Updated Lagrangian Particle Hydrodynamics (ULPH)Modeling of Natural Convection Problems

Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat transfer,climate,and fluid mixing in industrial processes.This work aims to use the Updated Lagrangian Particle Hydrodynamics(ULPH)theory to address natural convection problems.The Navier-Stokes equation is discretized using second-order nonlocal differential operators,allowing a direct solution of the Laplace operator for temperature in the energy equation.Various numerical simulations,including cases such as natural convection in square cavities and two concentric cylinders,were conducted to validate the reliability of the model.The results demonstrate that the proposed model exhibits excellent accuracy and performance,providing a promising and effective numerical approach for natural convection problems.

Asymptotic solution of a wide moving jam to a class of higher-order viscous traffic flow models

The boundary-layer method is used to study a wide moving jam to a class of higher-order viscous models. The equations for characteristic parameters are derived to determine the asymptotic solution. The sufficient and essential conditions for the wide moving jam formation are discussed in detail, respectively, and then used to prove or disprove the existence of the wide moving jam solutions to many well-known higher-order models. It is shown that the numerical results agree with the analytical results.

Solitary wave solutions to higher-order traffic flow model with large diffusion

This paper uses the Taylor expansion to seek an approximate Korteweg- de Vries equation （KdV） solution to a higher-order traffic flow model with sufficiently large diffusion. It demonstrates the validity of the approximate KdV solution considering all the related parameters to ensure the physical boundedness and the stability of the solution. Moreover, when the viscosity coefficient depends on the density and velocity of the flow, the wave speed of the KdV solution is naturally related to either the first or the second characteristic field. The finite element method is extended to solve the model and examine the stability and accuracy of the approximate KdV solution.

Analytical Higher-Order Model for Flexible and Stretchable Sensors

The stretchable sensor wrapped around a foldable airfoil or embedded inside of it has great potential for use in the monitoring of the structural status of the foldable airfoil.The design methodology is important to the development of the stretchable sensor for status monitoring on the foldable airfoil.According to the requirement of mechanical flexibility of the sensor,the combined use of a layered flexible structural formation and a strain isolation layer is implemented.An analytical higher-order model is proposed to predict the stresses of the strain-isolation layer based on the shear-lag model for the safe design of the flexible and stretchable sensors.The normal stress and shear stress equations in the constructed structure of the sensors are obtained by the proposed model.The stress distribution in the structure is investigated when bending load is applied to the structures.The numerical results show that the proposed model can predict the variation of normal stress and shear stress along the thickness of the strain-isolation（polydimethylsiloxane）layer accurately.The results by the proposed model are in good agreement with the finite element method,in which the normal stress is variable while the shear stress is invariable along the thickness direction of strain-isolation layer.The high-order model is proposed to predict the stresses of the layered structure of the flexible and stretchable sensor for monitoring the status of the foldable airfoil.

Robust Adaptive Gain Higher Order Sliding Mode Observer Based Control-constrained Nonlinear Model Predictive Control for Spacecraft Formation Flying

This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.

兼顾能力与知识状态的Higher-Order CD-CAT选题方法

Higher-order CD-CAT的选题方法是传统单目标(即只对知识状态自适应)选题方法,这将导致被试能力的测量精度不高.基于此,在高阶模型和PWKL选题方法的框架下,该文开发了适用于Higher-order CD-CAT的新选题方法,该方法在选题时能同时兼顾能力和知识状态.实验结果表明:与传统选题方法相比,新选题方法的能力和知识状态估计精度都更高,并且在题库安全性上也具有明显的优势.

HIGHER ORDER BOUSSINESQ-TYPE EQUATIONS FOR WATER WAVES ON UNEVEN BOTTOM

Higher order Boussinesq-type equations for wave propagation over variable bathymetry were derived. The time dependent free surface boundary conditions were used to compute the change of the free surface in time domain. The free surface velocities and the bottom velocities were connected by the exact solution of the Laplace equation. Taking the velocities on half relative water depth as the fundamental unknowns, terms relating to the gradient of the water depth were retained in the inverse series expansion of the exact solution, with which the problem was closed. With enhancements of the finite order Taylor expansion for the velocity field, the application range of the present model was extended to the slope bottom which is not so mild. For linear properties, some validation computations of linear shoaling and Booij' s tests were carried out. The problems of wave-current interactions were also studied numerically to test the performance of the enhanced Boussinesq equations associated with the effect of currents. All these computational results confirm perfectly to the theoretical solution as well as other numerical solutions of the full potential problem available.

Sliding Mode Control Design via Reduced Order Model Approach

This paper presents a design of continuous-time sliding mode control for the higher order systems via reduced order model. It is shown that a continuous-time sliding mode control designed for the reduced order model gives similar performance for thc higher order system. The method is illustrated by numerical examples. The paper also introduces a technique for design of a sliding surface such that the system satisfies a cost-optimality condition when on the sliding surface.

