A mixed finite element/finite volume approach for solving biodegradation transport in groundwater

A numerical model for the simulation of flow and transport of organic compounds undergoing bacterial oxygen- and nitrate-based respiration is presented. General assumptions regarding microbial population, bacteria metabolism and effects of oxygen, nitrogen and nutrient concentration on organic substrate rate of consumption are briefly described. The numerical solution techniques for solving both the flow and the transport are presented. The saturated flow equation is discretized using a high-order mixed finite element scheme, which provides a highly accurate estimation of the velocity field. The transport equation for a sorbing porous medium is approximated using a finite volume scheme enclosing an upwind TVD shock-capturing technique for capturing concentration-unsteady steep fronts. The performance and capabilities of the present approach in a bio-remediation context are assessed by considering a set of test problems. The reliability of the numerical results concerning solution accuracy and the computational efficiency in terms of cost and memory requirements are also estimated. © 1998 John Wiley & Sons, Ltd.     

基于镭同位素示踪的青海湖金沙湾沿岸地下水排放研究

青海湖作为我国内陆最大的咸水湖，针对其水域的研究具有重要的环境意义。采集青海湖金沙湾沿岸9个间隙水样，2个井水样，1个湖水样以及2个降水样。调查研究了青海湖金沙湾间隙水溶解态镭同位素活度的空间分布情况，发现间隙水中²²³Ra和²²⁴Ra的平均活度为3.5 dpm/100 L和162.6 dpm/100 L，均高于井水和湖水。通过对沿湖岸线水平向和垂直向的间隙水镭同位素活度分布研究发现，金沙湾间隙水镭同位素活度随离岸距离的增大而增大、随深度的加深而减小，这与湖水镭同位素活度随离岸距离的变化规律相反。结合镭同位素活度随盐度的变化，发现湖水与间隙水在离岸30 m左右发生了交换，交换深度在1 m以下。最后，通过水平涡动扩散模型估算了金沙湾沿岸表层地下水的排放通量为0.20 m3·m^-2·d^-1。     

电感耦合等离子体原子发射光谱法(ICP-OES)测定地下水中多种元素

应用电感耦合等离子体原子发射光谱法(ICP-OES)测定地下水中钾、钠、钙、镁、铁、锰元素的含量,使用分光光度法测定氟的含量,测定的相对标准偏差为0.7%~2.8%,加标回收率为92.1%~105.2%。结果表明,大部分地区地下水中钠和氟化物的含量均偏高,常量与微量元素的组成含量差别不大。     

液相色谱-原子荧光光谱联用法测定地下水中的三价砷和五价砷

建立了一种利用液相色谱-原子荧光光谱联用法测定地下水中三价砷和五价砷含量的方法。流动相为磷酸二氢钾和磷酸氢二钠,流速1.0mL/min,方法的标准曲线线性相关性好,进样后在10min内分离、测定完毕,操作自动化程度高,重现性好,方法准确可靠,检出限低(As~(3+)、As~(5+)都是0.02μg/L),可同时测定地下水中As~(3+)、As~(5+)的含量。     

Quantum-Like Interdependence Theory Advances Autonomous Human–Machine Teams (A-HMTs)

As humanity grapples with the concept of autonomy for human–machine teams (A-HMTs), unresolved is the necessity for the control of autonomy that instills trust. For non-autonomous systems in states with a high degree of certainty, rational approaches exist to solve, model or control stable interactions; e.g., game theory, scale-free network theory, multi-agent systems, drone swarms. As an example, guided by artificial intelligence (AI, including machine learning, ML) or by human operators, swarms of drones have made spectacular gains in applications too numerous to list (e.g., crop management; mapping, surveillance and fire-fighting systems; weapon systems). But under states of uncertainty or where conflict exists, rational models fail, exactly where interdependence theory thrives. Large, coupled physical or information systems can also experience synergism or dysergism from interdependence. Synergistically, the best human teams are not only highly interdependent, but they also exploit interdependence to reduce uncertainty, the focus of this work-in-progress and roadmap. We have long argued that interdependence is fundamental to human autonomy in teams. But for A-HMTs, no mathematics exists to build from rational theory or social science for their design nor safe or effective operation, a severe weakness. Compared to the rational and traditional social theory, we hope to advance interdependence theory first by mapping similarities between quantum theory and our prior findings; e.g., to maintain interdependence, we previously established that boundaries reduce dysergic effects to allow teams to function (akin to blocking interference to prevent quantum decoherence). Second, we extend our prior findings with case studies to predict with interdependence theory that as uncertainty increases in non-factorable situations for humans, the duality in two-sided beliefs serves debaters who explore alternatives with tradeoffs in the search for the best path going forward. Third, applied to autonomous teams, we conclude that a machine in an A-HMT must be able to express itself to its human teammates in causal language however imperfectly.     

