PPT-Modelling

Vocational Excellence Petri Nokelainen School of Education University of Tampere Finland Contents Introduction Theoretical framework Method Results MoVE First phase AVE Second phase. 2 OVERVIEW OF CONSEQUENCE MODELLING IN THE HAZARD ASS ESSMENT PACKAGE PHAST Henk WM Witlox DNV Software London UK Corresponding author address Henk WM Witlox DNV Software Palace House 3 Cat hedral S Pipeline . Qra. Seminar. Pipeline risk assessment . Software for consequence modelling. 2. What is consequence modelling?. Effects from accident (e.g. release or explosion). Strict physical effect (e.g. overpressure from explosion, flow from release and concentration at distance). (Extra Content). Robert Hogg. Architect. Black Marble. FBCS, CEng. Senior Architect. Black Marble LTD. Robert Hogg. The “Oslo” Back Story. A Lap around “Oslo”. The Repository. M. IntelliPad. Quadrant. of. Applied . Sciences. Architecture. , Wood . and. . Civil. Engineering. COST Action FP1005. Working Group Meeting (WG 3). Nancy, 13/10/2011. Two sectors, same questions: . Flow simulations as tools in paper and wood-based panel manufacture. A journey into different representations. Waterslide. Where’s the maths?. “. solving a problem simply means representing it so as to . make the . solution transparent.”. Herbert . Simon. Father of problem solving research. Enabling diagrammatic de-abstraction and modelling of engineering problems. Peter Hale – PhD supervision team, Tony . Solomonides. and Ian Beeson. Abstract. Problem. -. Enable de-abstraction of engineering problems from engineers' representation to computer models and code. Modelling for Engineering Processes. Peter Hale UWE. University of the West of England, Bristol. Abstract. Problem. -. Enable translation of human problems/representation to computer models and code.. John Hughes. Software. Software = Programs + Data. Modelling Data. A big part of designing software is . modelling the data. in an appropriate way. Numbers are not good for this!. We model the data by defining . Dr Andy . Evans. I. ndividual level.. A. gents interact with environment and each other.. M. odel behaviour and decision making.. Agent-Based Models. Typical social science model:. Agents are burglars.. 3.5. Demonstrate understanding of how technological modelling supports technological development. Aims for this session. To share key messages for technological modelling level 3. T. o develop understanding of how . Your exam. Lesson objectives. To be able to define and understand:. Definition . of a simulation model.. Advantages and disadvantages of using simulation models. .. Benefits of Spreadsheet software. Uses of simulation modelling for weather forecasting, car crash analysis and financial forecasting.. Predictions in ecology rely on models. . What is a model?. Matrix algebra. Linear regression models. More on regression. Variance analysis. Model selection techniques. Classification techniques. Eigenvector techniques. Barotse. floodplain, Zambia. . Tom Willis. 1. , Mark Smith. 1. , Donall Cross. 2. , Andrew Hardy. 3. , Georgina Ettritch. 3. , Happiness Malawo. 4. , . Mweemba. Sinkombo. 4. , Cosmas Chalo. 4. , Elizabeth Mroz. Prof. Dr. . Steffen Flessa. Department of Health Care Management. University of Greifswald. Population: 82,000,000. Prof. Dr. Steffen Fleßa. 1966. Married, 2 children. BA, MBA, . PhD, .