Opti mal higher order learning adaptive control approach for a class of SISO nonlinear systems

In this paper, an optimal higher order learning adaptive control approach is developed for a class of SISO nonlinear systems. This design is model-free and depends directly on pseudo-partial-derivatives derived on-line from the input and output information of the system. A novel weighted one-step-ahead control criterion function is proposed for the control law. The convergence analysis shows that the proposed control law can guarantee the convergence under the assumption that the desired output is a set point. Simulation examples are provided for nonlinear systems to illustrate the better performance of the higher order learning adaptive control.

Influence of higher-order ionospheric delay correction on GPS precise orbit determination and precise positioning

At present, Global Navigation Satellite Systems（GNSS） users usually eliminate the influence of ionospheric delay of the first order items by dual-frequency ionosphere-free combination. But there is still residual ionospheric delay error of higher order term. The influence of the higher-order ionospheric corrections on both GPS precision orbit determination and static Precise Point Positioning（PPP） are studied in this paper. The influence of higher-order corrections on GPS precision orbit determination, GPS observations and static PPP are analyzed by neglecting or considering the higher-order ionospheric corrections by using a globally distributed network which is composed of International GNSS Service（IGS） tracking stations. Numerical experimental results show that, the root mean square（RMS） in three dimensions of satellite orbit is 36.6 mme35.5 mm. The maximal second-order ionospheric correction is 9 cm, and the maximal third-order ionospheric correction is 1 cm. Higher-order corrections are influenced by latitude and station distribution. PPP is within 3 mm in the directions of east and up. Furthermore, the impact is mainly visible in the direction of north, showing a southward migration trend, especially at the lower latitudes where the influence value is likely to be bigger than 3 mm.

Higher-Order Squeezing for Atomic Dipole of a Three-Level Atom in the Kerr-Like Medium Cavity Fields

In this paper, evolution of the higher order squeezing for atomic dipole of three level atom in the Kerr like medium is investigated. The atom discussed has two configurations and is driven by the single mode coherent state field. Our results show that the squeezing effects are clearly influenced by nonlinear parameters, the initial atom state and the detuning.

人机争论探究法:一种争论式智能会话机器人支持的学生高阶思维能力培养模式探索

大量学生利用生成式人工智能生成作业,导致了学生高阶思维能力难以有效培养。在人机会话中嵌入“争论噪音”,将是解决这一问题的可能途径。研究采用准实验研究设计,基于高阶思维、建构主义和争论学习理论,利用文心一言、学习分析和腾讯QQ等技术工具,开发了争论式智能会话机器人,构建了人机争论探究法教学模式。结果表明,实验组的学习成绩、批判性思维能力、问题解决能力和学习态度显著优于对照组,但是创新能力效果不显著。为提高人机争论学习效果,教师需要构建特定的高阶思维学习支架,优化人机争论学习的算法机制,培养学生的人机争论素养,研制师生机三元协同争论机制。

用T4C模式培养高阶能力:对杜威教学法的重建

约翰·杜威的五步教学法在教育领域具有重要意义。本研究重新审视了杜威的五步教学法,强调该教学法忽视的杜威哲学中的要素:民主、共同体中的交流与合作、对工具的使用、对结果的反思,以及最终作品的产生和共同体的改善。本文通过深入研究杜威著作,结合其中蕴含的其他重要要素提出了T4C模式。T4C模式强调个体的探究性学习(C1代表批判性思维和问题解决,杜威称之为反思性思维或实践)是在共同体中利用工具(Tools,如概念、技术等)以合作(C2)和交流(C3)的方式开展的。这种探究性学习的预期结果是获得创造性的新体验和新工具(C4)。T4C模式为现代社会所迫切需要的工具使用能力、批判性思维、交流能力、合作能力和创新能力等高阶能力,提供了培养框架,其本质在于用高阶能力培养高阶能力,有助于实现杜威社会政治理想中民主与教育的根本关联。

智能群体多维感知机器人支持的人机协同研学教学模式--以“孔子”大语言模型会话机器人的研发与教学为例

在大语言模型教育应用中,人机会话反馈形式单一问题一直未得到较好解决,这严重影响了学生的高阶思维能力培养。开发具有智能群体多维感知能力的会话机器人,是解决这一问题的重要途径。为此,研究者以群体感知、同伴反馈和研究性学习理论为基础,利用文心一言、飞书开发平台和学习分析等技术,开发了智能群体多维感知会话机器人“孔子”,构建了人机协同研学教学模式。教学实验以“现代教育技术应用”课程为教学内容,采用准实验研究设计,邀请数学专业学生参与实验。结果表明,与直接使用文心一言的教学相比,人机协同研学教学模式能显著提升学生的问题解决能力、批判性思维能力、创新能力和外在学习动机,但对学习绩效、内在动机和协作学习能力效果欠佳。为了提高教学效果,研究者需提高多维感知评价精准性、感知维度全面性、情境学习多样性和教师教学技能。

