可控震源振动器系统不确定性分析

为了解决可控震源施工过程中振动器系统的安全性问题,采用故障树法建立仿真 模型。通过失效分析得出各故障单元的失效模式及单元间分布规律,计算出振动器系统 的可靠度。开展对该系统敏感性的不确定性分析,得出影响振动器系统可靠性的关键因 素为重锤上部密封失效。采用有限元法对其应力场进行模拟仿真。结果表明:随着工作 频率的升高,O形圈应力波动越大,密封越容易失效。Von Mises应力随压缩率的增大先 减小后增大,随槽口半径的增大而增大;接触应力在一定范围内随压缩率及槽口半径的 增大而增大。为振动器的结构优化与可靠性设计提供理论依据,并为油气资源勘探开发 的安全作业提供工程应用指导。     

考虑逆向物流的应急物资配置流程SPN建模分析

应急物资的高效快速配置是降低灾害损失和顺利实施应急救援的有力保障。应急逆向物流包括废旧物资的回收利用以及可重复利用物资的回收再利用,能起到缓解应急物资匮乏,减少环境污染的作用。本文根据随机Petri网理论,构建考虑逆向物流的应急物资配置模型,通过对同构于该模型的马尔可夫链进行仿真,求得各种状态的稳态概率,结合马尔可夫链性质对关键因素进行静态分析和动态分析;通过“雅安地震”的案例应用表明,当地震灾害发生时,此模型可以反映各因素对应急物资配置整体流程的影响,并通过数值变化趋势反映不同条件下应急物资配置的关键环节,可以为灾后救援和应急物资的利用提供理论支持。     

不同组合比例煤岩的电荷感应与微震规律试验研究

针对煤岩在屈服破坏过程中有微震和电荷信号产生这一特征,利用自行设计的微震和电荷感应信号监测试验系统,分析不同组合比例煤岩在变形破裂过程中微震和电荷信号的变化规律。研究结果表明:微震和电荷信号是低频信号,信号频谱集中分布在0~80 Hz,应力突变与微震信号和电荷信号的产生及变化有较好的一致性;随着“煤-岩”高度比的增加,试样的单轴抗压强度减小,试样屈服破裂时微震和电荷信号幅值增大,同步性增强,试件破坏的突发性增强;试件破坏过程中电荷比微震信号数更多,初次明显的电荷信号也早于初次明显的微震信号。     

区域水战略方案选优的动态组合评价模型研究

水安全危机是人类进入新世纪以来在生存及发展方面所面临的最严重挑战之一。研究科学合理的水安全战略成为区域可持续发展的重大课题。针对区域水战略问题涉及众多因素且各因素之间动态关联的特点,提出了基于水战略方案优选的兼容度极大化动态组合评价模型（CMM—DCEM）,并将其成功地应用于我国广东省北江下游及其三角洲地区水安全战略方案优选评价。评价结果及模型基于不确定性的敏感性分析结果证明：CMM—DCEM实现了主、客观赋权方法以及单一评价模型的融合,使用实码加速遗传算法求解目标函数,克服了传统的组合评价方法计算繁琐的不足,评价过程更加科学合理。     

湿地甲烷排放估算模型的研究进展

湿地是大气甲烷（CH₄）的主要排放源,大气甲烷排放量的日益增加,给全球气候变化带来很大影响,准确估算湿地甲烷的排放量意义重大。目前湿地甲烷排放量估算模型主要有经验模型、机理过程模型和遥感参数模型,通过对三种模型的发展过程、应用状况及优缺点的对比分析和总结,分析了湿地甲烷排放、监测过程及模型估算方面的不确定性,指出了湿地甲烷排放估算的发展趋势,提出遥感参数模型将是湿地甲烷排放估算模型今后的发展方向。     

Estimating the uncertainty of pesticide residue analysis from mango using multi-residue analysis and validation of method

Validation of method was performed for various pesticides on mango matrix involving the processing of sample at ambient and cryogenic conditions. The linearity, limits of detection, repeatability, matrix effect, and recovery were studied as the aspects of method validation. The effect of matrix on recovery was found to be medium (20–50%) and strong (>50%). After correction by matrix-matched calibration curves, the recovery was calculated to be in the range of 80–107% and 80–105% at ambient and cryogenic processing, respectively. The precision estimated for the recovery of pesticides obtained from both solvent- and matrix-matched calibration curves and at both the processing conditions was determined to be >20% except for chlorpyrifos and atrazine. The uncertainty established for the methodology was >20%, which substantiates the efficiency and reliability of methodology used for pesticide residue analysis in mango in this study.     

Uncertainty analysis of a pharmacokinetic modeling for inorganic arsenic

This paper presents an uncertainty and sensitivity analysis of a pharmacokinetic modeling of inorganic arsenic deposition in rodents for a short‐term exposure. Efforts to develop the pharmacokinetic model are directed towards predicting the kinetic behavior of inorganic arsenic in the body, including tissue and blood concentrations, and especially, the urinary excretion of arsenic and its methylated metabolites. However, the use of the model raises an important question when fixed values of model parameters are used: how is the uncertainty in the model prediction based on the collective uncertainties in the model inputs? This study focuses on an “epistemic”; uncertainty in order to handle this problem. In this case, the uncertainty refers to an input that has a single value which cannot be known with precision due to a lack of knowledge about items or its measurement. The combination of the pharmacokinetic model and the uncertainty analysis would help understand the uncertainties in risk assessment associated with inorganic arsenic.     

Effects of sepiolite and biochar on microbial diversity in acid red soil from southern China

Sepiolite and biochar can immobilize heavy metals and organic pollutants in soil effectively, but their impact on the soil microbial community and diversity is still unclear. High-throughput Illumina MiSeq method was used to study the effects of sepiolite and biochar on the diversity of microbial communities in acid red soil amended with cadmium and atrazine. A total of 47,472 microbiological Operational Taxonomic Units (OTUs) were found in all the treated soil samples. Sepiolite and biochar enriched the diversity of soil microbes at different classification levels and OTUs, but the effect of biochar was stronger than that of sepiolite. A Venn diagram showed that compared with other treatments, adding 2% biochar could promote the growth of specific microbes, which is better than the case for 5% biochar. The heat map of species abundance cluster showed that the dominant microbes in soil were different for different treatment doses of sepiolite and biochar. Among all the soil treatments, the top ten dominant bacterial phyla (from high to low dominance) were: Actinobacteria, Proteobacteria, Firmicutes, Bacteroidetes, Acidobacteria, Gemmatimonadetes, Chloroflexi, Planctomycetes, Cyanobacteria­, and Verrucomicrobia. The addition of sepiolite and biochar promoted the restoration of the microbial community diversity in contaminated soil.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method, identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

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