Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

炉渣在锅炉湿法除尘废水处理中的应用

利用燃煤炉渣直接过滤处理锅炉湿法除尘废水 ,可以提高出水水质 ,对废水中 SS、CODcr和HSO4- 有显著去除效果 ,出水可以满足循环回用要求     

基于离线采集模式的高低温低气压试验箱校准技术的研究

针对高低温低气压箱校准技术展开研究,分析了传统校准方案的不足之处,提出了一种基于离线采集模式的高低温低气压试验箱温度、压力校准方案,并结合虚拟仪器、数据库与MATLAB,完成了该方案的设计与实现。最后通过实验验证了该方案的可靠性与可行性,并应用到环境与可靠性工作中。     

Identification of managerial shaping factors in a petrochemical plant by resilience engineering and data envelopment analysis

Resilience engineering (RE) is a novel approach that is capable of controlling and limiting incidents and accidents. This study identifies managerial shaping factors in a petrochemical plant by RE and data envelopment analysis (DEA). To do this, a standard questionnaire containing resilient factors is completed by managers of a petrochemical plant. Then, the best DEA model is selected based on average efficiency and statistical test. In addition, sensitivity analysis are performed to identify the most important shaping factors. Reporting culture, management commitment, and preparedness are identified as the most important factors in this paper, respectively. Finally, the proposed model is validated and verified through statistical experiment. The proposed approach would help managers to have a comprehensive understanding of the plant with respect to the RE. To the best of our knowledge this is the first paper that examines resilient shaping factors in a petrochemical plant with respect to management and organization by DEA.     

A new methodology for the synthesis of an optimum flexible water networks

This paper presents a new optimization model for the synthesis of direct reuse/recycle water networks with data uncertainties. In this case, data uncertainties were originated from the varying parameters of the water sources and sinks, which fluctuate within a given range of values. The aim of the method is to design an optimum flexible water network (FWN) that ensures minimum fresh water consumption and yet fulfilling all process constraints and uncertain parameters. The resulting FWN also features the minimum number of pipelines, which will ease process operation and control. Due to the complexity of the problem, multistep solving method based on theorem of corner points has been developed. The FWN obtained using the proposed method also includes information on the maximum flow rate in the pipelines, which is essential for detailed network design stage. The resulting model is a mixed integer linear problem (MILP), which may be solved to obtain global optimum solution. Two case studies were used to elucidate the newly proposed method.     

旋风除尘器筒体倾斜角的仿真与优化

旋风除尘器结构简单、造价低廉、能耗极低,故得以长期应用,但其除尘效率因设计方法比较粗糙一般在60%以下,从而限制了其使用范围。很多结构参数均影响除尘器的效率,其中除尘器筒体的倾斜角度对效率的影响程度最高。以有限元理论为基础,以Fluent软件为工具,对关于除尘效率与倾斜角度依赖关系进行了系列仿真和优化,得出结论:若空气中颗粒物直径大于2.5μm,除尘器倾斜角为12.4°时,其除尘效率理论上可达到97%以上。通过实验初步验证了上述结果的可信度。     

Development and case study of a science-based software platform to support policy making on air quality

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias < 2% and assisting in air quality policy making in near real time.     

Atmospheric sulfur hexafluoride in-situ measurements at the Shangdianzi regional background station in China

We present in-situ measurements of atmospheric sulfur hexafluoride（SF6） conducted by an automated gas chromatograph–electron capture detector system and a gas chromatography/mass spectrometry system at a regional background site, Shangdianzi,in China, from June 2009 to May 2011, using the System for Observation of Greenhouse gases in Europe and Asia and Advanced Global Atmospheric Gases Experiment（AGAGE）techniques. The mean background and polluted mixing ratios for SF6 during the study period were 7.22 × 10-12（mol/mol, hereinafter） and 8.66 × 10-12, respectively. The averaged SF6 background mixing ratios at Shangdianzi were consistent with those obtained at other AGAGE stations located at similar latitudes（Trinidad Head and Mace Head）, but larger than AGAGE stations in the Southern Hemisphere（Cape Grim and Cape Matatula）. SF6 background mixing ratios increased rapidly during our study period, with a positive growth rate at 0.30 × 10-12year-1. The peak to peak amplitude of the seasonal cycle for SF6 background conditions was 0.07 × 10-12, while the seasonal fluctuation of polluted conditions was 2.16 × 10-12. During the study period, peak values of SF6 mixing ratios occurred in autumn when local surface horizontal winds originated from W/WSW/SW/SWS/S sectors, while lower levels of SF6 mixing ratios appeared as winds originated from N/NNE/NE/ENE/E sectors.     

The impact of privatization approaches on the productivity growth of the water industry: A case study of Chile

The water industry faces the challenge of implementing privatization reforms. This process mainly adopts the following two approaches: the privatization of public water and sewerage services (WSS) and the privatization of water companies’ ownership. This paper investigates the impact of both privatization approaches on changes in productivity in the water industry. In doing so, the Luenberger productivity indicator (LPI) was computed for a sample of Chilean water and sewerage companies (WaSCs) for the period 1997–2013. Unlike the most commonly applied index (Malmquist productivity index), the LPI simultaneously takes into account output expansion and input contraction. The results evidenced that productivity in the Chilean water industry decreased after its privatization. However, in the sub-periods in which the ownership of WaSCs was privatized, the productivity of the water industry increased due to technical improvements. On the other hand, the concession of WWS to private WaSCs involved a regression in productivity. From a policy perspective, regulators and managers of WaSCs at the international level can learn important lessons from the Chilean case to improve the productivity of the water industries in their countries.     

The issue of sustainability and disclosure. A case study of selective garbage collection by the Urban Cleaning Service of the city of Rio de Janeiro, Brazil - COMLURB

The Urban Cleaning Company of the City of Rio de Janeiro - COMLURB launched the Recycling Separation Center Project (Projeto Central de Separação de Recicláveis or CSR) in 2003. The objectives of the project were the adequate disposal of solid urban waste as well as the generation of employment and income. The COMLURB Project had economic, environmental and social facets, and the researchers sought to establish whether COMLURB had prepared reports that would enable evaluation of the investment made and the results obtained. In particular, the researchers sought to establish whether COMLURB financial statements set out the results of actions inherent to the CSR. We concluded from our analysis of the Project that the three elements of sustainability (social, environmental and economic), despite being fully present, were not adequately demonstrated. This study therefore proposes a model report with a view to enabling various information users to evaluate the results of the CSR Project.