We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple elect...We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple electronic states while simultaneously tracking their time-dependent electronic,vibrational,and rotational dynamics.As an illustrative example,we consider neutral H_(2)molecules and simulate the laser-induced excitation dynamics of electronic and rotational states in strong laser fields,quantitatively distinguishing the respective contributions of electronic dipole transitions(within the classical-field approximation)and non-resonant Raman processes to the overall molecular dynamics.Furthermore,we precisely evaluate the relative contributions of direct tunneling ionization from the ground state and ionization following electronic excitation in the strong-field ionization of H_(2).The developed methodology shows strong potential for performing high-precision theoretical simulations of electronic-vibrational-rotational state excitations,ionization,and dissociation dynamics in molecules and their ions under intense laser fields.展开更多
With the increase of wireless devices and new applications,highly dense small cell base stations(SBS)have become the main means to overcome the speed bottleneck of the radio access network(RAN).However,the highly-dens...With the increase of wireless devices and new applications,highly dense small cell base stations(SBS)have become the main means to overcome the speed bottleneck of the radio access network(RAN).However,the highly-dense deployment of SBSs greatly increases the cost of network operation and maintenance.In this paper,a base station sleep strategy combining traffic aware and high-low frequency resource allocation is proposed.To reduce the service level agreement(SLA)default caused by base station sleep,Long Short-Term Memory(LSTM)algorithm is introduced to predict the traffic flow,based on the predict result,the SBSs sleep and frequency resource allocation are introduced to increase the energy efficiency of the network.Moreover,this paper improves the decision-making efficiency by introducing Kuhn Munkres algorithm(KM)and genetic algorithm(GA).Simulation results show that the proposed strategy can greatly reduce the energy consumption of small cells and the occurrence of SLA default rate.展开更多
This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.B...This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.By combining the amplification capability of the active IRS and the signal regeneration function of the DF relay,the proposed system effectively mitigates path loss and fading.We derive closed-form upper bounds on the achievable rate and develop an optimal power allocation strategy under a total power constraint.Numerical results demonstrate that the hybrid scheme significantly outperforms conventional passive IRS-assisted or active IRS-only configurations,particularly under conditions of limited reflecting elements or moderate signal-to-noise ratios.展开更多
The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population,especially in relation to falls.While falls can lead to significant cognitive impairments,timely i...The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population,especially in relation to falls.While falls can lead to significant cognitive impairments,timely intervention can mitigate their adverse effects.In this context,the need for non-invasive,efficient monitoring systems becomes paramount.Although wearable sensors have gained traction for monitoring health activities,they may cause discomfort during prolonged use,especially for the elderly.To address this issue,we present an intelligent,non-invasive Software-Defined Radio Frequency(SDRF)sensing system,tailored red for monitoring elderly people’s falls during routine activities.Harnessing the power of deep learning and machine learning,our system processes the Wireless Channel State Information(WCSI)generated during regular and fall activities.By employing sophisticated signal processing techniques,the system captures unique patterns that distinguish falls from normal activities.In addition,we use statistical features to streamline data processing,thereby optimizing the computational efficiency of the system.Our experiments,conducted for a typical home environment while using treadmill,demonstrate the robustness of the system.The results show high classification accuracies of 92.5%,95.1%,and 99.8%for three Artificial Intelligence(AI)algorithms.Notably,the SDRF-based approach offers flexibility,cost-effectiveness,and adaptability through software modifications,circumventing the need for hardware overhaul.This research attempts to bridge the gap in RF-based sensing for elderly fall monitoring,providing a solution that combines the benefits of non-invasiveness with the precision of deep learning and machine learning.展开更多
Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determ...Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determination and parameter estimation due to little understanding of the flow mechanism. Support vector machines （SVMs） based on statistical learning theory provide a novel tool for nonlinear system modeling. The work presented here examines the feasibility of applying SVMs to high angle.-of-attack unsteady aerodynamic modeling field. Mainly, after a review of SVMs, several issues associated with unsteady aerodynamic modeling by use of SVMs are discussed in detail, such as sele, ction of input variables, selection of output variables and determination of SVM parameters. The least squares SVM （LS-SVM） models are set up from certain dynamic wind tunnel test data of a delta wing and an aircraft configuration, and then used to predict the aerodynamic responses in other tests. The predictions are in good agreement with the test data, which indicates the satisfving learning and generalization performance of LS-SVMs.展开更多
Abstract Based on the Reynolds-averaged Navier--Stokes （RANS） equations and structured grid technology, the calibration and validation of Y-Reo transition model is preformed with fifth-order weighted compact nonline...Abstract Based on the Reynolds-averaged Navier--Stokes （RANS） equations and structured grid technology, the calibration and validation of Y-Reo transition model is preformed with fifth-order weighted compact nonlinear scheme （WCNS）, and the purpose of the present work is to improve the numerical accuracy for aerodynamic characteristics simulation of low-speed flow with transition model on the basis of high-order numerical method study. Firstly, the empirical correlation functions involved in the Y-Reo transition model are modified and calibrated with experimental data of turbulent flat plates. Then, the grid convergence is studied on NLR-7301 two-element airfoil with the modified empirical correlation. At last, the modified empirical correlation is validated with NLR-7301 two-element airfoil and high-lift trapezoidal wing from transition location, velocity pro- file in boundary layer, surface pressure coefficient and aerodynamic characteristics. The numerical results illustrate that the numerical accuracy of transition length and skin friction behind transition location are improved with modified empirical correlation function, and obviously increases the numerical accuracy of aerodynamic characteristics prediction for typical transport configurations in low-speed range.展开更多
