form is adopted here that consists of the first-order PDE part for Maxwell’s equations coupled with the second-order ODE part(i.e.,the auxiliary differential equations)modeling the linear and nonlinear dispersion in the material.The main contribution is a new numerical strategy to treat the Kerr and Raman nonlinearities to achieve provable energy stability property within a second-order temporal discretization.A nodal discontinuous Galerkin(DG)method is further applied in space for efficiently handling nonlinear terms at the algebraic level,while preserving the energy stability and achieving high-order accuracy.Indeed with d_(E)as the number of the components of the electric field,only a d_(E)×d_(E)nonlinear algebraic system needs to be solved at each interpolation node,and more importantly,all these small nonlinear systems are completely decoupled over one time step,rendering very high parallel efficiency.We evaluate the proposed schemes by comparing them with the methods in Bokil et al.(2017)and Lyu et al.(2021)(implemented in nodal form)regarding the accuracy,computational efficiency,and energy stability,by a parallel scalability study,and also through the simulations of the soliton-like wave propagation in one dimension,as well as the spatial-soliton propagation and two-beam interactions modeled by the two-dimensional transverse electric(TE)mode of the equations.
文摘The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver(Ag)−Magnesium oxide(MgO)hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone,with the influence of transverse magnetic field and thermal radiation.The physical flow problem has been modeled with coupled partial differential equations.We apply similarity transformations to the nondimensionalized equations,and the resulting nonlinear differential equations are solved using overlapping grid multidomain spectral quasilinearization method.The flow behavior for the fluid is scrutinized under the impact of diverse physical constraints,which are illustrated graphically.The results of the skin friction coefficient and Nusselt number varying different flow parameters are presented in the form of a table.It is observed that the main flow of the hybrid nanofluid,nano particle fraction of silver and Magnesium/water,enhances compared to the mono-nano fluid MgO as the coupling number increases.The application of studies like this can be found in the atomization process of liquids such as centrifugal pumps,viscometers,rotors,fans.
基金Deanship of Scientific Research at King Khalid University,Abha,Saudi Arabia,for funding this work through theResearch Group Project underGrant Number(RGP.2/610/45)funded by the Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2024R102)PrincessNourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The research examines fluid behavior in a porous box-shaped enclosure.The fluid contains nanoscale particles and swimming microbes and is subject to magnetic forces at an angle.Natural circulation driven by biological factors is investigated.The analysis combines a traditional numerical approach with machine learning techniques.Mathematical equations describing the system are transformed into a dimensionless form and then solved using computational methods.The artificial neural network(ANN)model,trained with the Levenberg-Marquardt method,accurately predicts(Nu)values,showing high correlation(R=1),low mean squared error(MSE),and minimal error clustering.Parametric analysis reveals significant effects of parameters,length and location of source(B),(D),heat generation/absorption coefficient(Q),and porosity parameter(ε).Increasing the cooling area length(B)reduces streamline intensity and local Nusselt and Sherwood numbers,while decreasing isotherms,isoconcentrations,and micro-rotation.The Bejan number(Be+)decreases with increasing(B),whereas(Be+++),and global entropy(e+++)increase.Variations in(Q)slightly affect streamlines but reduce isotherm intensity and average Nusselt numbers.Higher(D)significantly impacts isotherms,iso-concentrations,andmicro-rotation,altering streamline contours and local Bejan number distribution.Increased(ε)enhances streamline strength and local Nusselt number profiles but has mixed effects on average Nusselt numbers.These findings highlight the complex interactions between cooling area length,fluid flow,and heat transfer properties.By combining finite volume method(FVM)with machine learning technique,this study provides valuable insights into the complex interactions between key parameters and heat transfer,contributing to the development of more efficient designs in applications such as cooling systems,energy storage,and bioengineering.
