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。     

产品碳足迹评价中不确定度与敏感度相结合的数据质量分析

产品碳足迹评价中,数据种类、来源、获取途径和量化方法的选择不同将直接影响到评价结果的可靠与否.本文建立了结合敏感度和DQI-Monte Carlo不确定度分析的产品碳足迹评价数据质量分析模型.首先通过敏感度分析识别出产品碳足迹评价中的主要数据,再采用DQI-Monte Carlo不确定度分析方法对主要数据进行数据质量判定,甄选出影响评价结果可靠性的关键数据,并由此有针对性地提出数据质量改进意见,从而有效地优化数据收集方案,减少碳足迹评价结果的不确定度.建立的方法应用于我国某塑料软包装印刷企业的印刷前阶段碳足迹评价中.     

Fuzzy optimization of multi-period carbon capture and storage systems with parametric uncertainties

Carbon capture and storage (CCS) is an important technology option for reducing industrial greenhouse gas emissions. In practice, CO₂ sources are easy to characterize, while the estimation of relevant properties of storage sites, such as capacity and injection rate limit (i.e., injectivity), is subject to considerable uncertainty. Such uncertainties need to be accounted for in planning CCS deployment on a large scale for effective use of available storage sites. In particular, the uncertainty introduces technical risks that may result from overestimating the limits of given storage sites. In this work, a fuzzy mixed integer linear program (FMILP) is developed for multi-period CCS systems, accounting for the technical risk arising from uncertainties in estimates of sink parameters, while still attaining satisfactory CO₂ emissions reduction. In the model, sources are assumed to have precisely known CO₂ flow rates and operating lives, while geological sinks are characterized with imprecise fuzzy capacity and injectivity data. Three case studies are then presented to illustrate the model. Results of these examples illustrate the tradeoff inherent in planning CCS systems under parametric uncertainty.     

优化、RSA和GLUE方法在非线性环境模型参数识别中的比较

参数识别是数学模型应用的前提,本文对非线性环境模型常用的3种参数识别方法进行了比较分析.优化方法是出现最早、应用最广泛的参数识别方法之一.但在观测误差存在的情况下,采用优化方法识别的最优参数进行模型预测,存在很大的决策风险.考虑到这种不足,RSA方法和GLUE方法摒弃了识别单一最优参数的传统思维,而把识别参数扩大到多点组成的参数集.RSA方法与GLUE方法不同的是,RSA方法把可行的参数点看成是同等接受的,而GLUE方法则根据模拟值与实测值的差别,确定其似然度,代表参数的可信度水平.除参数识别以外,RSA方法和GLUE方法也是全局灵敏度分析的重要工具.     

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.     

太原市多环芳烃(PAHs)排放清单与分布特征分析

根据太原市11种主要排放源的排放因子和活动量数据,估算了美国国家环境保护局(US EPA)优先控制污染物清单中16种多环芳烃(PAHs)的年排放量.结果表明2010年太原市16种PAHs的排放量约为332.10t,其中7种致癌性PAHs排放总量为35.11t.从排放源看,生活燃煤和炼焦煤是太原市排放PAHs的主要来源,占总排放量的65%以上.从各地区的PAHs排放情况看,排放量最大的地区是清徐县(87t/a),占总排放的27%.其次为古交市(54t/a)、晋源区(44t/a)、尖草坪区(40t/a).各地区人均收入与单位GDP排放量之间呈负相关 (R2=0.727);各地区PAHs排放量与农村人口之间呈正相关(R2=0.813),从排放谱看,排放以低环PAHs为主(81%),致癌性PAHs占总排放量的10.6%.结果表明,太原市PAHs的排放与太原市特殊的能源结构和人群结构有关.     

基于国内实测燃煤电厂烟气汞排放估算的不确定度

参照测量不确定度评定与表示的国家技术规范,基于近年来我国燃煤电厂常规污控设备协同脱汞的现场测试数据(文献报道和实测值)及各省原煤w(汞)的实测值,初步构建了国内燃煤电厂烟气汞排放不确定度的计算方法,并以2010年的燃煤量、污控方式布局为基础,计算了该年度汞排放的不确定度. 结果表明:2010年我国燃煤电厂烟气汞排放的总不确定度为48.8t,占平均排放总量的34.3%;其中60.2%源于污控设备脱汞效率的不确定度,39.8%源于原煤w(汞)的不确定度;采用ESP(静电除尘)、ESP+WFGD(静电除尘+湿法脱硫)、SCR+ESP+WFGD(选择性催化还原脱硝+静电除尘+湿法脱硫)和FF(袋式除尘)大气污控组合的机组各存在6.0、32.2、9.7和0.9t的烟气汞排放不确定度,分别占各对应机组烟气汞排放量的19.3%、32.8%、84.6%和53.6%,其中SCR+ESP+WFGD污控组合烟气汞排放的相对不确定度最大. 随着我国烟气脱硝工作全面推行,2015年以后,SCR+ESP+WFGD污控措施(组合)的机组所占比例将会提高到66%以上,如果仍以现有数据为基础,则来自SCR+ESP+WFGD污控措施(组合)机组的烟气汞排放不确定度将会大幅增加,因此急需增加对该类装置脱汞效率的实测样本数量.      

广东货船水运的温室气体排放和低碳发展对策

作为我国港口大省和低碳试点省,广东需先行测算船舶水运的GHG(温室气体)排放量基线,以探究低碳水运对策. 通过文献调研收集适用数据和资料,基于引擎功率法,测算了广东抵港货船在2010年的GHG排放量. 结果表明:广东专属经济区海域内货船水运的GHG总排放量为2887×104t,不确定性在-36%~45%之间,其中在领海区域内的排放量为730×104t;远洋集装箱船是GHG最大排放源,占总排放量的43%;集装箱船、干散货船、油轮和其他货船的GHG排放量不确定性均介于-30%~50%之间,远洋货船的主引擎在正常航行模式下输出功率是最主要的不确定性源. 基于分析船舶水运的GHG排放特征,提出船舶减速、向远洋货船供应岸电和内河货船主引擎转用天然气共3项低碳节能措施,共可减排40%的GHG排放量.该研究结果不仅为广东低碳水运发展提供基础性的GHG排放数据,也可为其他港口地区提供估算水运业GHG排放量的技术方法参考和实践经验.      

区域层面温室气体清单不确定性量化研究

基于《IPCC国家温室气体清单优良做法指南和不确定性管理》中不确定性分析的理论和方法,以编制包括省级、地市级在内的区域层面温室气体清单为背景,就不确定性分析的难点、来源和组成进行分析,并通过实例研究对适用于区域层面温室气体清单的不确定性量化方法进行说明,进而提升不确定性分析的可操作性和透明性,为完善温室气体清单提供有价值的参考。