具有相依利息率的离散时间保险风险模型的破产问题

进一步研究离散时间保险风险模型，在利率具有一阶自回归结构的情况下，得到了描述破产严重程度的破产前一时刻的盈余分布与破产持续时间的分布的递推公式．     

Prediction of impacts of wheeled vehicles on terrain

Traffic of off-road vehicles can disturb soil, decrease vegetation development, and increase soil erosion. Terrain impacts caused by wheeled off-road vehicles were studied in this paper. Models were developed to predict terrain impacts caused by wheeled vehicles in terms of disturbed width and impact severity. Disturbed width and impact severity are not only controlled by vehicle types and vehicle dimensions, but also influenced by soil conditions and vehicle dynamic properties (turning radius, velocity). Field tests of an eight-wheeled vehicle and a four-wheeled vehicle were conducted to test these models. Field data of terrain–vehicle interactions in different vehicle dynamic conditions were collected. Vehicle dynamic properties were derived from a global position system (GPS) based tracking system. The average prediction percentage error of the theoretical disturbed width model is less than 20%. The average absolute error between the predicted impact severity and the measured value is less than an impact severity value of 12%. These models can be used to predict terrain impacts caused by off-road wheeled vehicles.     

基于频率二阶摄动的结构损伤识别方法

结构损伤的定位和定量是结构健康监测的关键技术之一。本文将矩阵摄动理论、结构振动理论和有限元理论相结合推导出结构固有频率变化的二阶摄动公式,由此公式可以反演结构的损伤位置与损伤程度。该方法仅需要在役结构的固有频率测量值就能识别出结构的损伤位置和损伤程度,而且还可以识别出结构的老化程度。通过数值仿真算例证明了该方法的有效性和实用性。该方法可用于大型结构的损伤识别和健康监测。     

基于大样本电梯抽查数据的风险评估Logistic模型

为了提高在用电梯监督抽查工作效率及有效性,在统计分析G市电梯安全监管抽查的大样本数据基础上,构建以电梯使用情况、电梯基本参数及制造维保相关情况等为指标的管理体系。根据电梯抽查数据的实质,先对数据进行变量筛选,然后构建风险分级,最后对前人的方法作出改进形成风险矩阵法并提出以Logistic方法为电梯整机风险建立量化模型,最终形成电梯整机风险评估体系。从理论的角度看,通过使用LIFT统计量和K-S统计量比较两种风险值计算模型,得出用Logistic方法进行风险分层更为准确。而实际的工程应用表明,利用Logistic回归法与基于平均风险值赋权比例法的组合为电梯安全监管抽样调查提供的筛选比例,比现有的方法更合理准确。     

油料保障人员胜任特征指标筛选与评估模型构建

对已有油料保障人员胜任特征进行了实证研究,运用SPSS软件统计筛选出3个指标作为关键胜任特征指标并分别赋予权重,提出了评估方法,构建了油料保障人员胜任特征评估模型,并进行简单的应用.     

氢气比例和点火能量对CH4-H2混合气体爆炸强度影响的实验研究

在20 L标准球形爆炸罐内开展了当量比为1的甲烷-氢气-空气混合气体爆炸实验,通过改变点火能量和氢气体积分数,探讨点火能量和气体比例对其爆炸压力和爆炸强度的影响。研究发现:氢气比例越高,爆炸冲击波传播速度越快,点火能对冲击波传播速度的影响相对较小;点火能量的提高对峰值超压有增强作用,氢气比例低时,此增强作用较显著,氢气比例高时,此增强作用较弱;点火能量对爆炸强度指数KG的影响较小,而氢气比例对爆炸强度指数KG的影响十分明显,氢气比例低于50%时,氢气比例的增加对爆炸强度的增强作用较弱,氢气比例高于50%时,氢气的增加对爆炸强度的激励作用急剧增强。另外发现,相同当量比条件下,氢气的爆炸强度指数近似为甲烷爆炸强度指数的10倍。     

Analysis of Factors Contributing to the Severity of Large Truck Crashes

Crashes that involved large trucks often result in immense human, economic, and social losses. To prevent and mitigate severe large truck crashes, factors contributing to the severity of these crashes need to be identified before appropriate countermeasures can be explored. In this research, we applied three tree-based machine learning (ML) techniques, i.e., random forest (RF), gradient boost decision tree (GBDT), and adaptive boosting (AdaBoost), to analyze the factors contributing to the severity of large truck crashes. Besides, a mixed logit model was developed as a baseline model to compare with the factors identified by the ML models. The analysis was performed based on the crash data collected from the Texas Crash Records Information System (CRIS) from 2011 to 2015. The results of this research demonstrated that the GBDT model outperforms other ML methods in terms of its prediction accuracy and its capability in identifying more contributing factors that were also identified by the mixed logit model as significant factors. Besides, the GBDT method can effectively identify both categorical and numerical factors, and the directions and magnitudes of the impacts of the factors identified by the GBDT model are all reasonable and explainable. Among the identified factors, driving under the influence of drugs, alcohol, and fatigue are the most important factors contributing to the severity of large truck crashes. In addition, the exists of curbs and medians and lanes and shoulders with sufficient width can prevent severe large truck crashes.     

Quality rating of a metal matrix-diamondcomposite from its thermal conductivity and electric resistance

The efficiency of hot-pressed diamond-containing composite materials (DCM) for various tool applications is greatly affected by microdefects, namely, the residual porosity of the metal matrix, damaged diamond grains, and imperfect diamond-matrix interfaces. An instrumental evaluation of these microdefects, predetermining the quality of a tool equipped with DCM, is rather difficult due to the small size, the nonstandard shape, and the strong heterogeneity of specimens. Proposed here is an alternative, nondestructive technique of DCM quality rating, which includes the measurement of electric resistance and thermal conductivity of diamond-containing composites and processing the obtained data by the methods of composite mechanics. It exploits the fact that diamond, being a dielectric, possesses an extremely high thermal conductivity, which allows estimating the residual porosity of a sintered metal matrix from the ratio of specific electric resistances, one being measured and another predicted by a theory. These data, in turn, are utilized to predict the thermal conductivity ofDCMwith an imperfect matrix. Matching with experiments, after solving the inverse problem gives the thermal resistance of diamond-matrix interface, which, within the frame work of the given model, simulates the damage of both the diamond grains and their bonds with the matrix. Thus, the numerical rating of quality is given in terms of two dimensionless parameters. The first one, 0 < K < 1, reflects the quality of the sintered metal matrix, whereas the second one, 0 < R <1, is an aggregate measure of the integrity of diamond grains and the perfection degree of composite interfaces. The quite satisfactory agreement observed between the theory and experiment confirms the efficiency of the technique and the reliability of the data obtained. Russian translation published in Mekhanika Kompozitnykh Materialov, Vol. 42, No. 3, pp. 361–374, May–June, 2006.     

Utility indifference valuation of corporate bond with rating migration risk

A pricing model for a corporate bond with rating migration risk is established in this article. With the technology of utility-indifference valuation under the Markov-modulated framework, we analyze the price of a multi-rating bond and obtain closed formulae in a three-rating case. Based on the pricing formulae, the impacts of the parameters on the indifference price are analyzed and some reasonable financial explanations are provided as well.