为研究不同外场作用下的胆甾相液晶旋光特性，将向列相液晶TEB30A与左旋手性剂S8-11混合，制备了胆甾相液晶器件，并对其旋光性能进行了测试。实验结果显示：温度由24℃升至32℃时，胆甾相液晶的结构色由黄色转变为蓝色，Bragg反射带中心波长蓝移了97.41 nm,旋光角度减小了15.0°;电压由0 V增至7 V时，液晶织构由平面态转变为焦锥态，Bragg反射带中心波长蓝移了4.40 nm,旋光角度减小了3.9°。依据麦克斯韦方程组建立了胆甾相液晶的波动方程，并采用有限元方法对其进行数值求解。模拟计算结果显示：温度由24℃升至32℃时，旋光角度减小了14.03°;电压由0 V增至7 V时，旋光角度减小了1.62°;数值模拟与实验测量结果基本吻合。本文研究结果可为胆甾相液晶在光电调控领域的应用提供重要参考。
To investigate the optical rotation characteristics of cholesteric liquid crystals(CLCs) under different external fields, a CLC device was fabricated by mixing the nematic liquid crystal TEB30A with the left-handed chiral dopant S8-11.Experimental results revealed that as temperature increased from 24 ℃ to 32 ℃,the structural color of the cholesteric liquid crystal shifted from yellow to blue, accompanied by a 97.41 nm blue shift in the central wavelength of the Bragg reflection band and a 15.0° decrease in optical rotation angle.When the applied voltage increased from 0 V to 7 V,the liquid crystal texture transitioned from planar to focal conic state, resulting in a 4.40 nm blue shift and a 3.9° reduction in optical rotation angle.Based on Maxwell's equations, the wave equation of the CLC was established and numerically solved using the finite element method.Simulation results revealed a 14.03°decrease in optical rotation as temperature increased from 24 ℃ to 32 ℃,and a 1.62° decrease as voltage increased from 0 V to 7 V,which showed good agreement with the experimental data.The results of this study can provide valuable guidance for the application of cholesteric liquid crystals in optoelectronic modulation technologies.
拨叉作为制导火箭弹舵机的关键传动构件，其结构刚度与固有频率对火箭弹飞行控制影响显著。针对传统拨叉结构材料利用率不足及设计优化空间受限问题，开展拓扑优化设计，从而实现结构轻量化并提高固有频率。利用SoildWorks软件构建拨叉三维模型，将其导入Ansys有限元软件中开展受力分析，提取等效应力与总变形，对比初始模型是否符合拨叉使用要求。符合要求后对初始模型基于变密度法进行拓扑优化设计，与初始模型相比，在保证条件不变的情况下，优化后的模型质量减少了17.89%。对优化前后模型进行模态分析，对比优化前后的静力学特性及前3阶的模态振型，结果变形量增加了0.017 6 mm,最大应力增加了44.01 MPa,且第1、2、3阶模态均有提升，实现了拨叉优化设计的目的，为制导火箭弹零件结构设计提供思路。
As a critical transmission component of the guidance rocket's servo, the structural stiffness and natural frequency of the fork significantly impact the rocket's flight control.To address the issues of insufficient material utilization and limited design optimization potential in traditional fork structures, a topology optimization design was conducted to achieve structural lightweighting and enhance the natural frequency.A 3D model of the fork was constructed using SolidWorks software and imported into Ansys finite element software for stress analysis.Equivalent stress and total deformation were extracted to verify whether the initial model met the operational requirements of the fork.After confirming compliance, the initial model underwent topology optimization design based on variable density method.Compared to the initial model, the optimized model achieved a 17.89% reduction in mass while maintaining the same constraints.Modal analysis was performed on both pre-and post-optimization models, comparing static characteristics and the first three modal shapes.Results indicated that the deformation increased by 0.017 6 mm, the maximum stress increased by 44.01 MPa, and the first, second, and third modes all improved.It achieved the optimization objective for the fork design, providing insights for structural design of guided rocket components.