Local mesh refinement is one of the key steps in the implementations of adaptive finite element methods. This paper presents a parallel algorithm for distributed memory parallel computers for adaptive local refinement...Local mesh refinement is one of the key steps in the implementations of adaptive finite element methods. This paper presents a parallel algorithm for distributed memory parallel computers for adaptive local refinement of tetrahedral meshes using bisection. This algorithm is used in PHG, Parallel Hierarchical Grid Chttp：//lsec. cc. ac. cn/phg/）, a toolbox under active development for parallel adaptive finite element solutions of partial differential equations. The algorithm proposed is characterized by allowing simukaneous refinement of submeshes to arbitrary levels before synchronization between submeshes and without the need of a central coordinator process for managing new vertices. Using the concept of canonical refinement, a simple proof of the independence of the resulting mesh on the mesh partitioning is given, which is useful in better understanding the behaviour of the biseetioning refinement procedure.展开更多
Mitigation of sonic boom to an acceptable stage is a key point for the next generation of supersonic transports. Meanwhile, designing a supersonic aircraft with an ideal ground signature is always the focus of researc...Mitigation of sonic boom to an acceptable stage is a key point for the next generation of supersonic transports. Meanwhile, designing a supersonic aircraft with an ideal ground signature is always the focus of research on sonic boom reduction. This paper presents an inverse design approach to optimize the near-field signature of an aircraft, making it close to the shaped ideal ground signature after the propagation in the atmosphere. Using the Proper Orthogonal Decomposition(POD) method, a guessed input of augmented Burgers equation is inversely achieved. By multiple POD iterations, the guessed ground signatures successively approach the target ground signature until the convergence criteria is reached. Finally, the corresponding equivalent area distribution is calculated from the optimal near-field signature through the classical Whitham F-function theory. To validate this method, an optimization example of Lockheed Martin 1021 is demonstrated. The modified configuration has a fully shaped ground signature and achieves a drop of perceived loudness by 7.94 PLdB. This improvement is achieved via shaping the original near-field signature into wiggles and damping it by atmospheric attenuation. At last, a nonphysical ground signature is set as the target to test the robustness of this inverse design method and shows that this method is robust enough for various inputs.展开更多
Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane....Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother （EKF-MBF） method for aerodynamic coefficient identification, the radial basis function （RBF） neural network method for aerodynamic mod- eling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil air- plane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.展开更多
A CFD-based Numerical Virtual Flight(NVF)simulator is presented,which integrates an unsteady flow solver on moving hybrid grids,a Rigid-Body Dynamics(RBD)solver and a module of the Flight Control System(FCS).A techni...A CFD-based Numerical Virtual Flight(NVF)simulator is presented,which integrates an unsteady flow solver on moving hybrid grids,a Rigid-Body Dynamics(RBD)solver and a module of the Flight Control System(FCS).A technique of dynamic hybrid grids is developed to control the active control surfaces with body morphing,with a technique of parallel unstructured dynamic overlapping grids generating proper moving grids over the deflecting control surfaces(e.g.the afterbody rudders of a missile).For the flow/kinematic coupled problems,the 6 Degree-Of-Freedom(DOF)equations are solved by an explicit or implicit method coupled with the URANS CFD solver.The module of the control law is explicitly coupled into the NVF simulator and then improved by the simulation of the pitching maneuver process of a maneuverable missile model.A nonlinear dynamic inversion method is then implemented to design the control law for the pitching process of the maneuverable missile model.Simulations and analysis of the pitching maneuver process are carried out by the NVF simulator to improve the flight control law.Higher control response performance is obtained by adjusting the gain factors and adding an integrator into the control loop.展开更多
Experiment design method is a key to construct a highly reliable surrogate model for numerical optimization in large-scale project. Within the method, the experimental design criterion directly affects the accuracy of...Experiment design method is a key to construct a highly reliable surrogate model for numerical optimization in large-scale project. Within the method, the experimental design criterion directly affects the accuracy of the surrogate model and the optimization efficient. According to the shortcomings of the traditional experimental design, an improved adaptive sampling method is proposed in this paper. The surrogate model is firstly constructed by basic sparse samples. Then the supplementary sampling position is detected according to the specified criteria, which introduces the energy function and curvature sampling criteria based on radial basis function （RBF） network. Sampling detection criteria considers both the uniformity of sample distribution and the description of hypersurface curvature so as to significantly improve the prediction accuracy of the surrogate model with much less samples. For the surrogate model constructed with sparse samples, the sample uniformity is an important factor to the interpolation accuracy in the initial stage of adaptive sam- pling and surrogate model training. Along with the improvement of uniformity, the curvature description of objective function surface gradually becomes more important. In consideration of these issues, crowdness enhance function and root mean square error （RMSE） feedback function are introduced in C criterion expression. Thus, a new sampling method called RMSE and crowd- ness enhance （RCE） adaptive sampling is established. The validity of RCE adaptive sampling method is studied through typical test function firstly and then the airfoil/wing aerodynamic opti- mization design problem, which has high-dimensional design space. The results show that RCE adaptive sampling method not only reduces the requirement for the number of samples, but also effectively improves the prediction accuracy of the surrogate model, which has a broad prospects for applications.展开更多
