Force chains based mesoscale simulation on the dynamic response of Al-PTFE granular composites

Force chains based mesoscale simulation is conducted to investigate the response behavior of aluminum-polytetrafluoroethylene (Al-PTFE) granular composites under a low-velocity impact. A two-dimensional model followed the randomly normal distribution of real Al particles size is developed. The dynamic compressive process of Al-PTFE composites with varied Al mass fraction is simulated and validated against the experiments. The results indicate that, force chains behavior governed by the number and the size of agglomerated Al particles, significantly affects the impact response of the material. The failure mode of the material evolves from shear failure of matrix to debonding failure of particles with increasing density. A high crack area of the material is critical mechanism to arouse the initiation re-action. The damage maintained by force chains during large plastic strain builds up more local stresses concentration to enhance a possible reaction performance. In addition, simulation is performed with identical mass fraction but various Al size distribution to explore the effects of size centralization and dispersion on the mechanical properties of materials. It is found that smaller sized Al particle of com-posites are more preferred than its bulky material in ultimate strength. Increasing dispersed degree is facilitated to create stable force chains in samples with comparable particle number. The simulation studies provide further insights into the plastic deformation, failure mechanism, and possible energy release capacity for Al-PTFE composites, which is helpful for further design and application of reactive materials.     

Transverse relaxation characteristic and stress relaxation model considering molecular chains of HTPB coating based on pre-strained thermal aging

In order to accurately describe the transverse relaxation characteristic and stress relaxation modulus of HTPB coating during pre-strain thermal aging process, a one month thermal aging test was carried out at 70 C with pre-strain of 0％, 3％, 6％ and 9％, respectively. The low-field 1H NMR and stress relaxation modulus tests were carried out for HTPB coating at different aging stages. The stress relaxation model considering the molecular chains was proposed according to the changes of crosslinking chain and dangling chain of HTPB coating during pre-strain aging. The results showed that with the increase of aging time, the decay rate of transverse relaxation curve became faster, the transverse relaxation time decreased, the value of combined parameter qMrl increased, the proportion of crosslinking chain decreased, while the proportion of dangling chain increased. Moreover, the stress relaxation modulus increased, the crosslinking network structure of HTPB coating became denser and the degree of cross-linking increased. At the initial aging stage, the pre-strain will destroy the crosslinking network structure of HTPB coating to a certain extent. With the increase of aging time, the effect of pre-strain will gradually weaken and the influence of aging on materials will gradually increase. The correlations between the stress relaxation model considering the molecular chains and the test results were more than 0.9950, which can accurately describe the stress relaxation modulus of HTPB coating during the pre-strain thermal aging process.     

Visual-attention gabor filter based online multi-armored target tracking

The multi-armored target tracking (MATT) plays a crucial role in coordinated tracking and strike. The occlusion and insertion among targets and target scale variation is the key problems in MATT. Most state-of-the-art multi-object tracking (MOT) works adopt the tracking-by-detection strategy, which rely on compute-intensive sliding window or anchoring scheme in detection module and neglect the target scale variation in tracking module. In this work, we proposed a more efficient and effective spatial-temporal attention scheme to track multi-armored target in the ground battlefield. By simulating the structure of the retina, a novel visual-attention Gabor filter branch is proposed to enhance detection. By introducing temporal information, some online learned target-specific Convolutional Neural Networks (CNNs) are adopted to address occlusion. More importantly, we built a MOT dataset for armored targets, called Armored Target Tracking dataset (ATTD), based on which several comparable experiments with state-of-the-art methods are conducted. Experimental results show that the proposed method achieves outstanding tracking performance and meets the actual application requirements.     

装备保障兵力机动模型的建立

在分析未来战争中机动作战对装备保障要求的基础上,明确了建立装备保障兵力机动模型的重要性。通过分析影响装备保障部(分)队机动状况的因素,建立了装备保障部(分)队的机动模型,研究了模型的计算流程。     

二次型极小化问题带误差的迭代算法

证明了二次型极小化问题带误差的迭代算法的有效性,所得结果推广了关于二次型极小化问题迭代的收敛性。     

坦克外部磁场的有限元分析

采用有限元数值计算方法,参考坦克的旋转椭球模型的计算公式,对坦克外部的磁场进行了计算机模拟计算.     

信息化战争中的纳米科技

纳米材料由于其独特的光、电、力、磁效应近年来受到人们广泛的关注,综述了目前国内外纳米科技的研究动态,着重介绍了现有纳米科技在高科技战争中的应用,及其潜在的发展方向．     

LPG储罐区池火灾危险性分析及扑救对策

综合SFPE推荐的池火灾火焰热辐射计算模型,结合热辐射伤害破坏准则,分析了LPG储罐区池火灾的危险性,应用该方法计算分析了某LPG站发生池火灾时的伤害破坏范围。根据计算分析结果,在扑救LPG储罐区池火灾的过程中,对于按照有关国家标准规定的防火距离布置的LPG储罐区,仍然需要重点冷却着火罐及相邻罐,防止长时间火焰热辐射作用导致储罐破裂,发生沸腾液体扩展蒸气爆炸,同时,确定了消防人员和装备的安全距离。     

高校学生宿舍楼火灾危险性的模糊综合评价

依据高校学生宿舍楼火灾危险性的影响因素,应用模糊识别理论构建了高校学生宿舍楼火灾危险性评价指标体系,并利用层次分析和多级模糊评价相结合的方法对某高校学生宿舍楼火灾危险性进行综合评价。研究表明:该方法的评估结果符合实际情况,且简便可行,具有较强的实际应用性。     

有机化学教材中有机物命名法质疑

通过对一些广泛应用的有机化学教材中关于有机物命名法的研究和分析,提出有机化学教材中关于有机物命名法的几点不足,并提出了相应的解决方法和一些建议。