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关键词： 大跨径   连续桥梁   施工   悬臂   张拉   线形控制  

摘要： 为了系统提升大跨径连续桥梁的施工质量与安全控制水平,展开大跨径连续桥梁施工技术研究。通过介绍桥梁工程的概况、设计标准与施工工艺设计,分析钢托架及钢支墩安装、上部结构悬臂浇筑、挂篮悬臂作业、预应力智能张拉与线形控制等关键技术的实施要点,提出相应的施工控制方法。研究结果表明:采用对称安装与预压技术能有效保障临时支撑体系的稳定性,结合智能张拉与动态线形监控可显著提高预应力施加精度与成桥线形平顺度,最终确保合龙段高差与结构内力状态符合设计要求,为同类桥梁工程提供了重要的技术参考。

关键词： 分段函数   动区间   数形结合   换元法   求解策略   方程解判定  

摘要： 分段函数动区间问题因参数变化导致函数性质与方程解情况复杂,解题难度大.本文聚焦数形结合与换元法,探索其在该类问题中的应用:通过绘制分段函数图像,分析参数对单调性、零点个数的影响;用换元法拆解嵌套函数方程,结合图像确定实根个数;对典型方程观察图像交点判断解的情况.两种方法有效降低求解难度,准确判定解的个数与参数范围,形成标准化求解框架,为解题提供指导.

关键词： 数学学科核心素养   高中数学   课堂教学设计  

摘要： 随着数学学科核心素养成为高中数学课程改革的核心,如何通过课堂教学设计落实这一素养成为关键问题。本文先明确数学学科核心素养是学生应具备的与数学相关的思维品质和关键能力,包括数学抽象、逻辑推理等素养,阐述其作为教学导向及高考考查重点的重要地位;进而提出以学生为中心、情境创设、多元评价的教学设计原则;最后以“三角函数的概念”为例,从教材、学情分析到教学目标、重难点设定,再到具体教学过程设计,为教师课堂教学提供理论支撑和实践参考,助其落实核心素养培养目标,提升教学效果。

关键词： 排种器   图像拼接   粒距   计算机视觉   特征提取   特征匹配  

摘要： 针对传统田间作业人工检测粒距费时费力且精度不高的问题,提出了一种基于图像特征检测和连续图像动态拼接的计算机视觉检测方法,能够较为准确、高效地在排种试验台上检测粒距。根据种子纹理特征,选取多张排种图像,分别使用SIFT、ORB和SURF 3种算法对排种图像进行特征提取;通过试验比较暴力匹配和FLANN匹配两种算法对于相邻两帧排种图像的拼接时间,选定了FLANN特征匹配算法作为排种图像拼接的方法,与传统的基于工业相机帧率和种床带速度的拼接方法相比,克服了种床带速度不稳定带来的图像重叠或缺失的问题;利用种子轮廓的凸包缺陷分割种子,能够较好地分开图像中粘连的种子,再利用轮廓点求出种子的形心(种子中心点)坐标,进而求出粒距。在排种器试验台上进行试验,结果表明:在不同的种床带速度(模拟田间作业速度)下,该方法均能够很好地检测出粒距,系统检测平均误差约为3 mm。

关键词： 高阶思维   数列   核心素养  

摘要： 高阶思维是建立在较高认知水平层次上的心智活动或认知能力.它是落实学科核心素养的有效载体,是培养新时代创新型人才的关键内核,也是助力学生深度学习的关键.本文以苏教版高中数学“数列”章节为例,通过“创设真实情境,搭建思维脚手架”“问题引领,点燃思维火花”“建构知识,完善认知结构”等教学手段,探讨培养学生高阶思维发展的教学路径和策略.

关键词： Turbulence control   Boundary layers   Drag reduction   Riblets  

摘要： Direct numerical simulations of turbulent boundary layers over two types of discontinuous converging and diverging riblets are performed to validate their drag reduction performances and investigate their impacts on turbulence statistics and coherent structures. To suppress the total drag increases in the diverging region of traditional converging and diverging riblets (T-riblets), we design new converging and diverging riblets (N-riblets) with the heights gradually decreasing from the convergence line to the diverging line. Results show that both riblet configurations reduce the skin-friction drag, but the pressure drag is increased. The N-riblets are able to relieve the net drag increase from 7.42% to 0.93%, suggesting their potential in reducing the total drag. Both the discontinuous converging and diverging riblets cause the generation of large-scale secondary flows that originate from the ribbed walls and persist in the downstream wakes over the smooth walls. Their impacts on the time-averaged flow fields and Reynolds stresses are shown to be different between the T- and N-riblets. Moreover, two-point correlations of streamwise velocity fluctuations are calculated to show their modifications on coherent structures, providing more insights to explain the different impacts of T- and N-riblets on the fluid dynamics over the ribbed walls and in the downstream wakes.

