沿海风暴潮预警预报与灾情评估系统研究

台风是一种严重的自然灾害,引起的风暴增水会对沿海城市产生较大危害,快速准确的风暴潮预警预报及灾情评估是当前研究的热点和难点问题。结合实际业务需求,借鉴类似系统的开发模式,设计提出适用于沿海风暴潮预警预报与灾情评估系统的总体架构,开发预报与评估系统前端主要功能和服务器端相关功能组件,并在广东省进行应用部署。应用结果表明,预报和评估系统实用性和可操作性强,可为沿海防汛部门在台风期的防台会商决策提供强有力的技术支撑。     

Scalability of an Unstructured Grid Continuous Galerkin Based Hurricane Storm Surge Model

This paper evaluates the parallel performance and scalability of an unstructured grid Shallow Water Equation (SWE) hurricane storm surge model. We use the ADCIRC model, which is based on the generalized wave continuity equation continuous Galerkin method, within a parallel computational framework based on domain decomposition and the MPI (Message Passing Interface) library. We measure the performance of the model run implicitly and explicitly on various grids. We analyze the performance as well as accuracy with various spatial and temporal discretizations. We improve the output writing performance by introducing sets of dedicated writer cores. Performance is measured on the Texas Advanced Computing Center Ranger machine. A high resolution 9,314,706 finite element node grid with 1 s time steps can complete a day of real time hurricane storm surge simulation in less than 20 min of computer wall clock time, using 16,384 cores with sets of dedicated writer cores.     

Modelling coastal barrier breaching flows with well-balanced shock-capturing technique

This paper presents a coastal hydrodynamic model for simulating coastal barrier breaching flows through an inlet which are mostly induced by extreme hydrological conditions such as storm/hurricane surges, waves and tides. In order to simulate wave field and wave-induced flow field in a coast, a wave action spectral model is coupled with a hydrodynamic model. The Godunov-type shock-capturing technique is used in the hydrodynamic model to simulate the supercritical flows and shocks driven by the extreme storm conditions. The hydrodynamic model is based on the solution of depth-averaged non-linear shallow water equations with all physical forcings common to coastal hydrological conditions so that it is capable of simulating multiple flow regimes, in which subcritical, transcritical, or supercritical flows may happen. The bed slope terms in the system of equations are treated in such a way that exact balance between flux gradient and bed slope terms is achieved under still water condition. The wave model readily provides the radiation stresses that represent the shortwave-averaged forcings in a water column and take into account wave-induced nearshore currents. In the coupled system, the models are operated systematically. The coastal hydrodynamic model is shown to accurately reproduce analytical and benchmark numerical solutions. To further test the accuracy of the model, flow through a coastal inlet with a storm surge is simulated and the results are compared with an established coastal flow model. Finally, the model is examined to simulate a severe storm surge that develops supercritical flows and the results are found to be encouraging.     

Predictions of typhoon storm surge in Taiwan using artificial neural networks

Accurate predictions of storm surge and surge deviation are essential for industrial activities in coastal areas. Usually numerical hydrodynamic models or empirical methods are used to estimate the storm surge. This paper proposes an alternative back-propagation neural network (BPN) approach to forecast the storm surge and surge deviation. The prediction of storm surge from a previous typhoon is used as a training set to form predictions for the next event. Wind velocity, wind direction, atmospheric pressure and astronomical tide were selected as inputs in the neural network. The observations obtained during three typhoons from four stations in Taiwan were used to illustrate performance of the BPN model. Comparisons with numerical methods indicate that the storm surge and surge deviation can be efficiently predicted using BPN.     

Intelligent sleeping car berth inventory control system in the case of variable capacity of railcars

Managing ticket reservations in passenger rail transport is a complex task. A hybrid algorithm is developed as a decision support tool. The aim of the proposed algorithm is to provide real‐time decisions on seat inventory allocation taking into account relevant information from the past. This paper considers the revenue management application in passenger rail transport with variable capacity of sleeping cars. Uncertainty of capacity availability is embedded in the developed algorithm through a payoff table, while an Artificial Neural Network is used as a tool for making real‐time decisions. The algorithm is tested on hypothetical data.     