This paper numerically studies the aerodynamic performance of a bird-like bionic flapping wing.The geometry and kinematics are designed based on a seagull wing,in which flapping,folding,swaying,and twisting are consid...This paper numerically studies the aerodynamic performance of a bird-like bionic flapping wing.The geometry and kinematics are designed based on a seagull wing,in which flapping,folding,swaying,and twisting are considered.An in-house unsteady flow solver based on hybrid moving grids.is adopted for unsteady flow simulations.We focus on two main issues in this study,i.e.,the influence of the proportion of down-stroke and the effect of span-wise twisting.Numerical results show that the proportion of downstroke is closely related to the efficiency of the flapping process.The preferable proportion is about 0.7 by using the present geometry and kinematic model,which is very close to the observed data.Another finding is that the drag and the power consumption can be greatly reduced by the proper span-wise twisting.Two cases with different reduced frequencies are simulated and compared with each other.The numerical results show that the power consumption reduces by more than 20%,and the drag coefficient reduces by more than 60% through a proper twisting motion for both cases.The flow mechanism is mainly due to controlling of unsteady flow separation by adjusting the local effective angle of attack.These conclusions will be helpful for the high-performance micro air vehicle (MAV) design.展开更多
It is common for aircraft to encounter atmospheric turbulence in flight tests.Turbulence is usually modeled as stochastic process noise in the flight dynamics equations.In this paper,parameter estimation of nonlinear ...It is common for aircraft to encounter atmospheric turbulence in flight tests.Turbulence is usually modeled as stochastic process noise in the flight dynamics equations.In this paper,parameter estimation of nonlinear dynamic system with both process and measurement noise was studied,and a practical filter error method was proposed.The linearized Kalman filter of first-order approximation was used for state estimation,in which the filter gain,along with the system parameters and the initial states,constituted the parameter vector to be estimated.The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method,and the sensitivities of observations to unknown parameters were calculated by finite difference approximation.Some practical aspects of the method application were discussed.The proposed filter error method was validated by the flight simulation data of a research aircraft.Then,the method was applied to the flight tests of a subscale aircraft,and the aerodynamic stability and control derivatives were estimated.All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach.It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.展开更多
For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of structured preconditioners through matrix transformation and matrix approximations. For the specific versions such a...For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of structured preconditioners through matrix transformation and matrix approximations. For the specific versions such as modified block Jacobi-type, modified block Gauss-Seidel-type, and modified block unsymmetric (symmetric) Gauss-Seidel-type preconditioners, we precisely describe their concrete expressions and deliberately analyze eigenvalue distributions and positive definiteness of the preconditioned matrices. Also, we show that when these structured preconditioners are employed to precondition the Krylov subspace methods such as GMRES and restarted GMRES, fast and effective iteration solvers can be obtained for the large sparse systems of linear equations with block two-by-two coefficient matrices. In particular, these structured preconditioners can lead to high-quality preconditioning matrices for some typical matrices from the real-world applications.展开更多
The performance of an optimized aerodynamic shape is further improved by a second-step optimization using the design knowledge discovered by a data mining technique based on Proper Orthogonal Decomposition(POD) in the...The performance of an optimized aerodynamic shape is further improved by a second-step optimization using the design knowledge discovered by a data mining technique based on Proper Orthogonal Decomposition(POD) in the present study. Data generated in the first-step optimization by using evolution algorithms is saved as the source data, among which the superior data with improved objectives and maintained constraints is chosen. Only the geometry components of the superior data are picked out and used for constructing the snapshots of POD. Geometry characteristics of the superior data illustrated by POD bases are the design knowledge, by which the second-step optimization can be rapidly achieved. The optimization methods are demonstrated by redesigning a transonic compressor rotor blade, NASA Rotor 37, in the study to maximize the peak adiabatic efficiency, while maintaining the total pressure ratio and mass flow rate.Firstly, the blade is redesigned by using a particle swarm optimization method, and the adiabatic efficiency is increased by 1.29%. Then, the second-step optimization is performed by using the design knowledge, and a 0.25% gain on the adiabatic efficiency is obtained. The results are presented and addressed in detail, demonstrating that geometry variations significantly change the pattern and strength of the shock wave in the blade passage. The former reduces the separation loss,while the latter reduces the shock loss, and both favor an increase of the adiabatic efficiency.展开更多