为满足高功率激光窗口片表面光洁度检测需求，设计一套基于优化YOLOv5与平行光明场成像的激光窗口片表面缺陷检测系统。系统采用460～470 nm蓝色平行光源与远心镜头结合的明场成像方案，实现无畸变成像，提升图像清晰度与缺陷识别能力。依据美国军用标准MIL-PRF-13830B构建缺陷样本数据集，采用YOLOv5算法对划痕与麻点进行分类识别。模型经5 060组样本100次训练后，精确率为0.995,召回率为0.985,mAP@0.5为0.994,mAP@0.5～0.95为0.823,实现高精度识别。系统具有较强的鲁棒性和适应性，能够有效应对不同类型的表面缺陷，具有较高的工业应用价值。未来可继续优化检测算法和数据处理，扩展系统的应用范围，满足更大规模光学元件检测的需求。
To meet the requirements for surface finish detection of high-power laser windows, a surface defect detection system for laser window based on optimized YOLOv5 and parallel light bright-field imaging was designed.A bright-field imaging scheme combining a 460～470 nm blue parallel light source and a telecentric lens was adopted in the system.Distortion-free imaging was achieved, and the image clarity and defect recognition capability were improved.A defect sample dataset was constructed in accordance with the MIL-PRF-13830B standard.The YOLOv5 algorithm was used to classify and identify scratches and pitting.After the model was trained with 5 060 samples for 100 epochs, the precision was 0.995,the recall rate was 0.985,mAP@0.5 was 0.994,and mAP@0.5～0.95 was 0.823,realizing high-precision recognition.The system has strong robustness and adaptability.It can effectively deal with different types of surface defects and has high industrial application value.In the future, the detection algorithm and data processing can be further optimized, and the application range of the system can be expanded to meet the needs of larger-scale optical component detection.
为探究古建筑火灾烟气蔓延特性，以徽派古建筑慎思堂为研究对象，采用PyroSim软件研究不同风速、风向和通风面积条件下穿堂风对古建筑火灾烟气蔓延规律的影响。结果表明：风速在2～6 m/s间增加，火灾烟气蔓延速率逐渐加快；而风速在6～9 m/s间增加，火灾烟气蔓延速率反而减慢；临界风速为6 m/s,此时古建筑火灾危险性最高；风向为正西方时，与通风路径平行，可形成稳定的穿堂风，能见度分布更加均匀；风向为西偏北10°或西偏南10°时，气流以逆或顺时针的运移模式加快或减缓火灾烟气蔓延；随着通风面积的增大，火灾烟气蔓延速率线性增大。本文的研究结果可为类似条件下古建筑火灾防控与修复保护提供参考。
To investigate the characteristics of the fire in ancient timber structures, the influence of cross ventilation on spread law of fire and smoke in the Huizhou-style heritage building “Shensi Hall” was studied using PyroSim software, whose variable factors include wind speed, wind direction, and ventilation area.The simulation results showed that the spread rate of fire and smoke increases with the increase of the wind speed within the range of 2～6 m/s, while it decreases with the increase of the wind speed when it is between 6～9 m/s.So, it has the highest fire risk at the wind speed of 6 m/s, which is the critical speed.And a due west wind direction that is parallel to the main movement path of the cross ventilation generates a stable flow of the cross ventilation and induces more uniform distribution of smoke visibility.However, the wind from 10° west-northwest or 10° west-southwest severally induces the counterclockwise or clockwise airflow patterns and increases or decreases the spread rate of fire and smoke, respectively.Additionally, the spread rate of fire and smoke also linearly increases with the increase of ventilation area.It can provide the valuable insight for fire prevention strategies and restoration practices of historical timber structures under similar conditions.