湿热环境下多孔功能梯度圆管的非线性弯曲行为

圆管作为重要的工程结构,广泛应用于各个领域,其几何特征特殊,传统的梁理论不能满足其内外表面切应力为0的边界条件,采用合适的梁理论对其进行研究至关重要.文章采用一种修正的高阶剪切变形梁理论,研究了湿热环境下多孔功能梯度圆管的非线性弯曲行为.考虑材料物性与温度相关,基于修正的高阶剪切变形梁理论和von Kármán非线性理论,利用最小势能原理,建立了多孔功能梯度圆管的非线性弯曲控制方程,采用二次摄动法对控制方程进行求解,通过数值算例讨论了孔隙分布模型、孔隙率、梯度指数、内半径、湿度和温度对多孔功能梯度圆管非线性弯曲行为的影响.提出了针对湿热环境下多孔功能梯度圆管的非线性弯曲行为分析方法,得到了该问题的半解析解,将为优化多孔功能梯度圆管的结构和材料参数提供理论依据.结果表明:当孔隙率较大时,非均匀孔隙分布模型比均匀孔隙分布模型的多孔功能梯度圆管具有更好的抗弯曲变形能力,因此在实际轻量化设计过程中,孔隙分布应优先采用非均匀分布模型.

6G数字孪生网络分布式架构及关键技术

面对新一轮科技与产业变革,新型信息领域创新性技术正在不断脱颖而出,以数字孪生等为代表的新型技术正在为6G网络的发展打开新的格局。数字孪生作为支撑网络统一规划、编排和管理的发展范式,是赋能6G演进的重要技术方向。文章深入分析数字孪生网络的现状和发展态势,提出面向6G的数字孪生网络分布式架构体系,并针对数据、建模和编排预验证三大核心技术进行详细研究,提出创新性的解决方案,可有效应对数字孪生网络面临的关键挑战。

不同扩散成像模型在子宫内膜癌中的研究进展

扩散加权成像(DWI)是一种无创性的功能MRI技术,是子宫内膜癌(EC)术前诊断及分期的重要检查手段。体素不相干运动成像(IVIM)、扩散峰度成像(DKI)、分数阶微积分(FROC)模型、连续时间随机游走(CTRW)模型等多b值扩散成像技术目前亦用于EC的诊断及评估。就不同扩散成像模型在EC中的研究现状进行综述,以期为EC病人的精准医疗提供更多依据。

股指预测的创新深度学习策略:Transformer 模型与GRU融合及其变体的效能探究

随着金融市场的不断发展和全球经济的变化,准确预测股市指数成为投资者和决策者关注的焦点之一。本文旨在探讨深度学习神经网络中的Transformer模型及其注意力机制在金融指数预测中的应用。通过摒弃常规的控制变量设计,转而采用基于历史股指数据的高阶自回归模型,本文创新性地提出了三种Transformer模型的变体:Multi-attention Transformer、GRU Transformer、Attention-Free Transformer,并对它们在单步选代预测和多步一次预测两种方式下的表现进行比较。实证分析基于2000年1月1日至2024年3月11日的上证指数日度数据,通过将数据扩充和标准化,利用Python进行处理。结果显示:GRU Transformer模型结合单步选代预测在测试集上的平均均方误差最低,为0.00041,且在参数数量和运行时间上均表现优异,表明其在预测准确性、参数效率和运行时间方面具有显著优势。本文的创新点包括:采用基于历史时间序列数据的高阶自回归模型简化模型结构,保持预测准确性;提出并验证了三种Transformer模型变体在金融时间序列预测中的有效性;比较了单步选代预测和多步一次预测两种方式的组合效果。本文研究为金融市场的分析和预测提供了新的视角和方法,未来研究可以进一步验证模型的有效性并探索其他潜在的改进策略。

指向高阶思维培养的PBL学习活动模型设计研究

随着人工智能技术的快速发展,高阶思维能力成为个体竞争力的关键。基于问题的学习(PBL)作为一种有效的教学方法,旨在通过引导学生主动探索、合作与交流,培养其问题解决能力、创新思维和自主学习能力。然而,当前PBL实践研究对高阶思维的影响研究不足。深入分析高阶思维及问题解决理论,构建面向高阶思维培养的学生问题解决能力模型。通过探索数字化学习中的自主、探究、合作途径,为PBL教学实践提供理论支持和实践指导,旨在培养具备高阶思维能力的创新人才。

可解释的局部和全局对比多行为推荐算法

针对传统的多行为推荐模型无法高效学习异构信息网络的复杂结构以及缺乏可解释性的问题,提出一种多行为推荐模型,即可解释的局部和全局对比多行为推荐。运用一种被广泛应用于提取全局结构的元路径视图从特定的语义角度捕获每个节点之间的特征。设计一个能捕获局部特征和元路径之间的交互信息的超元路径图来捕获多个元路径之间的交互信息,区分不同用户面对不同类别物品的不同行为模式。采用一种异质性可解释对比学习,确定行为类型的重要性,得出更加优质的正负样本进行对比。在两个公共数据集上的实验中,所提模型优于主流先进推荐模型。