神经网络在自行火炮发动机燃油系统故障诊断中的应用

在讨论神经网络快速算法的基础上,研究了自行火炮发动机燃油供给系统几种常见故障的诊断方法,并在发动机实际运行中进行试验,结果表明,神经网络的采用使诊断模型具有智能化特点,用于发动机故障诊断效果是明显的。     

油耗线法测定柴油机机械效率的理论分析

本文阐明了用油耗线法测定柴油机机械损失的理论依据,并指出该法所得结果为接近空载时的值.     

气动剥离液滴的附面层分析方法

本文根据附面层理论,对高速气流中的液滴,因气流和液滴表面相互作用而产生的气动剥离现象进行了分析,建立了气液两相附面层耦合问题的理论分析模型,得到了发生气动剥离时的最小气流速度的计算公式,为液体燃料在高速气流申雾化机理研究提供参考。     

基于矩估计的高原航空备件消耗规律研究

针对高原航空备件消耗规律难把握的问题,提出了一种解决低消耗器材消耗预测的方法,利用矩估计把握器材的消耗规律和Monte Carlo仿真器材消耗的数据,找出储备量与满足率之间的关系,预测年平均消耗量。     

基于BP和Hopfield神经网络的航空肼燃料保障安全评价

针对航空肼燃料保障安全评价的复杂性和非线性,提出并建立了基于BP和Hopfield神经网络的动态安全评价模型。在综合分析国内外肼燃料保障安全评价的基础上,针对航空肼燃料保障过程中出现的问题,构建并优化了指标体系,选取前馈神经网络中的BP网络和反馈神经网络中的Hopfield网络建立评价模型。在详细说明了BP和Hopfield神经网络的构建方法后,进行实例验证,并对预测效果进行了比较分析。仿真表明,两种模型都能正确评价安全保障状态。但在收敛速度、联想记忆功能方面Hopfield神经网络优于BP神经网络。将BP和Hopfield神经网络用于肼燃料保障安全评价过程中,具有适用性和可行性,对于航空肼燃料保障的安全建设与安全管理研究具有重要意义。     

Scheduling combat logistics force replenishments at sea for the US Navy

The Replenishment at Sea Planner (RASP) is saving the U.S. Navy millions of dollars a year by reducing fuel consumption of its Combat Logistics Force (CLF). CLF shuttle supply ships deploy from ports to rendezvous with underway U.S. combatants and those of coalition partners. The overwhelming commodity transferred is fuel, ship‐to‐ship by hoses, while other important packaged goods and spare parts are high‐lined, or helicoptered between ships. The U.S. Navy is organized in large areas of responsibility called numbered fleets, and within each of these a scheduler must promulgate a daily forecast of CLF shuttle operations. The operational planning horizon extends out several weeks, or as far into the future as we can forecast demand. We solve RASP with integer linear optimization and a purpose‐built heuristic. RASP plans Replenishment‐at‐Sea (RAS) events with 4‐hour (Navy watch) time fidelity. For five years, RASP has served two purposes: (1) it helps schedulers generate a daily schedule and animates it using Google Earth, and (2) it automates reports command‐to‐ship messages that are essential to keep this complex logistics system operating.     

发动机冷却燃料超临界压力下做功潜力㶲分析

在高马赫数飞行下,超燃冲压发动机的燃料冷却量大于燃料燃烧量。为了降低燃料的冷却量以及实现燃料冷却量和燃烧量的匹配,采用分析法对超燃冲压发动机壁面燃料冷却工质在超临界压力下进行做功潜力分析。发动机壁面冷却燃料的特性决定其热量大小。根据发动机壁面温度分布、热流密度分布计算热量,建立稳定流动燃料工质的平衡方程。结果表明:在壁面最高温度为1200 K时,传入壁面的热量为562.4 k W,其中理论热量为541.3 k W;冷却燃料工质流量增加,最大输出功减小;燃料工质出口温度增加,输出功减小;燃料工质出口压力增加,输出功基本不变。     

可调喷油规律下柴油机性能随喷油提前角的影响

为获取可调喷油规律条件下,喷油提前角对柴油机性能的影响规律及成因机理。在实现可调喷油规律喷射的基础上,基于Fire软件建立了柴油机工作过程计算模型,并通过试验对模型中的主要参数进行了标定,进而利用模型分析了靴形喷油规律下柴油机性能随喷油提前角的变化。结果表明：随着增压时刻的滞后,喷油规律由矩形过渡到斜坡形再到靴形,实现了灵活可调的喷油规律。在靴形喷油规律条件下,存在一个最佳的喷油提前角,使柴油机的动力性和经济性均达到最优。同时,随着喷油提前角的增大,柴油机缸内压力、缸内温度以及放热率均逐渐升高,且到达各自最大值的时刻前移,而NOx排放量和碳烟排放量则分别呈现出增加和减小的趋势。     

基于灰色神经网络的装甲部队油料消耗预测

油料消耗量的精确预测直接影响装甲部队后勤保障能力的提升,而传统预测模型精度不高,应用范围也有一定的局限,难以满足信息化战争精确保障的需要。提出一种装甲部队油料消耗预测的组合模型,对历史油料消耗数据和油耗影响因素进行统计分析,求出各影响因素与油耗量的关联度作为权重系数;通过改进GM(1,1)模型预测某部队下一次军事行动的油耗量;用GM(1,1)模型的预测值、加权后的各影响因素值和油耗实际值训练网络,对下一次想定的军事行动油耗量进行预测。通过平均相对误差计算表明,组合预测模型比单一的GM(1,1)模型预测精度高,能够较好地指导部队进行下一步的油料供管工作。     

REFASHIONING AUSTRALIA'S NUCLEAR BARGAIN?

This article explores the challenges that Australia faces in reconciling its commitments to nonproliferation and uranium exports during a time when the international nuclear nonproliferation regime is under major stress and the world uranium market is bullish. The “grand bargain” that has framed Australian participation in the nonproliferation regime and the nuclear fuel market since the 1970s was only tenable in an era of stagnant uranium demand and a stable nuclear balance. However, contemporary nuclear proliferation dynamics and the revival of interest in nuclear energy have accentuated the incompatibility between Australia's commitment to nonproliferation and the desire to profit from uranium exports. The contemporary international strategic environment, international nonproliferation regime, and nuclear energy market are characterized by developments that not only undermine the basis of Australia's grand bargain, but also present challenges and opportunities for the refashioning of Australian policy.