Physically accurate nonlinear models for fault detection and diagnosis: the case of a power plant

This paper deals with two main contributions. The first is the definition of an accurate nonlinear model of a section of a real 320 MW power plant. Within the framework of this global method, the second contribution is the modelling of the most common faults that may occur in plants like the one considered in the paper. All these models allow the simulation of the system both under normal working conditions and under anomalous conditions due to the occurrence of one of the faults modelled. The simulated model can be integrated with the automation system of the plant and used in real time, thus providing the plant technicians with crucial information on the plant behaviour, for instance, fault detection and diagnosis can be accomplished in a natural way. Simulation results and comparisons with real data show the effectiveness of the proposed approach.     

A system for simulation, monitoring and diagnosis of controlled continuous processes with slow dynamics

This paper presents a modelling approach specifically designed to be used in a monitoring and diagnosis system based on the simulation of relevant process and control system variables. The model is based on semantically extended data flow diagrams with each computational process representing the incremental behaviour of a component of the plant to be modelled. Variable as well as delay time behaviour is associated with each component model to support an event-driven simulation which, in turn, reduces computation time. This plant model of independent but interacting computational processes is easily extendable, modifiable and adjustable according to changes in the plant.

The modelling approach is applied to a coal power plant process and is implemented in G2, an object-oriented, real-time expert system shell with built-in simulation and online external connection capabilities. Generic rules guiding the event-driven simulation and monitoring allow for modular adaptation of the model as the plant's structure and functionality change without requiring changes in the rule set.     

Modelling and simulation of fabrication and assembly plants: an object-driven approach

This paper presents the technical characteristics and methodologies underlying the computer-aided modelling and simulation of fabrication and assembly plants through an object-driven approach. The paper is organized in four main sections. The first and second sections discuss the needs for model integration and then outline the modelling and simulation approach used. The third and fourth sections illustrate an application of the approach for modelling and simulating a specific fabrication and assembly plant.     

A simulation model of a sulphuric acid production process as an integrated part of an energy system

Power plant process simulation software is well-suited for the modelling of energy systems and more importantly, tools for analysing the energy efficiency are often built into the software. This work presents the development of a simulation model for a sulphuric acid plant using a commercial software package for power plant process simulation. This will be of value to for instance small consultant and engineering companies involved with audits and analysis of energy systems. For small sized companies the cost of acquiring and maintaining many different specialised software packages will be noticeable. However, companies involved with audits and analysis of energy systems will in most cases have access to at least one software package for power plant process calculations. The use of this kind of software for also modelling chemical plants would be valuable to these companies. The results of this work shows that it is possible to use an inexpensive but powerful power plant process simulation software for modelling a common chemical process as a part of a large energy system.     

Modelling and dynamic simulation of a parabolic trough power plant

Investigational dynamic simulations of an existing 50 MW_el parabolic trough solar thermal power plant in Spain are carried out during clear days and slightly cloudy periods. This work is the first research, which presents a detail dynamic model of a parabolic trough power plant. Besides the thermal energy storage system and solar field, the developed model describes the heat transfer fluid and steam/water paths in detail. Advanced control circuits, including drum level, economiser water bypass, attemperator and steam bypass controllers are also included. The parabolic trough power plant is modelled using Advanced Process Simulation Software (APROS). The comparison between the simulation results and measured data is documented, showing a reliable prediction of the real behaviour of the investigated solar power plant. The validated model offers a possibility for accurate simulation of further operation processes of the real plant.     

Event-based intelligent control of saturated chemical plant using an endomorphic neural network model

An event-based control system with an endomorphic neural network model is designed and realized to control a saturated non-linear plant. The scheme employed in this system is based on an event-based control paradigm previously proposed to control monotonic plants. However, this scheme is different from the previous one in that it can be used to control plants with saturation property. This new scheme may be viewed as a combined method of a time-based diagnosis mechanism in an event-based control system and a state-based control mechanism in a neural network control system. A chemical plant having strong non-linearity and complicated dynamics is controlled using this realized event-based control system. This paper discusses the structure of an event-based controller, the neural network modelling methodology, some related problems, and the simulation results.     

A feasible timetable generator simulation modelling framework for train scheduling problem

An important problem in management of railway systems is the train scheduling/timetabling problem. This is the problem of determining a timetable for a set of trains that do not violate track capacities and satisfy some operational constraints. In this study, a feasible timetable generator framework for stochastic simulation modelling is developed. The objective is to obtain a feasible train timetable for all trains in the system. The feasible train timetable includes train arrival and departure times at all visited stations and calculated average train travel time. Although this study focuses on train scheduling/timetabling problem, the developed simulation framework can also be used for train rescheduling/dispatching problem if this framework can be fed by real time data. The developed simulation model includes stochastic events, and can easily cope with the disturbances that occur in the railway system.     