为优化采动应力监测实验教学方式，将先进的光弹技术引入采动应力监测实验教学中，介绍光弹实验系统组成、应力监测原理。以淮南矿区工程地质及开采条件为背景，设计光弹实验并进行实验教学，通过学生问卷调查和成绩对比分析教学效果。结果表明：光弹实验结果能够清晰地展示采场围岩应力分布形态与演化特征，促进学生更加深入理解采动应力形成与演化全过程。与传统实验教学方式相比，光弹实验教学更有助于学生掌握矿山压力理论知识，同时能够提高学生的创新意识，激发学生的创新兴趣，整体教学效果良好。
To optimize the experimental teaching method for mining dynamic stress monitoring, the advanced photoelastic technology was introduced into the teaching process.This approach explains the components of the photoelastic experimental system and the principles of stress monitoring.Against the background of the engineering geology and mining conditions in the Huainan Mining Area, a photoelastic experiment was designed and implemented for teaching purposes.The effectiveness of this method was evaluated through student questionnaires and a comparative analysis of academic performance.The results indicate that the photoelastic experiment clearly demonstrates the distribution patterns and evolution characteristics of stress in surrounding rock masses, enabling students to gain a deeper understanding of the entire process of mining-induced stress formation and evolution.Compared with traditional experimental teaching methods, the photoelastic approach proves more effective in helping students master theoretical knowledge of rock pressure.Additionally, it enhances innovative thinking and stimulates creative interest, resulting in an overall positive teaching outcome.
光学相干断层扫描(optical coherence tomography, OCT)具有无创、分辨率高的特点，在视网膜疾病的早期诊断中发挥了重要作用。视觉Transformer(vision Transformer, ViT)模型中传统多层感知机(MLP)模块在处理复杂医学图像时依赖于全局静态的激活函数，难以自适应地聚焦于图像中高度局部化的关键区域(如肿瘤边缘、微钙化点),导致一些细微但至关重要的结构信息在特征提取过程中被模糊化或丢失，为此引入Kolmogorov-Arnold网络(KAN)替代传统MLP,以增强模型对局部结构和非线性特征的建模能力，并与Transformer模型中的注意力机制互为补充，有效提升细粒度病灶识别效果。在由公开数据集OCT-C4扩充得到的混合OCT分类数据集上进行实验，结果表明，KAN模块对提升模型的整体性能具有积极作用，对OCT数据集的分类准确率为95.6%、精确率为95.8%、召回率为95.4%、F1分数为95.6%,优于Resnet-50和EfficientNet等主流基线模型，研究结果可为细粒度医学图像分类提供参考。
Optical coherence tomography(OCT)is a non-invasive, high-resolution imaging technique that plays a vital role in the early diagnosis of retinal diseases.In vision Transformer(ViT)model, the traditional multilayer perceptron(MLP)module relies on globally static activation functions when processing complex medical image, making it difficult to adaptively focus on highly localized critical regions—such as tumor margins and microcalcifications—in medical images.As a result, subtle yet crucial structural information may become blurred or lost during feature extraction.To address this issue, we introduce the Kolmogorov-Arnold network(KAN)to replace the conventional MLP,enhancing the model's ability to capture local structures and nonlinear features.This approach complements the self-attention mechanism in Transformer, thereby improving fine-grained lesion recognition.Experiments are conducted on a hybrid OCT classification dataset augmented from the public OCT-C4 dataset.The results demonstrate that the KAN module positively contributes to the overall performance of the model, achieving a classification accuracy of 95.6%,precision of 95.8%,recall of 95.4%,and an F1-score of 95.6% on the OCT dataset.These results outperform mainstream baseline models such as ResNet-50 and EfficientNet.The findings provide a valuable reference for fine-grained medical image classification.
