#### Clone of EasyJet Fliers Model

##### Håvard Gjelseth

Model of growth from diffusion from John Morecroft's Strategic Modelling and Business Dynamics Book Ch6 p174-191. A discussion of a bigger model of People's Express is in http://bit.ly/HdaGy4 for a related You Tube video by John Morecroft on Reflections on System Dynamics and Strategy

- 5 years 11 months ago

#### Bio103 Growth Models

##### John Petersen

- 2 years 5 months ago

#### Clone of model - flights

##### biren pat

model

- 6 years 10 months ago

#### Clone of OVERSHOOT GROWTH INTO TURBULENCE

##### Brian Lee

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Strategy Weather

- 3 years 4 months ago

#### Clone of FORCED GROWTH INTO TURBULENCE

##### Brayan Triminio

**FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION**

**BEWARE pushing increased growth blows the system!**

**(governments are trying to push growth on already unstable systems !)**

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Strategy Weather

- 2 years 7 months ago

#### Dynamika růstu hostingové firmy

##### Slavek Bro

- 8 months 1 day ago

#### Clone of Clone of Oyster Growth based on Phytoplankton Biomass

##### Bechara Assouad

Simple model to illustrate oyster growth based on primary production of Phytoplankton as a state variable, forced by light and nutrients, running for a yearly period.

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

*Modèle simple pour illustrer la croissance des huîtres sur la base de la production primaire de phytoplancton comme une variable d'état, forcé par la lumière et les éléments nutritifs, en cours d'exécution pour une période annuelle.*

*La croissance du phytoplancton sur la base de Steele et équations de Michaelis-Menten), où:*

*Production primaire = (([Pmax] * [I] / [Iopt] * exp (1 - [I] / [Iopt]) * [S]) / ([K] + [S]))*

*Pmax: production maximale (d-1)I: L'énergie lumineuse en profondeur de l'intérêt (Ue m-2 s-1)Iopt: L'énergie lumineuse à laquelle se produit Pmax (Ue m-2 s-1)S: concentration des éléments nutritifs (N umol L-1)KS: Demi constants de saturation en nutriments (N umol L-1).*

*D'autres développements:- Les éléments nutritifs comme variable d'état dans le cycle de détritus de phytoplancton et d'huîtres de la biomasse.- Lumière limitée par la concentration de phytoplancton.- Effet de la température sur le phytoplancton et la croissance des huîtres.*

Environment Phytoplankton Primary Production Bivalves Growth

- 5 years 8 months ago

#### Clone of POPULATION LOGISTIC MAP (WITH FEEDBACK)

##### Pieter van der Ploeg

the maximum population is set to be one million, and the growth rate constant mu = 3. Nj: is the “number of items” in our current generation.

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.

Environment MATHS Mathematics Chaos Fractals BIFURCATION Model Economics Finance TURBULENCE Population Growth DECAY STABILITY SUSTAINABLE Engineering Science Demographics Strategy

- 2 years 6 months ago

#### Clone of POPULATION LOGISTIC MAP (WITH FEEDBACK)

##### Andriy Samilyak

the maximum population is set to be one million, and the growth rate constant mu = 3. Nj: is the “number of items” in our current generation.

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.

Environment MATHS Mathematics Chaos Fractals BIFURCATION Model Economics Finance TURBULENCE Population Growth DECAY STABILITY SUSTAINABLE Engineering Science Demographics Strategy

- 2 years 6 months ago

#### Clone of Goodwin Model

##### leimeng zhang

**Goodwin Model:**This is a basic version of the Goodwin Model based on Kaoru Yamagushi (2013), Money and Macroeconomic Dynamics, Chapter 4.5 (link)

Equilibrium conditions:

- Labor Supply = 100

- 3 years 6 months ago

#### Clone of Clone of Oyster Growth based on Phytoplankton Biomass

##### Eduardo

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 5 years 3 months ago

#### Clone of Clone of Clone3f micro algae , biogas and bioelectricity

##### Mark Nickelo Blanco

The biomass model uses an example, Phytoplankton growth based on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Once this is understood, it looks upon the viability of biogas production from the microalgae biomass.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of Clone of micro algae , biogas , bioelectrcidades

##### Mark Nickelo Blanco

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of Clone3f micro algae , biogas and bioelectricity

##### Mark Nickelo Blanco

The biomass model uses an example, Phytoplankton growth based on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Once this is understood, it looks upon the viability of biogas production from the microalgae biomass.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### population time N

##### neşe ipekli

- 10 months 2 weeks ago

#### Clone of FORCED GROWTH INTO TURBULENCE

##### Thibaud Métral

**FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION**

**BEWARE pushing increased growth blows the system!**

**(governments are trying to push growth on already unstable systems !)**

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Strategy Weather

- 2 years 4 months ago

#### Clone of Clone3f micro algae , biogas , bioelectrcidades

##### Mark Nickelo Blanco

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of POPULATION LOGISTIC MAP (WITH FEEDBACK)

##### Roman Knaus

the maximum population is set to be one million, and the growth rate constant mu = 3. Nj: is the “number of items” in our current generation.

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.

Environment MATHS Mathematics Chaos Fractals BIFURCATION Model Economics Finance TURBULENCE Population Growth DECAY STABILITY SUSTAINABLE Engineering Science Demographics Strategy

- 1 year 11 months ago

#### Clone of Clone of micro algae , biogas , bioelectrcidades

##### Rajesh Shivanahalli Kempegowda

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of Clone of micro algae , biogas , bioelectrcidades

##### Mark Nickelo Blanco

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of PannirbrClone4f micro algae , biogas , bioelectrcidades

##### Mark Nickelo Blanco

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Biogas, model as well birefineray option to seperate c02 , chp from bogas model are proposed

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of Clone of micro algae , biogas , bioelectrcidades

##### Rajesh Shivanahalli Kempegowda

Phytoplankton growth based on on Steele's and Michaelis-Menten equations), where:

Primary Production=(([Pmax]*[I]/[Iopt]*exp(1-[I]/[Iopt])*[S])/([Ks]+[S]))

Pmax: Maximum production (d-1)

I: Light energy at depth of interest (uE m-2 s-1)

Iopt: Light energy at which Pmax occurs (uE m-2 s-1)

S: Nutrient concentration (umol N L-1)

Ks: Half saturation constant for nutrient (umol N L-1).

Further developments:

- Nutrients as state variable in cycle with detritus from phytoplankton and oyster biomass.

- Light limited by the concentration of phytoplankton.

- Temperature effect on phytoplankton and Oyster growth.

Environment Phytoplankton Primary Production Bivalves Growth

- 2 years 3 months ago

#### Clone of Miniwelt nach Bossel

##### Thomas Neher

- 3 years 2 months ago

#### Clone of Simple Economic Growth Model

##### Pavan Srinath

- 2 years 6 months ago