优化GD-模糊规则的滑坡预报模型研究

为了提高滑坡灾害预报准确率，改善传统的滑坡监测和预报中存在的参数选取困难及模糊控制系统作为预报模型精确度不高的问题，首先采用山体结构稳定性分析法进行滑坡灾害参数的选取，得出降雨量、含水率、土压力及岩土表面位移增量作为预报参数的结论；其次将选取的参数作为模糊系统的输入，建立滑坡灾害发生概率模型，并引入优化的GD算法修正预报模型中的动态参数，使模糊控制模型具有自适应性；同时与未优化的模糊控制模型以及单独模糊控制模型进行仿真对比，仿真结果表明，该控制算法收敛速度快，具有很好的收敛性；最后将该模型在某滑坡重点灾区实验区进行实验测试，实验结果显示该模型具有较好的收敛性，且预报精度达到90%。     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

Inhibitory effects of three chemical dust suppressants on nitrocellulose dust cloud explosion

Three types of self-prepared chemical dust suppressants (CDSs) were investigated for their inhibitory effects on nitrocellulose (NC) cloud dust explosion. The results revealed that NC is extremely sensitive to electric sparks and has a high explosion intensity. CaCl₂-CDS effectively increased the particle size to control fly dust substantially inhibiting dust cloud explosions. However, both Na₂SO₄-CDS and MgCl₂-CDS exhibited poor abilities and even promoted explosion. Therefore, neither Na₂SO₄-CDS nor MgCl₂-CDS is recommended as a CDS for NC. Inappropriately using CDSs may engender severe explosions. Furthermore, a mechanism underlying NC dust cloud combustion and explosion was proposed. NC has three stages of heat release: autoxidation, thermal decomposition, and combustion. Thermal decomposition, combustion, and explosion were triggered depending on the energy provided from autoxidation. CaCl₂-CDS inhibited only combustion. This study reveals the mechanism underlying NC dust cloud explosions and provides useful information for the development of more optimized CDSs.     

金川深部高应力巷道锚喷支护设计与数值模拟技术

针对金川深部高应力巷道变形特征,首次提出了以预应力锚索为支护手段的综合控制技术,为预测支护效果和支护参数优化,进行了高应力挤压碎裂蠕变围岩的锚喷支护巷道稳定性数值分析研究。首先给出了综合控制技术中的两次支护型式和参数;然后,考虑巷道围岩的碎裂蠕变特性,研究采用了分段线性软化模型和剪胀特性参数,并探索提出了锚固体支护强度指标,定量考虑锚固围岩的强度效应;最后,采用提出的计算模型和分析方法,进行了1178m分段道数值模拟和参数优化,取得了较好的分析效果。     

浅谈对污水回用的认识

介绍了污水回用的巨大潜力，探讨了污水回用的原则，分析了污水回用的经济性及效益，论述了污水回用带给规划、设计的变化及污水回用中存在的问题，并对污水回用的前景进行了展望，以促进污水回用的发展。     

项目进度管理实施中的奖惩机制研究

对项目进度管理中的奖惩机制建立了数学模型,从承包商和业主两方面分析研究奖惩机制的决定因素,并对其进行了优化分析,提出了资源制约强度,浮动资金使用强度两个新概念。在此基础上从承包商和业主双方分别对以往的项目进度模型进行了优化,并建立了两个新的优化模型并对模型进行了说明。     

汽车空调出风口注塑模优化设计

结合汽车空调出风口塑件的结构特点,使用局部分型和整体分型相结合的优化设计办法对模腔分型,依据塑件的脱模需要确定模具结构为单腔布局、直接浇口浇注两板模具。模具模架改进为增加1次开模打开,以驱动定模侧的斜顶机构完成先抽芯。针对塑件上众多且复杂的附加特征的脱模,设计了7个脱模机构用于这些特征的脱模,包括1个定模斜顶机构、2个动模斜顶机构,2个动模斜导柱滑块机构及2个动模油缸斜抽芯机构。动模斜顶机构优化为万能斜顶机构以缩减机构对模架尺寸的使用要求。各成型滑块上,针对小尺寸特征的成型,成型件优化设计为组合型小镶件,有效降低了滑块成型件的加工难度。模具结构布置合理,机构结构形式使用恰当,能为同类塑件的注塑模制造生产提供有益借鉴。     

含分布式电源的直流配电网供电能力评估

针对分布式电源(DG)输出功率随机性的特点,提出概率函数圆的抽样方法改进了传统的蒙特卡洛抽样,构建了DG概率模型。提出了直流配电网供电能力评估指标以及多目标评估函数,基于德尔菲法利用判断矩阵对指标进行定性和定量分析,最终采用改进遗传算法进行最优化求解。算例中针对辐射型、环形、网格状结构的直流配电网在DG渗透率不同的条件下进行计算及比较分析,验证了该方法的可行性,对未来的直流配电网供电能力研究提供参考。     

分形维数计算的流水线优化方法研究

分形维数计算具有计算复杂度高、计算时间长等特点,严重影响计算的实时性。针对此问题,在充分分析分形维数计算内在特性的基础上,利用分形维数具有流水线计算的特点,提出了一种计算分形维数的流水线体系结构,可有效提高分形维数计算的实时性。由于嵌入式并行处理硬件平台资源有限,对分形维数计算实时性进行优化的同时还需要考虑资源消耗的优化。通过对不同级数流水线运行时间和资源消耗的分析,建立基于运行时间与资源消耗的优化目标函数,从而得到运行时间与资源消耗最优的流水线结构。并与已有的计算分形维数的并行算法进行对比分析,实验结果表明,本文提出的优化方法在提高计算实时性的同时有效降低了资源消耗,实现了运行时间与资源消耗的优化。     

Adaptive Multimodal In‐Vehicle Information System for Safe Driving

This paper proposes an adaptive multimodal in‐vehicle information system for safe driving. The proposed system filters input information based on both the priority assigned to the information and the given driving situation, to effectively manage input information and intelligently provide information to the driver. It then interacts with the driver using an adaptive multimodal interface by considering both the driving workload and the driver's cognitive reaction to the information it provides. It is shown experimentally that the proposed system can promote driver safety and enhance a driver's understanding of the information it provides by filtering the input information. In addition, the system can reduce a driver's workload by selecting an appropriate modality and corresponding level with which to communicate. An analysis of subjective questionnaires regarding the proposed system reveals that more than 85% of the respondents are satisfied with it. The proposed system is expected to provide prioritized information through an easily understood modality.