针对传统后张法预应力摩阻检测中操作误差大、数据离散性高及人为因素干扰等问题，提出一种基于改进Levenberg-Marquardt(L-M)算法的摩阻系数求解方法，并开发相应的检测系统。该系统集成高精度传感器与LoRa无线通信技术，可实现多终端张拉力数据的同步采集与标准化处理，有效避免人为误差的引入，提升检测效率与数据精度。同时，改进L-M算法，通过引入自适应加权策略和基于中位数绝对偏差(MAD)的动态阈值机制，提升预应力筋与孔道壁之间的摩擦系数μ和孔道每米局部偏差对摩擦影响系数k的计算可靠性，在异常数据干扰下仍保持高精度，与传统二元回归算法相比表现出优异的抗干扰性能。试验验证结果表明，系统优化后μ和k的重复测量标准差分别从传统人工检测的0.009 17和0.001 025下降至0.004 22和0.000 1,并通过工程应用进一步验证了系统的高稳定性和可靠性，可为预应力施工质量控制提供技术支持。
To address the issues of high operational errors, data variability, and human interference in traditional post-tensioned prestress friction detection, this study proposes a method for friction coefficient calculation based on an improved Levenberg-Marquardt(L-M)algorithm and develops a corresponding detection system.The system integrates high-precision sensors and LoRa wireless communication technology, enabling synchronized multi-terminal tension data acquisition and standardized processing, effectively minimizing human-induced errors while improving detection efficiency and accuracy.The enhanced L-M algorithm incorporates an adaptive weighting strategy and a dynamic threshold mechanism based on median absolute deviation(MAD),improving the reliability of calculating the friction coefficient(μ)between the prestressing tendon and the duct wall, and the wobble coefficient(k)representing the local deviation per meter of the duct.Compared to traditional binary regression, it demonstrates superior anti-interference performance under abnormal data conditions.Experimental results show that the optimized system reduces the standard deviation of repeated measurements for μ and k from 0.009 17 and 0.001 025(manual detection) to 0.004 22 and 0.000 1,respectively.The application in engineering further validate the system's high stability and reliability, providing robust technical support for prestressed construction quality control.
针对储罐安全检测工作现场环境复杂，能够接收到的声发射信号相对较弱且存在噪声信号，从而导致无法采集到有效信号，严重影响储罐底板安全检测问题，提出一种基于声学黑洞的信号增强技术。通过分析液体中声信号的传播特性，设计并加工适用于罐壁传感器的声学黑洞结构(半径8 mm,剩余高度1 mm,幂指数2.2),利用其能量聚焦特性增强声发射信号。实验结果表明：该结构可使信号峰值频率提高1.5～2.8倍，最大幅值电压提升1.5～2.4倍，且不改变信号结构，能将部分低于检测门槛的微弱信号有效放大。研究证实，声学黑洞结构为储罐声发射检测提供新的增强路径，可应用于常压储罐安全监测。
To address the challenges of complex on-site conditions during storage tank safety inspections—where received acoustic emission signals are relatively weak and contaminated by noise, leading to ineffective signal acquisition and severely impacting the safety assessment of tank bottoms—a signal enhancement technique based on acoustic black holes is proposed.By analyzing the propagation characteristics of acoustic signals in liquids, an acoustic black hole structure(radius 8 mm, residual height 1 mm, power index 2.2) suitable for tank wall sensors is designed and fabricated.Its energy-focusing properties are used to the enhance acoustic emission signal.Experimental results demonstrate that this structure increases peak signal frequency by 1.5～2.8 times and maximum amplitude voltage by 1.5～2.4 times without altering signal structure, significanly amplifying weak signals below detection thresholds.The study confirms that acoustic black hole structures provide a novel amplification pathway for tank acoustic emission detection, applicable to safety monitoring of atmospheric storage tanks.
