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Computer modelling and simulations

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  • Transcript

    • 1. Computer Modeling and Simulations
    • 2. Computer Simulations and ModelsA simulation is basically an attempt toimitate reality. Simulation is used in manycontexts, including the modeling of naturalsystems or human systems in order to gaininsight into their functioning. A computermodel is the mathematical representation ofthe functioning of a process, concept orsystem, presented in the form of a computerprogram.
    • 3. Feedback LoopsGood computer models are dependent offeedback loops. Essentially, feedback loopsare the part of the system model that, basedon the current output, allows for responseand / or self-correction to achieve thedesired output.
    • 4. Feedback Loop Input Process Output FeedbackFeedback - the response to the output, whichinputs new information into the model to the desired effect
    • 5. Steps involved in creating simulations• Gather and prepare accurate data to reflect the real world.• Create mathematical formulas (algorithms) to generate output data from that which is input.• Create animations, graphs or other output displays for the information.• Verify and validate the data by re-testing the scenarios to ensure that the same result occurs.
    • 6. Advantages of modeling and simulations• Safety - able to test or experiment without harming the person or environment.• Economic savings from the use of models to design and test new products before prototypes or the final product is made.• Projection - can look into the future and highlight potential impacts and address them before they occur.• Visualisation - can see and understand relationships. Can speed up or slow down time.• Replication - able to look at things under a variety of different scenarios
    • 7. Disadvantages of modeling and simulations• The mathematical (computational) calculations are very complex, maybe too complex, to simulate real life situations or activities. Therefore, simulations really identify possible trends.• Faulty or hidden assumptions• Extent and effect of the simplification of reality• Processing power needed to create complex models• Can be costly to purchase the processing power and labour
    • 8. Complexity and Assumptions• Mathematical models are built on assumptions, many of which are difficult to verify.• Possibility for the assumptions to be faulty, the creators of the model to overlook things (hidden assumptions) and also clerical errors can be made with the programming.• Daily weather report - to be 100% accurate is too difficult. Usually, the report is 55-65% accurate.• Errors with computer models can have disastrous results.
    • 9. Weather Forecasting and Climate Models• The importance of the weather and the need to predict it accurately is illustrated by the fact that every local news show includes weather forecasts.• People need to know what the weather will be like–either where they are or where they are going–so that they can plan their activities accordingly.
    • 10. A brief history Weather forecasting is no new trend. As far back as 650 BC, there is evidence of early humans attempting to read the weather.• Observing cloud patterns• Colour of the sunset e.g. red These forecasting methods proved to be primitive and unreliable.
    • 11. A brief history1837 did real weather forecasting trulybegin. With the creation of the telegraph,people could now begin to draw more orless accurate reports of weather conditions.In the 1840s, the telegraph allowed people torecord weather conditions over a muchlarger area.
    • 12. A brief history1922 when Lewis Fry Richardson proposedhis idea of using numerical weatherprediction to forecast the weather.“Numerical weather prediction usedmathematical models of the atmosphere topredict the weather.” This new idea was notused until 1955.
    • 13. Five basic steps of weather forecasting• Data collection (observations from surface, stratosphere or satellite)• Data assimilation - production of a model• Numerical weather prediction• Model processing - adds human observations• Presentation of a forecast
    • 14. Stakeholders• General public• Air traffic• Military / Navy• Farmers• Utility companies e.g. Origin Energy• Private companies
    • 15. Issues - Reliability• Not always accurate; extent of situation could be overestimated• Better safe than sorry or don’t provide warnings
    • 16. Issues - Integrity• Accuracy of the data and the instruments collecting the data
    • 17. Equality of Access• Quite easy to translate forecasts because of visual information• Not everyone has access to radio, TV, Internet for emergency warnings
    • 18. Issues - Control• The weather forecast may control our day• Companies respond to forecasts - potential economic cost
    • 19. Issues - People and Machines• Requires people to interpret the information produced by the models• Need for human observation to be added to the forecast• Future weather forecasts may be able to be delivered without the aid of humans.
    • 20. Digital Experimentation• Digital Experimentation is the act of conducting experiments on a computer without ever physically touching the test subject.• For example, engineers can create digital models to crash-test a car to observe how the crash-test dummies would react to the impact.• Another way to digitally experiment is by using image- enhancing programs like Photoshop. Let’s say you’re wondering what you would look like with purple hair but you don’t actually want to dye it: by using certain tools and techniques on Photoshop, you can!
