基于Omniclass的唯一编码及水利工程BIM集成交付

数据编码的统一性决定了BIM数据传递效率与集成化交付质量。对比Omniclass、KKS等不同编码类型,提出一种Omniclass与KKS编码的映射规则。建立水利工程中以功能分建筑物、以功能分空间和元素3种分类标准,扩展至水利工程全生命周期BIM信息分类。提出基于Omniclass分类技术的新型BIM唯一编码结构,对该编码结构进行广义和简化广义定义。提出水利工程BIM唯一编码的实践流程和存储交换方式。以水利工程中典型泵闸工程为例,应用Bentley平台对模型加载该新型唯一编码,导出整体模型编码用于数据存储及交换。借鉴CoBie标准,通过以BIM唯一编码为核心牵引作用,以LOD的模型精细度为框架数据模板,实现了服务于水利工程的BIM管理平台和BIM数据集成交付。     

A Rough Set Based Model in Water Quality Analysis

Due to pollution caused by the expansion of human activities and economic development, water quality has gradually deteriorated in many areas of the world. Therefore, analysis of water quality becomes one of the most essential issues of modern civilization. Integrated interdisciplinary modeling techniques, providing reliable, efficient, and accurate representation of the complex phenomenon of water quality, have gained attention in recent years. With the ability to deal with both numeric and nominal information, and express knowledge in a rule-based form, the Rough Set Theory (RST) has been successfully employed in many fields. However, the application of RST has not been widely investigated in water quality analysis. The reducts generated by RST models become very time-consuming as the size of the problem increases. Using multinomial logistics regression (MLR) techniques to provide reducts of RST models, this investigation develops a hybrid Multinomial Logistic Regression and Rough Set Theory (MLRRST) model to analyze relations between degrees of water pollution and environmental factors in Taiwan. Empirical results indicate that the MLRRST model could analyze water qualities efficiently and accurately, and yield decision rules for the staff of water quality management. Thus, the proposed model is a promising and helpful scheme in analyzing water quality.     

基于改进组合赋权物元可拓模型的泥石流危险性评价

针对泥石流危险性评价中权重和危险度,基于改进的组合赋权物元可拓评价模型,提出确定权重的优化算法。首先,根据文献分析泥石流危险度的分级标准,建立危险度评价指标,然后结合可拓物元评价理论,针对可拓法各指标权重确定的问题,将层次分析法计算得到的主观权重结合投影寻踪法所得到的客观权重通过距离函数进行耦合,从而获取各指标最终的综合权重,结合投影寻踪法优化蝙蝠算法进行求解,形成泥石流评价的组合赋权物元可拓模型。最后,借助Mat lab语言,调用内嵌工具箱和相应数学函数,编制程序得以实现。结合已有工程实例验证表明:危险性评价与实际工程相符合,评价结果相对合理,具有一定的工程应用价值。     

基于协商对策的群决策模型及其在跨流域调水方案优选中的应用

本文分析了调水方案决策的多目标性和群决策性特点,研究基于"满意原则"的多人多目标决策模型。重点针对决策者利益的有限冲突性,提出基于协商对策的多目标群决策模型。以辽宁省"引细入汤"工程方案决策为例,构筑了由冲突双方和仲裁方组成的三方仲裁局势,并详细阐述模型的求解过程。该模型在满足公平性原则前提下,兼顾了冲突双方及整体利益,具有较强的可操作性和实用性。     

Comprehensive Evaluation Model of Debris Flow Risk in Hydropower Projects

Debris flow risk in hydropower project is influenced by many factors such as own characteristics of debris flow, the scale and importance of hydropower project. It is a multi-index comprehensive evaluation problem for debris flow risk. According to the features on debris flow risk in hydropower project, the case-based reasoning method and fuzzy optimal recognition method are adopted to build the evaluation model for debris flow risk. Firstly, an evaluation index system of debris flow risk, which can describe the multiple influence factors on debris flow risk in hydropower project, is proposed. Based on the historical debris flow data, a typical debris flow base is established. Secondly, considering the uncertainty of debris flow in hydropower project, two evaluation models of debris flow risk, namely case-based reasoning model and fuzzy optimal recognition model, are established. Lastly, the two models are used to analyze and evaluate the debris flow risk in one actual hydropower project. The capabilities of two models are compared. It is indicated that the proposed models are suitable to be used to implement the comprehensive evaluation of debris flow risk in hydropower projects.     

