ADS熔盐散裂靶中子学性能研究

与传统加速器驱动次临界系统（ADS）采用金属靶作为散裂中子靶的设计不同,加速器驱动次临界熔盐堆（AD-MSRs）采用靶堆一体的设计,直接使用燃料熔盐作为散裂中子靶。由于熔盐靶的中子学性能直接影响AD MSRs的能量放大系数、核废物的嬗变和核燃料增殖的效率,所以本研究基于MCNPX程序,详细计算了高能质子轰击氟盐和氯盐两种熔盐靶产生的散裂中子产额、散裂中子能谱、能量沉积分布以及散裂产物等中子学性能,并与液态Pb和铅铋共熔体（LBE）两种液态金属靶进行了对比。计算结果表明,熔盐靶在散裂中子产额上与液态金属靶有一定的差距,但熔盐靶内能量沉积分布的梯度较小,更有利于靶区的热量导出。与液态Pb和LBE靶相比,熔盐靶的散裂产物中包含更多的气体以及高质量数的α发射体核素。     

Tradeoff Analysis for RMS of Equipment Based Operation Availability and Life Cycle Cost

Reliability, maintainability, supportability (RMS) are the important performance indexes of equipment, which affect not only the availability, but also the life cycle cost (LCC) of the equipment. First discussed is the qualitative relation between reliability and LCC and the costs which may be used to enhance the reliability. Secondly, the factors that affect the maintainability are summarized, and if maintainability is advanced, the trend of the LCC is depicted. Thirdly, the qualitative relation between th...     

Minimum-Weight Design of Multipurpose Tie-Beam of Solid Cross-Section

The paper presents the minimum-weight design of an elastic, simply-supported member of solid cross-section that is to act as a tie for a part of its design life and as a beam for the rest, but not both at any given time. Upper bounds are prescribed on the longitudinal elongation under an axial tension and on the maximum deflection under a transverse concentrated load. The range of constraints is divided into regions of possible single-purpose minimum-weight designs. The effectiveness of optimization is judged against a prismatic bar having the same transverse stiffness.     

一种在线学习的目标跟踪与检测方法

针对现有在线学习跟踪方法缺乏监督机制的缺点,提出一种新的跟踪框架。以随机森林在线学习理论构造分类器作为目标检测器,用SURF特征点匹配方法作为目标跟踪器,跟踪过程中用可靠跟踪的结果形成对检测结果的监督机制,不对低置信度样本或错误样本进行学习,避免了分类器分类精度的逐渐下降,同时在跟踪失败时用目标检测器对目标进行重新捕获,形成跟踪、学习、检测三者有机结合的跟踪框架。对不同视频序列的测试结果表明,本文算法能有效避免目标出现较大外观变化或被大面积遮挡等复杂情况下的跟踪失败问题。     

冲击声的固有结构建模及目标识别

将统计数据驱动方法应用于冲击声的固有结构建模,研究了单个冲击信号及冲击声组的时域和频域特征提取方法,并将所提特征用于圆柱壳冲击声和公路空洞检测冲击声分类,获得了良好效果,证实了该方法用于冲击声目标分类的有效程度。     

Boolean difference techniques in fault tree analysis

For an electrical, mechanical, or hybrid system described diagramatically as a network of interconnected components, fault tree modeling of system reliability as a function of individual component failure probabilities gives rise to logic expressions obtained from the network connections. Application of the method of Boolean differences in the analysis of such Boolean expressions is discussed, and it is shown that the influence of the status of specific components on the reliability of the total system may be investigated by straightforward algebraic operations on the network failure function.     

基于差分进化算法的面目标瞄准点寻优

瞄准点的寻优选取是导弹火力筹划的核心理论问题之一。针对此问题,本文基于矩形面目标毁伤面积计算设计评价函数,利用差分进化算法原理对面目标的瞄准点坐标进行实数编码,并设计差分进化算子,建立面目标瞄准点寻优模型。通过设计面目标计算实例对模型进行验证,实验结果表明,差分进化算法的稳定性较强且具有较好的操作性,模型求得的瞄准点可信度较高,能够提升导弹打击效果并降低打击成本,为火力筹划中瞄准点寻优提供了新方法。     

CSatDTA: Prediction of Drug–Target Binding Affinity Using Convolution Model with Self-Attention

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug–target affinity is crucial. The proposed model, the prediction of drug–target affinity using a convolution model with self-attention (CSatDTA), applies convolution-based self-attention mechanisms to the molecular drug and target sequences to predict drug–target affinity (DTA) effectively, unlike previous convolution methods, which exhibit significant limitations related to this aspect. The convolutional neural network (CNN) only works on a particular region of information, excluding comprehensive details. Self-attention, on the other hand, is a relatively recent technique for capturing long-range interactions that has been used primarily in sequence modeling tasks. The results of comparative experiments show that CSatDTA surpasses previous sequence-based or other approaches and has outstanding retention abilities.     

Dempster-Shafer证据理论在目标意图预测中的应用

为了准确对目标意图进行预测,以便我方及时合理地作出战术决策,采用D-S证据理论对目标意图进行预测。首先提取出影响目标意图预测的各个态势因素,然后分析每个因素的影响效果。在此基础上建立目标意图预测的数学模型,利用D-S合成法则将所有因素的影响进行综合,并计算出各个可能命题的概率赋值并给出相应决策。最后,通过仿真实例验证了该方法在目标意图预测中的可行性和实用性。     

基于潮流跟踪的最小负荷削减费用计算

电网可靠性的经济性价值日益受到人们的重视,如何对其进行定量计算具有重要的现实意义.该文建立了体现电网可靠性经济价值的负荷削减费用模型,模型中综合考虑了节点负荷用户类型的分类和缺电损失评价率随停电时间的变化情况.在潮流跟踪法的基础上,提出了衡量负荷削减对缓解系统过负荷支路程度的经济性指标,并利用该指标对模型进行求解.算例结果验证了该方法的有效性和实用性.