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 th
Fractals Growth Health Population Economics Biology Demographics Science Navier Stokes Engineering TURBULENCE Chaos BIFURCATIONS MTBF Physics Mathematics Finance Environment Strategy Weather
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
Sayantan Das
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
Navier Stokes Health Physics Population Risk MTBF Failure TURBULENCE Biology Growth BIFURCATIONS Environment Economics Finance Chaos Mathematics Demographics Engineering Fractals Strategy Science
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 BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Guilherme Werpel Fernandes
An steel cylinder oscillates inside a glass tube and over confined air within a glass bottle. As consecuence one observes an oscilation of the inside presure and the inner energy (temperature).
Thermodynamics Didactics Physics
An steel cylinder oscillates inside a glass tube and over confined air within a glass bottle. As consecuence one observes an oscilation of the inside presure and the inner energy (temperature).
Rüchardts experiment 14 10 2021
Philipp von Bülow Duden
How relativistic dynamics can be explained by adding a kinetic mass component due to E=mc^2.
Physics
How relativistic dynamics can be explained by adding a kinetic mass component due to E=mc^2.
Relativistic dynamics (including energy calculations)
David J. Ulrich
This shows the motion of a driven damped harmonic oscillator, described in terms of the undamped natural frequency, and a frequency gamma that reflects the degree of damping, parameterized as a damping ratio gamma/natural frequency.  The oscillator is driven with a force that is a sine function o
Physics Mechanics
This shows the motion of a driven damped harmonic oscillator, described in terms of the undamped natural frequency, and a frequency gamma that reflects the degree of damping, parameterized as a damping ratio gamma/natural frequency. 

The oscillator is driven with a force that is a sine function of time, with a frequency that can be varied, expressed as a forcing ratio driving frequency/natural frequency.

An accurate solution requires a small time step and RK4 as the integration algorithm.
Clone of Driven damped oscillator
Rolf Widmer
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 th
TURBULENCE Population Growth Environment BIFURCATIONS Demographics Economics Science Navier Stokes MTBF Engineering Finance Mathematics Physics Biology Health Strategy Fractals Weather Chaos
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
Anca Badea
This shows the motion of a mass suspended from a spring. An accurate solution requires a small time step and RK4 as the integration algorithm.
Physics Mechanics
This shows the motion of a mass suspended from a spring. An accurate solution requires a small time step and RK4 as the integration algorithm.
Simple harmonic oscillator
Alfredo Louro
11
Electron in a Coulomb potential (H atom) W2=-3.401 eV
Physik Physics Niedderer Schecker
Electron in a Coulomb potential (H atom)

W2=-3.401 eV
-3.4 electron in a Coulomb potential (H atom)
Hans Niedderer
7
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
Strategy Economics TURBULENCE Engineering Failure Growth Science Environment Navier Stokes Health Fractals Finance Mathematics BIFURCATIONS Physics Demographics Biology Chaos MTBF Population Risk
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 BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Te Kou Gage
3
Insight diagram
Slope Physics
Modeling Rocket Flight
Jessica Crane
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
Strategy Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Risk Failure
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
Alena Peskova
Ein mg 214Pb zerfällt in 214Bi, danach in 214Po, dann blitzschnell in 210Pb.
Physics Physik decay
Ein mg 214Pb zerfällt in 214Bi, danach in 214Po, dann blitzschnell in 210Pb.
Radioaktiver Zerfall
Easy Physics Werner Maurer
Spring-Mass model used in IACS physics class
Physics Kinematics Spring Periodic Motion IACS
Spring-Mass model used in IACS physics class
Clone of Spring-Mass Model
Kaitlyn Fraser
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
Environment Finance Economics Physics Biology Health Fractals Strategy Chaos Failure TURBULENCE Engineering Risk MTBF Navier Stokes BIFURCATIONS Growth Population Demographics Science Mathematics
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
Alena Peskova
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 th
MTBF Weather Growth Strategy Health Engineering Fractals TURBULENCE Chaos BIFURCATIONS Biology Mathematics Finance Population Science Demographics Economics Navier Stokes Physics Environment
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
Te Kou Gage
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
Science Strategy Failure Risk MTBF BIFURCATIONS Growth Population Demographics Navier Stokes Engineering TURBULENCE Chaos Fractals Health Biology Physics Mathematics Finance Economics Environment
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
Ivan Stamenkovic
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 th
Finance Physics Health Mathematics Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Biology Economics Environment BIFURCATIONS MTBF Strategy Weather
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
Thibaud Métral
Insight diagram
IACS Kinematics Wind Resistance Physics
Clone of Rocket Model 2015 DiCarlo
Mac Rozen
3
Insight diagram
Motion Physics
Simple Pendulum
Pau Fonseca
Uma empresa de transportes precisa efetuar a entrega de uma encomenda o mais breve possível. Para tanto, a equipe de logística analisa o trajeto desde a empresa até o local da entrega. Ela verifica que o trajeto apresenta dois trechos de distâncias diferentes e velocidades máximas permitidas dif
Physics Kinematics Computational Modeling SYSTEM DYNAMIC Simulation.

Uma empresa de transportes precisa efetuar a entrega de uma encomenda o mais breve possível. Para tanto, a equipe de logística analisa o trajeto desde a empresa até o local da entrega. Ela verifica que o trajeto apresenta dois trechos de distâncias diferentes e velocidades máximas permitidas diferentes. No primeiro trecho, a velocidade máxima permitida é de 80 km/h e a distância a ser percorrida é de 80 km. No segundo trecho, cujo comprimento vale 60 km, a velocidade máxima permitida é 120 km/h. Supondo que as condições de trânsito sejam favoráveis para que o veículo da empresa ande continuamente na velocidade máxima permitida, qual será o tempo necessário, em horas, para a realização da entrega? 

Fonte: Enem 2012

Clique aqui para ver uma descrição do que é Movimento Uniforme.

Clone of Movimento Uniforme
Paulo Villela
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
Demographics Failure Environment Fractals Health Economics Strategy Population Growth Chaos Physics Biology Risk TURBULENCE MTBF Engineering Navier Stokes Science BIFURCATIONS Finance Mathematics
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
sub cribed
Insight diagram
Thermodynamics Physics
conducción térmica 2D 4x4
Philipp von Bülow Duden
6
An steel cylinder oscillates inside a glass tube and over confined air within a glass bottle. As consecuence one observes an oscilation of the inside presure and the inner energy (temperature).
Thermodynamics Didactics Physics
An steel cylinder oscillates inside a glass tube and over confined air within a glass bottle. As consecuence one observes an oscilation of the inside presure and the inner energy (temperature).
Clone of Rüchardts experiment 24 11 2023
Philipp von Bülow Duden
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 compon
Demand TURBULENCE Engineering Fractals Chaos Environment Mathematics Finance Health Biology Navier Stokes Economics Physics Supply Strategy
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)
Ricardo Santana Cabello