System Dynamics | Insight Maker

An overview of this quantitative systems science method based on Kurt Kreuger's workshops for public health

System dynamics

11 months ago

Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).

Clone of Sterman Model (2002)

Amanda Lengnick-Hall

Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).

Clone of Sterman Model (2002)

rebeca Guerrero

Physician Workforce Model

Modelo baseado na Figura 1 do paper "Forecasting the need for medical specialists in Spain: application of a system dynamics model" (*) de Patricia Barber (**), Beatriz González López-Valcárcel.

(*) https://human-resources-health.biomedcentral.com/articles/10.1186/1478-4491-8-24

(**) pbarber@dmc.ulpgc.es - University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de G.C., Canary Islands, Spain

Physician Workforce Model

Paulo Villela

This model represents a repair contract to fix a group of houses with unresolved construction defects.

Clone of System Dynamics Model for repair cycle FUNCIONA

chikwa mwanza

A new archetype, The Tyranny of Small Steps (TYST) has been observed. Explained through a system dynamics perspective, the archetypical behaviour TYST is an unwanted change to a system through a series of small activities that may be independent from one another. These activities are small enough not to be detected by the ‘surveillance’ within the system, but significant enough to encroach upon the “tolerance” zone of the system and compromise the integrity of the system. TYST is an unintentional process that is experienced within the system and made possible by the lack of transparency between an overarching level and a local level where the encroachment is taking place.

Reference:

Haraldsson, H. V., Sverdrup, H. U., Belyazid, S., Holmqvist, J. and Gramstad, R. C. J. (2008), The Tyranny of Small Steps: a reoccurring behaviour in management. Syst. Res., 25: 25–43. doi: 10.1002/sres.859

The Tyranny of small steps archetype (agent based)

H Haraldsson

3

Ciclo 2 extra work accidents rework

Ciclo 2 Construccion FUNCIONA

Nestor Ramirez

Rabits birth rate is increase 50%

Clone of Investigation of Predator/Prey Modal 1 Scenario 4

SSC

Ciclo 1 extra repair consturction errors rework

Clone of Construction Rework SD

chikwa mwanza

This forecasting model can be used to predict global data center electricity needs, based on understanding usage growth. Please note that the corresponding problem description, model developments, and results are discussed in the following paper:

Koot, M., & Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291, 116798. DOI: https://doi.org/10.1016/j.apenergy.2021.116798.

Clone of Usage impact on global data center electricity needs

Guillaume BOUDRY

Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).

Clone of Sterman Model (2002)

Brian Ray

Problém časové alokace

Semestrální práce

V této simulaci můžeme pozorovat přibližnou dobu na dokončení projektu, který má zadané parametry, jenž ovlivňují dobu jeho dokončení. Zároveň také znázorňuje zjednodušené nabývání znalostí a nárůst (případně pokles) mzdy v poměru se znalostmi.

Celý model obsahuje 3 hladiny - vývojový čas, plat a znalosti vývojářů. Mezi parametry, jenž lze zadávat a jenž ovlivňují celkovou dobu vývoje, patří: počet vývojářů (1 - 10), základní mzda (35.000 - 120.000), termín (1 - 6) a obsáhlost projektu (0.4 - 2).

Celkový počet vývojářů a znalosti vývojářů ovlivňují výslednou mzdu jednotlivých vývojářů. Termín určuje za jak dlouhou dobu si přeje klient projekt dokončen (pravý čas se dozví v simulaci) a obsáhlost projektu představuje o jak velký projekt se jedná.

V simulaci lze pozorovat tři grafy. První porovnává požadovaný čas s reálným časem stráveným na projektu, spolu s křivkou komplexnosti jednotlivých prvků, které se vyskytly během vývoje. Druhý graf nám ukazuje nárůst znalostí aktuálního týmu (tým se znalostí 1 dokonale rozumí dané problematice) a na třetím grafu lze vidět vývoj mzdy vývojářů během projektu (mzda je závislá na znalostech, tedy graf má stejný tvar).

Clone of Problém časové alokace

Stanislava Mildeova

Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).