An efficient MPI/OpenMP hybrid parallel Radial Basis Function (RBF) strategy for both continuous and discontinuous large-scale mesh deformation is proposed to reduce the computational cost and memory consumption.Unlik...An efficient MPI/OpenMP hybrid parallel Radial Basis Function (RBF) strategy for both continuous and discontinuous large-scale mesh deformation is proposed to reduce the computational cost and memory consumption.Unlike the conventional parallel methods in which all processors use the same surface displacement and implement the same operation,the present method employs different surface points sets and influence radius for each volume point movement,accompanied with efficient geometry searching strategy.The deformed surface points,also called Control Points (CPs),are stored in each processor.The displacement of spatial points is interpolated by using only 20-50 nearest control points,and the local influence radius is set to 5-20 times the maximum displacement of control points.To shorten the searching time for the nearest control point clouds,an Alternating Digital Tree (ADT) algorithm for 3D complex geometry is designed based on an iterative bisection technique.Besides,an MPI/OpenMP hybrid parallel approach is developed to reduce the memory cost in each High-Performance Computing (HPC) node for large-scale applications.Three 3D cases,including the ONERA-M6 wing and a commercial transport airplane standard model with up to 2.5 billion hybrid elements,are used to test the present mesh deformation method.The robustness and high parallel efficiency are demonstrated by a wing deflection case with a maximum bending angle of 450 and more than 80% parallel efficiency with 1024 MPI processors.In addition,the availability for both continuous and discontinuous surface deformation is verified by interpolating the projecting displacement with opposite directions surface points to the spatial points.展开更多
To understand fundamental problems in hypersonic laminar-turbulent boundary layer transition for three-dimensional complex vehicles,a new standard model with typical lifting-body features has been proposed,named as hy...To understand fundamental problems in hypersonic laminar-turbulent boundary layer transition for three-dimensional complex vehicles,a new standard model with typical lifting-body features has been proposed,named as hypersonic transition research vehicle(HyTRV).The configuration of HyTRV is fully analytical,and details of the design process are discussed in this study.The transition characteristics for HyTRV are investigated using three combined methods,i.e.,theoretical analyses,numerical simulations,and wind tunnel experiments.Results show that the fully analytic parameterization design of HyTRV can satisfy the model simplification requirements from both numerical simulations and wind tunnel experiments.Meanwhile,the flow field of HyTRV reveals typical transition mechanisms in six relatively separated regions,including the streamwise vortex instability,crossflow instability,secondary instability,and attachment-line instability.Therefore,the proposed HyTRV model is valuable for fundamental researches in hypersonic boundary layer transition.展开更多
With the great commercial success of several IPTV (internet protocal television) applications, PPLive has received more and more attention from both industry and academia. At present, PPLive system is one of the most ...With the great commercial success of several IPTV (internet protocal television) applications, PPLive has received more and more attention from both industry and academia. At present, PPLive system is one of the most popular instances of IPTV applications which attract a large number of users across the globe; however, the dramatic rise in popularity makes it more likely to become a vulnerable target. The main contribution of this work is twofold. Firstly, a dedicated distributed crawler system was proposed and its crawling performance was analyzed, which was used to evaluate the impact of pollution attack in P2P live streaming system. The measurement results reveal that the crawler system with distributed architecture could capture PPLive overlay snapshots with more efficient way than previous crawlers. To the best of our knowledge, our study work is the first to employ distributed architecture idea to design crawler system and discuss the crawling performance of capturing accurate overlay snapshots for P2P live streaming system. Secondly, a feasible and effective pollution architecture was proposed to deploy content pollution attack in a real-world P2P live streaming system called PPLive, and deeply evaluate the impact of pollution attack from following five aspects:dynamic evolution of participating users, user lifetime characteristics, user connectivity-performance, dynamic evolution of uploading polluted chunks and dynamic evolution of pollution ratio. Specifically, the experiment results show that a single polluter is capable of compromising all the system and its destructiveness is severe.展开更多
Rough set theory has a very good effect in information processing and knowledge discovery.In an information table,the current scholars regard all objects as a universe,and then establish various rough set models.Howev...Rough set theory has a very good effect in information processing and knowledge discovery.In an information table,the current scholars regard all objects as a universe,and then establish various rough set models.However,in the analysis of many data problems,it is more reasonable to select parts of objects which are useful to us or can meet the actual needs as a universe.Therefore,in order to make up for the deficiency of traditional models,a new model is introduced from the perspective of variable universe.Then,some interesting properties of this model,such as approximation sets,reduct of attributes and maximum part of universe,are discussed.Through the study of this paper,it can be seen that the model developed in our paper is not only more accurate but also more effective in describing uncertain knowledge.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFA1602502)the National Natural Science Foundation of China(Grant No.12450404)。
文摘We present a fully time-dependent quantum wave packet evolution method for investigating molecular dynamics in intense laser fields.This approach enables the simultaneous treatment of interactions among multiple electronic states while simultaneously tracking their time-dependent electronic,vibrational,and rotational dynamics.As an illustrative example,we consider neutral H_(2)molecules and simulate the laser-induced excitation dynamics of electronic and rotational states in strong laser fields,quantitatively distinguishing the respective contributions of electronic dipole transitions(within the classical-field approximation)and non-resonant Raman processes to the overall molecular dynamics.Furthermore,we precisely evaluate the relative contributions of direct tunneling ionization from the ground state and ionization following electronic excitation in the strong-field ionization of H_(2).The developed methodology shows strong potential for performing high-precision theoretical simulations of electronic-vibrational-rotational state excitations,ionization,and dissociation dynamics in molecules and their ions under intense laser fields.
