Iterator模式产生原因和实例分析

讨论Iterator模式的产生原因和具体应用分析。利用Herator模式提供了顺序访问聚合对象中各个元素，而又不需暴露该对象的内部表示的特点，解决了客户端代码无法重用的问题。对Iterator模式的适用性和对聚合接口的简化也做了一定程度的说明。

设计模式——Iterator模式实现研究

设计模式为软件开发人员提供了一种使用专家设计经验的有效途径。文章介绍了设计模式的主要特点和益处,并以迭代器(Iterator)模式在Java集合框架类中的典型实现为例,说明此模式的实现方法以及利用此模式带来的好处。

316LN不锈钢真空电子束焊接工艺试验

本文对30mm的316LN不锈钢进行了真空电子束焊试验。随后对典型工艺参数下焊缝组织在常温及77K低温下焊接接头的力学性能进行了研究。微观组织SEM观察的结果表明,316LN的电子束焊接接头均不同程度地出现了气孔。力学性能测试结果表明,77K下接头的强度系数为83%,室温下接头的强度系数则达87%。此外,显微维氏硬度测试结果表明,接头区硬度约为母材的80%。

托卡马克高约束稳态物理的探路者——东方超环

人类已经在实验室通过托卡马克装置实现了10MW量级的可控氘氚核聚变反应,磁约束聚变研究进入到了实验堆时代。托卡马克高约束稳态运行成为开发商用聚变能的关键。中国全超导托卡马克装置(东方超环,EAST)瞄准国际热核聚变实验堆(ITER)和未来聚变堆稳态运行的需求,在前沿稳态物理研究中获得重要进展,率先演示了托卡马克高约束稳态模式的长脉冲运行,为ITER运行和未来聚变堆设计提供了重要参考。

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

全钨ITER朗缪尔探针的高热负荷测试及损伤行为

本文研究了全钨ITER朗缪尔探针在高热负荷条件下的耐热性能、绝缘性能和损伤行为。利用核工业西南物理研究院的60 kW电子束测试平台,对探针在10 MW/m^(2)稳态热负荷、20 MW/m^(2)瞬态热负荷及15 MW/m^(2)高参数稳态热负荷下进行模拟测试。实验结果表明,全钨朗缪尔探针能够承受10 MW/m^(2)热负荷100分钟、20 MW/m^(2)热负荷300次循环以及15 MW/m^(2)热负荷3000次循环。在15 MW/m^(2)条件下,探针表面在前1000次循环中无明显损伤,但在3000次循环后出现裂纹,且部分探针表面发生再结晶现象。研究表明,现有全钨朗缪尔探针的设计能够满足当前ITER装置的服役条件,但面对未来DEMO堆更加苛刻的条件可能还需要进一步优化。

西物院ITER项目强矩阵管理模式探索与成效

ITER计划是目前全球规模最大、影响最深远的国际大科学工程,由欧盟、中国、美国、日本、俄罗斯、韩国、印度等七方共35个国家参与,也是我国参与的最大的国际合作项目,我国承担任务在所有七方中完成最好,多次受到ITER总干事的表扬。文章主要针对西物院ITER项目强矩阵管理模式探索进行了总结,希望为未来参与大科学工程项目提供借鉴。

Data-Driven Active Disturbance Rejection Control of Plant-Protection Unmanned Ground Vehicle Prototype: A Fuzzy Indirect Iterative Learning Approach

Dear Editor,This letter proposes a fuzzy indirect iterative learning(FIIL)active disturbance rejection control(ADRC)scheme to address the impact of uncertain factors of plant-protection unmanned ground vehicle(UGV),in which ADRC is a data-driven model-free control algorithm that only relies on the input and output data of the system.Based on the established nonlinear time-varying dynamic model including dynamic load(medicine box),the FIIL technology is adopted to turn the bandwidth and control channel gain online,in which the fuzzy logic system is used to update the gain parameters of iterative learning in real time.Simulation and experiment show the FIIL-ADRC scheme has better control performance.

MAUN:Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction

Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D measurements.The algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivotal in the imaging process.Early approaches painstakingly designed networks to directly map compressive measurements to HSIs,resulting in the lack of interpretability without exploiting the imaging priors.While some recent works have introduced the deep unfolding framework for explainable reconstruction,the performance of these methods is still limited by the weak information transmission between iterative stages.In this paper,we propose a Memory-Augmented deep Unfolding Network,termed MAUN,for explainable and accurate HSI reconstruction.Specifically,MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm,introducing an extra momentum incorporation step for each iteration to alleviate the information loss.Moreover,to exploit the high correlation of intermediate images from neighboring iterations,we customize a cross-stage transformer(CSFormer)as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features,which is the first attempt to model the long-distance dependencies between iteration stages.Extensive experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and metrically.Our code is publicly available at https://github.com/HuQ1an/MAUN.