Clone of Sterman Model (2002)

ilyadorosh

Internet of Things and Data Collection - Active and Passive Data under Conditions of Regulation.

Clone of Active and Passive Internet of Things - Regulated

Rob

Overview

The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.

How Does the Model Work?

Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.

Interesting Insights

Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.

Simulation of Derby Mountain Bikes versus Forestry

Silong Lou

This is a model which explains the difference between Mountain bikes riding compared to logging in the Tasmanian forests.

Simulation of Derby Mountain bikes riding versus logging

Maylis P

An Initial System Dynamics Model for GFS in certain region(s) of Africa

GFS Raw Input Food Production

Camilo Silva

Overview
This model is a working simulation of the competition between the mountain biking tourism industry versus the forestry logging within Derby Tasmania.

How the model works

The left side of the model highlights the mountain bike flow beginning with demand for the forest that leads to increased visitors using the forest of mountain biking. Accompanying variables effect the tourism income that flows from use of the bike trails.
On the right side, the forest flow begins with tree growth then a demand for timber leading to the logging production. The sales from the logging then lead to the forestry income.
The model works by identifying how the different variables interact with both mountain biking and logging. As illustrated there are variables that have a shared effect such as scenery and adventure and entertainment.

Variables
The variables are essential in understanding what drives the flow within the model. For example mountain biking demand is dependent on positive word mouth which in turn is dependent on scenery. This is an important factor as logging has a negative impact on how the scenery changes as logging deteriorates the landscape and therefore effects positive word of mouth.
By establishing variables and their relationships with each other, the model highlights exactly how mountain biking and forestry logging effect each other and the income it supports.

Interesting Insights
The model suggests that though there is some impact from logging, tourism still prospers in spite of negative impacts to the scenery with tourism increasing substantially over forestry income. There is also a point at which the visitor population increases exponentially at which most other variables including adventure and entertainment also increase in result. The model suggests that it may be possible for logging and mountain biking to happen simultaneously without negatively impacting on the tourism income.

Clone of Simulation of Derby Mountain biking versus logging

Steven D'Alessandro

This forecasting model can be used to predict global data center electricity needs, based on understanding usage growth. Please note that the corresponding problem description, model developments, and results are discussed in the following paper:

Koot, M., & Wijnhoven, F. (2021). Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy, 291, 116798. DOI: https://doi.org/10.1016/j.apenergy.2021.116798.

Usage impact on global data center electricity needs

M. Koot

8 last month

Based on model discussed by John D. Sterman (p 508) in All models are wrong: reflections on becoming a systems scientist (2002). Task: (A) Sketch what you think the resultant graph will be (see directions for drawing in model). (B) Then Run Simulation. Optional Extension: Replace Graph In/Out Flow connection with a connection from Trig. function. Repeat (A) & (B).

Clone of Sterman Model (2002)

Elisavet Mavroudi

Evolution of Covid-19 in Brazil:

A System Dynamics Approach

Villela, Paulo (2020)
paulo.villela@engenharia.ufjf.br

This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.

Clone of Evolution of Covid-19 in Brazil: A System Dynamics Approach

Nilo Guimaraes

Event management forecasting in post COVID-19 period

A. Andersons

Instructions

Adjust values by using the sliders below or typing in values, then press "Simulate"

To find total cases or total cost with or without WGS, run the simulation twice with WGS = 0 and WGS = 1 (make sure you record the values each time)

Refresh page to restore default values

Warning:

Initial proportion of asymptomatically colonised patients + Initial proportion of symptomatically infected patients must be < 1

Proportion of admissions asymptomatically colonised + Proportion of admissions with symptomatic infection must be <1

Email amy.buchanan-hughes@costellomedical.com with queries or comments

Clone of C difficile and Whole Genome Sequencing

chlubna

Aztecs

Aztecas

Systemic Collapse of Tenochtitlan: Feedback Dynamics of the Smallpox Epidemic and Its Role in the Conquest.

Why the Aztecs Fell

Pedro D. Almaguer Prado

7 months ago

System Dynamics Models