anglicky
česky
německy
In this course students will be familiar with the theoretical and practical knowledge in the field of systems thinking and system dynamics, such as system archetypes, nonlinearities, feedback, delay, mental models, causal loop diagrams, etc. Students will also be introduced to tools for the description and modeling dynamical systems. The course will explain how to create dynamic models. Through examples of modeling practices, students learn about the modeling tool Powersim.
First System - definition view of the objects from the systemic perspective, depth and resolution of the system, the angle, open closed systems, types, elements, links, system, subsystem, internal variables, external variables, diagram of system boundaries
Second Complexity and complexity - the complexity of the concept, detailed and dynamic complexity, interdependence, nonlinearity, uncertainty, feedback (positive, negative, additive, proportional feedback, the effects of delay), delay
Third Systems thinking - mental models, systems thinking skills
4th System tools and creative thinking
5th System archetypes
6th System dynamics
7th To create models - problem definition, data collection, determine the assumptions and hypotheses, definitions of variables, their units and determine their types (levels, flows, constants, variables), formulation and formalization of the model, testing the model, what if analysis and simulation of the model etc.
8th Modeling of dynamic systems - definitions of variables, elements utilized in the model (flow, level, constants, variables, connections), and set the time step in the simulation, integration methods
9th Advanced modeling tools options - elements for entering the input values of the model (graph functions, input fields, potentiometers, etc..), Components for displaying the results of simulations (graphs, value fields, tables, etc.), creation of a simulator
10th Advanced options modeling tools - Export and import values for a file, using arrays
11th Modeling basic building blocks of mathematical models and their interpretation (sample transfer mathematical description - differential equations to model) - positive feedback, negative feedback, S curve
12th Modeling basic building blocks of models - overshoot and collapse, oscillations, simultaneous streams
13th Practical examples of models - limits to growth, population aging chain, tank, loan, bank account
14th Presentation software other means for modeling dynamics (Powersim, Vensim, Stella, IThing, Dynamo)