Insight diagram
​HYSTERESIS
The lost energy associated with delay.
Hysteresis is the dependence of a system not only on its current environment but also on its past environment. This dependence arises because the system can be in more than one internal state. To predict its future development, either its internal state or its history must be known.[1] If a given input alternately increases and decreases, the output tends to form a loop as in the figure. However, loops may also occur because of a dynamic lag between input and output.
Hysteresis is produced by positive feedback to avoid unwanted rapid switching. Hysteresis has been identified in many other fields, including economics and biology.

Economic systems can exhibit hysteresis. For example, export performance is subject to strong hysteresis effects: because of the fixed transportation costs it may take a big push to start a country's exports, but once the transition is made, not much may be required to keep them going.
Hysteresis is used extensively in the area of labor markets. According to theories based on hysteresis, economic downturns (recession) result in an individual becoming unemployed, losing his/her skills (commonly developed 'on the job'), demotivated/disillusioned, and employers may use time spent in unemployment as a screen. In times of an economic upturn or 'boom', the workers affected will not share in the prosperity, remaining long-term unemployed (over 52 weeks). Hysteresis has been put forward[by whom?] as a possible explanation for the poor unemployment performance of many economies in the 1990s. Labor market reform, or strong economic growth, may not therefore aid this pool of long-term unemployed, and thus specific targeted training programs are presented as a possible policy solution.

One type of hysteresis is a simple lag between input and output. A simple example would be a sinusoidal input X(t) and output Y(t)that are separated by a phase lag φ:

Such behavior can occur in linear systems, and a more general form of response is

where χi is the instantaneous response and Φd(t-τ) is the response at time t to an impulse at time τ. In the frequency domain, input and output are related by a complex generalized susceptibility.[3]

Clone of HYSTERESIS
12 months ago
Insight diagram
This model is an attempt to map out a template for a general implementation plan or strategy for the Enabling a Better Tomorrow process for use with New Community Paradigms
Clone of Clone of Strategy for Enabling a Better Tomorrow New Community Paradigms
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
Clone of THE BUTTERFLY EFFECT
Insight diagram
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

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)

Clone of OVERSHOOT GROWTH INTO TURBULENCE
Insight diagram
Stock Flow diagram of automobile leasing with feedback between new and used cars
Clone of Gone today,here tomorrow_2
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that



Clone of THE BUTTERFLY EFFECT
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
\mathrm{e}^{a\tau} \, d(x,y)." src="http://upload.wikimedia.org/math/8/3/5/8355530aeaa6df83fe2a7851508f881a.png" style="border: none; vertical-align: middle;">
Clone of Deterministic chaos
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
Clone of THE BUTTERFLY EFFECT
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

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 working containers (villages communities)

Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram
Factors influencing strategy implementation
Insight diagram
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)

Clone of FORCED GROWTH INTO TURBULENCE
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
Clone of Clone of THE BUTTERFLY EFFECT
Insight diagram
This map shows the tactics of those in power in the story plot
The antagonist will already have many in place before the protagonist and his team realize there is a problem and there is a story to be told to identify and remove the antagonist team by using tactics suited to them that destroy the antagonist and complete the problem solving process
STRATEGIC POWER TACTICS
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
\mathrm{e}^{a\tau} \, d(x,y)." src="http://upload.wikimedia.org/math/8/3/5/8355530aeaa6df83fe2a7851508f881a.png" style="border: none; vertical-align: middle;">
Clone of THE BUTTERFLY EFFECT
Insight diagram

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

EasyJet Fliers Model
Insight diagram
Butterfly Effect
Sensitivity To Initial Conditions
(sensitive dependence on initial conditions)
Navier Stokes Equations
Lorenz Attractor
Chaos Theory, Disorder and Entropy

Although the butterfly effect may appear to be an esoteric and unlikely behavior, it is exhibited by very simple systems: for example, a ball placed at the crest of a hill may roll into any of several valleys depending on, among other things, slight differences in initial position. Similarly the direction a pencil falls when held on its tip, or an universe during its initial stages.
These attractors apply to social systems and economics showing jumps between potential wells, and showing the strategic scaling behavior of rotating and cyclic systems whether they be social, economic, or complex spin or rotation of planets affecting weather and climate or spin of galaxies or elementary particles, or even a rock on the end of a piece of string.

What Playing with numbers is all about :)

If M is the state space for the map , then  displays sensitive dependence to initial conditions if for any x in M and any δ > 0, there are y in M, with  such that
Clone of THE BUTTERFLY EFFECT
Insight diagram
This model describes the link between acquisition and retention and their impact on total customers
Earn share vs stimulate demand
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

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 working containers (villages communities)

Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

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 working containers (villages communities)

Clone of Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram
Stock Flow diagram of automobile leasing with feedback between new and used cars
Gone today,here tomorrow 2
Insight diagram
This model is an attempt to map out a template for a general implementation plan or strategy for the Enabling a Better Tomorrow process for use with New Community Paradigms
Strategy for Enabling a Better Tomorrow New Community Paradigms
Insight diagram
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
Clone of Clone of Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Insight diagram

model

Clone of model - flights
Insight diagram
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK