船舶停靠过程三维虚拟仿真分析

船舶停靠过程建模对于船舶驾驶教学具有重要的应用价值。传统的船舶停靠过程三维虚拟模型在建立的过程中复杂性较高,模型逼真度较差。为此,提出基于特征动态优化算法的船舶停靠过程三维虚拟模型建立方法。根据采集的船舶停靠过程图像特征,计算船舶动态变化中心,为船舶停靠过程三维虚拟模型提供了准确的数据基础。提取船舶停靠过程图像的特征点,建立船舶图像特征网格模型,从而实现了船舶停靠过程三维虚拟模型的构建。实验结果表明,利用该方法建立船舶停靠过程的三维虚拟模型,能够有效提高模型的逼真度,效果令人满意。     

基于ArcScene和SketchUp的流域三维模型建立

流域三维可视化是“数字流域”中的一个重要组成部分,流域三维可视化作为一种新的管理方法和技术手段在流域管理中越来越体现其重要性。本文以构建漓江流域三维可视化场景为例,提出了一种采用ArcScene和Google SketchUp软件,快速有效地构建三维流域的方法。     

利用LISP编程,在AutoCAD中实现螺纹三维仿真

本文介绍了基于AutoCAD平台,利用LISP编程,根据螺纹加工原理、三维实体造型和对象布尔运算等实现螺纹加工的三维动态仿真技术。     

Bottom-up estimation of industrial and public R&D investment by technology in support of policy-making: The case of selected low-carbon energy technologies

This paper discusses a bottom-up approach to estimate the level of R&D investment by technology in areas where data are scarce. It develops a four-step methodology for the estimation of corporate R&D investments at technology level. This approach can overcome gaps in existing data by combining publicly available information in a novel way, even though it introduces some uncertainty. This is illustrated for a set of low-carbon energy technologies that were identified as key for meeting Europe's long-term energy and climate objectives by the European Strategic Energy Technology Plan. The paper finds that the aggregated R&D investments dedicated to these technologies amounted to €3.3 billion in the EU in 2007, including public funding from European Union Member States and at EU-level, and industrial research activities from companies with headquarters registered in the EU. The results allow conclusions on the European energy research policy to be drawn, such as the dominance of industrial funds, and have provided significant input to the European policy making in this field. The paper ends with suggestions on how to further enhance the accuracy of the approach and how to widen its application to other sectors.     

三维数值模拟研究W波段折叠波导慢波结构

折叠波导以其宽频带、加工方便而成为一类重要的毫米波行波管慢波线结构,文章利用三维粒子模拟软件对某-W波段折叠波导慢波结构进行了模拟分析。对该行波管的色散特性、耦合阻抗模拟结果表明色散平坦、耦合阻抗高。非性注波互作用模拟结果表明,该管在工作频带内的连续波输出功率达到263．1W、增益为24dB。     

水力旋流器内清水流场空气柱的三维数值模拟

本文依据计算流体动力学(CFD)的计算方法,利用Fluent软件对带有空气柱的固-液分离用水力旋流器内清水流场进行了三维数值模拟研究。文章中首次采用mixture模型对空气柱进行模拟,模拟所得的流场与实测结果作对比,证明效果良好。本文的工作对进一步研究旋流器固-液分离现象提供了一定的基础和参考。     

三维虚拟仿真技术在发酵工厂设计教学中的应用优势

本文针对传统发酵工厂设计中工程图纸教学方法存在的诸多问题,提出嵌入三维虚拟仿真技术到发酵工厂设计中实现动态的、数字化的、三维高仿真教学模式,具有变被动学习为兴趣好学、在创造性活动中体现知识的价值以及易于实现开放式教学等优势,有利于全面提升教学质量,培养高素质应用型工程技术人才,促进发酵工厂设计教学改革。     

基于时域有限差分法的二维光子带隙结构的能带研究

时域有限差分法是解决Maxwell方程最常用的一种方法,在计算光子晶体能带结构的问题上,时域有限差分法可应用的结构范围更为广泛。本文用时域有限差分法分析二维光子晶体的色散特性,和参考文献的结论吻合得很好。     

水中悬浮隧道锚索在剪切流中的涡激响应

以Iwan改进的尾流振子模型为基础，给出了剪切流中水中悬浮隧道锚索横向涡激振动的工程分析方法，分析了悬浮隧道重浮比以及剪切流特性对锚索涡激响应的影响。计算结果表明，悬浮隧道重浮比的改变，使锚索各阶模态的频锁区域分布发生变化，从而改变了结构的涡激振动响应；剪切流陡度参数的增大会使锚索涡激响应的幅值减小，若使用均匀流场代替剪切流场计算悬浮隧道锚索的涡激振动，会过高估计其响应幅值。     

Artificial intelligence implication on energy sustainability in Internet of Things: A survey

The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.