Data-Driven Learning Control Algorithms for Unachievable Tracking Problems

For unachievable tracking problems, where the system output cannot precisely track a given reference, achieving the best possible approximation for the reference trajectory becomes the objective. This study aims to investigate solutions using the Ptype learning control scheme. Initially, we demonstrate the necessity of gradient information for achieving the best approximation.Subsequently, we propose an input-output-driven learning gain design to handle the imprecise gradients of a class of uncertain systems. However, it is discovered that the desired performance may not be attainable when faced with incomplete information.To address this issue, an extended iterative learning control scheme is introduced. In this scheme, the tracking errors are modified through output data sampling, which incorporates lowmemory footprints and offers flexibility in learning gain design.The input sequence is shown to converge towards the desired input, resulting in an output that is closest to the given reference in the least square sense. Numerical simulations are provided to validate the theoretical findings.

Gyrokinetic simulations of the kinetic electron effects on the electrostatic instabilities on the ITER baseline scenario

The linear and nonlinear simulations are carried out using the gyrokinetic code NLT for the electrostatic instabilities in the core region of a deuterium plasma based on the International Thermonuclear Experimental Reactor(ITER)baseline scenario.The kinetic electron effects on the linear frequency and nonlinear transport are studied by adopting the adiabatic electron model and the fully drift-kinetic electron model in the NLT code,respectively.The linear simulations focus on the dependence of linear frequency on the plasma parameters,such as the ion and electron temperature gradientsκ_(Ti,e)≡R=L_(Ti,e),the density gradientκ_(n)≡R/L_(n)and the ion-electron temperature ratioτ=T_(e)=T_(i).Here,is the major radius,and T_(e)and T_(i)denote the electron and ion temperatures,respectively.L_(A)=-(δ_(r)lnA)^(-1)is the gradient scale length,with denoting the density,the ion and electron temperatures,respectively.In the kinetic electron model,the ion temperature gradient(ITG)instability and the trapped electron mode(TEM)dominate in the small and large k_(θ)region,respectively,wherek_(θ)is the poloidal wavenumber.The TEMdominant region becomes wider by increasing(decreasing)κ_(T_(e))(κ_(T_(i)))or by decreasingκ_(n).For the nominal parameters of the ITER baseline scenario,the maximum growth rate of dominant ITG instability in the kinetic electron model is about three times larger than that in the adiabatic electron model.The normalized linear frequency depends on the value ofτ,rather than the value of T_(e)or T_(i),in both the adiabatic and kinetic electron models.The nonlinear simulation results show that the ion heat diffusivity in the kinetic electron model is quite a lot larger than that in the adiabatic electron model,the radial structure is finer and the time oscillation is more rapid.In addition,the magnitude of the fluctuated potential at the saturated stage peaks in the ITGdominated region,and contributions from the TEM(dominating in the higher k_(θ)region)to the nonlinear transport can be neglected.In the adiabatic electron model,the zonal radial electric field is found to be mainly driven by the turbulent energy flux,and the contribution of turbulent poloidal Reynolds stress is quite small due to the toroidal shielding effect.However,in the kinetic electron model,the turbulent energy flux is not strong enough to drive the zonal radial electric field in the nonlinear saturated stage.The kinetic electron effects on the mechanism of the turbulence-driven zonal radial electric field should be further investigated.

Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach

In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuoustime Markov jump piecewise-affine(PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration information and the current feedback mechanism. The auxiliary feedback channel optimizes the response speed of the observer, therefore the estimation error would converge to zero rapidly. Then, sufficient conditions for stochastic stability with guaranteed performance are demonstrated for the estimation error system, and the equivalence relations between the system information and the estimated information can be established via iterative accumulating representation.Finally, two illustrative examples containing a class of tunnel diode circuit systems are presented to fully demonstrate the effectiveness and superiority of the proposed iterative learning observer with current feedback.

