反相微乳液法制备陶瓷彩喷墨水(Ⅱ)

通过红外光谱仪测定两种墨水的微乳液结构。结果表明,醚氧键中的羟基与H2O分子作用后因形成氢键,而且有强烈的相互作用;正己醇分子在该反相微乳液中水分子作用很弱,而且推断它位于反相微乳液的栅状层;随着微乳液中含水量的增大,水分子O-H伸缩振动峰的强度和频率均发生变化,其吸收强度变大,峰面积增加,频率也向低频方向位移;体系中存在三种水:结合水、捕获水和自由水。并探讨了其反应机理。     

海上风机基础与塔架体系实时安全评估方法研究

海上风机所处环境恶劣,基础与塔架等支撑结构在使用阶段受到荷载和非荷载因素,会产生累积损伤和性能退化。为了实时掌握基础与塔架体系的运行状态及安全性,进行合理的检修与维护,提出了一种基于神经网络的实时安全评估方法。结果表明:结合风况、风机运行等信息,仅在风机基础及塔架关键部位设置少量监测设备即可满足安全实时评估的数据要求;考虑限值比较、单点误差分析、总体误差分析后,可对基础与塔架局部及整体安全性进行实时评价。经实例论证,预测结果与监测数据较为接近,具有较好的实用性,可为类似工程提供参考。     

板柱与梁板结构受力性能对比研究

以某工程为算例,分别选取合理板柱与梁板结构计算模型,按照相关规范进行大型广场在平时工况与战时工况顶板各构件承载力计算,并对其两种结构型式的受力性能分析对比,以总结出地下人防结构顶板的适用原则,为实际工程设计提供参考依据。     

重力坝深层抗滑稳定设计初探

针对某水库重力坝坝基地层倾角平缓(8°~15°),基岩为薄层状结构,坝基深层抗滑设计是工程关键技术,在利用抗剪断强度理论进行坝基抗滑稳定计算的基础上,通过分析比较常见的坝基基础处理措施,最终确定重力坝坝基采用坝趾处设置混凝土深齿墙措施,可同时提高坝基浅层及深层抗滑稳定安全系数。     

斜拉桥预应力混凝土索塔锚固结构受力性能分析

为了研究U形与直线预应力束混合布置索塔锚固结构的受力特性,以国内某姊妹塔斜拉桥的菱形桥塔为例,采用通用有限元程序建立索塔锚固结构的节段有限元模型,分析索塔锚固结构在预应力荷载与斜拉索水平力共同作用下的受力情况。结果表明:在索塔锚固结构中采用U形与直线预应力束混合布置能较好的满足设计要求,使锚固区整体处于较为合理的压力状态之下,除局部的应力集中外,基本消除了斜拉索作用下顺桥向塔柱的拉应力;在齿块与塔柱内壁的结合处存在应力集中现象,应当引起足够的重视,施工时应严格控制施工质量。     

框架结构护岸新技术在城市河道中的应用

好溪堰河是贯穿浙江省丽水市主城区的一条千年古河道,在河道整治过程中,受制于河道周边的密集建筑物,传统的河道护岸技术均难以同时满足水利、市政、交通及景观的多元化要求。在分析其他创新河道护岸技术特点及存在问题的基础上,提出了适用于城市河道的桩柱式、框柱式两种框架结构护岸新技术,这两种护岸在维护河道周边建筑物稳定的同时,均具有不加深河床就可拓宽河道过流断面、不减少河岸用地、保持岸路畅通、改善水质及生态效果、提高亲水性等优点,在丽水好溪堰河水系整治工程中应用较为成功。     

Photocatalysts using hexa- and octa-titanates with different tunnel space for water decomposition

Photocatalytic activities for water decomposition were examined for photocatalysts using hexa- and octa-titanates and TiO2(B) with different tunnel space in the structure. Using RuO2 as promoter, M2Ti6O13 (M = Li, Na, K, Rb) showed the stoichiometric production of Hz and O₂ except for Li, whereas H₂Ti₈O₁₇ and TiO₂(B) had very low activity producing only hydrogen as a product. The effects of promoters on Na₂Ti₆O₁₃ showed that the activity increased in the order of RuO₂ > RuO₂ + IrO₂ > IrO₂ > RuO₂ + Pt > MnO₂. These effects along with other related ones are discussed: it emerges that the presence of the tunnels is important for the achievement of high photocatalytic activity.     

