introduction in simulation dr. christoph laroque summer 2012

Fakultät Informatik, Institut für Angewandte Informatik, Professur Modellierung und Simulation

Dresden, 04.07.2012

Introduction in Simulation

Dr. Christoph LaroqueSummer 2012

04.07.2012

Einführung in die Simulation Folie Nr. 2

Folie Nr. 2

Next week

04.07.2012

1. Answer open questions to the lecture, either content or organisation. Please reflect and send open questions till Monday, 6 p.m. via email.

2. Practise with FlexSim… 3. Decide, if presentation by google can take place on

Thursday 12th - yes, still an open issue..

• extra-practise – self-management – interest?


Folie Nr. 3

VALIDATION & VERIFICATION

Introduction in SimulationSummer 2012

04.07.2012


Folie Nr. 4

Objectives of V&V

The objectives of the validation and verification of simulation models and experiments are:

• Create comprehensible principles about the credibility of the model• Recognize errors during the modeling at an early stage• Ensure, that lessons-learned is incorporated in further modeling• Proper use of good models and correct interpretation


Folie Nr. 5

Approach in a simulation study - II

DATA MODELSproblemdefinition

Planningthe Data

collection

Datacollection

Dataprocessing

Experiments

System analysis

Model formalization

Implemen‐tation

Evaluation

Validation and Ve

rification of data

Validationand Verification of m

odels

Interim results


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Terms

Validation is a continuous review, whether the models reproduce the behavior of the illustrated system with sufficient accuracy.

(Does it the right thing?)

Verification is the review, whether a model has been transformed from a mode of description in a different mode of description correctly.

(Does it the right thing right?)


Folie Nr. 7

Terms

Testing occurs regularly from the beginning of the development to completion. We distinguish:

• Factual correctness (sufficiently accurate reproduction)• Functional correctness (all functions available for the target

position?)• Technical correctness (If all conditions met, for example, computer

time, interfaces?)


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Criteria

A Model can be only checked against the background of a specific purpose for its validity.

General criteria can be determined as:

• Completeness (correctness of the content and structure)• Consistency (correctness of the content and structure)• Accuracy (reasonableness of the result)• Relevance (adequacy of the result)• Appropriateness (adequacy of the result)• Plausibility (reasonableness of the result)• Intelligibility (adequacy of the result)• Feasibility (feasibility)• Availability (feasibility)


Folie Nr. 9

Result documentation

The individual phases of the simulation study can be secured by specified documents:

• target description• task specification• concept model• formal model• executable model• simulation results• raw data• formatted data


Folie Nr. 10

Result documentation task specification

(Extract from outline proposal)

1. Description of the target and tasks2. Description of the investigated system3. Necessary information and data4. Planned use of model

Period of use User community and qualification Type of model use

5. Approach and method6. Requirements of model and modeling


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Result documentation task specification

(Excerpt of evaluation questions)

• If the task specification being examined with the department heads?

• Is the selection of the chosen solution methods substantiated?• If the purpose of the simulation study clearly defined?• Is the description of the system as a whole coherent and

understandable?• Is the named V&V approach to cost and benefit points of view

adequate?


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Techniques of verification and validation

• Animation• Assessment• Dimension test• validity test event• Read-only test• Limit Test• Monitoring• Writing test• Sensitivity analysis• Statistical techniques• Structured runaway• Test of internal validity• Test of partial models

• Trace Analysis• Turing test• Cause-effect graph • Validation dialog• Validation of predictions• Comparison with other models• Compared with recorded data


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Techniques: Animation

With animation can be particularly pointed out that the behavior of a model in certain situations is not valid.

advantage:• Verification of the model behavior in selected model sections• Localization errors of detail• Direct observation of the model curve

disadvantage:• Misrepresentation of detail• Rarely occurring error is not detected


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Techniques: Writing Test

Careful review of their own work in terms of completeness, accuracy, consistency and clarity

advantage:• Own work will be reconsidered again at rest

disadvantage:• Certain errors are not detected (blindness)

note:• Consult any other person and validation dialog


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Techniques: sensitivity analysis

This will select critical input parameters of the model and determines the impact on output parameters

advantage:• identification of particularly sensitive parameters• comparison with real behavior

disadvantage: • dynamic effect relationships and interaction effects of the

parameters are not recognized


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Techniques: Structured runaway

Technology in software development. Responsible go together through each statement in the program.

advantage:• 4-eye principle (at least)• unity of all project managers

disadvantage:• very time consuming, especially for complex models and / or long

documents


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Process Model - Guidelines

1. V&V are to be performed integrated; all the measures, procedures, etc. for verification for validation are treated together

2. V&V is a process which always accompanies the entire simulation study

3. Basis are documented period results

4. The data must be considered a special way.


Folie Nr. 18

Process Model

Hier kommt das Bild


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Quality criteria

Quality is the totality of features and feature values are one unit on its ability to meet all specified and assumed requirements.

• Refers not only on results but also on the approach• Quality of a simulation project is depending on project-specific

requirements• Is determined by the care and systematic implementation of the

project preparation• Comparisons deadly sins of Liebl


Folie Nr. 20

Quality criteria

Five major quality criteria can be distinguished:

1. Careful project preparation2. Consistent documentation of all project activities3. Collaborative verification and validation4. Continuous integration of the client5. Systematic project implementation


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Quality criterion for project preparation

As part of project preparation some early policy decisions are made:

• Check dignity of simulation• Determine the acceptance of the simulation method • Formulate a clear major task for study• Selecting a service provider• Selecting of a simulation tool

• Consistent documentation


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QUESTIONS?

[email protected]

Introduction in SimulationSummer 2012

04.07.2012

introduction in simulation dr. christoph laroque summer 2012

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