This simulator walks the user through a model showing the spread of the COVID, or Corona Virus through a city. You can implement policies, change assumptions about the disease and see the impacts in realtime.

Agriculture offers many modeling opportunities. In this Systems in Focus, we look at the life cycle of a dairy herd, including milk production. This model could be used as the basis for methane production control, trade agreements about milk and how that impacts herd size, increasing production with demand, etc. Visit https://iseesystems.com/resources/systems-in-focus/agriculture/ for more information.

© Will Noyes 2020 This is an educational tool to learn about the commonly used builtin formulas in Stella. For each formula there is a basic description, a model representation that allows you to control the different inputs, and one or two output graphs that show the result of that formula. If you would like more information on any of these builtins or on any that are not demonstrated here, remember that you can always consult Stella Help.

One of the greatest environmental challenges we face is how to do more with less: Less raw materials, less pollution, less damage to the environment. This model shows the life-cycle assessment for the aggregate products manufactured and consumed in a firm, an industry, a region, a nation, or the world. It focuses on solid waste, though it would be easy to add air or water pollution generated and energy consumed at each stage.

A lot is happening behind the scenes to create this picturesque vista. Rainfall on land creates runoff and therefore stream flow. Some of this runoff is absorbed into the soil. Some of that flows beneath the ground to the stream and some returns to the air through evapotranspiration. Another part of it percolates further down through the soil layers to become part of the groundwater, which provides a base level flow for the stream. Using Stella Professional, we are able to draw a map that corresponds closely to the physical world and then simulate that map to see what happens. This both increases our understanding of how this system works and allows us to experiment with different policies that might lead to alternate, more desirable outcomes.

Market-capitalism typically goes through cycles of expansion and contraction. Every now and then, these common economic cycles go off the hinges. They become unstable and can lead to recessions, crises and depressions—phenomena that economists typically look to exogenous forces to explain. Alternative, mostly Marxian and Keynesian, explanations for the instabilities have been sought within the structure of the economic system itself. One such explanation is provided by Steve Keen in his Goodwin-Minsky model. The model effectively mimics the dynamics of key indicators prior to, during and after the 2007/08 crisis. However, the model is also over-specified, highly sensitive to initial conditions and therefore more difficult to convey. In line with George Box’s plea for parsimony, this paper presents a more straightforward version of Keen’s model that remains consistent with its fundamental behaviour. The model also illustrates the potential for further dialogue between Marxian economics and system dynamics.

Fishing areas are within the commons, which encourages greater investment in ships when there is demand. More importantly, we can never really know the population of the given fishery and therefore whether it is in danger of being fished out. This model explores the trade-offs between investing in more ships to catch more fish and the long-term viability of the fishery.

This models the COVID-19 pandemic as an SEIR model disaggregated by age. DIfferent ages have different contact rates, death rates, and conformance to social distancing. A thrid-order material delay is used to create the distribution for the tie to become infected and the time to recover.

This model is an extension of the Simple Agrarian Society model from Dynamic Systems. The extensions are to add a CO2 cost to the industrialization, an impact of CO2 on global temperature, an impact of global temperature on drought frequency, and impact of drought on food production and an impact of global temperature on polar sea ice.

This model is a second extension of the Simple Agrarian model from Dynamic Systems that modifies the simple agrarian society model to include drought, industry produced CO2 and ice sheet dynamics. Primarily this is published as a test of porting from Stella 10.1 and learning how the new Stella Online operates. Several of the converter weights have been fine tuned to provide a better behaved model than the first adaptation. At some point a user interface and story will be added and the starting conditions calibrated to approximate treating Earth as an industrialized, agrarian society.

© Daria Yermolova & Valentina Orliuk 2020 A model that examines the various factors affecting the electric car market in Norway, originally built for the course GEO-SD304 at UiB.

