PERSISTING SEDIMENT YIELDS AND SEDIMENT DELWERY CHANGES1

ABSTRACT: The Buffalo River is a tributary to the Mississippi River in west-central Wisconsin that drains a watershed dominated by agricultural land uses. Since 1935, backwater from Lock and Dam 4 on the Mississippi River has inundated the mouth of the Buffalo's valley. Resurveys of a transect first surveyed across the lake in 1935 and cesium-137 dating of backwater sediments reveal that sedimentation rates at the Buffalo's mouth have remained unchanged since the mid-1940s. Study results indicate that sediment yields from the watershed have persisted at relatively high levels over a period of several decades despite pronounced trends toward less cultivated land and major efforts to control soil erosion from agricultural land. The maintenance of sediment yields is probably due to increased channel conveyance capacities resulting from incision along some tributary streams since the early 1950s. Post-1950 incision extended the network of historical incised tributary channels, enhancing the efficient delivery of sediment from upland sources to downstream sites.     

论人的失误

人的失误所造成的事故占事故总数的７０—８０％，研究人的失误对控制伤亡事故的发生具有重要意义。为此，分析人的行为模式，论述人失误的原因，并对控制人失误的方法进行了探讨，认为减少人失误的根本途径是大力倡导安全文化，提高操作者的安全素质。     

基于CREAM的高温熔融金属作业人员可靠性分析

为了对冶金企业高温熔融金属作业人员的可靠性进行评估和量化,基于认知可靠性与失误分析方法(CREAM),提出了适用于高温熔融金属作业的人员可靠性分析方法。该方法给出了通用效能条件(Common Performance Condition, CPC)的评估细则,采用层次分析法(Analytic Hierarchy Process,AHP)与熵值法相结合的CPC因子权重确定方法,利用模糊数学原理实现CPC因子输入的模糊化,从而计算高温熔融金属作业人员失误概率(HEP)和可靠度。通过对炼钢冶炼作业的人员可靠性分析的结果表明:该方法合理有效,具有一定的应用性。     

核电厂防人因失误管理有效性探讨

介绍了核电人因管理的发展历史,在国际核电业界防人因失误管理标准的基础上,结合部分国内外核电厂的防人因失误管理实践,探讨了影响核电厂人因管理的模型,对业界普遍存疑的概念进行了辨析,分析了影响人因管理有效性的关键因素,提出了提高核电厂防人因失误管理有效性的建议以及良好实践。     

航迹误差对无人机坠地伤人风险评估的影响

为提高无人机(UAV)安全风险评估的精确性和置信度,在坠地安全风险评估过程中,考虑航迹误差导致的事故瞬间UAV位置和高度的不确定性,及其对坠地撞击点和撞击速度的影响,分析UAV坠地的水平位置误差和高度误差分布特征,确定UAV失效瞬间位置和高度,建立坠地撞击点预测模型,计算其坠地撞击速度,并以M210-RTK型UAV为例,分析不同航迹误差对坠地时间、地面撞击点位置和坠地动能的影响。结果表明:航迹误差作用下,坠地撞击点分布遵循正态分布特征;随着飞行高度的增加,航迹误差对坠地位置的影响逐渐下降,高度误差对坠地动能的影响呈先增后减的趋势。     

基于光散射法粉尘个体监测仪研制*

为研制矿山呼吸性粉尘浓度个体监测仪,采用MIE光散射方法,试制以红外线发光二极管作为光源的呼吸性粉尘浓度个体监测仪,该监测仪主要由气路部分、光路部分及电路部分组成。利用中国安全生产科学研究院自制的粉尘简易试验装置,在气体流量为2 L/min、颗粒粒径不大于5 μm的条件下,研究试制仪器电压输出值和流入粉尘质量浓度二者的对应关系。结果表明:根据不同粉尘质量浓度下的输出电压数据,在0~300 mg/m3测量范围内,试制仪器输出电压值和粉尘浓度之间具有线性函数关系,说明呼吸性粉尘浓度个体监测仪是合理可行的;粉尘监测仪测试结果与比对仪器测量结果对比分析可知,测量误差最大为1.59%,满足粉尘检定规程要求。     

基于多故障冲击模型和故障树的PFDavg计算方法研究*

为提高安全仪表功能（SIF）要求时危险失效平均概率（PFDavg）计算结果的精确度,提出1种能准确计算SIF在多重共因失效影响下的PFDavg的数学模型。建立包含多重共因失效的系统失效故障树,然后利用多故障冲击模型区分普通失效率和多重共因失效率,根据瞬时不可用率的定义和故障树的逻辑关系计算出SIF的瞬时不可用率;基于PFDavg的定义,计算出SIF的PFDavg,以某化工企业SIF为例进行验证。结果表明:方法有效考虑了多重共因失效对SIF的影响,通过模型计算出SIF的PFDavg大于基于马尔可夫（Markov）方法的软件计算结果,但二者处于相同的数量级。模型在评估SIF的PFDavg时比传统方法偏保守,能提高安全仪表功能的安全性。     

以大辽河为例分析中小河流入海通量的估算方法

通过对目前河流入海通量估算方法的比较分析,针对我国北方的大部分河流属中小河流,监测频率不高,潮周径流量与进潮量之比很小的情况,指出了估算河流人海通量的技术障碍,分析各种河流、河口通量估算方法的误差来源、应用条件,比较潮时通量法、水期加权法、年平均法、概率分布法以及对流-扩散模式法等各种时段通量的估算方法.从河口上游水文站时段通量、河口段流达率、区间排放量的关系出发,提出实用化的河流人海通量的计算方法,并用于水质监测频率较低的感潮河流人海通量的估算和分析.通过对2003年大辽河人海通量进行实例计算,全面考虑时段离散通量,验证了方法估算结果的合理性.     

A model of deforestation by human population interactions

A differential equation was employed in modelling deforestation by human population interactions to yield an explicit mathematical model. The theoretical relation and many possible models were applied to the grid cell data in Hiroshima Prefecture, and relative appropriateness of each model was evaluated by Akaike's information criterion (AIC) using raw data. Intensive further verification was executed bythe bootstrap method. It was demonstrated that the theoretical relation was in the best agreement among many other models in comparison.     

A Bayesian approach to evaluating site impairment

In the United States, each state is required to list water resources that are declared to be impaired under guidelines set by the Clean Water Act. Measurements are typically collected on a number of chemical constituents and compared with a standard. If there are too many measurements exceeding the standard, then the site is declared impaired. The approach is non-statistical but similar to a Binomial test. The Binomial approach would convert the measurements to binary data then test if the proportion exceeding the standard is excessive. Both methods convert measurements to binary values hence exclude potentially important information in the data. We present a statistical approach using a Bayesian model that uses the raw data instead of the binary transformed data. The population distribution of a family of location-scale parameter models is studied under the model. Posterior distributions from the Bayesian analysis are used in the decision-making process and error probabilities for the Bayesian and the Binomial approaches are compared for a normal population.