An alignment-free fingerprint bio-cryptosystem based on modified Voronoi neighbor structures

Bio-cryptography is an emerging security technology which combines cryptography with biometrics. A good bio-cryptosystem is required to protect the privacy of the relevant biometric data as well as achieving high recognition accuracy. Fingerprints have been widely used in bio-cryptosystem design. However, fingerprint uncertainty caused by distortion and rotation during the image capturing process makes it difficult to achieve a high recognition rate in most bio-cryptographic systems. Moreover, most existing bio-cryptosystems rely on the accurate detection of singular points for fingerprint image pre-alignment, which is very hard to achieve, and the image rotation transformation during the alignment process can cause significant singular point deviation and minutiae changes. In this paper, by taking full advantage of local Voronoi neighbor structures (VNSs), e.g. local structural stability and distortion insensitivity, we propose an alignment-free bio-cryptosystem based on fixed-length bit-string representations extracted from modified VNSs, which are rotation- and translation-invariant and distortion robust. The proposed alignment-free bio-cryptosystem is able to provide strong security while achieving good recognition performance. Experimental results in comparison with most existing alignment-free bio-cryptosystems using the publicly-available databases show the validity of the proposed scheme.     

End-to-end scene text recognition using tree-structured models

Detecting and recognizing text in natural images are quite challenging and have received much attention from the computer vision community in recent years. In this paper, we propose a robust end-to-end scene text recognition method, which utilizes tree-structured character models and normalized pictorial structured word models. For each category of characters, we build a part-based tree-structured model (TSM) so as to make use of the character-specific structure information as well as the local appearance information. The TSM could detect each part of the character and recognize the unique structure as well, seamlessly combining character detection and recognition together. As the TSMs could accurately detect characters from complex background, for text localization, we apply TSMs for all the characters on the coarse text detection regions to eliminate the false positives and search the possible missing characters as well. While for word recognition, we propose a normalized pictorial structure (PS) framework to deal with the bias caused by words of different lengths. Experimental results on a range of challenging public datasets (ICDAR 2003, ICDAR 2011, SVT) demonstrate that the proposed method outperforms state-of-the-art methods both for text localization and word recognition.     

甲醇制烯烃流化床内流化特性的多尺度CFD模拟

近些年，我国成功开发了以煤为原料的甲醇制烯烃(Methanol to Olefins, MTO)生产工艺和技术，带动煤制烯烃产业的快速发展，保障了国家能源安全。流化床式反应器是MTO工业生产的核心反应装置，通过计算流体力学(Computational Fluid Dynamics, CFD)方法深入认知MTO流化床内的流化特性规律具有重要的意义，它可以从理论上更加准确地指导MTO流化床的优化与放大。本工作采用基于宏观?亚网格层次的气泡EMMS曳力和传统TFM耦合计算的多尺度CFD方法，对工业尺度MTO流化床内的多相流化行为进行了三维数值模拟。模拟结果表明，该多尺度CFD方法考虑了气泡结构对气?固相间曳力的影响，能较准确地预测MTO流化床内轴向颗粒浓度的“S-型”分布规律，且得到实验数据的验证；所预测的径向颗粒浓度分布呈现出经典的“环?核”分布规律，气体/颗粒的轴向时均速度在径向上的分布也与实际情况相互佐证，表明该多尺度CFD方法显著改善了基于均匀曳力的传统TFM对于宏观流场的预测能力。下一步工作将多尺度CFD方法拓展应用于MTO流化床优化放大及反应特性的研究。