Implementation of a TMO‐structured real‐time airplane‐landing simulator on a distributed computing environment

In real‐time simulation, the simulated system should display the same (or very close) timing behavior as the target system. The simulation accuracy is increased as the simulation time unit is decreased. Although there are several models for such systems, the TMO model is particularly appropriate due to its natural support for real‐time distributed object‐oriented programming. This paper discusses the results of the implementation of a real‐time airplane‐landing simulator on a distributed computing environment using the TMO model. Copyright © 2004 John Wiley & Sons, Ltd.     

Project Mercury's man-in-space real-time computer system:“you have a go, at least seven orbits”

Project Mercury was the first US venture to send a man into space. The project lasted 55 months, involved more than 2 million people, and cost more than $400 million. In retrospect, Project Mercury's real time computer programming, and data processing aspects seem a minor element of the total project. Historical accounts of Project Mercury do not say much, if anything, about its computer based activities. These computer based activities include the real time computing accomplishments of a team of about 100 scientists, programmers, and engineers that paved the way for future manned space projects and gave the computer profession its first glimpse of a real time computing system that was predicated on the safety requirements of a man-in-the-loop. The article describes the real time computational requirements, the procedures, and the equipment that were developed to support this pioneering project, as well as some personal observations     

并行搜救算法在确定灾后搜救路线中的应用*

针对风暴潮辅助决策系统中对受灾区域进行灾后搜救的问题,提出了将搜救队伍扩展为两支的特殊情况下如何进行搜救路线的确定。根据总体上搜救效率达到最优的要求,在Prim算法基础上提出了并行搜救调度算法,实现了高效的搜救路线图的确定,从而使搜救行动可以高效地进行,保证了良好的辅助决策效果。     

Dynamic speed control of a machine tool with stochastic tool life: analysis and simulation

We discuss a tool management model for a flexible machine equipped with a tool magazine, variable cutting speed, and sensors to monitor tool wear, when tool life due to flank wear is stochastic. The objective is to adjust the cutting speed as a function of remaining distance, each time a tool change occurs, in order to minimize the expected processing time (sum of cutting and tool setup time). We address the computational aspects of finding optimal decision rules and we present numerical results suggesting that easily computed decision rules of a simple static model are near-optimal for our dynamic programming model. Dynamic adjustment is assessed with simulation experiments.     

Real‐time nonlinear moving horizon observer with pre‐estimation for aircraft sensor fault detection and estimation

This paper presents a real‐time nonlinear moving horizon observer (MHO) with pre‐estimation and its application to aircraft sensor fault detection and estimation. An MHO determines the state estimates by minimizing the output estimation errors online, considering a finite sequence of current and past measured data and the available system model. To achieve the real‐time implementability of such an online optimization–based observer, 2 particular strategies are adopted. First, a pre‐estimating observer is embedded to compensate for model uncertainties so that the calculation of disturbance estimates in a standard MHO can be avoided without losing much estimation performance. This strategy significantly reduces the online computational complexity. Second, a real‐time iteration scheme is proposed by performing only 1 iteration of sequential quadratic programming with local Gauss‐Newton approximation to the nonlinear optimization problem. Since existing stability analyses of real‐time moving horizon observers cannot address the incorporation of the pre‐estimating observer, a new stability analysis is performed in the presence of bounded disturbances and noises. Using a nonlinear passenger aircraft benchmark simulator, the simulation results show that the proposed approach achieves a good compromise between estimation performance and computational complexity compared with the extended Kalman filtering and 2 other moving horizon observers.     

Modelling decision support and uncertainty for large transport infrastructure projects: The CLG-DSS model of the Øresund Fixed Link

This paper presents a decision support system, named the CLG-DSS model, which makes it possible for decision makers to assess various uncertainties in project appraisal in a systematic and explicit way. This model, a decision support system (DSS) developed within the Danish Centre for Logistics and Freight Transport (CLG) is based on cost-benefit analysis (CBA) embedded in a wider multi-criteria analysis (MCA) by the use of some principles for composite modelling assessment (COSIMA). The CLG-DSS model is set up to make use of scenario analysis (SA) and Monte Carlo simulation (MCS). A particular concern in the model is the handling of varying information across the assessment criteria and the application of SA to inform the MCS parameter setting. After the presentation of the modelling principles some ex-post case calculations for the Øresund Fixed Link are illuminating different aspects of appraisal uncertainty and thereby, at the same time, demonstrate the features of the CLG-DSS model as a useful decision support tool. It is finally concluded that appraisal of large infrastructure projects can be effectively supported by dealing with uncertainty issues in accordance with the principles described.     