© Will Noyes 2021 This model is intended to teach and demonstrate various concepts related to building policy models. This model specifically seeks a policy to increase bus ridership in Bergen through expanding bus route availability. The policy takes into account a dynamic goal that factors in population growth and includes financial impact analysis to demonstrate how to incorporate financial and budgetary considerations into a policy proposal.

Building capacity in alternative energy sectors takes time and large investments. The transition to other sources has to be financially feasible, as well as timely to prevent further damage from pollution. How can the mix of electricity generation technology change, based on both cost and pollution? This Systems in Focus model analyses how capacity can be developed in different energy sectors over time.

This model was copied from Gigaroff: 1. French (in English in 2.) Modèles pour mieux comprendre la dynamique d'une épidémie et comment les mesures prises permettent d'en atténuer les effets" - Projet interdisciplines Hervé Gigaroff, Lycée "Emile Combes" de Pons 17 (France)-
 • Ceci est le Modèle de base “1.B” pour commencer à mieux comprendre la dynamique d'une épidémie, type CoVid 19, , simplifiée mais tout à fait réaliste… …Avant de voir, avec des modèles suivants, comment les mesures prises permettent d'en atténuer les effets" Pour les “matheux”, fans d’équations différentielles, ce modèle n’est jamais que la mis en forme, selon les lois de le “SYSTÉMIQUE DYNAMIQUE” de ce qui est représenté , en équations différentielles dans cette excellente vidéo: https://www.youtube.com/watch?v=-2tI3MQFqkI&fbclid=IwAR3QdfrTCQPKNUogozNchAlpu0SwTlvQx_fPNaTDjZ1ijdk6wc0snzJc69k Donc ce modèle permet aux “non-matheux” d’aborder cette compréhension… 2 jeux “Épidémie Covid19 #1 et #2” , permettant de vivre (en”pour de semblant”) la dynamique d’une épidémie, vont accompagner ces modèles , qui ne sont que le débriefing de ce qui s’est passé dans ces “jeux”. • Websites récents sur "Epidémies & modélisation" : 1.https://www.youtube.com/watch?v=bM7AOBxqjnE, titré "Cette pandémie, vue depuis 2021" du site "Dirty Biology", 2.https://sciencetonnante.wordpress.com/2020/03/12/epidemie-nuage-radioactif-et-distanciation-sociale/ , titré "Épidémie, nuage radioactif et distanciation sociale", 3.https://medium.com/tomas-pueyo/coronavirus-le-marteau-et-la-danse-bce68d354c0c, titré "Coronavirus, le marteau et la danse". -------------------------------------------------------------------------------------------------------------------- • 2. English: Models for a better understanding of the dynamics of an epidemic and how protective measures make it possible to mitigate the effects "- Interdisciplinary project Hervé Gigaroff, High-school Emile Combes de Pons 17 (France) • Here is Basic model “1.B” to begin to better understand the dynamics of an epidemic, type CoVid 19, in asimplified but completely realistic way… … Before seeing, with the further models, how measures taken can mitigate the effects For the "math minded students”, fans of differential equations, this model is nothing else than the shaping, according to the laws of the "DYNAMIC SYSTEM" of what is represented, in differential equations in this excellent video : https://www.youtube.com/watch?v=-2tI3MQFqkI&fbclid=IwAR3QdfrTCQPKNUogozNchAlpu0SwTlvQx_fPNaTDjZ1ijdk6wc0snzJc69k So this model allows the "non-math minded students" to approach this understanding ... 2 games “Covid19 epidemic # 1 and # 2”, allowing to live (“for pretense”) the dynamics of an epidemic, will accompany these models, which are only the debriefing of what happened in these “games”. • Websites récents sur "Epidémies & modélisation" : 1.https://www.youtube.com/watch?v=bM7AOBxqjnE, titled "This pandemia, seen from 2021" from website "Dirty Biology", 2.https://sciencetonnante.wordpress.com/2020/03/12/epidemie-nuage-radioactif-et-distanciation-sociale/ , titled "Epidemic, nuage radioactive cloud and social distanciation", 3.https://medium.com/@tomaspueyo/coronavirus-the-hammer-and-the-dance-be9337092b56 , titled "Coronavirus, the hammer and the dance".