Rule-based Decision Support System for the Morphological Rehabilitation of Watercourses

A rule-based decision support system (DSS) has been developed to assist decision makers in preparing the EU programme of measures. The rehabilitation of morphological structures of small and medium-sized watercourses in Germany is the main objective. The lack of quantitative date and knowledge is the main obstacle in hydromorphological modelling. Therefore, DSS manipulates the decision-making process in a qualitative manner based on the knowledge of experts. The acquired knowledge is used to formulate ‘if–then’ rules to solve modelling problems. The developed DSS enables decision makers to select any watercourse in the German state of North Rhine-Westphalia (NRW), investigate the feasibility of different rehabilitation measures, predict the impact on the morphological structure and prepare a programme of morphological measures including cost estimation. The system has been implemented for the watercourses in NRW and validated with field data. First results show good agreement between the proposed morphological rehabilitation measures and the implemented ones as well as a satisfactory performance in predicting the morphological structure after implementation of the rehabilitation measures.     

Model-Based Optimization of Downstream Impact during Filling of a New Reservoir: Case Study of Mandaya/Roseires Reservoirs on the Blue Nile River

The aim of this paper is to develop a methodology based on coupled simulation-optimization approach for determining filling rules for the proposed Mandaya Reservoir in Ethiopia with minimum impact on hydropower generation downstream at Roseires Reservoir in Sudan, and ensuring power generation at Mandaya Reservoir in Ethiopia. The Multi-Objective Optimization (MOO) approach for reservoir optimization presented in this paper is a combination of simulation and optimization models, which can assist decision making in water resource planning and management (WRPM). The combined system of reservoirs is set in MIKE BASIN Simulation model, which is then used for simulation of a limited set of feasible filling rules of the Mandaya reservoir according to the current storage level, the inflow, and the time of the year. The same simulation model is then coupled with Multi-Objective optimization Non-dominated Sorting Genetic Algorithm (NSGA-II), which is adopted for determining optimial filling rules of the Mandaya Reservoir. The optimization puts focus on maximization of hydropower generation in both the Mandaya and the Roseires Reservoirs. The results demonstrate that optimal release- (and correspondingly filling-) rules for Mandaya Reservoir which maximize the hydropower generation in both Mandaya and Roseires reservoirs can be found. These rules are determined along the Pareto frontier obtained by the optimization algorithm, which can serve as a decision support tool for choosing the actual filling rule. The results also showed that the NSGA- II is an efficient and powerful tool that could assist decision makers for solving optimization problems in complex water resource systems.     

An Intelligent Decision Support System for Management of Floods

Integrating human knowledge with modeling tools, an intelligent decision support system (DSS) is developed to assist decision makers during different phases of flood management. The DSS is developed as a virtual planning tool and can address both engineering and non-engineering issues related to flood management. Different models (hydrodynamic, forecasting, and economic) that are part of the DSS share data and communicate with each other by providing feedback. The DSS is able to assist in: selecting suitable flood damage reduction options (using an expert system approach); forecasting floods (using artificial neural networks approach); modeling the operation of flood control structures; and describing the impacts (area flooded and damage) of floods in time and space. The proposed DSS is implemented for the Red River Basin in Manitoba, Canada. The results from the test application of DSS for 1997 flood in the Red River Basin are very promising. The DSS is able to predict the peak flows with 2% error and reveals that with revised operating rules the contribution of Assiniboine River to the flooding of Winnipeg city can be significantly reduced. The decision support environment allows a number of “what-if” type questions to be asked and answered, thus, multiple decisions can be tried without having to deal with the real life consequences.     