Integrated time–cost tradeoff and resources leveling problems with allowed activity splitting

Resource leveling and time–cost tradeoff are among the most challenging optimization problems in project management. These two problems are usually addressed separately because each problem optimizes different objective functions. In this paper, we develop an integrated model that addresses both problems when activities are allowed to split for better utilization of resources. The formulated mixed integer linear program (MILP) model considers the tradeoff between the crashing‐dependent costs; direct and indirect costs, and resource utilization related costs; acquiring, releasing, and splitting costs. The model can be used as a decision tool to determine whether crashing is recommended when decision makers are also concerned with the better utilization of project's resources. A one‐way sensitivity analysis was conducted to assess total cost savings achieved through the integration of time–cost tradeoff and resource leveling problems. Another experimental study was undertaken to evaluate the performance of the MILP runtime.     

Software development with imperfect information

Delivering software systems that fulfill all requirements of the stakeholders is very difficult, if not at all impossible. We consider the problem of coping with imperfect information, like interpreting incomplete requirement specifications or vagueness in decisions, one of the main reasons that makes software design difficult. We define a method for tracing design decisions under imperfect information. To model and compare requirements with estimations, we present fuzzy and stochastic techniques. This approach offers adequate decision support that can deal with imperfect information during software design. The approach is illustrated by a real-world example, based on a storm surge barrier system.     

A model‐based development approach for the verification of real‐time Java code

Many real‐time systems are safety‐and security‐critical systems and, as a result, tools and techniques for verifying them are extremely important. Simulation and testing such systems can be exceedingly time‐consuming and these techniques provide only probabilistic measures of correctness. There are a number of model‐checking tools for real‐time systems. Although they provide formal verification for models, we still need to implement these models. To increase the confidence in real‐time programs written in real‐time Java, this paper proposes a model‐based approach to the development of such programs. First, models can be mechanically verified, to check whether they satisfy particular properties, by using current real‐time model‐checking tools. Then, programs can be derived from the model by following a systematic approach. We introduce a timed automata to RTSJ Tool (TART), a prototype tool to automatically generate real‐time Java code from the model. Finally, we show the applicability of our approach by means of four examples: a gear controller, an audio/video protocol, a producer/consumer and the Fischer protocol. Copyright © 2011 John Wiley & Sons, Ltd.     

A 3D visualization system for hurricane storm-surge flooding

Three-dimensional computer visualization and animation can provide a substitute for coastal residents', lack of personal experience with hurricane-surge flooding. Tremendous progress has been made in 3D animation in the last decade, which movies such as Perfect Storm and The Day After Tomorrow have demonstrated. However, the 3D visualization and animation system for storm-surge flooding differs from those in Hollywood movies in three aspects. First, objects such as buildings, roads, and trees in a synthetic 3D visualization environment not only have to be able to duplicate the real-world feature visually, but also be georeferenced so users can find real locations through addresses or spatial coordinates. The sizes and shapes of buildings and trees have to be accurate so users can sense the severity of flooding by comparing the water level with heights of familiar objects. Second, the magnitude, extent, and process of storm-surge flooding have to be accurate enough to represent the real situation. This information has to be based on hydrodynamics of storm surge. Third, the damage extent of a property caused by storm surge and waves, such as the collapse of a house, must be determined by engineering rules. Recent advances in high-resolution remote-sensing technology and numerical modeling make it possible to provide accurate data for the earth's surface features and storm-surge flooding.     