Computer-aided physical multi-domain modelling: Some experiences from education and industrial applications

For the purposes of this paper, computer-aided physical modelling means a type of modelling in which a computer-aided approach is used, with the basic aim being to maintain the physical structure of a real system or its topology as much as possible in the model. Bond graphs represent a very efficient and traditional approach. However, new, object-oriented and multi-domain tools based on the Modelica language are more appropriate for industrial staff or for the people who do not have a deep insight into modelling and simulation. In this paper we describe several educational and industrial application projects in the Dymola–Modelica environment: a process-systems library, two mechanical systems (an inverted pendulum and a laboratory helicopter), a model of thermal and radiation flows in buildings and two models of processes in mineral-wool production, i.e., a pendulum system and a recuperator system. We describe some experiences from these projects, but also from a more general use of the Matlab–Simulink and Dymola–Modelica environments over many years. One simple conclusion is that we need to educate with two approaches: a more physical and advanced acausal Modelica-like approach, but also a more traditional causal or block-oriented approach according to the historical CSSL standard. The important advantages and disadvantages of both approaches are described. The Modelica-based approach enables true ‘physical’ modelling with fully reusable components. However, there is a particular danger, i.e., users occasionally forget some basic modelling principles when using sophisticated libraries. The result is a very complex modelling structure that is relatively inefficient for the simulation and sometimes has many numerical problems. It is usually very difficult to detect the real reasons for that.     

景观表现中高真实度竹林仿真的研究

高真实度大场景植物仿真技术一直是景观表现中虚拟植物仿真建模和渲染研究的热点和难点。提出了一套从贴图数据采集,植物仿真建模到高仿真森林景观表现的完整解决方案。该方案从竹林形态特征结构、贴图数据采集、自然生长环境三个方面实现竹林的高仿真表现。通过竹叶形态、竹叶分布、模型面数、多角度还原度等因素的不断对比和改进,形成三套凤尾竹建模方案。根据渲染时间和内存使用的数据对比,得到了资源最优化真实度最大化的建模方法,解决了大规模虚拟森林模型运算的速度问题;根据云南当地凤尾竹林的实际景观,利用多层次混合光照模拟技术搭建完整的竹林场景,解决了现实环境中复杂的光照模拟问题。最终实现了在提高渲染速度的前提下依然保证高仿真的竹林景观表现效果的目标。     

OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Root growth model: a novel approach to numerical function optimization and simulation of plant root system

This paper presents a general optimization model gleaned ideas from root growth behaviours in the soil. The purpose of the study is to investigate a novel biologically inspired methodology for complex system modelling and computation, particularly for optimization of higher-dimensional numerical function. For this study, a mathematical framework and architecture are designed to model root growth patterns of plant. Under this architecture, the interactions between the soil and root growth are investigated. A novel approach called “root growth algorithm” (RGA) is derived in the framework and simulation studies are undertaken to evaluate this algorithm. The simulation results show that the proposed model can reflect the root growth behaviours of plant in the soil and the numerical results also demonstrate RGA is a powerful search and optimization technique for higher-dimensional numerical function optimization.     

Implementation of a predictive controller for thermal treatment processes

This paper is concerned with multivariable predictive control and its implementation in thermal treatment processes. The choice of a control structure that ensures decoupling is discussed. A unified predictive controller is used to implement the monovariable control systems for each channel of the decoupled plant. Aspects of the modelling and performance of the control scheme are dealt with and illustrated by plant results. The model of the thermal treatment processes has been used to check the controller behaviour before its real implementation and some simulation results are also given.     

Supply network modelling and simulation methodology

Supply network management in today’s business climate characterized by high uncertainty, globalization of business, outsourcing, shorter product life-cycles, and high customer expectations is extremely challenging. Simulation can be a valuable tool for supply network analysis, planning, optimization, evaluation, and risk management. This paper presents a methodology for modelling both structure and dynamics of complex supply networks based on process approach. It also describes the model-driven simulation methodology and the main components of the simulation software solution: model database, process library, knowledge base, and execution engine. Finally, simulation results of the case supply network are presented.     

Evaluating environmental strategies in a textile printing and dyeing enterprise by an agent-based simulation model

To improve the capabilities of saving energy and reducing pollutant emission of textile printing and dyeing (PD) industry, this article presents a novel agent-based simulation model for assessing the impacts of environmental strategies on a PD enterprise. Two typical PD enterprises in China are simulated with different modelling granularities: one is at a module level, while the other is at an enterprise level. The module-level simulation model depicts detailed production processes in a PD enterprise and evaluates five candidate strategies on their capabilities of improving energy usage and waste emission. The enterprise-level simulation model views a PD enterprise as an agent and assesses three tax strategies for waste discharge. The simulation results show that the proposed general model could be a valuable tool to explore potential solutions to saving energy and reducing waste emission in PD enterprises, after being calibrated to a real case.     