文摘With the increase of wireless devices and new applications,highly dense small cell base stations(SBS)have become the main means to overcome the speed bottleneck of the radio access network(RAN).However,the highly-dense deployment of SBSs greatly increases the cost of network operation and maintenance.In this paper,a base station sleep strategy combining traffic aware and high-low frequency resource allocation is proposed.To reduce the service level agreement(SLA)default caused by base station sleep,Long Short-Term Memory(LSTM)algorithm is introduced to predict the traffic flow,based on the predict result,the SBSs sleep and frequency resource allocation are introduced to increase the energy efficiency of the network.Moreover,this paper improves the decision-making efficiency by introducing Kuhn Munkres algorithm(KM)and genetic algorithm(GA).Simulation results show that the proposed strategy can greatly reduce the energy consumption of small cells and the occurrence of SLA default rate.
基金supported in part by National Key R&D Program of China(2022YFB2903500)NSFC Grant 62331022,Grant 62371289+4 种基金Grant 624B2094in part by the Shanghai Jiao Tong University 2030 Initiative,and the Guangdong Science and Technology program under grant 2022A0505050011in part by the Outstanding Doctoral Graduates Development Scholarship of Shanghai Jiao Tong Universityin part by Shanghai Kewei under Grant 22JC1404000Grant 24DP1500500.
文摘This paper proposes a hybrid wireless communication framework that integrates an active intelligent reflecting surface(IRS)with a decode-andforward(DF)relay to enhance spectral efficiency in extended-range scenarios.By combining the amplification capability of the active IRS and the signal regeneration function of the DF relay,the proposed system effectively mitigates path loss and fading.We derive closed-form upper bounds on the achievable rate and develop an optimal power allocation strategy under a total power constraint.Numerical results demonstrate that the hybrid scheme significantly outperforms conventional passive IRS-assisted or active IRS-only configurations,particularly under conditions of limited reflecting elements or moderate signal-to-noise ratios.
基金supported in part by the Institute of Advanced Technology,University of Science and Technology of China (USTC) under Grant PF02023001Ythe Zayed Health Center at United Arab Emirates University (UAEU) under Grant G00003476COMSATS University Islamabad,Attock Campus。
文摘The global increase in life expectancy poses challenges related to the safety and well-being of the elderly population,especially in relation to falls.While falls can lead to significant cognitive impairments,timely intervention can mitigate their adverse effects.In this context,the need for non-invasive,efficient monitoring systems becomes paramount.Although wearable sensors have gained traction for monitoring health activities,they may cause discomfort during prolonged use,especially for the elderly.To address this issue,we present an intelligent,non-invasive Software-Defined Radio Frequency(SDRF)sensing system,tailored red for monitoring elderly people’s falls during routine activities.Harnessing the power of deep learning and machine learning,our system processes the Wireless Channel State Information(WCSI)generated during regular and fall activities.By employing sophisticated signal processing techniques,the system captures unique patterns that distinguish falls from normal activities.In addition,we use statistical features to streamline data processing,thereby optimizing the computational efficiency of the system.Our experiments,conducted for a typical home environment while using treadmill,demonstrate the robustness of the system.The results show high classification accuracies of 92.5%,95.1%,and 99.8%for three Artificial Intelligence(AI)algorithms.Notably,the SDRF-based approach offers flexibility,cost-effectiveness,and adaptability through software modifications,circumventing the need for hardware overhaul.This research attempts to bridge the gap in RF-based sensing for elderly fall monitoring,providing a solution that combines the benefits of non-invasiveness with the precision of deep learning and machine learning.
文摘Abstract Accurate aerodynamic models are the basis of flight simulation and control law design. Mathematically modeling unsteady aerodynamics at high angles of attack bears great difficulties in model structure determination and parameter estimation due to little understanding of the flow mechanism. Support vector machines （SVMs） based on statistical learning theory provide a novel tool for nonlinear system modeling. The work presented here examines the feasibility of applying SVMs to high angle.-of-attack unsteady aerodynamic modeling field. Mainly, after a review of SVMs, several issues associated with unsteady aerodynamic modeling by use of SVMs are discussed in detail, such as sele, ction of input variables, selection of output variables and determination of SVM parameters. The least squares SVM （LS-SVM） models are set up from certain dynamic wind tunnel test data of a delta wing and an aircraft configuration, and then used to predict the aerodynamic responses in other tests. The predictions are in good agreement with the test data, which indicates the satisfving learning and generalization performance of LS-SVMs.
