避暑山庄的选址

造园首在选址。选址得当,可以事半功倍。计成在《园冶》中指出,只有“相地合宜”,才能“构园得体”。地址要好,清洁卫生,有丘有壑,草地和树林相间”。避暑山庄之所以能够在造园史上独树一帜,选址得当是其中一个重要原因。避暑山庄当时所以选择这块地方建造宫苑,除政治上的原因之外,主要是因为它具有优越的自然条件。避暑山庄的园林艺术成就,已得到世人的公认,造园家相地择址的匠心,也会给我们许多有益的启示。     

Commercial objectives,technology transfer,and systems analysis for fusion power development

Fusion is an essentially inexhaustible source of energy that has the potential for economically attractive commercial applications with excellent safety and environmental characteristics. The primary focus for the fusion-energy development program is the generation of centralstation electricity. Fusion has the potential, however, for many other applications. The fact that a large fraction of the energy released in a DT fusion reaction is carried by high-energy neutrons suggests potentially unique applications. These include breeding of fissile fuels, production of hydrogen and other chemical products, transmutation or burning of various nuclear or chemical wastes, radiation processing of materials, production of radioisotopes, food preservation, medical diagnosis and medical treatment, and space power and space propulsion. In addition, fusion R&D will lead to new products and new markets.Each fusion application must meet certain standards of economic and safety and environmental attractiveness. For this reason, economics on the one hand, and safety and environment and licensing on the other hand, are the two primary criteria for setting long-range commercial fusion objectives. A major function of systems analysis is to evaluate the potential of fusion against these objectives and to help guide the fusion R&D program toward practical applications. The transfer of fusion technology and skills from the national laboratories and universities to industry is the key to achieving the long-range objective of commercial fusion applications.     

机器人三维路径规划问题的一种改进蚁群算法

本文研究移动机器人三维空间路径规划问题,针对三维空间的复杂地形特点,提出了一种基于改进蚁群算法的路径规划算法。文中首先描述了一种简单有效的环境建模方法,然后给出了算法在信息素呈现、路径点选取、信息素更新以及启发式函数设计等方面的改进方法。仿真结果证明了算法的可行性和可靠性。     

未知环境下基于约束点的移动机器人路径规划

针对未知环境中障碍物种类多样性和位置不确定性的特点,提出了基于约束点的路径规划方法。首先对机器人在未知环境中检测到的局部障碍物信息进行分类和几何特征属性描述,得其约束点信息,然后引入改进后的A*算法,将其搜索范围局限于约束点上,计算约束点的评价函数值后得到子目标点,机器人到达子目标点后,若陷入死区,则采取回溯路径策略,重新选择子目标点,否则根据该点所属的障碍物种类采取跨越或绕行避障策略,最后移动机器人在未知环境中顺利到达目标点。仿真研究说明本文提出的路径规划方法具有可行性和有效性。     

步进电机S曲线精确控制的研究与验证

针对生产中对步进电机运行时间和距离有精确要求的常见工况,设计一套步进电机S曲线控制算法,根据不同的运行要求灵活设定运动过程,设定较少参数即能规划整个运动路径,达到理想的运动效果。设计新型余弦S曲线,搭建MATLAB/Simulink仿真控制模型和硬件测试系统进行仿真和试验验证。结果显示电机实际加减速过程运行平滑,起步稳定振动小,设定参数下可以精确运行,与直接起停相比,运行效果有很大改善。新型余弦S曲线已在全自动号码机项目中得到实际应用。     

高温混合障碍空间中的移动机器人路径规划

为了解决高温场景中移动机器人全局路径规划所面临的安全与效率问题,提出高温热源虚拟障碍的定义,建立混合障碍空间模型,将高温场景中的路径规划问题转化为高温混合障碍空间中考虑路径温度代价和长度代价的多目标优化问题. 改进NSGA-Ⅱ算法,通过选取优秀非可行解扩展种群,提高了种群多样性和进化效率,提出新的交叉和变异概率计算方法. 根据种群进化进程和个体代价函数值调整概率,实现了种群前期搜索能力和后期收敛性的平衡. 仿真所得的最优路径结果表明,该改进算法的路径长度代价虽然比原算法和其他改进算法略有增加,但温度代价大幅降低,更有效地避免了陷入局部最优.     

Pathways to eliminate carbon emissions via renewable energy investments at higher education institutions

Higher education institutions are among the many public and private sector entities that have committed to long-term sustainability goals in response to the threat of climate change. A key challenge for these institutions is establishing a commitment to make targeted investments in renewable energy technologies in support of emissions reduction goals. Such strategies require a vision to simultaneously coordinate strategic investments in renewable energy technologies with tactical operational decisions to achieve the desired benefits. In this paper, we formulate and solve a least-cost renewable energy capacity investment planning model to determine pathways to achieve emissions reduction strategies. Specifically, we apply our model to Rutgers University to evaluate its target of 100 % carbon neutrality. Using these insights, we share recommendations on how these strategies can be executed. This research serves as a springboard for administrators to assess and deploy their emissions reduction strategies, while ensuring system and financial constraints are satisfied.     

Neural network-based control for the fiber placement composite manufacturing process

At McDonnell Douglas Aerospace (MDA), an artificial neural network-based control system has been developed and implemented to control laser heating for the fiber placement composite manufacturing process. This neurocontroller learns the inverse model of the process on-line to provide performance that improves with experience and exceeds that of conventional feedback control techniques. When untrained, the control system behaves as a proportional-integral (PI) controller. However, after learning from experience, the neural network feedforward control module provides control signals that greatly improve temperature tracking performance. Faster convergence to new temperature set points and reduced temperature deviation due to changing feed rate have been demonstrated on the machine. A cerebellar model articulation controller (CMAC) network is used for inverse modeling because of its rapid learning performance. This control system is implemented in an IBM-compatible 386 PC with an A/D board interface to the machine. Work supported by the McDonnell Douglas Independent Research and Development Program Export Authority: 22CFR 125.4(b)(13)     

基于操纵平稳性的液压挖掘机轨迹规划方法

以既能达到良好的轨迹规划精度,又有优良的操纵平稳性为目标,提出了一种挖掘机器人的智能轨迹规划方法.以挖掘姿态角为优化变量;油缸进程和加速度梯度为双目标;位置盲角和最佳切削范围为约束建立优化数学模型,采用遗传算法寻找最优值.对3种规划策略：被动修正法、主动调整法和智能规划法进行了行程和速度梯度对比,结果表明,采用优化规划方法可以大幅减少液压系统冲击和振动,使挖掘机操纵更加平稳.     

在线监测结晶器调宽换向阀阀芯卡阻方法的实现

对某炼钢厂铸机结晶器在线调宽液压系统的工作原理进行了分析,并重点分析了调宽过程中换向阀阀芯卡阻的问题,针对该问题对其液压系统进行了改进,改进后可以在线监测换向阀阀芯是否卡阻。该改进的实施在减少结晶器在线调宽时发生漏钢故障方面起到了重要作用。