    • 21. Car Crash SimulatorsCar Crash simulations offer away to gain information aboutthe causes of the accidents andhow to improve the safety of thecar bodies.
    • 22. How car crash test simulators workThey use the finite elementmethod - grid superimposed onthe object and numerical data isentered to each correspondingsquare of the to provideinformation on density, strengthand elasticity.
    • 23. Calculating the effect of a head-on collision• Data can be initialised to represent a crash into a wall at a specified speed.• The program computes the force, acceleration and displacement of each grid square, plus the stress and strain of each element of the model.• Program relies on intense computation and highly dependent of graphics programs.
    • 24. Benefits• Can look at a variety of designs before building the prototype.• Saves several design being built and having to be crash-tested. Each crash test costs between A$ 100,000 to 1.6 million.• Saves on material waste.
    • 25. Issues - Reliability• Good understanding of the physics involved, especially force and acceleration.• Material properties are relatively well known.• Behaviour of the materials under abrupt acceleration e.g. high speed impact and at near breaking point are less understood
    • 26. Issues - Reliability• Simplification involved in the model. Cars are smooth and a grid does not replicate this.You can produce smaller grids but such a model requires far more processing power and cost.• Comparison with real-life situation is, arguably, good. Use of video cameras on actual crash tests with data, such as displacement points, fed back into the computer model.
    • 27. Issues - Integrity• Incorrect entry of data• Hackers changing data
    • 28. Issues - Equality of Access• Small companies looking to break into the car market would need a lot of money to compete with big corporations such as GM.
    • 29. Issues - Policy and Standards• Saves on environment in terms of materials used• Economic savings• Saves time
    • 30. Traffic Simulation ModelsDefinition:A computer program that uses mathematicalmodels to conduct experiments with trafficevents on a transportation facility or systemover extended periods of time.
    • 31. Complex NetworksNetwork traffic simulation is a process usedin telecommunications engineering tomeasure the efficiency of a communicationsnetwork. Telecommunications systems arecomplex real-world systems, containing manydifferent components, which interact, incomplex interrelationships.
    • 32. Determining the efficiency of a road netwrok• Most obvious efficiency factor - the pattern of roads that currently existIn addition, consider first the travel behaviour -• Number of trips (data loggers)• Origin and destination of trips• Transport mode• Route taken
    • 33. Use of zones• Models incorporates zoning e.g. some 542 zones across the Greater Dublin area.• Zones define the demand for travel in terms of origins and destinations.• Need to consider external zones for trips into and out of the area.
    • 34. Increasing efficiency Once the ‘general’ efficiency is found, control measures that may assist improve the efficiency of the model may be incorporated:-• Speed limits• Overtaking bans for trucks, especially at uphill or downhill sections• Restrictions for lane changing, especially before or at merging regions• Traffic flow control at on on-off ramps at intersections
    • 35. Improving Efficiency Traffic simulation models can also be used to look at future scenarios:-• To simulate the effect of new infrastructure before it has been build.• To simulate the influence of vehicles with adaptive cruise-control systems. If an increasing percentage of vehicles has such systems, does traffic become more stable? Can the traffic flow per lane be increased?• Finally one can even simulate different or new traffic rules. For example, allowing overtaking on freeways at either side combined with a speed limit.
    • 36. Advantages of traffic simulation models• It is possible to easily compare alternative designs so as to select the optimal system• The actual process of developing the simulation can itself provide valuable insights into the inner workings of the network which can in turn be used at a later stage• Time and money saving• Possible to test new traffic rules without putting humans into dangerous situations and comparing the results of different types of traffic rules
    • 37. Disadvantages of traffic simulations• Data can be incorrectly input• Accurate simulation model development requires extensive resources• The simulation results are only as good as the model and as such are still only estimates• It is very costly to develop a good, reliable and realistic simulation
    • 38. Issues - Reliability and Integrity• Data can be incorrectly input• Data becomes out of date quickly• Vast networks difficult to survey• Need for accurate for casting e.g. number trips determined by population projections and level of car ownership or even environmental consciousness
    • 39. Issues - Security• Need to protect the simulation from those who may wish to tamper with it.
    • 40. Issues - Equality of Access• Costly and extremely difficult to do in developing countries
    • 41. Demographic ModelsDemographics refers to certain populationcharacteristics such as race, age, gender,income, disabilities, literacy rate, homeownership, employment status, and location.It is useful for the government of a country,coming up with marketing strategies, and foreconomic research.
    • 42. Population Pyramids

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