堆积体边坡渐进性破坏的随机模型

为精确模拟堆积体边坡变形破坏过程,根据堆积体所固有的非连续性、非均质性、各向异性等特点,以及边坡变形破坏的渐进性特征,采用改进的有限单元法(FEM)对堆积体边坡进行模拟。考虑堆积体边坡从连续位移函数到不连续位移函数的突变。破裂发生前,用连续位移函数进行计算;破裂发生后,引入不连续位移函数。研究结果表明,破裂面上不同点的安全系数(FOS)是不同的,但都随着破坏过程而降低。同时,可以得出不同非均匀程度下安全系数的概率分布。     

A Recourse‐Based Interval Fuzzy Programming Model for Point‐Nonpoint Source Effluent Trading under Uncertainty

In this study, a recourse‐based interval fuzzy programming (RIFP) model is developed for tackling uncertainties expressed as fuzzy, interval, and/or probabilistic forms in an effluent trading program. It can incorporate preregulated water‐pollution control policies directly into its optimization process, such that an effective linkage between environmental regulations and economic implications (i.e., penalties) caused by improper policies due to uncertainty existence can be provided. The RIFP model is applied to point‐nonpoint source effluent trading of the Xiangxi River in China. The efficiency of trading efforts between water quality improvement and net system benefit under different degrees of satisfying discharge limits is analyzed. The results are able to help support (1) formulation of water‐pollution control strategies under various economic objectives and system‐reliability constraints, (2) selection of the desired effluent trading pattern for point and nonpoint sources, and (3) generation of tradeoffs among system benefit, satisfaction degree, and pollutant mitigation under multiple uncertainties. Compared with the traditional regulatory approaches, the results demonstrate that the water‐pollution control program can be performed more cost‐effectively through trading than nontrading.     

战略环境影响评价程序设计的探讨

政策是分阶段作用于生态环境的规律,故可将战略环境影响评价分析程序分为三个分程序①政策审查分析和生态评价;②政策与生态环境相互作用的作用机制和作用网络分析程序 ;③政策环境影响量化和计算程序.对每个分程序的分析原理、依据、方法、技术、手段、步骤进行了简明扼要地分析.     

平交道口冗余控制系统的建模及成本收益分析

将成本收益的分析方法应用在控制系统设计中。采用随机Petri网基于控制过程及系统可靠性对道口控制系统进行建模。在可靠性建模中,基于冗余系统的冷备及热备原理对控制系统的各个部件分别进行描述。基于统计数据确定非冗余控制系统Petri网模型参数。针对冷备及热备的冗余控制系统各部件的系统模型,通过仿真确定冗余系统相对非冗余系统所降低的道口事故率,继而计算出冗余控制的收益。将收益与增加设备的成本进行对比分析,结果表明,控制系统中不同部件的冷备及热备冗余都具有不同的成本收益。     

基于Monte-Carlo方法的静电除尘器除尘效率

针对经典除尘效率未考虑诸多随机因素影响的问题,提出了基于Monte-Carlo方法的效率分析模型,并通过实验数据验证其可靠性。通过该模型分析了粒径大小、电场气流速度、电晕电压、两极间距、粒子浓度等因素对收尘效率的影响规律,结果表明:基于Monte-Carlo方法的仿真结果精度更高,能有效预测静电除尘器的收尘效率,对于改进静电除尘器设计具有一定的理论意义和实用价值。     

DPX快速萃取程序升温大体积进样GC/MS法测定水中19种多溴联苯化合物

建立DPX快速吸附萃取、程序升温(PTV)大体积进样与气相色谱/质谱(GC/MS)联用,SIM模式同时测定水中19种多溴联苯(PBBs)单体的方法。该方法在PBBs质量浓度1~50μg/L范围内线性良好,19种PBBs单体检出限为0.147~0.230μg/L,相对标准偏差为6.61%~10.5%,加标回收率为61.5%~82.6%。     

Economic and Spatial Impacts of an Existing Reserve Network on Future Augmentation

An optimization model for land reservation was developed that explicitly selects parcels in the most compact or contiguous manner possible while meeting habitat requirements and a budget limitation. The model was used to compare the effects of an existing reserve network on future parcel spatial locations and total cost. Using habitat and land value data from Josephine County, Oregon, it was found that a system of existing reserves created by various policies and overseen by different agencies can decrease future reserve compactness and contiguity, and increase total cost. This work suggests that coordinated planning can result in more efficient conservation efforts for less cost.     

Modelling of Materials Policies

This paper discusses the REAP1 model and its application for the analysis of CO₂ reduction and waste management policies for Japanese petrochemicals. The pros and cons of this modelling approach in comparison to other tools is elaborated. This is followed by a discussion of the model code and the modelling results. The results show that CO₂ policies can have significant impacts on waste flows and waste policies can have significant CO₂ benefits. As a consequence both effects must be considered in policy assessment. Pricing instruments are recommended instead of regulations because of the complex physical relations in the materials life cycle that extend beyond sector boundaries. A taxation approach is superior to a subsidy approach because rebound effects can be avoided.     

Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.