Simulation-optimization model of reservoir operation based on target storage curves

This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization （IPSO） algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.     

A realistic linear decision rule for reservoir management

A generalized linear decision rule is presented which takes into account the aspect of spill in a multi-lag LDR model. The proposed rule incorporates past inflow experience to determine the optimum release rules based on a stochastic (linear) programming optimization model. It also prescribes a procedure of determining spill, should it occur, and the method of adjusting the release policy, accordingly, for the subsequent periods, which are directly affected by the spill of the current period. The use of the rule also makes it possible to produce a specification for a reservoir with a smaller capacity by taking liberal constraints on the reservoir freeboard during the monsoon months. The problem is solved, for the purpose of illustration, using the historical data of a river located in central India. Two synthetic streamflow series of a duration of 50 years each are generated under lognormal flow assumption. The prescribed release rules are applied to a hypothetical reservoir with the optimum capacity determined by the linear programming method, and the generated series as the inflow. The results and findings are quite satisfactory.     

An information-based rough set approach to critical engineering factor identification

In order to analyze the main critical engineering factors, an information-based rough set approach that considers conditional information entropy as a measurement of information has been developed. An algorithm for continuous attribute discretization based on conditional information entropy and an algorithm for rule extraction considering the supports of rules are proposed. The initial decision system is established by collecting enough monitoring data. Then, the continuous attributes are discretized, and the condition attributes are reduced. Finally, the rules that indicate the action law of the main factors are extracted and the results are explained. By applying this approach to a crack in an arch gravity dam, it can be concluded that the water level and the temperature are the main factors affecting the crack opening, and there is a negative correlation between the crack opening and the temperature. This conclusion corresponds with the observation that cracks in most concrete dams are influenced mainly by water level and temperature, and the influence of temperature is more evident.     

水资源危机预警模型

针对水资源危机的特点,提出用尖点突变模型进行系列年水资源危机识别,将识别因子作为条件属性、识别结果作为决策属性来构建决策表,用粗糙集理论对决策表进行属性约简,得到水资源危机预警指标和预警决策规则,用BP神经网络滚动预测预警指标,将指标的预测结果带入预警决策规则进行水资源危机判别,以此建立了水资源危机预警的CC-RS-BP模型。该模型是以规则形式进行预警判别,易被理解和利用,为水资源危机预警提供了新的思路。     

川藏铁路宋家沟泥石流发育特征及危险性分析

宋家沟为一条活跃的泥石流沟,该沟历史上曾爆发过较大规模泥石流灾害,对沟口新建川藏铁路升航大桥构成潜在威胁。通过区域资料收集、遥感解译技术、野外地质调查、室内实验分析与参数计算等综合手段,在研究泥石流的发育特征及形成条件的基础上,评价其危险性,针对泥石流对铁路工程的影响,给出防治建议。研究结果表明:宋家沟流域内泥石流的松散固体物质来源的类型主要包括坡面及冲沟物源、崩塌物源、工程弃渣物源和沟道物源;宋家沟泥石流活动处于发展期,泥石流的危险度属于中度危险,与实际调查结果一致。研究成果可为新建川藏铁路类似工程的防灾减灾提供借鉴。     

泥石流柔性防护系统破坏原因分析与设计对策

泥石流柔性防护系统对于中小型泥石流有很好的防治效果,但在实际工程中很容易发生破坏。为研究泥石流柔性防护系统破坏原因,介绍了泥石流柔性防护系统的构成与优势、破坏原理、破坏形式,并针对四川省道217某段公路改建工程的泥石流柔性防护工程,分析了系统的设计、构件、基础等方面的问题,得出主要破坏原因是设计不合理,未完全按照定型化设计,基础发生破坏,构件发生破坏。同时对泥石流柔性防护工程的设计提出了一些建议,以期提高其拦截能力。     