Fast and Accurate Predictor-Corrector Methods Using Feedback-Accelerated Picard Iteration for Strongly Nonlinear Problems

Although predictor-corrector methods have been extensively applied,they might not meet the requirements of practical applications and engineering tasks,particularly when high accuracy and efficiency are necessary.A novel class of correctors based on feedback-accelerated Picard iteration(FAPI)is proposed to further enhance computational performance.With optimal feedback terms that do not require inversion of matrices,significantly faster convergence speed and higher numerical accuracy are achieved by these correctors compared with their counterparts;however,the computational complexities are comparably low.These advantages enable nonlinear engineering problems to be solved quickly and accurately,even with rough initial guesses from elementary predictors.The proposed method offers flexibility,enabling the use of the generated correctors for either bulk processing of collocation nodes in a domain or successive corrections of a single node in a finite difference approach.In our method,the functional formulas of FAPI are discretized into numerical forms using the collocation approach.These collocated iteration formulas can directly solve nonlinear problems,but they may require significant computational resources because of the manipulation of high-dimensionalmatrices.To address this,the collocated iteration formulas are further converted into finite difference forms,enabling the design of lightweight predictor-corrector algorithms for real-time computation.The generality of the proposed method is illustrated by deriving new correctors for three commonly employed finite-difference approaches:the modified Euler approach,the Adams-Bashforth-Moulton approach,and the implicit Runge-Kutta approach.Subsequently,the updated approaches are tested in solving strongly nonlinear problems,including the Matthieu equation,the Duffing equation,and the low-earth-orbit tracking problem.The numerical findings confirm the computational accuracy and efficiency of the derived predictor-corrector algorithms.

A Modified Iterative Learning Control Approach for the Active Suppression of Rotor Vibration Induced by Coupled Unbalance and Misalignment

This paper proposes a modified iterative learning control(MILC)periodical feedback-feedforward algorithm to reduce the vibration of a rotor caused by coupled unbalance and parallel misalignment.The control of the vibration of the rotor is provided by an active magnetic actuator(AMA).The iterative gain of the MILC algorithm here presented has a self-adjustment based on the magnitude of the vibration.Notch filters are adopted to extract the synchronous(1×Ω)and twice rotational frequency(2×Ω)components of the rotor vibration.Both the notch frequency of the filter and the size of feedforward storage used during the experiment have a real-time adaptation to the rotational speed.The method proposed in this work can provide effective suppression of the vibration of the rotor in case of sudden changes or fluctuations of the rotor speed.Simulations and experiments using the MILC algorithm proposed here are carried out and give evidence to the feasibility and robustness of the technique proposed.

On traceable iterated line graph and hamiltonian path index

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

Hybrid Block Diagonalization Precoding for Multi-User Weighted Sum-Rate Maximization

This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.

Iteration and evaluation of shale oil development technology for continental rift lake basins

By benchmarking with the iteration of drilling technology,fracturing technology and well placement mode for shale oil and gas development in the United States and considering the geological characteristics and development difficulties of shale oil in the Jiyang continental rift lake basin,East China,the development technology system suitable for the geological characteristics of shale oil in continental rift lake basins has been primarily formed through innovation and iteration of the development,drilling and fracturing technologies.The technology system supports the rapid growth of shale oil production and reduces the development investment cost.By comparing it with the shale oil development technology in the United States,the prospect of the shale oil development technology iteration in continental rift lake basins is proposed.It is suggested to continuously strengthen the overall three-dimensional development,improve the precision level of engineering technology,upgrade the engineering technical indicator system,accelerate the intelligent optimization of engineering equipment,explore the application of complex structure wells,form a whole-process integrated quality management system from design to implementation,and constantly innovate the concept and technology of shale oil development,so as to promote the realization of extensive,beneficial and high-quality development of shale oil in continental rift lake basins.

Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete Information

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof.The players are divided into two groups in the learning process and adapt their policies sequentially.Our method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based frameworks.Furthermore,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control laws.The efficacy of our method is illustrated by three examples.

A novel algorithm for evaluating cement azimuthal density based on perturbation theory in horizontal well

Cement density monitoring plays a vital role in evaluating the quality of cementing projects,which is of great significance to the development of oil and gas.However,the presence of inhomogeneous cement distribution and casing eccentricity in horizontal wells often complicates the accurate evaluation of cement azimuthal density.In this regard,this paper proposes an algorithm to calculate the cement azimuthal density in horizontal wells using a multi-detector gamma-ray detection system.The spatial dynamic response functions are simulated to obtain the influence of cement density on gamma-ray counts by the perturbation theory,and the contribution of cement density in six sectors to the gamma-ray recorded by different detectors is obtained by integrating the spatial dynamic response functions.Combined with the relationship between gamma-ray counts and cement density,a multi-parameter calculation equation system is established,and the regularized Newton iteration method is employed to invert casing eccentricity and cement azimuthal density.This approach ensures the stability of the inversion process while simultaneously achieving an accuracy of 0.05 g/cm^(3) for the cement azimuthal density.This accuracy level is ten times higher compared to density accuracy calculated using calibration equations.Overall,this algorithm enhances the accuracy of cement azimuthal density evaluation,provides valuable technical support for the monitoring of cement azimuthal density in the oil and gas industry.