Development of a process simulator using object oriented programming: Information modeling and program structure

Object Oriented Programming Languages (OOPL) offer the flexibility of language extension to the specific application of interest. The development effort required for process simulators can be greatly reduced if we extend OOPL with process simulator specific objects and use them for simulation. Design of objects is the most important aspect of development in using OOPL. But OOPL do not provide a methodology to aid in object design. The objects to be designed should reflect the nature of the application at hand.;The objective of this work is to develop an object oriented process simulator to illustrate the benefit of using OOPL in process simulation. An object design criteria is established, an analysis of the object model is performed, and a steady state process simulator using sequential and simultaneous approaches is developed using C++ as the underlying implementation language.;It is found that the object model has to be extended with operational behavior to effectively represent the process simulation information, the development effort is greatly reduced by using the object oriented approach for the process simulator, OOPL can act as common platforms for integrating process engineering activities, and C++ can be effectively used as an implementation language for object oriented process simulation.;Further work is necessary to extend the simulator with dynamic simulation capabilities and to make the simulator interactive and user friendly by developing a graphic interface

Use of high performance networks and supercomputers for real-time flight simulation

In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be consistent in processing time and be completed in as short a time as possible. These operations include simulation mathematical model computation and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to the Computer Automated Measurement and Control (CAMAC) technology which resulted in a factor of ten increase in the effective bandwidth and reduced latency of modules necessary for simulator communication. This technology extension is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC are completing the development of the use of supercomputers for mathematical model computation to support real-time flight simulation. This includes the development of a real-time operating system and development of specialized software and hardware for the simulator network. This paper describes the data acquisition technology and the development of supercomputing for flight simulation

Intelligent agent simulator in massive crowd

Crowd simulations have many benefits over real-life research such as in computer games, architecture and entertainment. One of the key elements in this study is to include elements of decision-making into the crowd. The aim of this simulator is to simulate the features of an intelligent agent to escape from crowded environments especially in one-way corridor, two-way corridor and four-way intersection. The addition of the graphical user interface enables intuitive and fast handling in all settings and features of the Intelligent Agent Simulator and allows convenient research in the field of intelligent behaviour in massive crowd. This paper describes the development of a simulator by using the Open Graphics Library (OpenGL), starting from the production of training data, the simulation process, until the simulation results. The Social Force Model (SFM) is used to generate the motion of agents and the Support Vector Machine (SVM) is used to predict the next step for intelligent agent

Going Around Again: Modelling Standing Ovations with a Flexible Agent-based Simulation Framework

We describe how we have used the CoSMoS process to trans- form a computer simulation originally developed for the simulation of plant development for use in modelling aspects of audience behaviour. An existing agent-based simulator is re-factored to simulate a completely dierent type of agent in 2D space. This is possible and desirable because the original simulator was designed with the intention that it could eas- ily be use to model a variety of dierent agents interacting in 2D and 3D space. The resulting simulation will be used to simulate the phe- nomena of standing ovations in audiences as a model system of tipping point behaviour. Continued development of this simulator, assisted by the CoSMoS process, has resulted in a general purpose lightweight sim- ulation framework

Integration of a failure monitoring within a hybrid dynamic simulation environment

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Development of the CELSS emulator at NASA. Johnson Space Center

The Closed Ecological Life Support System (CELSS) Emulator is under development. It will be used to investigate computer simulations of integrated CELSS operations involving humans, plants, and process machinery. Described here is Version 1.0 of the CELSS Emulator that was initiated in 1988 on the Johnson Space Center (JSC) Multi Purpose Applications Console Test Bed as the simulation framework. The run model of the simulation system now contains a CELSS model called BLSS. The CELSS simulator empowers us to generate model data sets, store libraries of results for further analysis, and also display plots of model variables as a function of time. The progress of the project is presented with sample test runs and simulation display pages

Model Predictive Control of a Continuous Vacuum Crystalliser in an Industrial Environment: A Feasibility Study

Crystallisers are essentially multivariable systems with high interaction amongst the process variables. Model Predictive Controllers (MPC) can handle such highly interacting multivariable systems efficiently due to their coordinated approach. In the absence of a real continuous crystalliser, a detailed momentum-model was applied using the process simulator in Simulink. This process has been controlled by a model predictive controller widely used in industry. A new framework has been worked out for the incorporation of the Honeywell Profit Suite controller to the simulator of the crystalliser. The engineering model and the controller were connected via OPC (OLE-Object Linking and Embedding for Process Control standard). Models were developed in Profit Suite using the new fully-automated identification method. The feasibility study illustrated that the applied identification tool gave an accurate and robust model, and that the non-linear crystalliser may be controlled and optimised very well with the Honeywell Profit Suite package. The developed system is proven to be useful in research and development

Hydrodynamic Analysis and Simulation of a Tidal Energy Converter

A new motion simulator has been developed to simulate Minesto AB’s tidal energy converter flying in water. The motion simulator is as a part of a new computer based development environment, aiming to shorten the company’s development process. The environment consists of a hydrodynamic analysis together with the new simulator to evaluate the performance of the company’s tidal energy converter. The new motion simulator is custom-made in MATLAB and Simulink for Minesto’s purposes, simulating the motion of a flying tidal energy converter with six degrees of freedom in variable flow conditions. The hydrodynamic forces used in the simulator are calculated in the hydrodynamic analysis. Quaternions are used to avoid singularities in the angle representation, enabling the device to move freely without mathematical restrictions. The flow conditions are set in an external flow model with the ability to simulate variable flows. A control system is integrated in Simulink to control the device’s rudder during the simulation. The simulations are valid for normal flight conditions and are usable for development of both device and control system designs but also for educational purposes, especially if integrated with a visualization program