为了增强纤维素气凝胶对水中Cr (Ⅵ)的吸附性能，以环氧氯丙烷为交联剂，采用壳聚糖对纤维素进行氨基改性，制备改性纤维素气凝胶。通过扫描电子显微镜(SEM)、傅里叶变换红外光谱仪(FTIR)和X射线衍射仪(XRD)等对改性纤维素气凝胶进行表征；利用条件实验探究改性纤维素气凝胶吸附性能的影响因素，并对其吸附过程进行热力学和动力学分析。结果表明：改性纤维素气凝胶呈现三维多孔网状结构；在壳聚糖添加量为0.20 g/g、环氧氯丙烷用量为5 mL条件下制备的改性纤维素气凝胶对Cr(Ⅵ)具有良好的吸附性能，在溶液初始pH为2、吸附时间为240 mim、改性纤维素气凝胶投加量为50 mg时，其对Cr(Ⅵ)的吸附率达到75.58%;改性纤维素气凝胶对Cr(Ⅵ)的吸附符合Langmuir等温吸附模型，吸附过程为自发进行的吸热过程，且采用准二级动力学模型可较好描述该过程。
In order to enhance the adsorption performance of cellulose aerogel on Cr(Ⅵ) from aqueous solution, epichlorohydrin was used as a crosslinker to amino-modify cellulose by chitosan to prepare modified cellulose aerogel.It was characterized by SEM,FTIR,and XRD.Conditional experiments examined the adsorption factors, and thermodynamic and kinetic analyses were conducted.Results showed it had a 3D porous network.The aerogel prepared with 0.2 g/g chitosan and 5 mL epichlorohydrin adsorbed Cr(Ⅵ)well.At pH 2,with 50 mg aerogel, after 240 min, the adsorption rate was 75.58%.The adsorption of Cr(Ⅵ)by modified cellulose aerogel conforms to the Langmuir isotherm model, and the adsorption is a spontaneous endothermic process that can be well described by a pseudo-second-order kinetic model.
为提升新能源汽车制动能量回收效率，针对模糊控制器设计主观性强及经典粒子群算法(particle swarm optimization, PSO)易陷入局部最优的问题，提出一种基于自适应免疫粒子群算法(adaptive immune particle swarm optimization, AIPSO)的优化策略。通过融合混合初始化、动态参数调整及免疫机制，构建改进算法。结合理想制动力分配I曲线、联合国欧洲经济委员会法规线(economic commission for Europe, ECE)等分配前、后轴制动力，并设计三输入、单输出模糊控制器。利用PSO与AIPSO分别优化模糊控制器，在MATLAB/Simulink中建立整车再生制动模型进行仿真验证。结果表明：在新欧洲驾驶循环工况(new european driving cycle, NEDC)下，相较于PSO,AIPSO优化后的控制策略可使电池荷电状态(state of charge, SOC)波动幅度降低3.09%,能量回收效率提升5.22%;改进算法优化后的控制策略提高了能量回收经济性，为复杂工况下再生制动系统参数优化提供理论依据。
To enhance braking energy recovery efficiency in new energy vehicles, this study addresses limitations in conventional fuzzy controllers' subjective design and classical particle swarm optimization(PSO) algorithms' susceptibility to local optima by proposing an adaptive immune particle swarm optimization(AIPSO) strategy.The improved algorithm integrates hybrid initialization, dynamic parameter adjustment, and immune mechanisms to strengthen optimization robustness.A front-rear axle braking force distribution strategy is developed based on the I-curve and economic commision for Europe(ECE) regulations, complemented by a three-input single-output fuzzy controller.Both PSO and AIPSO are employed to optimize the fuzzy controller, with validation conducted through a MATLAB/Simulink-based regenerative braking system model.Simulation results under the new european driving cycle(NEDC) demonstrate that compared with PSO,the AIPSO-optimized strategy achieves an 3.09% reduction in state-of-charge(SOC) fluctuation amplitude and a 5.22% improvement in energy recovery efficiency.The research confirms that the enhanced algorithm significantly improves energy recovery economics while maintaining braking stability, providing theoretical guidance for parameter optimization of regenerative braking systems under complex operating conditions.