梁结构振动支承约束反力控制

支承或连接构件对梁结构的动力学性能有至关重要影响,必须保证其在振动过程中不发生破坏或者失效。通过合理设计和布局附加弹性支承可以实现对这些重要连接构件所承受约束反力的控制。应用微分变换法推导含附加支承的梁结构支承约束反力及其对于附加支承位置和刚度的灵敏度表达式,并通过优化设计附加支承位置和刚度实现具有弹性约束端的简支梁结构各支承约束反力的平衡,可提高结构的动力学性能。     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。     

基于有限元的区域分解方法在永磁聚焦系统仿真中的应用

随着计算机技术以及并行求解技术的发展,区域分解方法越来越多地应用于计算电磁学的各个领域.针对微波管中的永磁聚焦系统仿真,该文提出一种基于有限元的非重叠区域分解方法,其引入一种新型传输条件,并采用内罚的方式推导出有限元弱形式.该区域分解法的最大优势是不需要引入多余的未知量,并且最终集成的有限元矩阵满足对称正定性,适合采用预处理共轭梯度法进行矩阵方程的求解.该文仿真了多个微波管永磁聚焦系统,并与商业软件Maxwell进行了详细的对比,结果表明所提出的区域分解方法和Maxwell精度相当,却拥有着更加优越的计算性能.     

一种大量元素水溶肥料的制备及其在玉米上的喷施效果

根据玉米需肥特性设计氮磷钾比例,制备了含中微量元素的大量元素水溶肥料,产品氮、磷、钾比例为2∶1∶4,属于高钾中氮低磷型.在河北省安平县前子文村和浙江省新昌县孟家塘村玉米上开展了叶面喷施试验.结果表明:玉米生物学性能得到改善,玉米产量、出籽率、百粒重与容重得到提高;与空白对照相比,平均增产率为5.45％,平均纯增收896.40元/公顷,平均产投比为5.43∶1.     

The surface carboxyl group of carbonaceous microspheres effects on the synthesis and structure of SiOC ceramics

In this study, C/SiOC and C/SiO₂ composites were prepared by using carbonaceous microspheres with different surface functional groups. Carbonaceous microspheres based on hydrothermal reaction of glucose contains hydroxyl group, while the surface carboxyl group increases after NaOH etching. The hydroxyl group increases the oxygen-enriched structural units of SiOC ceramics, and the C spheres are closely enwrapped in SiOC matrix after pyrolysis at 900 °C. However, the interfacial reaction of surface carboxyl with Si–OH results in the formation of cristobalite SiO₂, and C spheres are not only encased inside the SiOC matrix, but also dispersed outside of SiOC ceramics. After removal of C via calcination at 500 °C for 5 h, C/SiOC and C/SiO₂ composites are transformed into amorphous SiO₂ and cristobalite SiO₂, respectively. The thermogravimetric analysis indicates the oxidation resistance of SiOC is superior to that of C and SiO₂.     

Preparation and antifouling performance of thin inorganic ultrafiltration membrane via assisted sol-gel method with different composition of dual additives

A novel TiO₂ thin film was prepared on the ceramic hollow fiber by the sol-gel method using poly(vinylpyrrolidone) (PVP) and polyvinyl alcohol (PVA) as additives. SEM images verified the formation of TiO₂ layer with various thickness using different composition of titania sols. The effect of the PVP and PVA contents on the TiO₂ sol properties, the separation and the antifouling performance of the ultrafiltration membranes were investigated thoroughly. When the contents of PVP and PVA were 1.0 wt% and 0.8 wt%, respectively, the resultant membrane showed a thickness of 0.55 μm with a pure water flux of 255 L m^?2 h^?1. In addition, the adherent foulant bovine serum albumin was applied to evaluate the antifouling performance. During the three fouling-recovery cycles, the flux recovery ratio and the flux decay ratio maintained about 99% and 30%. The BSA flux and rejection were still 169 L m^?2 h^?1 and 96.9% after the cycles, indicating a superior antifouling property.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

One-Dimensional Deep Convolutional Neural Network for Mineral Classification from Raman Spectroscopy

Neural Processing Letters - Raman spectroscopy is often used for the composition determination and rapid classification of materials because it can reflect the molecular information of materials....