基于FLO-2D的泥石流工程治理效果分析——以都江堰银洞子沟泥石流为例

选取地震区典型泥石流沟银洞子沟作为研究对象,运用FLO-2D软件再现该沟2013年泥石流发生过程,验证了通过研究区雨量数据获取泥石流流量线方法的可靠性以及相关模拟参数选取的合理性。在此基础上,基于泥石流发生频率和暴雨爆发频率相同的假设,对不同爆发频率下的泥石流工程治理效果进行了分析。结果表明:工程治理后,当爆发频率为30,50 a时,工程治理效果显著;当爆发频率为100 a时,工程治理效果不显著。因此,建议相关管理部门加强极端降雨条件下泥石流的预警和防治工作。     

降雨型滑坡泥石流灾害预警原理及系统结构

降雨型滑坡泥石流预警必须具有超前性。通过对前期研究成果的分析总结,可以将降雨型滑坡泥石流预警分为空间预警和时间预警两大类型。空间预警的目标是预测宏观区域内滑坡泥石流灾害的发生趋势,划分不同时段的危险区范围;时间预警的目标是预报典型滑坡泥石流可能发生的时间阶段。根据预警分类原理,建立了实现两类灾害预警的技术方法体系,构建了降雨型滑坡泥石流预警的系统结构。     

A Forecast Model of Hydrologic Single Element Medium and Long-Period Based on Rough Set Theory

On the basis of rough set theory, this paper presents the single element medium- and long-term classification forecast model that uses historical data of a hydrologic series as forecast factors. The minimal rule set, i.e., forecast pattern set, is achieved according to the principle of maximal attribute significance and rules frequency. Maximal support strength is put forward and applied to predict by using the model. The model is applied to forecast annual runoff of Dahuofang reservoir. The result indicates that the forecast model based on rough set can describe the relationship between forecast factors and forecast object efficiently and accurately. This model, which is composed of simple solution rules, can be easily understood and applied.     

Spatial Decision Support System for Watershed Management

A prototype spatial decision support system (SDSS) is presented for watershed management. The SDSS integrates landuse/landcover derived from the remote sensing data, real-time hydrological data, geographic information system, and a model-based subsystem for computing soil loss, land capability classification and engineering measures. A graphical user interface has been developed to allow effective use by decision makers. The model-based subsystem employs a process-based soil erosion model to compute soil loss in spatial environment. Computed pixel-based soil loss information is an input to the land capability classification and watershed management modules. The developed SDSS can help the end users in avoiding the laborious procedures of soil erosion calculations and analysing various thematic layers to get suitable watershed management practices. The SDSS for watershed management is applied to the Tones watershed in India to compute soil loss, to prioritise watersheds, and to suggest various watershed management practices.     

入汇主河的泥石流龙头运动机理研究

作者基于野外观测资料和模型试验，提出了泥石流与主河交汇的两种模式，即：有上下分层交汇和无明显分层的潜入式交汇。建立了潜入式交汇的泥石流龙头运动方程，并讨论了模型参数的取值。计算结果得到以下结论：当主河水流费劳德数比较小(Fr＜0.35)时，入汇主河泥石流龙头在主河的运动速度近似以线性减速，且与试验值吻合较好；混合流粘滞系数和绕流系数对龙头运动速度影响较大；泥砂沉降速度对龙头内部体积比浓度有显著影响。     

Models for Better Environmental Intelligent Management within Water Supply Systems

The paper presents models for better environmental intelligent management within water supply systems. The following computer models were developed: supervising parameters (pressure and flow) of water supply network (classification models in the form of neural networks, hybrid neural networks, decision trees and multiple decision trees), forecasting of water supply network load in different intervals of time (prediction models in the form of neural networks and hybrid neural networks), preferences for network operator and consumer in the form of decision rules and decision trees, classification of exceptions, typical examples and preferences for controlling water flow, controlling of pumps in the water supply network in the form of decision and activity rules and controlling of pumps for filling up retention tanks in the form of decision and action rules. These models were compared with a view to obtaining optimal models to control the parameters of water supply networks. The models are embedded in intelligent decision support system with a knowledge acquisition module. The research was done for Municipal Water Supply and Sewage Company in Rzeszów, Poland.