摘要：The group-contribution (GC) methods suffer from a limitation concerning to the prediction of process-related indexes, e.g., thermal efficiency. Recently developed analytical models for thermal efficiency of organic Rankine cycles (ORCs) provide a possibility of overcoming the limitation of the GC methods because these models formulate thermal efficiency as functions of key thermal properties. Using these analytical relations together with GC methods, more than 60 organic fluids are screened for medium-low temperature ORCs. The results indicate that the GC methods can estimate thermal properties with acceptable accuracy (mean relative errors are 4.45%-11.50%);the precision, however, is low because the relative errors can vary from less than 0.1% to 45.0%. By contrast, the GC-based estimation of thermal efficiency has better accuracy and precision. The relative errors in thermal efficiency have an arithmetic mean of about 2.9% and fall within the range of 0-24.0%. These findings suggest that the analytical equations provide not only a direct way of estimating thermal efficiency but an accurate and precise approach to evaluating working fluids and guiding computer-aided molecular design of new fluids for ORCs using GC methods.

摘要：The martensitic transformation temperature is the basis for the application of shape memory alloys(Smas),and the ability to quickly and accurately predict the transformation temperature of Smas has very important practical *** this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored *** modeling and feature modeling were used to predict the phase transition temperature of the shape memory *** experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)*** results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition *** this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between *** work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

摘要：The dynamic design method is essentially the evolving processes of various information, it consists of dynamic design and information construction. It is a new technology of increasing popularity. Because of the particularity and complexity of the Qinghai-Tibet Railway construction, the technology of the dynamic design and information constructing was used tentatively. Based on processes of Qinghai-Tibet Railway construction, this paper discussed and analysed the idea of dynamic design and applications. Meanwhile in allusion to arisen problems in design and construction, some principles and suggestions of reinforced measurements were put forward. Though the works of construction and design are being carried through, good results have been obtained.

摘要：针对精密位姿调整时的大转角、高分辨率、高承载能力和结构紧凑性能需求,利用压电驱动器驱动柔顺机构设计了具有力增幅特性的纯中心黏滑旋转台。单驱动器致动避免了驱动冗余,同时改变桥式驱动机构的倾斜角度可对夹紧力放大特性进行调整。首先利用混合直圆和叶型柔性铰链的柔顺机构,设计了含有一对中心对称驱动足的桥式机构,并与圆形滑块结合,在放大夹紧力的同时实现无冗余、纯中心转动。然后通过有限元仿真分析了旋转台的单步转角、力放大倍数及应力,并与理论计算结果对比。最后搭建实验测试平台,验证了所设计旋转台的性能。旋转台整体尺寸为86 mm×86 mm×32 mm,在150 V输入电压的作用下,实验测得的最大负载为9 kg,旋转台的角分辨率为0.10μrad。

摘要：针对兰州重离子研究装置(HHIRFL)荧光靶历史图像数据存储系统所产生的数据不断递增和历史数据检索速度慢的问题,构建了基于MongoDB数据库的荧光靶历史图像数据存储系统。为了能够保存和观测分析荧光靶束流图像,搭建了基于EPICS的历史数据归档系统获取荧光靶图像过程变量(PV)数据,用MongoDB数据库分片技术对所得数据进行存储,通过Django框架完成图像的转化和Web页面的实现,并在系统中应用了图像分类算法,提高了数据读写的速率。该系统在HIRFL上可以稳定获取、存储、观测荧光靶束流历史图像,为束流分析、调束工作提供了便利。

摘要：岩质边坡阶梯状破坏路径由节理和破裂岩桥组成,为了从地质力学模型试验的角度研究其破坏机制,开展底摩擦试验并着重分析岩桥的破裂机制。针对缓倾节理、陡缓倾节理阶梯状分布和缓倾节理平行分布的3种边坡模型,从岩桥破裂演化过程和位移场变化特征揭示阶梯状破坏机制。基于力学机制分析给出岩桥的破裂模式,并从现场岩体破坏、模型试验结果和PFC^(2D)数值分析等方面进行验证。结果表明:边坡阶梯状破坏为“多级锁固拉裂型”和“层间块体拉裂型”,而在细部上岩桥破裂为压剪–拉裂和拉剪–拉裂。前一种破坏位移增大区呈条带并向坡表扩张,而后一种破坏呈片状相并相连,均展现了岩桥张拉破裂和块体分裂的过程。相比于平面型滑坡,在岩桥的破裂路径、断裂性质和扩展方向上,阶梯状破坏均有所不同。研究成果可为阶梯状破坏岩质边坡的稳定性分析提供理论支撑。