基金supported by the National Basic Research Program of China(No.2014CB744803)
文摘Abstract Based on the Reynolds-averaged Navier--Stokes （RANS） equations and structured grid technology, the calibration and validation of Y-Reo transition model is preformed with fifth-order weighted compact nonlinear scheme （WCNS）, and the purpose of the present work is to improve the numerical accuracy for aerodynamic characteristics simulation of low-speed flow with transition model on the basis of high-order numerical method study. Firstly, the empirical correlation functions involved in the Y-Reo transition model are modified and calibrated with experimental data of turbulent flat plates. Then, the grid convergence is studied on NLR-7301 two-element airfoil with the modified empirical correlation. At last, the modified empirical correlation is validated with NLR-7301 two-element airfoil and high-lift trapezoidal wing from transition location, velocity pro- file in boundary layer, surface pressure coefficient and aerodynamic characteristics. The numerical results illustrate that the numerical accuracy of transition length and skin friction behind transition location are improved with modified empirical correlation function, and obviously increases the numerical accuracy of aerodynamic characteristics prediction for typical transport configurations in low-speed range.
基金supported by the 973 Program of China 2005CB321702China NSF 10531080.
文摘Local mesh refinement is one of the key steps in the implementations of adaptive finite element methods. This paper presents a parallel algorithm for distributed memory parallel computers for adaptive local refinement of tetrahedral meshes using bisection. This algorithm is used in PHG, Parallel Hierarchical Grid Chttp：//lsec. cc. ac. cn/phg/）, a toolbox under active development for parallel adaptive finite element solutions of partial differential equations. The algorithm proposed is characterized by allowing simukaneous refinement of submeshes to arbitrary levels before synchronization between submeshes and without the need of a central coordinator process for managing new vertices. Using the concept of canonical refinement, a simple proof of the independence of the resulting mesh on the mesh partitioning is given, which is useful in better understanding the behaviour of the biseetioning refinement procedure.
文摘Mitigation of sonic boom to an acceptable stage is a key point for the next generation of supersonic transports. Meanwhile, designing a supersonic aircraft with an ideal ground signature is always the focus of research on sonic boom reduction. This paper presents an inverse design approach to optimize the near-field signature of an aircraft, making it close to the shaped ideal ground signature after the propagation in the atmosphere. Using the Proper Orthogonal Decomposition(POD) method, a guessed input of augmented Burgers equation is inversely achieved. By multiple POD iterations, the guessed ground signatures successively approach the target ground signature until the convergence criteria is reached. Finally, the corresponding equivalent area distribution is calculated from the optimal near-field signature through the classical Whitham F-function theory. To validate this method, an optimization example of Lockheed Martin 1021 is demonstrated. The modified configuration has a fully shaped ground signature and achieves a drop of perceived loudness by 7.94 PLdB. This improvement is achieved via shaping the original near-field signature into wiggles and damping it by atmospheric attenuation. At last, a nonphysical ground signature is set as the target to test the robustness of this inverse design method and shows that this method is robust enough for various inputs.
基金National Natural Science Foundation of China(60832012)
文摘Aerodynamic modeling and parameter estimation from quick accesses recorder （QAR） data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother （EKF-MBF） method for aerodynamic coefficient identification, the radial basis function （RBF） neural network method for aerodynamic mod- eling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil air- plane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.
基金supported partially by National Key Research and Development Program (No. 2016YFB0200701)National Natural Science Foundation of China (Nos. 11532016 and 11672324)
文摘A CFD-based Numerical Virtual Flight(NVF)simulator is presented,which integrates an unsteady flow solver on moving hybrid grids,a Rigid-Body Dynamics(RBD)solver and a module of the Flight Control System(FCS).A technique of dynamic hybrid grids is developed to control the active control surfaces with body morphing,with a technique of parallel unstructured dynamic overlapping grids generating proper moving grids over the deflecting control surfaces(e.g.the afterbody rudders of a missile).For the flow/kinematic coupled problems,the 6 Degree-Of-Freedom(DOF)equations are solved by an explicit or implicit method coupled with the URANS CFD solver.The module of the control law is explicitly coupled into the NVF simulator and then improved by the simulation of the pitching maneuver process of a maneuverable missile model.A nonlinear dynamic inversion method is then implemented to design the control law for the pitching process of the maneuverable missile model.Simulations and analysis of the pitching maneuver process are carried out by the NVF simulator to improve the flight control law.Higher control response performance is obtained by adjusting the gain factors and adding an integrator into the control loop.
