三普2#地热站供热工程设计方案优化分析

通过分析地热供热的相关概念，建立了高效利用地热能源的一系列实现途径。根据工程的基础材料，从技术和经济方面对单纯地热供热方案、地热燃气调峰方案、热泵配置方案以及最终的组合方案进行了优化和调整，从而为三普2#地热井供热工程提供了优化方案，提高了该地区的地热利用率。     

CONJUNCTIVE SURFACE AND GROUND WATER MANAGEMENT IN THE JAKARTA REGION,INDONESIA1

ABSTRACT: This study investigates the degree of economic inefficiency of the current institutional arrangements for surface and ground water management in meeting urban water demand in the Jakarta region. A numerical model of integrated surface and ground water management is developed using GAMS (General Algebraic Modelling System) software. The model maximizes the net present value of social benefits from piped water and ground water consumption across all users over time from 1999 to 2025. Four policy scenarios are examined: the status quo, the social planner's solution, and two ground water pumping quota scenarios: an aggregate ground water pumping quota and a partial quota applied to commercial and industrial users. Three variations in each policy scenario are considered: investment in water infrastructure of the Jakarta water enterprise (PAM Jaya), water demand growth, and discount rates. The status quo, depending on the investment option, the growth of water demand, and the discount rate, results in a 7.4 to 47.8 percent loss in economic efficiency relative to the social planner's solution. The partial quota is the most feasible, applicable, and manageable scenario. The optimal investment option could increase the volume of piped water supply and reduce the cost of water production. The volume of water delivery could increase by up to 156 percent, but it implies only a 35 percent increase in the surface raw water demands above the current level. However, it does not significantly reduce cumulative ground water extraction over the time period considered.     

MULTIPLE CRITERIA ANALYSIS FOR WATER QUALITY MANAGEMENT IN THE NITRA BASIN1

ABSTRACT: This paper presents the implementation of one element of a decision support system (DSS) for regional water quality management, applied to the Nitra River Basin in Slovakia. A model-based, aspiration-led methodology for multicriteria decision support has been used for the study. Several reusable, modular software tools have been developed and implemented: a problem-specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed-integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the imbedded water quality model), a summary of the aspiration-reservation-led multiple criteria optimization approach applied to decision support, and an overview of results that illustrate the applied approach and provide some interesting insights to the case study.     

A multi-objective optimization framework for surfactant-enhanced remediation of DNAPL contaminations

The occurrence of Dense Non-Aqueous Phase Liquid (DNAPL) contaminations in the subsurface is a threat for drinkwater resources in the western world. Surfactant-Enhanced Aquifer Remediation (SEAR) is widely considered as one of the most promising techniques to remediate DNAPL contaminations in-situ, be it with considerable additional costs compared to classical pump-and-treat remediations. A cost-effective design of the remediation set-up is therefore essential. In this work, a pilot SEAR test is executed at a DNAPL contaminated site in Belgium in order to collect data for the calibration of a multi-phase multi-component model. The calibrated model is used to assess a series of scenario-analyses for the full-scale remediation of the site. The remediation variables that were varied were the injection and extraction rate, the injection and extraction duration, and the surfactant injection concentrations. A constrained multi-objective optimization of the model was applied to obtain a Pareto set of optimal remediation strategies with different weights for the two objectives of the remediation: (i) the maximal removal of DNAPL and (ii) a total minimal cost. These Pareto curves can help decision makers to select an optimal remediation strategy in terms of cost and remediation efficiency. The Pareto front shows a considerable trade-off between the total remediation cost and the removed DNAPL mass.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Recent developments in the application of risk analysis to waste technologies