Data driven production modeling and simulation of complex automobile general assembly plant

Flexible manufacturing and customization has long been a topic in modern manufacturing society. However, challenges still remain on the responsiveness of production system to the fluctuation of market demand. In this paper, we developed a data driven simulation methodology to automatically model a production system and rapidly modify the model corresponding to dynamic requirements and real time information. This methodology provides a “rapid prototyping” capability for production system modeling and enables a quick analyzing and remodeling capability to respond to the fluctuation of demands. The approach is developed and applied to an automotive general assembly plant with an online material handling system. A complete information model based on IDEF1X is constructed for this domain specific modeling and simulation. The main simulation modules for assembly line and material handling system of the plant floor are analyzed and a simulator is implemented in ARENA by SIMAN/VBA program. The case study of an automotive assembly plant shows that the data driven approach enables the modeling and simulation of the complex assembly plant in a “real-time” fashion and therefore effectively improve the responsiveness and flexibility of the production line.     

Performance analysis of the TXOP burst transmission scheme in single-hop ad hoc networks with unbalanced stations

Transmission Opportunity (TXOP) is a promising burst transmission scheme defined in the IEEE 802.11e Medium Access Control (MAC) protocol to achieve differentiated Quality-of-Service (QoS) and improve the utilization of the scarce wireless bandwidth. Although performance modelling of the TXOP scheme has attracted tremendous research efforts from both the academia and industry, most existing analytical models have been developed under the unrealistic assumption that stations in wireless networks generate identical traffic loads. However, this assumption fails to capture the behaviour of wireless stations under the realistic working environment. To fill this gap, this paper proposes a new analytical model for the TXOP service differentiation scheme in single-hop ad hoc networks in the presence of unbalanced stations with different traffic loads. The QoS performance metrics including throughput, end-to-end delay, frame dropping probability, and energy consumption are derived. Extensive NS-2 simulation experiments are conducted to validate the accuracy of the developed model. The analytical results demonstrate the efficiency of the TXOP scheme for QoS differentiation and performance enhancement. Moreover, the analytical model is adopted as a cost-effective tool to investigate the impact of the buffer size and the number of stations on the performance of the TXOP scheme. The performance results show that the desirable throughput differentiation for different stations can be achieved by setting the appropriate TXOP limits.     

A mesoscopic simulation modelling methodology for analyzing and evaluating freight train operations in a rail network

This paper includes a mesoscopic simulation modelling methodology developed for analysing and evaluating freight train operations in a rail network. The product of this methodology is a simulation rail network model implemented using an event-based simulation computer package called SIMUL 8. For simulation modelling purposes a decomposition approach is used. This approach allows us to separate the rail network under study into its components such as rail lines, rail yards, rail stations, rail terminals and junctions. The components of the rail network are thought of as interconnected queuing systems that interact and influence one another, so that the global impact of freight train operations in a rail network is captured.The products presented in this paper are of interest to rail freight tactical management, where global benefits are pursued.     

Continuum modelling and numerical simulation of material damage at finite strains

Summary This paper describes in detail a general framework for the continuum modelling and numerical simulation of internal damage in finitely deformed solids. The development of constitutive models for material deterioration is addressed within the context of Continuum Damage Mechanics. Links between micromechanical aspects of damage and phenomenological modelling within continuum thermodynamics are discussed and a brief historical review of Continuum Damage Mechanics is presented. On the computational side, an up-to-date approach to the finite element solution of large strain problems involving dissipative materials is adopted. It relies on an implicit finite element discretization set on the spatial configuration in conjunction with the full Newton-Raphson scheme for the iterative solution of the corresponding non-linear systems of equations. Issues related to the numerical integration of the path dependent damage constitutive equations are discussed in detail and particular emphasis is placed on the consistent linearization of associated algorithms. A model for elastic damage in polymers and finite strain extensions to Lemaitre's and Gurson's models for ductile damage in metals are formulated within the described framework. The adequacy of the constitutive-numerical framework for the simulation of damage in large scale industrial problems is demonstrated by means of numerical examples.     

PlantGL: A Python-based geometric library for 3D plant modelling at different scales

In this paper, we present PlantGL, an open-source graphic toolkit for the creation, simulation and analysis of 3D virtual plants. This C++ geometric library is embedded in the Python language which makes it a powerful user-interactive platform for plant modeling in various biological application domains.PlantGL makes it possible to build and manipulate geometric models of plants or plant parts, ranging from tissues and organs to plant populations. Based on a scene graph augmented with primitives dedicated to plant representation, several methods are provided to create plant architectures from either field measurements or procedural algorithms. Because they are particularly useful in plant design and analysis, special attention has been paid to the definition and use of branching system envelopes. Several examples from different modelling applications illustrate how PlantGL can be used to construct, analyse or manipulate geometric models at different scales ranging from tissues to plant communities.