基于递归神经网络的风暴潮增水预测

风暴潮增水的准确预测能极大地减少人员伤害和经济损失,具有重要的实用价值。传统的风暴潮预报方法主要包括经验和数值预报,很难建立起相对准确的模型。现有的基于机器学习风暴潮预报方法大都只提取出静态数据间的关系,并没有充分挖掘出风暴潮数据背后的时序关联特性。文中提出了一种基于递归神经网络的风暴潮增水预测方法。本文对风暴潮时序数据进行特定的处理,并设计合适结构的递归神经网络,从而完成时序数据的预测。相较于传统的BP神经网络,递归神经网络能更好地应对时序数据的预测问题。将该方法用于潍坊水站的增水预测中,结果表明,相对于BP神经网络,递归神经网络能得到更好的预测结果,误差更小。     

Design and analysis of target‐sensitive real‐time systems

A significant number of real‐time control applications include computational activities where the results have to be delivered at precise instants, rather than within a deadline. The performance of such systems significantly degrades if outputs are generated before or after the desired target time. This work presents a general methodology that can be used to design and analyze target‐sensitive applications in which the timing parameters of the computational activities are tightly coupled with the physical characteristics of the system to be controlled. For the sake of clarity, the proposed methodology is illustrated through a sample case study used to show how to derive and verify real‐time constraints from the mission requirements. Software implementation issues necessary to map the computational activities into tasks running on a real‐time kernel are also discussed to identify the kernel mechanisms necessary to enforce timing constraints and analyze the feasibility of the application. A set of experiments are finally presented with the purpose of validating the proposed methodology. Copyright © 2015 John Wiley & Sons, Ltd.     

Worst‐case execution time analysis for a Java processor

In this paper, we propose a solution for a worst‐case execution time (WCET) analyzable Java system: a combination of a time‐predictable Java processor and a tool that performs WCET analysis at Java bytecode level. We present a Java processor, called JOP, designed for time‐predictable execution of real‐time tasks. The execution time of bytecodes, the instructions of the Java virtual machine, is known to cycle accuracy for JOP. Therefore, JOP simplifies the low‐level WCET analysis. A method cache, which fills whole Java methods into the cache, simplifies cache analysis. The WCET analysis tool is based on integer linear programming. The tool performs the low‐level analysis at the bytecode level and integrates the method cache analysis. An integrated data‐flow analysis performs receiver‐type analysis for dynamic method dispatches and loop‐bound analysis. Furthermore, a model checking approach to WCET analysis is presented where the method cache can be exactly simulated. The combination of the time‐predictable Java processor and the WCET analysis tool is evaluated with standard WCET benchmarks and three real‐time applications. The WCET friendly architecture of JOP and the integrated method cache analysis yield tight WCET bounds. Comparing the exact, but expensive, model checking‐based analysis of the method cache with the static approach demonstrates that the static approximation of the method cache is sufficiently tight for practical purposes. Copyright © 2010 John Wiley & Sons, Ltd.     

Developing a seabed resurvey strategy: A GIS approach to modelling seabed changes and resurvey risk

There has been a steady transition towards the representation, analysis and modelling of dynamic spatio-temporal relationships in geographical information systems (GISs). These developments open up opportunities for investigating and modelling the dynamic relationships that occur in the coastal and marine environments and how these relate to human activities. Such a spatio-temporal approach is applied in this research to address an issue faced by the bodies responsible for maintaining navigation safety in territorial waters and this paper introduces the developed resurvey decision support system. The developed system models morphological change in response to hydrodynamic conditions and determines the seabed locations that require resurvey based on the modelled change and navigation characteristics. System validation tests indicate that the morphological modelling tool is under-predicting the magnitude and lateral extent of the change which then influences the locations that require resurvey. Additional sensitivity tests of the morphological modelling parameters highlight the influence of the parameters on the outputs and derived predictions. The achieved modelling results and resurvey decision indicate the applicability of utilising a GIS to model seabed change as an input into decision support systems for planning and management purposes. The results also suggest the applicability of the modelling and decision support methodology to similar problems in the coastal and marine environments.     

Design and implementation of a decision support system for competitive electricity markets

In this paper we describe software which could be used as a decision support tool for decision makers in competitive electricity markets. The tool is based on the behavior of the competitors in the market, thus many different parameters around them are considered and, additionally, many different scenarios can be used. The possible results are obtained by simulation. Two modes are implemented; one to simulate the functioning of a competitive electricity market and the other, called manual, to evaluate the success of particular strategies by a user. Finally, some computational experience is reported to validate the simulation model.