摘要：为研究摩擦型高强螺栓抗剪连接的滑移行为,分析了钢结构全过程的受力和变形性能。采用简化的螺栓滑移数值计算方法,使用COMBIN39弹簧单元模拟了螺栓与盖板、芯板之间的摩擦行为以及螺杆与螺栓孔壁之间的接触挤压行为。通过ANSYS有限元软件模拟了单行四列螺栓连接抗剪滑移过程并采用试验加以验证。建模分析了三行六列螺栓群在摩擦阶段、滑移阶段和弹塑性变形阶段的连接抗剪滑移过程,总结出各行螺栓在各个阶段的传力比和芯板、盖板的应力分布规律。根据三阶段滑移过程,提出了螺栓群总滑移量的计算公式。以孔壁变形特点为依据,采用分段函数拟合出孔壁的变形-荷载曲线,并将拟合的曲线与芯板和盖板各螺栓孔壁变形平均值有限元结果进行了比对。结果表明:有限元计算的荷载-位移曲线与实测的荷载-位移曲线吻合良好,验证了有限元模型的正确性;拟合的变形-荷载曲线与有限元模拟值吻合良好;当外荷载为375 kN时,传力比最大的第1列螺栓首先开始松动,之后便出现微小滑移;当外荷载增加至905 kN时,第1列螺栓芯板位置处出现大面积塑性变形区并发生孔壁挤压破坏,可以认为芯板已经达到极限承载能力状态,但此时盖板的Von Mises应力仅为231.1 MPa,说明盖板没有进入屈服状态。研究结果可为摩擦型高强螺栓群的研究和设计提供参考。

摘要：从理论、关键技术,具体架构设计等层面研究了云边协同与区块链的融合应用。云边协同与区块链融合架构研究与设计包括了总体融合应用研究与设计、云边协同与区块链交互应用设计、基于云边协同的区块链管理功能设计、基于云边协同的智能合约管理设计、基于云边协同的区块链数据管理设计。通过研究云边协同与区块链融合的可行性和优势,设计出两者互相融合的通用性架构,该架构可以应用于智慧用电、智能网联汽车、智慧管网、工业物联网等应用场景。

摘要：针对现有花生播种机难以适应南方黏壤土作业环境及播种品种单一等问题,设计一种普适性较高的旋耕高垄单粒播种机。基于花生播种农艺要求,对播种机的关键部件进行理论分析与设计;为优选出能适用多个花生品种的排种器,以南方主要种植的花生品种‘四粒红’和‘湘花’为试验对象,以排种盘型号和排种轴转速为试验因素,粒距合格指数和破损率为评价指标,利用JPS-12型排种性能试验台开展单因素台架试验;试制2BHG-160型花生播种机样机进行田间试验。台架试验结果表明,‘四粒红’和‘湘花’播种的最佳排种盘型号为大粒盘,最佳排种轴转速为10 r/min;田间试验结果表明,‘四粒红’和‘湘花’的粒距合格指数分别为94.04和93.22,破损率分别为0.14%和0.62%,整机播种深度合格率、垄高稳定度及上沟宽稳定度分别为84%、96.69%和95.47%。机具作业性能良好,可用于南方粘壤土环境花生播种作业。

摘要：变形预测是堆石坝安全监测与健康诊断的重要手段,现有研究多根据堆石坝监测数据建立单测点预测模型,未充分考虑测点之间相关性进行整体建模,且现有模型难以对漂移数据进行长期精准预测。本文考虑堆石坝变形序列的时序依赖性和测点之间的协同相关性,提出了基于图卷积和循环神经网络、引入概率预测与全过程训练的时空融合变形预测模型。该模型首先采用图卷积网络对多测点特征进行自适应汇聚,然后利用循环神经网络中细胞状态与隐层记忆沿时间轴的传递性,实现对时空信息的挖掘与融合,最后通过线性层得到概率预测参数,提高了模型对监测数据噪声的鲁棒性。采用全过程训练方式,提高模型对影响因子与累积变形量内在关系的学习能力,实现对漂移数据的长期精准预测。最后以水布垭面板堆石坝为例,进行了模型对比实验与消融实验,介绍了该模型在堆石坝安全监测和健康诊断中的三种具体应用。结果表明,本文模型有效融合了时空信息,在预测精度方面显著高于现有模型,解决了现有模型对大坝整体变形规律学习能力差、漂移数据预测精度低的问题,可用于堆石坝变形长期预测、测点异常检测与缺损数据补全。