基金co-supported by the National Natural Science Foundation of China (Nos. 11402288 and 11372254)
文摘Experiment design method is a key to construct a highly reliable surrogate model for numerical optimization in large-scale project. Within the method, the experimental design criterion directly affects the accuracy of the surrogate model and the optimization efficient. According to the shortcomings of the traditional experimental design, an improved adaptive sampling method is proposed in this paper. The surrogate model is firstly constructed by basic sparse samples. Then the supplementary sampling position is detected according to the specified criteria, which introduces the energy function and curvature sampling criteria based on radial basis function （RBF） network. Sampling detection criteria considers both the uniformity of sample distribution and the description of hypersurface curvature so as to significantly improve the prediction accuracy of the surrogate model with much less samples. For the surrogate model constructed with sparse samples, the sample uniformity is an important factor to the interpolation accuracy in the initial stage of adaptive sam- pling and surrogate model training. Along with the improvement of uniformity, the curvature description of objective function surface gradually becomes more important. In consideration of these issues, crowdness enhance function and root mean square error （RMSE） feedback function are introduced in C criterion expression. Thus, a new sampling method called RMSE and crowd- ness enhance （RCE） adaptive sampling is established. The validity of RCE adaptive sampling method is studied through typical test function firstly and then the airfoil/wing aerodynamic opti- mization design problem, which has high-dimensional design space. The results show that RCE adaptive sampling method not only reduces the requirement for the number of samples, but also effectively improves the prediction accuracy of the surrogate model, which has a broad prospects for applications.
基金Project supported by the National Key Research and Development Program(No.2016YFB0200700)the National Natural Science Foundation of China(Nos.11532016 and 11672324)
文摘This paper numerically studies the aerodynamic performance of a bird-like bionic flapping wing.The geometry and kinematics are designed based on a seagull wing,in which flapping,folding,swaying,and twisting are considered.An in-house unsteady flow solver based on hybrid moving grids.is adopted for unsteady flow simulations.We focus on two main issues in this study,i.e.,the influence of the proportion of down-stroke and the effect of span-wise twisting.Numerical results show that the proportion of downstroke is closely related to the efficiency of the flapping process.The preferable proportion is about 0.7 by using the present geometry and kinematic model,which is very close to the observed data.Another finding is that the drag and the power consumption can be greatly reduced by the proper span-wise twisting.Two cases with different reduced frequencies are simulated and compared with each other.The numerical results show that the power consumption reduces by more than 20%,and the drag coefficient reduces by more than 60% through a proper twisting motion for both cases.The flow mechanism is mainly due to controlling of unsteady flow separation by adjusting the local effective angle of attack.These conclusions will be helpful for the high-performance micro air vehicle (MAV) design.
基金supported by the National Natural Science Foundation of China(No.11802325)。
文摘It is common for aircraft to encounter atmospheric turbulence in flight tests.Turbulence is usually modeled as stochastic process noise in the flight dynamics equations.In this paper,parameter estimation of nonlinear dynamic system with both process and measurement noise was studied,and a practical filter error method was proposed.The linearized Kalman filter of first-order approximation was used for state estimation,in which the filter gain,along with the system parameters and the initial states,constituted the parameter vector to be estimated.The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method,and the sensitivities of observations to unknown parameters were calculated by finite difference approximation.Some practical aspects of the method application were discussed.The proposed filter error method was validated by the flight simulation data of a research aircraft.Then,the method was applied to the flight tests of a subscale aircraft,and the aerodynamic stability and control derivatives were estimated.All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach.It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.
文摘For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of structured preconditioners through matrix transformation and matrix approximations. For the specific versions such as modified block Jacobi-type, modified block Gauss-Seidel-type, and modified block unsymmetric (symmetric) Gauss-Seidel-type preconditioners, we precisely describe their concrete expressions and deliberately analyze eigenvalue distributions and positive definiteness of the preconditioned matrices. Also, we show that when these structured preconditioners are employed to precondition the Krylov subspace methods such as GMRES and restarted GMRES, fast and effective iteration solvers can be obtained for the large sparse systems of linear equations with block two-by-two coefficient matrices. In particular, these structured preconditioners can lead to high-quality preconditioning matrices for some typical matrices from the real-world applications.
基金supported by the National Natural Science Foundation of China(Nos.51676003,51206003,and 11702305)
文摘The performance of an optimized aerodynamic shape is further improved by a second-step optimization using the design knowledge discovered by a data mining technique based on Proper Orthogonal Decomposition(POD) in the present study. Data generated in the first-step optimization by using evolution algorithms is saved as the source data, among which the superior data with improved objectives and maintained constraints is chosen. Only the geometry components of the superior data are picked out and used for constructing the snapshots of POD. Geometry characteristics of the superior data illustrated by POD bases are the design knowledge, by which the second-step optimization can be rapidly achieved. The optimization methods are demonstrated by redesigning a transonic compressor rotor blade, NASA Rotor 37, in the study to maximize the peak adiabatic efficiency, while maintaining the total pressure ratio and mass flow rate.Firstly, the blade is redesigned by using a particle swarm optimization method, and the adiabatic efficiency is increased by 1.29%. Then, the second-step optimization is performed by using the design knowledge, and a 0.25% gain on the adiabatic efficiency is obtained. The results are presented and addressed in detail, demonstrating that geometry variations significantly change the pattern and strength of the shock wave in the blade passage. The former reduces the separation loss,while the latter reduces the shock loss, and both favor an increase of the adiabatic efficiency.
