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 incre
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.
A Conveyor is essentially an infinite order exponential delay.  This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor.  The 10th order delay very closely aligns to the Delay 10 Conveyor.
A Conveyor is essentially an infinite order exponential delay.  This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor.  The 10th order delay very closely aligns to the Delay 10 Conveyor.
A Conveyor is essentially an infinite order exponential delay.  This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor.  The 10th order delay very closely aligns to the Delay 10 Conveyor.
A Conveyor is essentially an infinite order exponential delay.  This insight illustrates how increasing the order of an exponential delay begins to approximate a conveyor.  The 10th order delay very closely aligns to the Delay 10 Conveyor.
   Aztecs    Aztecas   Systemic Collapse of Tenochtitlan: Feedback Dynamics of the Smallpox Epidemic and Its Role in the Conquest.
Systemic Collapse of Tenochtitlan: Feedback Dynamics of the Smallpox Epidemic and Its Role in the Conquest.
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 Flo
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).
WIP Overview model structures of Khalid Saeed's 2014  WPI paper  Jay
Forrester’s Disruptive Models of Economic Behavior  See also General SD and Macroeconomics CLDs  IM-168865
WIP Overview model structures of Khalid Saeed's 2014 WPI paper Jay Forrester’s Disruptive Models of Economic Behavior  See also General SD and Macroeconomics CLDs IM-168865
From the 1988 killian lecture youtube  video  For more detailed biography See Jay Forrester memorial  webpage  For concepts and applications see  IM-185226
From the 1988 killian lecture youtube video For more detailed biography See Jay Forrester memorial webpage For concepts and applications see IM-185226
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 Flo
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).
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 Flo
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).
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and t
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels. 

I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.
A model shows the System Dynamics that represent the COVID-19 cases in Brgy. Rio Tuba, Bataraza, Palawan as of the month of May 2022.
A model shows the System Dynamics that represent the COVID-19 cases in Brgy. Rio Tuba, Bataraza, Palawan as of the month of May 2022.
A System Dymanic Model of a Predator-Prey interactions using the real-life data. The predator on this model is Equatorial Spitting Cobra while the prey is Palawan Mountain Rat
A System Dymanic Model of a Predator-Prey interactions using the real-life data. The predator on this model is Equatorial Spitting Cobra while the prey is Palawan Mountain Rat
Este modelo busca simular la demanda y oferta de materiales de construcción en la ciudad de Calí (Colombia), En cuanto a la demanda se presenta como principales iniciadores entre otros:  La salud económica (PIB regional, desempleo, cartera hipotecaria)  Estado de la construcción (Licenciamientos, in
Este modelo busca simular la demanda y oferta de materiales de construcción en la ciudad de Calí (Colombia), En cuanto a la demanda se presenta como principales iniciadores entre otros: 
La salud económica (PIB regional, desempleo, cartera hipotecaria)
Estado de la construcción (Licenciamientos, iniciaciones, obras civiles, despachos de cemento)
En cuanto a la oferta se presenta como principales iniciadores entre otros:
Capacidad de proveedores: (Disponibilidad de fuentes, Calidad)
Aspectos legales (Titulos mineros, socioambiental)
Transporte (Flete, estado de la red vial, precio de combustible, distancia de acarreo)

A simulation model that shows the relationship between the mountain biking trails in derby and the the effect it has on the tourism, 
A simulation model that shows the relationship between the mountain biking trails in derby and the the effect it has on the tourism, 
A pest known as a grape-leaf hopper can cause considerable losses in vineyards. Periodically it was found that a natural parasite, anagrus epos, drastically reduced the size of the hopper population. This, in turn, led to a reduction in food (hoppers) available to the parasite and the parasite popul
A pest known as a grape-leaf hopper can cause considerable losses in vineyards. Periodically it was found that a natural parasite, anagrus epos, drastically reduced the size of the hopper population. This, in turn, led to a reduction in food (hoppers) available to the parasite and the parasite population declined until the hopper population increased again. This cycle would repeat.It was found that the parasite, anagrus epos, also feeds on a non-pest leaf hopper which feeds on blackberries. By planting small patches of wild blackberries in the vineyards, the growers were able to maintain a stable parasite population that was large enough to control population explosions of both leaf hoppers.
 ​This model attempts to understand the behavior of average lifetime of companies in the S&P500 index. The reference mode for the model is a graph available at this link:  https://static-cdn.blinkist.com/ebooks/Blinkracy-Blinkist.pdf  (page 5) which was discussed in the System Thinking World Dis

​This model attempts to understand the behavior of average lifetime of companies in the S&P500 index. The reference mode for the model is a graph available at this link: https://static-cdn.blinkist.com/ebooks/Blinkracy-Blinkist.pdf (page 5) which was discussed in the System Thinking World Discussion forum.

Mergers & Acquisitions can be one of the reasons for older companies to be replaced with newer companies in the Index. With M&A of older companies, the empty slots are taken over by newer companies. However, overtime, these new companies themselves become old. With steady M&A, the stock of older companies decreases and stock of newer companies increases. The result is that average age of the companies in the S&P Index decreases.

The oscillations in the diagram, according to me, is due to oscillations in the M&A activity.

There are two negative feedback loops in the model. (1) As stock of new companies increases, the number of companies getting older increases which in turn decreases the stock. (2) As M&A increases, stock of older companies decreases which in turn decreases M&A activities.

Limits of the model

The model does not consider factors other than M&A in the increase in number of new companies in the Index. New companies themselves may have exceptional performance which will result in their inclusion in the Index. Changes in technology for example Information Technology can usher in new companies.

Assumptions

1. It is assumed that M&A results in addition of new companies to the Index. There could be other older companies too, which given the opportunity, can move into the Index. Emergence of new technologies brings in new companies.

At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and t
At first, I cloned the System Dynamics Model from the "Predator-Prey Interactions" tutorial. After I did this for populations of squirrels and mountain lions instead of moose and wolves, the model showed that the more squirrels mountain lions catch, the more the mountain lion population grows, and the squirrel population declines. The squirrel death rate, therefore, depends on the number of mountain lions and the mountain lion birth rate depends on the number of squirrels. 

I complicated the model by adding 15 hunters to the landscape. Now, the model starts with 150 squirrels, 100 mountain lions, and 15 hunters. This model operates under the assumption that hunters want to kill mountain lions, who presumably try to eat the farm animals that represent the hunters' livelihoods. I made the mountain lion death rate dependent on the number of hunters, and the model changed such that the squirrel population exploded and the mountain lion population approached extinction every 20 years. I based this model on a real event, which took place and is still taking place in the Sierra Nevada. Squirrel populations there apparently reached record levels when farmers seeking to protect their land killed off the vast majority of the mountain lion population there. Now, hunters in the area kill squirrels for sport because they disrupted the food chain so irrevocably.