The European waste sector is undergoing a period of unprecedented change driven by business consolidation, new legislation and heightened public and government scrutiny. One feature is the transition of the sector towards a process industry with increased pre-treatment of wastes prior to the disposal of residues and the co-location of technologies at single sites, often also for resource recovery and residuals management. Waste technologies such as in-vessel composting, the thermal treatment of clinical waste, the stabilisation of hazardous wastes, biomass gasification, sludge combustion and the use of wastes as fuel, present operators and regulators with new challenges as to their safe and environmentally responsible operation. A second feature of recent change is an increased regulatory emphasis on public and ecosystem health and the need for assessments of risk to and from waste installations. Public confidence in waste management, secured in part through enforcement of the planning and permitting regimes and sound operational performance, is central to establishing the infrastructure of new waste technologies. Well-informed risk management plays a critical role. We discuss recent developments in risk analysis within the sector and the future needs of risk analysis that are required to respond to the new waste and resource management agenda.     

Modeling thermal analysis for predicting thermal hazards relevant to transportation safety and runaway reaction for 2,2′-azobis(isobutyronitrile)

The pure decomposition behavior of 2,2′-azobis (isobutyronitrile) (AIBN) and its physical phase transformation were examined and discussed. The thermal decomposition of this self-reactive azo compound was explored using differential scanning calorimetry (DSC) to elucidate the stages in the progress of this chemical reaction. DSC was used to predict the kinetic and process safety parameters, such as self-accelerating decomposition temperature (SADT), time to maximum reaction rate under adiabatic conditions (TMR_ad), and apparent activation energy (E_a), under isothermal and adiabatic conditions with thermal analysis models. Moreover, vent sizing package 2 (VSP2) was applied to examine the runaway reaction combined with simulation and experiments for thermal hazard assessment of AIBN. A thorough understanding of this reaction process can identify AIBN as a hazardous and vulnerable chemical during upset situations. The sublimation and melting of AIBN near its apparent onset decomposition temperature contributed to the initial steps of the reaction and explained the exothermic attributes of the peaks observed in the calorimetric investigation.     

Joint analysis of process and operator performance in chemical process operational safety

Independent studies of case histories by the Health and Safety Commission in the UK and by a Honeywell led industrial consortium world-wide showed that human errors represent the major cause of failure in process plant operation. In contrast to this discovery the majority of previous studies on computer aided systems for fault detection and diagnosis has focused on the process side. This paper presents a methodology, which can involve human factors into the development of systems for automatic identification and diagnosis of abnormal operations and develops methods and techniques that can be used to simultaneously capture, characterise and assess the performance of operators as well as of the process. A joint process–operator simulation platform is developed which is used as a test-bed for carrying out the study. The process part is a simulator, which simulates in high fidelity the dynamic behaviour of the process that is subject to the influence of various disturbances and operators’ interventions. The operator module is developed as a real-time expert system, which emulates operator’s behaviour in interpretation of received signals, and planning and execution of decisions. The interaction between the two modules is managed through an interaction module, which handles the real-time exchange of data using Dynamic Data Exchange. The interaction module also contains the toolkits for analysing the dynamic behaviour of the joint process–operator system. The method and system are illustrated using a simulated case study.     

废水污染物总量监测中采样方法的研究

通过对21家有代表性的废水污染源进行现场采样、排放曲线分析、采样频率优化的研究,确定总量监测中采样频率优化结果,为污染源总量控制监测提供技术指导。     

高阶段尾砂胶结充填体力学研究与博弈树配比优化

在实验室试验了不同配比尾砂胶结试块强度,在充填采场取样测试了采场充填体强度.结果表明,如果以实验室试验的力学参数为充填配比设计依据,充填体最小设计安全系数为1.6～1.8比较合理.分析高阶段充填体受力,推导了分层充填力学计算公式及安全系数计算方法;根据充填工艺,确定最小充填高度,沿采场高度方向划分配比优化单元,建立了高阶段充填体配比优化设计模型;采用博弈树分析方法,解决了高阶段充填体配比优化问题,并对安庆铜矿5号矿房配比进行了优化.结果显示:与经验设计方法相比,采用本文方法优化充填配比,不仅使高阶段充填体内安全系数分布更趋合理,而且降低了水泥消耗.