Molecules of System Dynamics Structure: Small generic structures useful in building simulation models.

This model depicts a process with exogenous inflows where the efficacy of the process descreases in proportion to time spent in the process. It is followed by a quality control mechanism with sensitivities and specificities which also decrease with time spent in the quality process. This bounded process and quality control is then checked against a gold standard which then adjusts as necessary in alignment with larger policy goals and feeds a larger data set. This model represents a realistic vision of what frontline quality control mechanisms should exist in the healthcare delivery system. It can be used as a tool for policy making to determine what acceptable rates of efficacy and outcome can be tolerated as quality based payments grow in popularity.

This models the economic impacts of an extended shutdown due to the coronavirus pandemic and explore the policies adopted by the United States to mitigate these effects.

© Jefferson Rajah & Martin Grimeland 2022 Considering the complex and dynamic nature of food systems, the System Dynamics method was opted for investigating the questions posed. Representing the real-world system responsible for farmers´ livelihoods, a simulation SD model was constructed as a proof-of-concept for the councils' policy strategy. It is evident, based on the findings of the model, that increasing food system literacy does indeed increase the resilience of SME farmers' livelihoods.

© Jefferson Rajah 2021 Passionate workers join the non-profit sector only to experience a collapse in their passion level as a result of organisational conditions, and thus shore up their intention to leave over time. The results from this model suggest that work overload and physical exhaustion affecting productivity, fall in professional efficacy, and negative affection from perceived organisational injustice drive the collapse in passion. Of these, role overload and high expectations of passionate employees was found to have the highest impact. Originally developed for the course GEO-SD304 and presented at the International System Dynamics Conference.

In this simple example, we have modeled the basics of a bottling plant. Before we can model the process however, we need to consider the supplies required to create the final product, in this case, water. A bottling plant requires a constant supply of purified water. It is usually run through three sets of filters that remove smaller and smaller particles before being sterilized.

Yo listen up, here's the story About a little guy that lives in a blue world And all day and all night and everything he sees is just blue Like him, inside and outside Blue his house with a blue little window And a blue Corvette And everything is blue for him And himself and everybody around 'Cause he ain't got nobody to listen I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I have a blue house with a blue window Blue is the color of all that I wear Blue are the streets and all the trees are too I have a girlfriend and she is so blue Blue are the people here that walk around Blue like my Corvette, it's in and outside Blue are the words I say and what I think Blue are the feelings that live inside me I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I have a blue house with a blue window Blue is the color of all that I wear Blue are the streets and all the trees are too I have a girlfriend and she is so blue Blue are the people here that walk around Blue like my Corvette, it's in and outside Blue are the words I say and what I think Blue are the feelings that live inside me I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa I'm blue da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa Da ba dee da ba daa, da ba dee da ba daa, da ba dee da ba daa

Will Noyes, Faith Kiprono & Min Xiang 2020 This project aims to help Bergen meet the T9 goal that ‘all new passenger cars are fossil-free from 2025’. The project intends to identify the underlying causal relationships linking the different factors affecting a 100 % switch to fossil-free passenger vehicles.

A first attempt at conceptualizing the dynamic relationship between emotions and grit and their influence on student performance in cyberlearning environments

This model demonstrates the interaction between two agonists and allows the efficacy (Emax) of one to be varied

© Christina Gkini 2019 A psychosocial model on perfectionism, originally built for the course GEO-SD304.

© Christina Gkini, Ashish Shrestha & Birgit Kopainsky 2020 A model examining the devolution of power in community-based Natural Resource Management programmes, originally developed for the course GEO-SD325 at UiB and presented at the International System Dynamics Conference 2020.

Deciding when to expand a business is difficult in any industry. For the airline industry, there are both large investments and long delays involved in expansion, making it important to test your assumptions as you go.