基于易损性与冗余度分析的构件重要性评价方法

为合理评价构件在结构中的重要性,以构件材料的弹性模量为基本参数,并考虑构件刚度变化产生的影响,基于构件应变能对材料弹性模量的敏感性,建立了构件冗余度及其易损性评价指标,以衡量构件的脆弱性和冗余特性。在此基础上将构件的重要性指标定义为构件易损性系数与冗余度系数的比值,实现构件重要性的分类量化。结果表明,采用的构件重要性评价指标能正确反映构件在结构中的重要性,重要性系数高的构件为结构的高易损-低冗余构件,是结构的关键部位和薄弱环节所在,其失效后对结构整体性能的影响较大。加强高易损-低冗余关键构件对于提高结构的整体性能和抗连续倒塌的能力具有重要作用。     

Efficient stochastic finite element methods for flow in heterogeneous porous media. Part 2: Random lognormal permeability

Efficient and robust iterative methods are developed for solving the linear systems of equations arising from stochastic finite element methods for single phase fluid flow in porous media. Permeability is assumed to vary randomly in space according to some given correlation function. In the companion paper, herein referred to as Part 1, permeability was approximated using a truncated Karhunen-Loève expansion (KLE). The stochastic variability of permeability is modeled using lognormal random fields and the truncated KLE is projected onto a polynomial chaos basis. This results in a stochastic nonlinear problem since the random fields are represented using polynomial chaos containing terms that are generally nonlinear in the random variables. Symmetric block Gauss-Seidel used as a preconditioner for CG is shown to be efficient and robust for stochastic finite element method.     

紫外双光束单波长硝酸根原位监测传感器系统的研究

水中硝酸根含量的实时监测是一个亟待解决的现实问题,为了满足硝酸根监测的实时性要求,避免采样、预处理等繁琐的步骤,提出了一种新型的原位监测硝酸根传感器系统的研究设计,介绍了系统的工作原理和构成,该仪器利用双光束单波长标准测量法,不仅能有效消除材料及粒子散射对测量的干扰,而且简化了设计结构。并用紫外分光光度计进行了模拟实验,实验证明,这种新型的传感器系统能够满足指定水域的硝酸根实时监测要求。     

Numerical simulation of three-dimensional saturated flow in randomly heterogeneous porous media

This paper presents a numerical method for simulating flow fields in a stochastic porous medium that satisfies locally the Darcy equation, and has each of its hydraulic parameters represented as one realization of a three-dimensional random field. These are generated by using the Turning Bands method. Our ultimate objective is to obtain statistically meaningful solutions in order to check and extend a series of approximate analytical results previously obtained by a spectral perturbation method (L. W. Gelhar and co-workers). We investigate the computational aspects of the problem in relation with stochastic concepts. The difficulty of the numerical problem arises from the random nature of the hydraulic conductivities, which implies that a very large discretized algebraic system must be solved. Indeed, a preliminary evaluation with the aid of scale analysis suggests that, in order to solve meaningful flow problems, the total number of nodes must be of the order of 10⁶. This is due to the requirement that x _i gl _i L _i , where x _i is the mesh size, _i is a typical correlation scale of the inputs, and L _i is the size of the flow domain (i = 1, 2, 3). The optimum strategy for the solution of such a problem is discussed in relation with supercomputer capabilities. Briefly, the proposed discretization method is the seven-point finite differences scheme, and the proposed solution method is iterative, based on prior approximate factorization of the large coefficient matrix. Preliminary results obtained with grids on the order of one hundred thousand nodes are discussed for the case of steady saturated flow with highly variable, random conductivities.     

Solute Concentration Statistics in Heterogeneous Aquifers for Finite Péclet Values

A Lagrangian framework is used for analysing the concentration fields associated with transport of nonreactive solutes in heterogeneous aquifers. This is related to two components: advection by the random velocity field v(x) and pore-scale dispersion, characterized by the dispersion tensor D _d; the relative effect of the two components is quantified by the Péclet number. The principal aim of this paper is to define the probability density function (pdf) of a nonreactive solute concentration and its relevant moments >C< and ² _c as sampled on finite detection volumes. This problem could be relevant in technical applications such as risk analysis, field monitoring and pollution control. A method to compute the concentration statistical moments and pdf is developed in the paper on the basis of the reverse formulation widely adopted to study solute dispersion in turbulent flows. The main advantages of this approach are: (i) a closed form solution for concentration mean and variance is attained, in case of small size of the sampling volume; (ii) a numerically efficient estimate of the concentration pdf can be derived. The relative effects of injection and sampling volume size and Péclet number on concentration statistics are assessed. The analysis points out that the concentration pdf can be reasonably fitted by the beta function. These results are suitable to be employed in practical applications, when the estimate of probability related to concentration thresholds is required.