基金supported by the National Key Research and Development Program of China (No.2016YFB0200701)the National Natural Science Foundation of China (Nos. 11532016 and 91530325)
文摘An efficient MPI/OpenMP hybrid parallel Radial Basis Function (RBF) strategy for both continuous and discontinuous large-scale mesh deformation is proposed to reduce the computational cost and memory consumption.Unlike the conventional parallel methods in which all processors use the same surface displacement and implement the same operation,the present method employs different surface points sets and influence radius for each volume point movement,accompanied with efficient geometry searching strategy.The deformed surface points,also called Control Points (CPs),are stored in each processor.The displacement of spatial points is interpolated by using only 20-50 nearest control points,and the local influence radius is set to 5-20 times the maximum displacement of control points.To shorten the searching time for the nearest control point clouds,an Alternating Digital Tree (ADT) algorithm for 3D complex geometry is designed based on an iterative bisection technique.Besides,an MPI/OpenMP hybrid parallel approach is developed to reduce the memory cost in each High-Performance Computing (HPC) node for large-scale applications.Three 3D cases,including the ONERA-M6 wing and a commercial transport airplane standard model with up to 2.5 billion hybrid elements,are used to test the present mesh deformation method.The robustness and high parallel efficiency are demonstrated by a wing deflection case with a maximum bending angle of 450 and more than 80% parallel efficiency with 1024 MPI processors.In addition,the availability for both continuous and discontinuous surface deformation is verified by interpolating the projecting displacement with opposite directions surface points to the spatial points.
基金This work was supported by the National Natural Science Foundation of China(Grant 11702315,92052301)the National Key Research and Development Program of China(Grant 2016YFA0401200).
文摘To understand fundamental problems in hypersonic laminar-turbulent boundary layer transition for three-dimensional complex vehicles,a new standard model with typical lifting-body features has been proposed,named as hypersonic transition research vehicle(HyTRV).The configuration of HyTRV is fully analytical,and details of the design process are discussed in this study.The transition characteristics for HyTRV are investigated using three combined methods,i.e.,theoretical analyses,numerical simulations,and wind tunnel experiments.Results show that the fully analytic parameterization design of HyTRV can satisfy the model simplification requirements from both numerical simulations and wind tunnel experiments.Meanwhile,the flow field of HyTRV reveals typical transition mechanisms in six relatively separated regions,including the streamwise vortex instability,crossflow instability,secondary instability,and attachment-line instability.Therefore,the proposed HyTRV model is valuable for fundamental researches in hypersonic boundary layer transition.
基金Project(2007CB311106) supported by National Basic Research Program of ChinaProject(242-2009A82) supported by National Information Security Special Plan Program of China
文摘With the great commercial success of several IPTV (internet protocal television) applications, PPLive has received more and more attention from both industry and academia. At present, PPLive system is one of the most popular instances of IPTV applications which attract a large number of users across the globe; however, the dramatic rise in popularity makes it more likely to become a vulnerable target. The main contribution of this work is twofold. Firstly, a dedicated distributed crawler system was proposed and its crawling performance was analyzed, which was used to evaluate the impact of pollution attack in P2P live streaming system. The measurement results reveal that the crawler system with distributed architecture could capture PPLive overlay snapshots with more efficient way than previous crawlers. To the best of our knowledge, our study work is the first to employ distributed architecture idea to design crawler system and discuss the crawling performance of capturing accurate overlay snapshots for P2P live streaming system. Secondly, a feasible and effective pollution architecture was proposed to deploy content pollution attack in a real-world P2P live streaming system called PPLive, and deeply evaluate the impact of pollution attack from following five aspects:dynamic evolution of participating users, user lifetime characteristics, user connectivity-performance, dynamic evolution of uploading polluted chunks and dynamic evolution of pollution ratio. Specifically, the experiment results show that a single polluter is capable of compromising all the system and its destructiveness is severe.
基金supported by the National Natural Science Foundation of China(Nos.61976254,61772002)the Natural Science Foundation of Fujian Province(No.2020J01707)National Fund Cultivation program of Jimei University(No.ZP2020056).
文摘Rough set theory has a very good effect in information processing and knowledge discovery.In an information table,the current scholars regard all objects as a universe,and then establish various rough set models.However,in the analysis of many data problems,it is more reasonable to select parts of objects which are useful to us or can meet the actual needs as a universe.Therefore,in order to make up for the deficiency of traditional models,a new model is introduced from the perspective of variable universe.Then,some interesting properties of this model,such as approximation sets,reduct of attributes and maximum part of universe,are discussed.Through the study of this paper,it can be seen that the model developed in our paper is not only more accurate but also more effective in describing uncertain knowledge.