关键词： Transfer-function noise model   Autoregressive moving average model   Groundwater   Lysimeter   Nonlinear model  

摘要： The quantification of groundwater recharge processes is very crucial for sustainable groundwater resources management across the globe. However, the complexities of meteorological dynamics make it difficult to quantify short-term recharge flux. In this study, nonlinear transfer-function noise (TFN) models are applied to predict recharge and quantify groundwater levels. A nonlinear model to estimate groundwater recharge is established with a TFN model. The model is then compared with a traditionally applied linear model. An autoregressive moving average (ARMA) model was used to accurately simulate parameter unreliability and to estimate confidence intervals of simulated groundwater recharge. Groundwater level observations are used to calibrate the models at the Pakistan Council of Research in Water Resources (PCRWR) hydrological research station in Mughalpura, Lahore. The nonlinear root zone model was greatly superior to the linear model for the estimation of groundwater levels. The annual groundwater recharge simulated by using the nonlinear model is in a reasonable range compared to lysimeter observations. Similarly, shorter timescales of groundwater recharge (10-day intervals) computed by the nonlinear root zone model also agree reasonably well with lysimeter observations. The approach adopted in this study requires only a limited groundwater level, precipitation, and potential evaporation data.

关键词： Stiffness   Short fiber reinforced composite   Orientation distribution function   Orientation tensor  

摘要： This work analytically formulates the effective stiffness of arbitrarily misaligned short fiber reinforced composite (SFRC) by two approaches based on orientation distribution functions (ODF) and orientation tensors (OT) of the fibers, respectively. It is found that the original OT approach in the literature would yield unreasonable effective stiffness of the SFRC with anisotropic matrix, which could be modified by introducing an auxiliary fiber volume fraction that is related to the interactions between the fibers and matrix. By validating with experimental results of the SFRC with isotropic matrix, the modified OT approach could yield better agreement than the original OT approach. More importantly, for the SFRC with anisotropic matrix, the unreasonable prediction of the original OT approach is rectified in the modified OT approach by comparing with finite element results. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(OT)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)OT(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)-(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)OT(sic)(sic)(sic)(sic)(sic)OT(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). (sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)OT(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)OT(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

关键词： Extreme learning machine (ELM)   Cascade computing architecture   Linear/nonlinear partial differential equation   Ill-conditioning  

摘要： Extreme learning machine (ELM) is a single-hidden-layer feedforward neural network trained using the Moore-Penrose pseudo-inverse. While faster than backpropagation-based networks, ELM suffers from ill-conditioning due to random hidden layer coefficients. This causes the solution that tends to prioritize large components, making it challenging to accurately represent smaller components, thereby hindering its application in solving complex problems. To address this, we propose residual cascade ELM (RC-ELM), a cascaded ELM architecture that mitigates ill-conditioning by passing residuals through multiple ELM blocks. Each block employs regularized singular value decomposition, and the final solution accumulates components obtained from each block. It achieves a cascading representation of the solution at different scales under limited machine precision, alleviating the impact of ill-conditioning on the solution. We applied RC-ELM to solve various partial differential equations (PDEs), including Helmholtz, diffusion, and Korteweg-de Vries equations. Numerical results show that RC-ELM significantly improves accuracy over classical ELM, with the minimum achievable solution error decreasing by about more than four orders of magnitude and approaching machine precision. Also, the method exhibits high spectral convergence and requires only one expensive pseudo-inverse computation, keeping additional costs minimal compared to classical ELM. Comparative analysis with Chebyshev spectral methods further highlights its potential for solving complex PDEs.

关键词： Continuous fiber-reinforced polymers   Topology optimization   Fiber distribution optimization   Thermal-mechanical coupling   Continuous fiber path planning  

摘要： Continuous fiber-reinforced polymers (CFRPs) have been extensively utilized in aerospace industries, making it imperative for CFRP structural optimization to consider the effects of extreme service environments. In this paper, a thermal-mechanical coupling concurrent topology and fiber distribution optimization (TM-CTFDO) method is proposed, specifically tailored for CFRP structures subjected to extreme environmental conditions. The mapping relationships between fiber design variables and material properties are deduced based on the rule of mixture to realize the analysis of thermoelastic CFRP structures. The integrated optimization model for CFRP structures is established with minimizing structural compliance, adhering to the volume constraints of structural and fiber under mechanical and temperature loads. Sensitivity analysis and optimization solution are realized by adopting the adjoint method and the method of moving asymptotes, respectively. This approach culminates in the determination of the optimal topology, fiber orientation, and content. In the post-processing phase, a fiber path planning algorithm is investigated to achieve the continuous fiber path based on the optimization results, which also effectively controls the distribution of dense and sparse fiber. Several examples under uniform and varying temperature fields are provided to verify the effectiveness of the TM-CTFDO method. The influence of temperature and mechanical loads on the optimization results is discussed, which will provide guidance on CFRP structural design and fiber path planning under thermal-mechanical coupling.